dataesr/scientific-paragraphs-categorization huggingface dataset:
Model Performance and Statistical Analysis Spine-segmentation and lesion-segmentation performances were evaluated using the Dice coefficient. 26, 27  The Dice coefficient is a measure of overlapping defined as ͑2͉T പ P͉ Ϭ ͉T͉ ϩ ͉P͉͒, Where T is the criterion standard segmentation performed by a fellowship-trained neuroradiologist and P is the predicted segmentation of the SC. The proposed segmentation method (BASICseg) was compared with 2 state-of-the-art methods: Propseg (https://sourceforge. net/p/spinalcordtoolbox/wiki/sct_ propseg/)  16  and Deepseg,  28  both included in the SCT. 11  Deepseg (sct_deepseg_sc module in SCT; https://sourceforge. net/p/ spinalcordtoolbox/discussion/help/thread/c9972de78a/) is a recently described deep-learning-based spinal cord segmentation using a succession of 2 CNNs, the first one to detect the SC and the second one to perform the segmentation.
Furthermore, large multi-institutional studies incorporating high-volume MR imaging data would potentially benefit from our proposed image-processing pipeline, which is conducive to batch processing with few errors in automated segmentation. Application of radiomic and texture feature-analysis techniques may also potentially benefit from the proposed image-segmentation techniques. 34  Limitations of this study primarily relate to the relatively small sample size of patients with SCI, which both lowers the power of statistical tests using biomarkers and precludes the use of 3D convolutional neural networks. Despite application of data-augmen-tation techniques to ameliorate feature learning particular to the training set, differences in Dice values between training and validation datasets also suggest some degree of data overfitting for lesion segmentation.
Acknowledgments The authors would like to express their appreciation to  Prof. François Gautier  and  Dr. Adrien Pelat  from  LAUM CNRS at Le Mans University  for very fruitful discussion and comments. This study is part of the Chair program  VIBROLEG (Vibroacoustics of Lightweight  structures) supported by  IRT Jules Verne  ( French Institute in Research and Technology in Advanced Manufacturing Technologies for Composite, Metallic and Hybrid Structures ). The authors wish to associate the industrial and academic partners of this project; respectively.
Materials and methods The material used in this study is a primary low copper 356 foundry aluminum alloy. Its nominal composition is given in  table   Ingots are melted into a 80kg crucible at a temperature of 720   The statistical evaluation of the precipitate density was carried out by image analysis at the same magnification for each type of precipitate regardless of the heat treatment, using the ImageJ software on images in dark field in [001] Al zone axis.
Mechanical testing Tensile testing was performed using an electro-mechanic Instron 3382 system coupled to a 100kN Instron 2716-002 load cell. Extensometer is an Instron AutoX 750 high resolution automatic device. This system to belongs to class 05, which means it has +/-0. 5% uncertainty on the measurements. Data acquisition was set to 100Hz and Instron Bluehill software was used to postprocess the data. Finally, strain rate was 4mm. min -1. For each heat treatment, five tensile samples were utilized.
when forces applied to the spacecraft or the test masses are only those necessary to keep it in drag free and attitude control mode. In the following, the data are referenced by the Day of the Year (DoY ) measuring the number of days from the first of January 2016. LISA Pathfinder was launched on the 4th of December 2015 and was in commission mode during the month of February 2016. Science operations started on the 1st of March 2016. The mission was ended in July 2017. In section II, an overview of the thrusters hardware setup and in particular the gas feeding system is presented. Section III will describe the in-flights characterisation of the cold gas in term of noise and anomalies. In section IV potential consequences for LISA are presented and in section V some conclusions are given. II.
However, the observed spectral lines and the excess coherent noise will induce spacecraft motion that will couple with the test masses sensitive axis motion through stiffness and optical imperfections. Their expected level could be non-negligible. Dedicated studies or design strategy should therefore be devoted to explain or suppress their presence. VI. Acknowledgement -This work has been made possible by the LISA Pathfinder mission, which is part of the space-science programme of the European Space Agency. The French contribution has been supported by the CNES (Accord Specifique de projet CNES 1316634/CNRS 103747), the CNRS, the Observatoire de Paris and the University Paris-Diderot. E. Plagnol and H. Inchauspé would also like to acknowledge the financial support of the UnivEarthS Labex program at Sorbonne Paris Cité (ANR-10-LABX-0023 and ANR-11-IDEX-0005-02).
