dataesr/scientific-paragraphs-categorization huggingface dataset:
Carbon budgets from IPCC To assess carbon budgets available for power generation in LAC, we rely on the IAMC 1. 5°C database hosted by IIASA  (Huppmann et al 2018a). This database contains an ensemble of quantitative, model-based climate change mitigation pathways consistent with 1. 5°C and 2°C warming supporting the IPCC's special report on 1. 5°C  (IPCC 2018 , Huppmann et al 2018b). Table  2  provides a classification of the pathways reported. We use two variables from the IPCC database: CO 2 emissions of electricity supply, and carbon sequestration in the electricity supply. 6 We compute gross CO 2 emissions from the power sector as the sum of net CO 2 emissions from electricity supply and carbon sequestration in the electricity supply sector. To compute budgets, we aggregate emissions between 2019 and 2064 -which is the year when the last planned unit would operate under normal conditions according to our assumptions.
Committed emissions of operating and planned generators We first consider power generation capacity reported in PPT. The database reports that 4,146 existing generators in early 2019 use coal, peat and oil shale (coal for short); natural gas; or oil as their main fuel. This comprises 169 GW of fossil-based capacity. Their average age is 17 years (they have operated since 2002 on average), corresponding to an average remaining lifetime of 18 years (to 2037). Mexico and Argentina lead the natural gas capacity with 44 GW and 23 GW, respectively. For coal, Mexico and Chile have most of the capacity with 6 GW and 4. 9 GW, respectively. Brazil and Mexico lead oil capacity with 11 GW and 6. 7 GW, respectively. Figure  1  displays operational and planned capacity by technology in LAC 7 (the appendix 2 contains results per country).
7 GtCO 2 is slightly less than, but close to the 6. 9 GtCO 2 reported by  Pfeiffer et al. (2018)  for LAC. Pfeiffer et al. (2018)  merge five databases for generators allocating in the planned pipeline the generators under construction or planned statuses in early 2017. They use emission factor from individual fuels and historic heat rated from the IEA. Conversely, we use the PPT database comprising the planned pipeline to announced, authorized, bidding process and under construction statuses in early 2019. We calculate emission factors from the country dashboard from ENERDATA (2019). Figure  5  plots committed emissions against current emissions. For instance, the red dots on the right indicates that Mexico today emits 120 MtCO 2 /yr from the power sector. But existing power plants will emit about 1.
5°Ccompliant carbon budgets reported in the IPCC database, and above 50% of 2°C carbon budgets. If all planned power plants are built, the committed emissions would surpass 90% of the carbon budget scenarios consistent with 1. 5°C or 2°C. The above suggests that, if the climate goals set out in the Paris Agreement are to be achieved, roughly 8  52% to 55% of existing and planned fossil-fueled power plants in Latin America will need to be underutilized, retired early, or retrofitted with expensive CCS or efficiency upgrades, or -in other words-stranded.
Thus, a heat source was generated at the center of the minicomposite placed in the grips of the tensile machine. An infrared camera (Titanium 520M from FLIR) captures the infrared signal (IR) emitted by the outer surface of specimen. It has 320x256 InSb sensors and is equipped with a 50mm objective with an extension ring to reduce spatial resolution to a size of about 80 µm. Infrared images are recorded at 100Hz. Then a dedicated software (Altair-LI also supplied by FLIR) is used to compute maps of damping and phase shift. It is worthnoting that the reference phase is assumed to be given by the signal generator that is connected to the appropriate Lockin input of the camera. Infrared signal processing to estimate thermal diffusivity, is detailed in the next section. It should be noted that the exact shape of the spot and the amount of energy absorbed by the material do not affect the estimation of the thermal diffusivity.
Heterogeneity through the section It is worth pointing out that given the geometry and the properties of minicomposites, the Biot number is Bi = hL λ x ≈ 10 -5 (with h=10W. m -. K -1 ) which validates the assumption of onedimensional heat transfer, reasonably far from the local heat source (about two times the diameter). The first issue to be addressed is the heterogeneity through the cross-section. The minicomposite may be represented, at first approximation, as a wire (representing the SiC fibres bundle) embedded in SiC-CVI matrix. This simplified model was used to perform virtual experiments using finite element analysis. The partial diferential equation Eq. 2 was solved using the FlexPDE software in the axisymmetric domain defined in Fig. 5  a with the following boundary and initial conditions: • A modulated heat source was located at segment OA of the outer surface (Laser); • Convective heat flux was prescribed at segment AB of the outer surface (with h = 10W.
