dataesr/scientific-paragraphs-categorization huggingface dataset:
In the subsequent experiments, we generate random masks of the above two types with the number of missing pixels varying (2) Matlab code available at: http://www. greyc. ensicaen. fr/∼jfadili/ demos/WaveRestore/downloads/mcalab/Home. html in {20%, 30%, 40%, 50%} as a percentage of the total number of pixels. In practice, the case of randomly distributed burned lines appears in case of 2-D detectors based on wire chambers  [40] , while the case of randomly burned pixels is met in more modern acquisition systems, such as CCD cameras. Figure  3  shows corrupted instances for both images, X1 and X2, where the top row corresponds to a random mask with 50% of missing information, while the bottom row corresponds to a random lines mask, also with 50% of burned pixels. In our case, a successful inpainting of the observed GIXD images using MCA, is equivalent to recovering accurately the missing information such that the associated linecuts, estimated from the reconstructed images, to be close approximations of the linecuts corresponding to the original images.
CONCLUSIONS AND FUTURE WORK In this study, we exploited the efficiency of the recently introduced MCA algorithm for the decomposition of images in distinct morphological components, based on the achieved sparsity in appropriate over-complete redundant transform domains, with our objective being to solve the problem of recovering the missing information in corrupted GIXD images due to potential malfunction of the detectors. The experimental evaluation using high-resolution GIXD images of thin polythiophene-based films, showed that the proposed approach is highly efficient in recovering the missing information in the form of either randomly burned pixels, or whole burned rows, even at the order of 50% of the total number of pixels. This led to the derivation of accurate intensity 1-D plots (linecuts) from the recovered inpainted images, that will later allow for correct data interpretation.
ACKNOWLEDGMENTS This work is supported by  CS-ORION Marie Curie Industry -Academia Partnerships and Pathways (IAPP)  project funded by the  European Commission  in  FP7  ( PIAP-GA-2009-251605 ), and  Région Aquitaine and Arkema. We are also grateful to  Dr. G. Portale  for conducting the GIXD measurements in the  Dutch-Belgian Beamline (DUBBLE)  of the  European Synchrotron Radiation Facility (ESRF), Grenoble, France. The  Netherlands Organisation for Scientific Research (NWO)  and  ESRF  are acknowledged for granting the beamtime.
Inspection program An inspection program starts by defining the system and the performance criteria (Figure  13. 8); this step implies the collection of data concerning the system and its environment. A Qualitative Risk Analysis (QRA) is therefore performed to determine the failure modes, as well as their causes and consequences (using, for example, RAMS methods, as described in Part One). In this step, the logical representation of the system must be established, in order to define the required functions and the interactions between components and sub-systems. The next step consists of estimating the failure rates and consequences, in order to allow for ranking according to risk levels. We can therefore distinguish between two cases: -the case where defect measurement is sufficient to indicate the level of degradation and performance (direct evaluation of the limit state); and -the case where measurement, using models, can help to evaluate the limit state (by measurement of material properties, degradation parameters, etc.
En 2030 ou au plus tard 2040, ce pourcentage devrait atteindre 80 %. Cela signifie que l'on passera de un milliard à presque quatre milliards de personnes appartenant à la « classe moyenne », la majorité de cette progression se faisant en Asie. Ces consommateurs occuperont une place prépondérante pour définir de nouveaux itinéraires commerciaux et réseaux de transport du conteneur comme ceux reliant l'Asie et l'Afrique, ceci afin d'éviter les risques accrus associés à la supply chain et des chaînes de livraison trop longues par transbordement dans les hubs européens. Tous ces changements placent les opérateurs de fret au pied du mur. Le glissement des marchés les contraint à réagir aux changements très nets des routes commerciales globales. 5. 2. ACTIVITÉS ÉCONOMIQUES 5. 2. 1. Diminution durable de l'activité économique de l'Europe et de sa part du PIB mondial Pour autant et pour ces deux indices, le travail de synthèse des données recueillies, la construction de la base de données, l'élaboration de la matrice, la formulation des hypothèses et des scenarii n'engagent que l'auteur de cette étude.