Discussion The first generations of A. thaliana embryogenesis are characterized by stereotyped cell division patterns that present different orientations and volume-ratios between successive generations. Combining quantitative image analysis and a new 3D computational model of cell division, we report here an invariant positioning of division planes relative to mother cell geometries and show that a single geometrical rule linking cell geometry to division plane characteristics is able to explain the complete sequence of observed stereotyped patterns. Our data further suggested the rule could be interpreted based on area minimization constrained by the position of the nucleus, which was validated in leaf epidermal cell divisions. In the embryo, where the nucleus occupied a central position, the rule predicts the division plane as the minimum area surface among those passing through the mother cell centroid.
These parameters were computed on the 3D cell masks, which were obtained either directly from the segmented images or following reconstruction of mother cells based on lineage trees. Several shape factors were computed for each cell: three shape factors computed as ratios of volume, surface area, and mean breadth; three elongation factors computed as ratios of ellipsoid axis lengths; convexity, computed as the ratio of volume over the volume of the convex hull; geodesic elongation, defined as the ratio of geodesic diameter over the diameter of the inscribed ball. In total, 16 morphometric features described each cell. Division plane geometric measurements. For each division plane, a triangular mesh, a unit normal vector and a centroid were computed. The mesh was obtained by applying the Generate Surface function of Avizo Fire software (Copyright 2013 Visualization Sciences Group, an FEI Company) to the labeled image obtained by 3D segmentation.
The orientation of each division plane with respect to the external embryo wall was measured as the angle between its normal vector and the vector from G 1 to the centroid of the mother cell. To quantify changes in division plane orientation between generations, the angle between normal vectors to division planes from successive generations was measured. Statistical shape analysis. Using the individual cell morphometric features listed above, a multiple discriminant analysis was performed to quantitatively assess, at a given stage, the morphological differences between cell shapes in different domains of the embryo. The logarithm of the features was used to provide distributions closer to Gaussian ones. A linear discriminant analysis was applied on the centered and reduced data sets. We used the Fisher Linear Discriminant Analysis function contributed in Matlab by Sergios Petridis (https://fr.
Acknowledgments We thank  Jean-Denis Faure ,  Kian Hematy ,  Hermann Ho  ¨fte,  Patrick Laufs  and  Mark Tepfer  for helpful comments and critical reading of earlier versions of the manuscript. We used the cytology and imaging facility of the  Observatoire du Vegetal-Cytologie/imagerie  (supported by  Region Ile-de-France  and  Conseil General des Yvelines). This paper is dedicated to the memory of our colleague and friend  Olivier Grandjean , whose pioneer work and help contributed to the development of confocal microscopy at IJPB.
Pm-ERR gene activity by promoter cloning Gene activity was assessed by cloning the promoter region of Pm-ERR into a vector driving the expression of a GFP reporter. For this, a 1. 7 kbp fragment (-1705 from the Transcription Start Site, TSS, figure 6C) was selected from ascidian genome available on Aniseed database. This region, which is highly conserved with Phallusia fumigata, was amplified by PCR from P. mammillata genomic DNA and cloned upstream a H2B::Venus reporter by In-Fusion HD Cloning Plus kit (Takara Bio). The prepared construct (pERR>H2B::Venus) was microinjected in P. mammillata eggs and the transgenic embryos analyzed by confocal imaging (Leica TCS SP8).
Estrogen-Related Receptor (ERR) is expressed in Phallusia mammillata larvae In order to substantiate the possibility that BPA targets ERR in the ascidian embryo, we analyzed ERR transcripts and protein level during embryonic development (figure  5 ). Published transcriptomic data in the ascidian Aniseed database suggests that ERR transcripts are found at larvae (stage 26) but not before  (Gomes et al. 2019). ISH analysis revealed that, at stage 26, ERR is expressed within the sensory vesicle, more precisely above the ocellus, between otolith and ocellus and underneath the otolith, as well as in adhesive palps and trunk ganglion (figure 5A, black arrowheads). Since ISH staining using NBT/BCIP at such a late stage is made difficult by the secretion of the ascidian tunic (larvae become dark quickly), we further confirmed ERR zygotic expression by monitoring its promoter activity (pERR>H2B::Venus) in transgenic embryos (Stolfi and Christiaen 2012) (figure  5B ).