Thermal diffusivity Thermal diffusivity was estimated under constant load during the tensile tests while acoustic activity was continuously recorded. The plots of cumulative number of counts clearly show that damage did not grow during the thermal characterization. The plots of thermal diffusivity data reveals three of the domains that have been identified above (Fig. 13 ). • At low strains (<0. 1%) corresponding to elastic deformations, thermal diffusivity was constant. This indicates that there was no disturbance, as expected with elastic behavior. Then, this shows that elastic deformations do not affect thermal diffusivity. • Under higher strains (< 0. 4%) thermal diffusivity decreased by 15% for minicomposite M1 and by 35% for M2. This corresponds to the domain of matrix cracking and crack extension that occurs in this deformation range, as suggested by stress-strain behavior and acoustic emission.
Introduction Solute segregation to GBs may be either beneficial or detrimental for properties  [1]. For the past 60 years, GB segregation issue in Reactor Pressure Vessel (RPV) steels and other alloys, in particular the intergranular P segregation, has been intensively studied both experimentally and by modelling as reviewed in literature  [2] [3] [4] [5] [6] [7] [8] [9]. Experimental research is frequently carried out by Auger Electron Spectroscopy (AES) that requires GBs to be fractured. Analyses are performed on selected "brittle" GBs with a high segregation level  [10] [11] [12] [13]. AES has a fast acquisition speed to collect the data and a good precision on the composition measurement, but the crystallographic information is lost. Later, a new door has been opened with some advanced techniques, including Analytical Electron Microscopy (AEM)  [14, 15]  and Atom Probe Field Ion Microscopy (APFIM)  [16, 17].
Experimental method 2. 1 Material, sample preparation and experimental conditions The chemical composition of the 16MND5 weld steel is listed in Table  1. The P content is the subsequent stress-relief heat treatment was performed at 595-610°C for 16. 5 h, followed by a controlled cooling at 15°C/h down to 350°C and then air cooling to ambient temperature. The microstructure was observed by Scanning Electron Microscopy (SEM) and EBSD in a dual-beam SEM/FIB instrument (Zeiss Nvision 40 with the AZtec acquisition software and XB 540 with the TEAM-EDAX software). Specimens for SEM/EBSD analyses, in the shape of thin slices of 10×10×0. 3 mm 3 , were cut from as-received half Charpy sample and then fixed into a conductive resin with a diameter of 25 mm. Afterwards, the specimens were ground with coarse, medium and fine sandpaper discs and then polished on special cloths with diamond liquids.
To minimize the Galliumcontaminated layer in the tip, the final cleaning procedure was completed at 2 kV with a current of 100 pA. To ensure the specific GB being located near the apex of the final tip (Fig. 1e ), TKD was used during the final steps of annular milling. This is because the imaging contrast in SEM view failed to identify the GB location when the tip was too thin (<300-500 nm). In contrast, TKD technique can help to locate the GB's position during annular milling. The second advantage of using TKD is to obtain the 5 DOFs with the combination of APT 3D reconstruction. The HKL channel 5 software (or the TSL-OIM software) and Carine crystallography software were utilized for the identification of GB crystallography. It should be noticed that, for the GB plane identification, the maximum Miller index values are limited to 6 in these softwares.
The 3D reconstruction procedure for APT data analyses has been stated in relevant literature  [50] [51] [52]. According to these principles and the visible crystallographic poles from the detector event histogram map, the image compression factor and field factor were determined. Both the commercial IVAS software (CAMECA, v. 3. 6. 6) and the GPM 3D software (from GPM lab, v. 6. 3) were used for data reconstruction.