Remerciements Ce travail a bénéficié du soutien financier de l' Agence Nationale de la Recherche  ( OEDYP  No  ANR-09-BLAN-0206-01 ) et du  Conseil Régional d'Aquitaine (POLUX No   2010-13-04-002  et  COLA2 No 2. 1. 3-09010502 ). Les auteurs remercient  Rodrigue Bouillaud  pour son support technique, et Capucine Medina pour son aide précieuse sur le laser.
Our future plans include coupling the present software with the HYFRAC boundary element method developed by Mear and discussed in [19], as well as treating multiple cracks or multiphase flow in the reservoir and non Newtonian flow in the fracture. This article is organized as follows. The modeling equations are defined in Section 1. Section 2 summarizes theoretical results on the linear model. The numerical scheme and algorithm are described in Section 3. A numerical experiment illustrating the model is presented in Section 4. We end with some conclusions.
ACKNOWLEDGMENTS The first, fourth and fifth authors were funded by the  DOE  grant  DE-GGO2-04ER25617. The second author was funded by the  Center for Subsurface Modeling Industrial Affiliates  and by a J. T. Oden Faculty Fellowship. The third author was funded by  Conoco Phillips. The authors would like to thank  Drs. Rick Dean ,  Joe Schmidt , and  Horacio Florez  for their assistance in this paper. We also wish to thank  Omar Al Hinai  for his assistance with the fracture flow code.
INORGANIC SPECIATION DURING THERMAL CONVERSION PROCESSES The objective of this paragraph is: -to provide an overview of the species that can be released during the thermal treatment of biomass; -to identify the main elements and species that can be considered as problematic for the different components in various processes: -chlorides or sulphates that may cause corrosion; -species that condense in liquid or solid particles that may plug the pipes; -reactions leading to liquid phases in or with bed materials and may entrain bed agglomeration, etc. Thermodynamic calculations can help to make predictions of speciation of all these elements depending on temperature and pressure, when the binary, ternary and other systems are described in the associated databases. For the other cases, it is possible to use SGTE (Scientific Group Thermodata Europe) databases, taking into account that some limitations remain as liquid and solid solutions are not described in that case.
, 2013)  and with a focus on alkali behaviour  (Defoort et al. , 2012). They performed equilibrium calculations and characterisation of the gaseous and condensed phase at the exhaust of several equipment such as a bubbling fluidized bed linked to a high temperature gas reforming reactor  (Valin et al. , 2009 (Valin et al. , , 2010)). Thermodynamic calculations were carried out with the FACTSAGE software and associated databases to simulate several biomass gasification processes  (Bale et al. , 2009). In the experiments, several on-line and off-line analyses and sampling were implemented in the facilities to measure gas phase compositions these include lGC-TCD (micro-Gas Chromatography coupled with Thermal Conductivity Detectors) to follow, on line, sulphur containing species H 2 S and COS or FTIR (Fourier Transform Infra Red spectroscopy) to analyse on-line water soluble inorganic species (NH 3 , HCN, HCl).
Conclusion The CEA approach allows the elaboration of a deterministic methodology that enables: -either, to determine the optimum reactor operation temperature as a function of the actual ash composition; -or, to determine the composition and amount of additives that can be mixed with the resource in order to reach a pre-determined operation temperature and slag viscosity for a given ash composition. This technique allows therefore, adapting the operation parameters of an entrained flow reactor to diverse resources in order to control simultaneously: -the thickness of the solidified ash layer; -the slag viscosity; -the heat losses. Of course, reliable thermodynamic data bases are required for the calculations of the properties of slag mixtures. An effort to create and validate such data bases, and related methodologies, has been undertaken as part of the ANR INORGANIC and SLUGAS project.
Battery Thermal Management Simulation Model A Matlab/Simulink LV battery simulation model has been built and implemented in a powertrain system platform where all powertrain components (ICE, electric motors, inverters, gear boxes, etc. ) were previously developed and validated. The battery simulation model requires both electrical and thermal models, as illustrated in Appendix 3 in blue and red respectively. The battery simulation model is divided into different modules that are finally linked together: SOC, internal resistance, thermal losses, cell temperature, ageing factor, battery management restrictions for battery protection, etc. The battery model is then coupled to the vehicle A/C circuit model for co-simulation. The battery model provides thermal losses, cooler pressure drop and expansion valve setting as inputs to the A/C circuit model which answers with inlet refrigerant temperature and pressure and the electric power required by cooling components.