On the 20 injected larvae, all showed fluorescent nuclei (i. e. promoter activity) in the sensory vesicle, with 13 having additional cells in the adhesive palps, while the other 7 had additional cells in the trunk ganglion. Additionally, 2 larvae showed ectopic expression in the mesenchyme due to promoter leakiness previously reported in ascidians  (Stolfi and Christiaen 2012). Using an antibody specific for Pm-ERR (figure  5C ), ERR protein levels were measured during development by western blot analysis (figure  5D ). As expected from transcriptomic data available from the ascidian database Aniseed, ISH and promoter analysis, a strong band (≈ 50 kDa) was observed at stage 26 but not before.
BPA may target ERR during otolith movement in ascidian larvae Recent evidence demonstrates that BPA is a weak ligand for the estrogen receptor (ER) but high affinity ligand for the estrogen-related receptor gamma (ERR)  (Liu et al. 2014). This possibility was explored in the ascidian embryo. Ascidian genome have only one gene coding for ERR, and no estrogen nor steroid receptors  (Yagi et al. 2003). Transcriptomic data indicates ERR expression only at stage 26 for Ciona robusta and Phallusia mammillata (Aniseed database). In other ascidian species, PCR analysis showed that in Herdmania curvata ERR is expressed from gastrula (st. 10) throughout development  (Devine et al. 2002) , while Halocynthia roretzi ERR is expressed only from eggs up to gastrula  (Park et al. 2009). Transcriptomic data available for C.
the entire cDNAs were designed based on Aniseed (http://www. aniseed. cnrs. fr/) and Octopus (http://octopus. obs-vlfr. fr/index. php) databases and were obtained from the Phallusia mammillata cDNA library (pExpress-1 vector based) available in our laboratory. After amplification by PCR and confirmation by electrophoresis, PCR products were purified (Qiagen MinElute PCR purification kit, Qiagen) and DNA quantified. Digoxygenin-labeled antisense RNA probes (DIG RNA Labeling Mix, Roche) were then prepared and detection was based on NBT/BCIP (Roche) principle. The following genes were assessed: Tyr (gene ID: Phamm. g00005364), Rab32/38 (gene ID: Phamm. g00006935), Pax6 (gene ID: Phamm. g00010911), Cnga (gene ID: Phamm. g00015101), Coe (gene ID: Phamm. g00012706) and Islet (gene ID: Phamm. g00000576).
Acknowledgements The authors would like to thank  Filomena Ristoratore  and  Alberto Stolfi  for kindly providing ascidian tyrosinase-related protein and ßγCrystallin promoters, respectively. Furthermore, the authors would like to thank  Laurent Gilletta  and  Régis Lasbleiz  and the  Centre de Ressources Biologiques Marines of the Institut de la Mer de Villefranche (CRBM -IMEV ) that is supported by  EMBRC-France , whose French state funds are managed by the  Agence Nationale de la Recherche (ANR)  within the " Investissement d'Avenir" program  ( ANR-10-INBS-02 ). The experiments reported in this study were financed by an  ANR grant  ( Marine-EmbryoTox  project,  ANR-14-OHRI-0009-01-1 ). Ievgeniia Gazo thanks to the  Ministry of Education, Youth and Sports of the Czech Republic and projects CENAKVA  ( LM2018099 ) and  Reproductive and Genetic Procedures for Preserving Fish Biodiversity and Aquaculture  ( CZ.
0 specific requirements. According to predictions of World Economic Forum  [3] , it is expected a drastic change of the required skills in respect to the ones seen as important today. Future workforce requirements will cover cognitive abilities (52%), systems skills (42%), and complex problem solving skills (40%), in addition to the basics for information and communication technologies (ICT). Following the increasing of automation and digitalization of work processes, companies will depend on employees with ICT specializations who can analyze big data, make coding, develop applications and manage complex database networks. To perform effectively within Industry 4. 0 work environments, it is clear that employees should have continuous learning  [4] , updating their competencies not simply in their own professions but in a wider interdisciplinary perspective.