The smallest rotation angle between the two grains is the misorientation angle (or disorientation angle)  [28, 54]. And the θ/c pair can be deduced as below  [54] : cos " 1 2 ) ) * 1 + , + , + ,-. / * , * , * After acquiring the TKD image (Fig. 2b ), the θ/c pair can be calculated by the software. To recognize the GB planes, both the TKD information and the 3D data reconstruction information need to be combined. Next, an example is applied to illustrate the detailed procedures for identifying the two GB planes with Carine crystallography software. A crystal of grain A ( ) is created here. And the stereographic projection map is plotted along axis (as illustrated in Fig. 2a  in local coordinate system). Then, two rotations are applied to bring the GB plane perpendicular to the Y axis. The two rotation angles, α and β, from which the GB plane normal can be aligned with Y axis, are identified by the combination of the TKD map (Fig.
Acknowledgement This work was performed on the GENESIS platform, financially supported by  Centre National de la Recherche Scientifique (CNRS)  belonging to the project entitled " Investissements d'avenir " with a reference number  ANR-11-EQPX-0020. This work is part of the  EM2VM Joint Laboratory Study and Modeling of the Microstructure for Ageing of Materials. This work was supported by the  MAI-sn  ( Materials Ageing Institute-Scientific Network  (http://themai. org/scientific-network). The authors also owe their sincere gratitude to  Prof. Didier Blavette  for the fruitful discussions.
Les animaux, premiers détecteurs de pathologies par l'odorat Des manifestations spontanées de chiens (dognoseis) confrontés à divers cancers (mélanome, cancer du sein, etc. ) ont été rapportées dès 1989, mais de façon anecdotique et ponctuelle  [1]. Vignette : réseau astrocytaire mis en évidence dans un glomérule olfactif (Photo © Inserm -Lisa Roux). etc. ) qui génère, après traitement du signal, une signature, ou empreinte, caractéristique de l'environnement odorant  [12]. Cette signature sera analysée et comparée à une base de données obtenue lors d'une phase d'apprentissage. Depuis plus de 10 ans, de nombreuses études sont menées afin d'aboutir au développement et à la commercialisation de nez électroniques dans le domaine de la détection de pathologies, en particulier par analyse de l'haleine  [3].
Image processing Tracking of the cells (nucleus) was performed with ImageJ using Multiple Tracking plug-in. The generated coordinates were used to compute cell trajectories. Plots derived from data as well as statistical tests were done using OriginLab Pro (OriginLab). Force analysis made on focal contacts was performed with a custom Python code computing areas of adhesion zones, their orientations and barycenters, force vectors for each of them and total force vectors taking the rule 1 µm² corresponds to 5. 5 nN  (20) (21). Fits with experimental data were done through OriginLab Pro.
ACKNOWLEDGMENTS We thank  O. Pertz ,  P. Rossolilo  and  A. Dupont , the  Imaging Platform of IGBMC , the  Riveline Lab. for constructs and discussions. This study with the reference  ANR-10-LABX-0030-INRT  has been also supported by a  French  state fund through the  Agence Nationale de la Recherche  under the frame programme  Investissements d'Avenir labelled   ANR-10-IDEX-0002-02. SLV is supported by the  University of Strasbourg. R. T. was an IGBMC International PhD Programme fellow supported by  LabEx INRT  funds. D. R. acknowledges support from ciFRC  Strasbourg , the  University of Strasbourg ,  CNRS and Foundation Cino del Duca.
Ces dernières informations permettent de garantir la rentabilité de chaque formation car elles intègrent les coûts complets, c'est-à-dire les frais internes (salle de formation, supports de cours, utilisation des moyens opérationnels du GIP-CNFM pour les travaux pratiques, rémunération du formateur, …) et ceux externes (gestion de la formation par le service de formation continue). Tout personnel académique peut proposer une formation continue et ainsi enrichir la base de données, nommée GECO  (18). Cette base de données supporte trois plateformes hébergées par les Services Nationaux : CAO, FPGA et FORMATION (cf. Figure  3 ). Depuis la plateforme FORMATION, on peut consulter le catalogue, se connecter pour proposer une formation ou en modifier une existante. Pour créer une nouvelle fiche de formation, il est nécessaire de posséder un compte utilisateur en effectuant une requête auprès de l'administrateur.