3D NUMERICAL SIMULATION OF THE REACTOR USING A MULTI-FLUID CFD CODE Numerical predictions of the low-scale reactor are undertaken using multi-fluid CFD code NEP-TUNE_CFDV1. 08Tlse. NEPTUNE_CFD is a multiphase flow software developed within the framework of the NEPTUNE project which is a french industrial consortium, financially supported by CEA, EDF, IRSN and AREVA NP. A mono-solid gas-particle flow is assumed and for each phases, two different wall boundary conditions are used. Basically, for the gas phase we used a classical friction law dedicated to disturbed flows described with k À e model. For the solid, a no-slip boundary condition appears to be appropriate  [8].
ASHRAE, de sa part, a décidé d'intégrer certaines critiques et a financé des recherches, basées sur l'analyse de 21. 000 groupes de données compilées à partir d'études de terrain dans 160 bâtiments, situés sur quatre continents et appartenant à diverses zones climatiques. Le résultat a été la constitution d'un nouveau standard de confort qui est décrit sous le nom de Adaptive comfort et qui complète la traditionnelle base de données ASHRAE  (De Dear, Brager, 2002).
11Lesdonnées climatiques pour la ville de Calcutta ont été recueillies à partir de la base de données de l'Alipore Meteorological Centre. 12La consommation d'énergie est exprimée en unités. Une unité correspond à l'usage de 1 kWh, et elle est vendue pour environ 4 roupies. 13 Le choix de conduire cette phase finale de l' enquête dans les logements privés a été fait afin de pouvoir questionner les habitants et étudier l'ensemble des caractéristiques des ménages (n =11). 14 L'une des situations observées est détaillée ci-dessous. Quatre instruments de mesure (température et humidité) ont été installés à l'intérieur de deux logements appartenant au même bâtiment. Il s'agissait d'une maison pour deux familles à deux étages, édifiée dans le quartier de New Alipore, d'une bonne qualité (construite en 1960, avec des volets aux fenêtres, des murs épais, un jardin et des arbres, des vérandas).
Moreover, the measure of flatness may be easily extended for multidimensional signals. The sequel of this paper is organized as follows. In Section 1, we present the principles of 1-D and 2-D subband decompositions and the model of the resulting signals. Then in Section 2, the adaptive approach is detailed along with the stopping rule used. Section 3 is dedicated to the implementation issues and presents the summary of the algorithms. The procedure to download the MATLAB code of the method is also given. Finally, results on 1-D and 2-D experimental NMR signals are presented in Section 4. Conclusion are drawn at the end.
Summary of the Algorithms The complete algorithms for processing 1-D and 2-D NMR data are summarized in Tables  1  and 2  respectively. It is worth noting that a MATLAB implementation of the 1-D algorithm, called SPENCER (5) for Subband Parameter Estimation of Noisy Complex Exponential data Records, is available for free download. It includes all the procedure presented here, including adaptive subband decomposition and parameter estimation. Moreover, it integrates other functionalities such as baseline suppression, phase correction, line listing and graphic representations. Similarly, a MATLAB implementation of the 2-D algorithm is also available from the authors.
2-D NMR We consider an experimental 2-D NMR signal of size 64 × 2048. The 2-D decimation filter is separable into two 1-D filters which are the same as in the 1-D case (ripple amplitude 0. 1 dB, stopband attenuation -60 dB). Since the NMR data set has a large amount of samples in the second dimension, we fixed the minimum decimation level (without estimation) to min = 1; 2 and the maximum one to max = 2; 4. The notation x; y stands for column vectors, with x and y corresponding to the first and second dimension, respectively. We used the TLS-Prony method  [24]  with prediction orders set to p = N /2; M /2 , where N × M is the size of the subband signal. The final subbands obtained with our algorithm in the spectral region [-0. 25, 0] × [-0. 25, -0. 25] are shown in Figure  8. As it was the case in 1-D, one can observe that the decomposition is generally deeper in the spectral regions where several modes are located.