Infrastructure and environment To recall the good practices for managing the measuring environment where Fringe-projection Systems are in use. To safeguard reference standards to assure their integrity and stability. To assure fringe-projection performance by periodic maintenance and verification. As example, the seventh step is related to the data evaluation process, and it is one important element of attention in particular for Fringe-projection Systems. The related chapters cover the fundamentals of point cloud metrology. 3D measurement data generated by modern CMSs are large and dense sets of points representing the surfaces of parts (i. e. point clouds). Point clouds are the basis for the digitisation of parts into computer models, as needed for advanced product/process engineering and quality control.
Acknowledgements The authors wish to acknowledge the support of the  European Union  in the  Programme Erasmus+  through the  KA2  project " European Training for Coordinate Metrology 4. 0 ", agreement n°  2016-1-IT01-KA202-005441. The consortium includes 6 partners from 5 countries:  Università degli Studi di Padova, Italy ;  Centro e Apoio Tecnologico a Industria Metalomecanica Associacao , Portugal; CMTrain e. V. , Germany;  Friedrich-Alexander-Universität Erlangen Nürnberg, Germany ;  Interstaatliche Hochschule  für  Technik Buchs NTB, Switzerland ;  Ecole Normale Superieure Paris-Saclay, France. The authors also gratefully appreciate the feedback from employees of industrial companies and from university students that have participated to training courses and pilot testing activities.
Characterizations Structural characterizations of the Au, ZnO and AZO seed layers as well as ZnO NWs were performed using an X-ray Diffraction (XRD) with a CuK1 radiation on the high-resolution parallel beam diffractometer Brucker AXS D8 discover (Bruker, Karlsruhe, Germary). The morphological characterizations of the ZnO NWs surface and cross section were done by scanning electron microscopy (SEM) with a JEOL JSM-7900F (HRSEM, Croissy-sur-Seine, France). The extraction of the densities, lengths and diameters associated with the ZnO NWs was obtained using Image J software on SEM images  [31]. The surface topography of the seed layers was measured with a Dimension ICON Brucker Atomic Force Microscope (AFM, Bruker France SAS, Palaiseau, France). The resistivity of each seed layer was analyzed with a semi-automatic hall effect measurement system HMS 5000 Microworld (Microworld, Grenoble, France).
Acknowledgements. We thank the following for stimulating and fruitful discussions:  Jacques Magnaudet  ( Institut de Mécanique des Fluides, IMFT, Toulouse ),  Yannick Hallez  ( Laboratoire de Génie Chimique de Toulouse, LGC, Toulouse ),  Jean-Lou Pierson  ( Institut Francais du Pétrole Energies Nouvelles, IFPEN, Lyon ),  Jean-Luc Redelsperger  ( Laboratoire de Physique des Océans, IFREMER, Brest ),  Jean-Pierre Pinty  and  Juan Escobar  ( Laboratoire d'Aérologie, LA, Toulouse ),  Odile Thouron ,  Thibaut Lunet ,  Luc Giraud ,  Isabelle d'Ast  and  Gerard Dejean  ( Centre Européen de Recherche et Formation Avancée en Calcul Scientifique, CERFACS, Toulouse ). The simulations were performed on the Neptune/Nemo-CERFACS supercomputers on the Occigen-CINES Bull cluster (c2016017724 and a0010110079  GENCI  projects).
Regarding advances in simulations, Haervig et al. [21]  screened with a genetic optimization algorithm 26 common working fluids for a heat source in the temperature range of 50-280 • C. Critical conditions and the slope of the vapor line were found to be important criteria of optimization parameters for a given heat source temperature. Dickes et al. [22]  developed a charge-sensitive model of a 2 kWe recuperative ORC to characterize and optimize the performances of ORC for off-design operation. Regarding the available experimental studies screened thanks to the Landelle et al. [23]  database, two working fluids have been principally investigated in the corresponding ORC literature: R-245fa  [24, 25]  and R-123  [26, 27]. Galloni et al. [28]  and Chang et al. [29]  both studied an ORC system with a scroll expander and R-245fa as the working fluid in an ORC system.