Le clip a aussi été relayé sur le site des services nationaux et ses comptes sur les 3 réseaux sociaux, FB, LinkedIn et Twitter,  Le lancement de la première formation diplômante du réseau GIP-CNFM par le pôle CNFM PACA Marseille en collaboration avec l'école Polytech Marseille et le SFC de l'AMU (Aix-Marseille Université). Il s'agit du DESU (Diplôme d'Etudes Supérieures Universitaires) ingénieur produit en microélectronique. La formation se déroule sur 32,5 jours à raison de 2 jours par semaine et comprend 9 modules d'enseignement (38). Les modules sont capitalisables sur une durée maximale de 2 ans. Ce pôle a également enrichi son offre locale de formations continues professionnelles en adressant de nouvelles thématiques à savoir l'électronique RF (Radio Fréquence) (39), les protocoles RF (40), les techniques de fiabilité (41), les méthodes statistiques et bases de données (42),  Le lancement de formations professionnelles continues sur la programmation de microcontrôleur (43) par l'IUT GEII de Marseille, le pôle CNFM PACA Marseille et le SFC de l'AMU (Aix-Marseille Université).
Remerciements Les auteurs souhaitent remercier le GIP-CNFM (1), l' Université de Montpellier  (17) et la  Région Occitanie  ( 44 ) pour leur soutien. Ils remercient également tous les directeurs de pôle, sous-directeurs, enseignants-chercheurs et chercheurs qui se sont impliqués dans l'élaboration du catalogue en proposant des fiches de formation, ainsi que les directeurs et chargés de mission des Services de Formation Continue partenaires pour leur confiance et leur collaboration. Enfin, les auteurs remercient l' Agence Nationale de la Recherche (ANR) pour son soutien sous subvention   ANR-11-IDFI-0017  du projet IDEFI-FINMINA (5).
Ce pôle a également enrichi son offre locale de formations continues professionnelles en adressant de nouvelles thématiques à savoir l'électronique RF (Radio Fréquence) (39), les protocoles RF (40), les techniques de fiabilité (41), les méthodes statistiques et bases de données (42),  Le lancement de formations professionnelles continues sur la programmation de microcontrôleur (43) par l'IUT GEII de Marseille, le pôle CNFM PACA Marseille et le SFC de l'AMU (Aix-Marseille Université).
Due to this similarity between the mathematical procedure of the Voronoi tessellation and the physics of foam production, the tessellations can be created such that the cell geometry complies with Matzke's experimental work  [3]  on the liquid bubbles shapes. Roberts and Garboczi  [4]  created 3D Voronoi models of open and closed cell foams. Valuyskikh  [5]  was able to extract irregular stochastic models by deflecting cell centers with a regular structure of tetradecahedrons. We note however that by generating a random structure from an initial regular structure without any constraint on the cell morphology, the structure obtained will lack important characteristics of the real foam geometry. To overcome this problem, the tessellation is usually relaxed by minimizing the total surface energy area while preserving the cell-volume distributions using the Surface Evolver software.
This relaxation process creates several topological transitions within the local cell neighborhood that leads to soap froth that fully respects Plateau's laws. In particular, compared with the Voronoi tessellation, slightly curved faces and edges and significantly fewer short edges have been observed  [6]. In this regard, the Surface Evolver software originally developed by K. Brakke  [7]  to study a liquid surface shaped by surface tension and subject to various constraints, has allowed to make a significant leap forwards in the modeling of equilibrium foam microstructures. This approach is particularly interesting when large porosities are considered; however by nature it becomes inappropriate for nonequilibrium foam microstructures, where a coupling between surface tension and viscous stresses has to be considered.
The physicochemical characteristics of the materials were provided by our industrial partner and physically reasonable values for the mechanical properties were used (K0=10 12 Pa, η0=10 3 Pa. s, γ0=15mN/m). For this material input, one of the difficulties in determining precise values is due to chemical blowing agents that are exothermic when they decompose at high temperature. This may induce chemical reactions during the process. The process generates a cellular microstructure that is closely representative of actual polymeric foam microstructures as demonstrated in the discussion section here after, for a same kind of foam although with a little lower porosity. The finite element program MSC Marc was employed to perform numerical compressive tests within the framework of the large displacement theory.
The results were compared to experimental measurements carried out on five polymeric foam samples. These experimental tests were performed at ambient temperature under constant displacement rate using an INSTRON E3000 testing machine equipped with a 1kN load cell. The constitutive model chosen for the base material was determined using a Mooney Rivlin fit of the engineering tensile/compressive stress-strain curve of the bulk material (not foamed). One can report to the Supplementary data document for details. A model containing a large number of cells (587 cells) was chosen as representative volume element (RVE). The size of this RVE was carefully established in our previous work  [12]. It is also in good agreement with several previous studies  [32]. A standard model contained around 1. 5.