In this work, we propose a rigorous methodology based on the construction of consensus models. The final target of this work is actually the development of models for fuel blends but the present work is only concerned with pure compounds. The objective is to guide the future formulation of alternative fuels with the help of the simulation of targeted physical properties. The paper is organized as follows: in Section 1, we detail the products, the properties, the databases, the method and the models used; Section 2 is dedicated to the presentation and discussion of the results on the prediction of the different properties, on the comparison between experimental and predicted values, on the predicted trends versus the carbon number; Section 3 is dedicated to the synthesis with focus on the possible trade-off between the properties.
Methodology The methodology used to develop models concerning the prediction of the targeted properties is fully documented in previous papers  [20, 21]. The main steps are described in Figure  2. The 1 st step consists in building the local database from external databases. Indeed the database is of major importance as the predictive quality of QSPR models is largely influenced by its size and its quality. The database was built on the basis of experimental data gathered from different sources, such as the Design Institute for Physical Properties (DIPPR), database of chemical companies, the chemical database of the University of Akron (Ohio, USA) and the information available in Yaws' handbook  [22] [23] [24] [25] [26] [27]. It is important to notice the peculiarity of the CN database which was built on the basis of the compendium by Murphy et al.
[28]  for oxygenated compounds and from Creton et al. [29]  for hydrocarbons. The local and complete database contains FP of 625 molecules, CN of 299 molecules, 5 634 experimental density values for 730 molecules and 3 547 experimental viscosity for 407 molecules. Density and viscosity are properties that depend on temperature. Before building the QSPR models, the main database was split into three subsets: -the training set, used to train each learning algorithm; -the validation set serves as an additional tool to estimate the predictive error of individual QSPR models, as well as an indicator to determine which models generalize better; -the test set, used to estimate the predictive error of the final model. The split was carried out using a random sampling function. The data subsets for training, validation and test sets consist of 70, 20 and 10% of the entire database, respectively.
The local database is then completed by the definition of descriptors for each molecule. Two sets of descriptors were used: Molecular Descriptors (MD) and Functional Group Count Descriptors (FGCD). The next step is dedicated to the building of models. The analysis of the data was managed by the use of two kinds of models: linear models and nonlinear models. Linear models were obtained using approaches such as Genetic Function Approximation (GFA) and Partial Least Squares regression (PLS). Nonlinear models were obtained using approaches such as Feed-Forward Artificial Neural Networks (FF-ANN), General Regression Neural Networks (GRNN), Graph Machines (GM) and Support Vector Machines (SVM). The final step is the work on the consensus model and is an innovative approach to improve predictions.
REMERCIEMENTS Ce travail est réalisé suite à une collaboration scientifique entre l'UMR 547 PIAF de l'INRA Clermont-Ferrand -France et le Département de Biologie végétale de l'Université Cheikh Anta Diop (Dakar-Sénégal). Cette collaboration est rendu possible grâce à l'appui financier de l'Agence Universitaire de la Francophonie (AUF.
Comparaison des sections Le piston-cylindre 50 MPa N°1 a été étalonné par comparaison directe avec l'ensemble piston-cylindre Desgranges et Huot N° 6594, dont la valeur de section est référencée dans la base de données du BIPM et est issue de l'intercomparaison CCM. P-K1  [3] [4], sa valeur est égale à 980,492 9 mm². Cette comparaison a été effectuée en gaz pur pour des pressions comprises entre 0,1 et 1 MPa. Cette mesure nous a permis de trouver une section effective à pression nulle égale 196,098 90 mm² avec une incertitude type de 5,5 x 10 -6 x S. Soit un écart relatif de 3,6 ppm avec la valeur déterminée précédemment par mesures dimensionnelles. Cette nouvelle référence 50 MPa se compose de trois ensembles pistons-cylindre que nous avons comparés deux à deux et par rapport au 200 MPa N°5.
m -3 ), κ is the thermal conductivity of each layer (W. m -1. K -1 ), H i is the enthalpy of reaction of the species i with the MEA (J. mol -1 ) and C p is the thermal capacity (J. K -1. kg -  ). The three layers considered are connected by the following interface relations and boundary conditions: -axial direction (assuming counter-current flow pattern): -radial direction: The implementation is based on the method of lines and executed in Matlab. The specifications used are: gas flow on the shell side of the fibers, liquid flow on the lumen side and counter-current flows. The key assumptions are as follows: -negligible axial diffusion (in the gas and liquid phases); -amine compounds and water only present in the liquid phase (no evaporation); -no wetting of the membrane pores; -uniform fiber shapes and packing.