5%). Using the cells sizes as inferred from x-ray tomography data, the bubbles lifetimes can be estimated; as a consequence a nucleation rate with time can be defined. In the 3D view one must not attach too much importance to the fact that the outer cells appear different. Indeed as explained in details in  [12]  a cylindrical subvolume of the computed microtomography dataset is extracted from the final reconstructed image represented by a 3D array of voxels. As a result no periodic boundary conditions can be applied as they would be inadequate. Conversely, in numerical simulations the cells grow very quickly in the absence of external constraints. Therefore to overcome this discrepancy and minimize edge effects, we have extracted a Representative Elementary Volume (REV) with 400 cells at the end of the simulation.
It is clear that having developed a dynamic approach, despite its limitations, is an asset. In particular, as the nucleation of cells, their growth through gas expansion, and the interactions between growing cells are taken into account simultaneously, more realistic microstructures of the cellular material are generated, and this, over a large range of porosities (from a few to 95 percents). The morphometry parameters correspond closely to the ones of real polymeric foams in terms of porosity, polydispersity, cell shape, anisotropy and orientation of the cells, wall thicknesses. Some descriptions of these parameters and subsequent comparisons are given in the Supplementary data document besides this paper. Thus three main parameters govern the ultimate microstructure of the cellular material.
In order to improve the RF coupling between the resonator and the 50 Ω niobium coplanar waveguide (CPW) feedline, we remove the ground plane on this side of the pixel over its whole length. The meander is 1. 5 μm away from the 2 μm-width CPW central line. This does not affect the performance of the feedline as the length of the portion removed is much smaller than the RF readout's wavelength. In addition, the arms which are defined along the central line at the same distance (i. e. , 1. 5 μm), replace almost entirely the removed ground, thus contributing to optimizing the RF coupling between the feedline and the pixel as shown by the simulations in Fig. 2. They show the simulated forward transmission S21 response of the feedline as well as the current density within the parallel-plate capacitor LEKID with a full upper electrode using the electromagnetic simulation package SONNET  [16].
Acknowledgments We thank  Jean-Pierre Aoustin  and  Laurent Pelay  for copper box fabrication,  José Palamo  for Al2O3 deposition and  Martino Calvo  for support during the measurements. We acknowledge  Pascal Jagourel  for his continued support. The devices were fabricated in Paris Observatory clean-room facility and characterized at  AstroParticle and Cosmology (APC) Lab  as well as at  CNRS-Néel Institute.
Acknowledgments: The authors would like to thank  Olivier Hamant  for reviewing the manuscript, and  Thomas Laux ,  Ari Pekka Mähönen ,  Ben Scheres ,  ABRC  and  NASC  for providing seeds. This work was funded by the  National Natural Science Foundation of China  grants  31825002 ,  31861143021 ,  31430010  and  31861130355. YJ is a Newton Advanced Fellow of the  Royal Society. JT, FZ, WC were supported by the  ERC  advanced grant MORPHODYNAMICS (grant number:  294397 ). JT, FZ were also funded by the  ANR ERA CAPS  grant  Gene2Shape. JT, CG, OA and HO were supported by the  Inria Project Lab 'Morphogenetics'.
Determination of optimal extraction time and power In order to evaluate the optimal extraction time (it was until no more essential oil was obtained), different microwave irradiation powers of 300, 450, 600, 700 and 800 W were examined. Data presented in Fig. 2a  showed the evolutions of the extraction yield obtained via different microwave irradiation powers as a function of the extraction time Fig. 2b  showed the evolutions of microwave irradiations powers as a function of the total extraction time in the ESFME process, respectively. Results indicated that almost similar essential oil yields were found in different levels. At 600, 700 and 800 W power settings allow shorter extraction time of 30 min, but the power should not be too high to avoid the loss of volatile compounds. So, the microwave irradiation power of 600 W for 100 g of fennel seeds was chosen as an optimum power for later experiments, because this power gave a complete extraction of fennel essential oil in only 30 min.