Results from Pilot-Scale Setup Several experiments with varying liquid and gas flow rates were conducted with the industrial pilot-scale HFMM. The results considered here are for a range of liquid flow rates of 0. 50-3. 33 L. min -1 and gas flow rates of 5-30 L. min -1. The MEA is recirculated and so is already partially loaded with CO 2 , which is also measured at the start of each experiment. The inlet volume fraction of CO 2 in the N 2 is kept approximately constant at about 15%. The experimental results are then compared with simulation results from the 2D mass transfer model. Following the validation of the 2D model with the data from the lab-scale module, the parameters of the model describing the module design and MEA conditions are adjusted to simulate the pilot-scale module. The fibers in both modules are made from the same material, allowing for the membrane mass transfer coefficient determined from the fit with the lab-scale module experimental data to also be used in the simulations of the larger module.
Les dimensions des zones fondues se comparent très correctement. Les largeurs et positions de ces zones sont retrouvées. La pénétration du cordon dans le métal n'est cependant pas similaire en raison de l'absence d'un JA 2013 calcul de mécanique des fluides considérant la force de Marangoni. Le développement du calcul du champ de vitesse liquide pour ce procédé est en cours, pour permettre de retrouver des profondeurs comparables. De même, le calcul des champs de contraintes et de déformations finales des assemblages est l'objectif final poursuivi par ce projet. Les auteurs remercient l'Institut Carnot de Bourgogne, partenaire de ce projet ANR (SISHYFE / ANR-09-MAPR-0019), pour les observations expérimentales.
The main steps of the used approach are illustrated in Figure  1. Section 1 concerns the homogenization of the mechanical behaviour of the cement paste at a very early age. For this purpose, a multi-scale approach, that uses the evolution of volume fractions of the different components of the cement paste during hydration, is used. Section 2 deals with the necessary mechanical and chemical inputs for obtaining the evolution of volume fractions of the different components of the cement paste. The intrinsic mechanical properties of solid constituents are recovered from nano-indentation testing data coming from the literature, while the evolution of volume fractions is determined from a cement hydration kinetics model for the four clinker components of a class G oilwell cement. Section 3 is devoted to the experimental characterization of the class G oilwell cement paste.
Determination of Hydration Kinetics from Calorimetric Data The Langavant semi-adiabatic calorimeter was used to quantify the heat Qt ðÞ emitted during the exothermic chemical reactions between anhydrous cement and water. Such a calorimeter can be used only at atmospheric pressure. The overall hydration degree is then calculated by using Equation  (20)  where Qt ðÞis the measured hydration heat. This measurement allows to validate the overall hydration degree obtained from the hydration model of the previous section. However, this comparison is possible at the condition to know the total heat production. This total production has been evaluated by using two different kinds of estimations coming from the literature, as shown in Figure  9 , which displays predicted (from Sect. 2) and measured estimations of the overall hydration degree.
ACKNOWLEDGMENTS The authors are particularly grateful to  Florence Adje´mian  ( IFPEN ) for fruitful discussions concerning primary cementing technique in wells and  Laurent Can-ge´mi (IFPEN)  for stimulating discussions during the course of this work. The authors also want to express their special acknowledgement to  Nathalie Ferrer  and  Alain Rivereau  ( IFPEN ) for their technical support during the experimental part of the study and to  Hoang Duc Hieu  ( MSME ) who strongly helped for the computations related to the GSC homogenization scheme.
Molecular Dynamics Molecular dynamics is mostly used for two purposes in the present study: -relaxing the structure of carbon-based amorphous solids, for which the detailed structure is known on a statistical basis only; -accessing the dynamics of gas molecules in the microporosity of the solid. In both cases, the dynamics depends on the motion of the atoms of the solid, inter alia. Appropriate thermostat and barostat have to be used to scale velocities at regular time intervals if temperature T and pressure P are imposed. It must be stressed that the bulk gas pressure P in Equation (2) and the barostat pressure are formally independent, as the barostat pressure acts also on the solid. In the MedeA Ò software environment, we are using LAMMPS (large scale atomic massively parallel software) for molecular dynamics simulations  [5].