To the best of the authors' knowledge, less than 20 experimental studies are available in the current ORC literature, and, consequently, each of them has been implemented in the available database to be clearly compared. Theoretical and simulation analyses of zeotropic mixtures' impacts in the ORC have provided some trends and assumptions in terms of ORC behaviors and performances. Xiao et al. [66]  and Zhai et al. [67]  studied the reduction of irreversibility in hot and cold ORC exchangers. They pointed out that the use of zeotropic mixtures could lead to an optimization of the heat and sink sources according to specific operations of an ORC system and improve the exchanger and global installation performances. Zhai et al. [67]  and Zhao et al. [68]  studied the optimal heat source temperature for a zeotropic mixture.
Instrumentation All sensors used for measurements and data acquisitions are shown in the PFD of the installation in Figure  1a. The characteristics of the measurement devices are listed in Table  2. The working fluid and the heat source and cooling source loops are equipped with Type-K thermocouples to measure temperatures between the various components. The working fluid circuit is equipped with absolute pressure sensors (APS) at the turbine inlet and outlet to measure the two pressure stages within the installation. Volumetric flow rate measurements of hot and cold circuits were performed using electromagnetic flow meters (EFMs). The mass flow rate of the working fluid is determined by the energy balance at the condenser of the experimental installation. The electrical power produced at the turbine was measured by means of a wattmeter.
Thermodynamic Investigation The study of the ORC installation, based on experimental data, was carried out using a zero-dimensional (0D) model, by solving energy balances on components and the global system, developed with EES software  [77]. A coupling was carried out with the REFPROP v9. 1 software  [78]  to allow for the implementation of thermodynamic properties in the mixture and the pure fluid. These properties result from Helmholtz's model adapted for the considered fluids  [79, 80]. According to the theory of uncertainties propagation, the measurement uncertainties for the calculated output variables of the model were calculated using the root-sum-square method. The uncertainty U Y of the variable Y was calculated as a function of the uncertainties U Xi for each measured variable X i , as defined in Equation  (1).
ORC Literature Comparison The present installation was analyzed in terms of global ORC performances regarding its thermal efficiency and its second law efficiency. To perform an accurate analysis in comparison with other ORC installations and working fluids, the best operating point of the ORC in pure Novec TM 649 and the zeotropic mixture Novec TM 649/HFE7000 were compared with those in the available experimental ORC literature database  [23]. The global ORC performances have reached respectively for the pure fluid and the mixture the value of 5% and 5. 6% for the net thermal efficiency, and the value of 20. 8% and 22. 4% for the net second law efficiency. These efficiencies refer to the experimental points with the highest power production at the expander outlet mentioned in the previous Section 4.
1. To carry out the broadest comparison possible with the literature, efficiencies were screened as their gross efficiencies. The other calculated data for the optimized highest points are listed in Table  4. The T-s diagrams of the ORC for these two points are also presented in Figure  8. It can be noticed that, for the zeotropic mixture, the highest point corresponds to a good agreement between the evolution of the zeotropic glide and the evolution of the sink source temperature. Extracted from the literature database, experimental ORCs were arranged from the lowest to the highest gross thermal efficiency or gross second law efficiency by their cumulative distribution function for the selected power range up to 10 kW and heat source temperature lower than 200 • C. This ordering method allows us to rank the ORC investigated in this study and to compare its performances to those of other installations.
32 g/cm 2 ) on Ge (density 5. 32 g/cm 2 ), for monoenergetic beams of 5, 10, and 20 keV are given in Supplementary Fig. 5. These parameters were calculated using the Monte Carlo simulation CASINO  83  package in order to optimize the CL emission depth profile of GaAs films and compare the recombination behavior at the surface and in the bulk for each substrate. CASINO simulation of the electron interaction volume of a 300 nm-thick GaAs film grown on Ge substrate is presented in Fig. 7a, e. The color scale indicates the irradiated electron energy concentration. The thickness of GaAs used in this work has been overlaid in the diagram to facilitate comparison. Simulations show that interactions occurring near the surface could be revealed using 5 keV e-beam and across the entire layer of GaAs using 20 keV e-beam.
For the NVS, we observe a significant recovery of   7  Effect of reducing dislocations on optical properties. Monte-Carlo simulations using CASINO software of the electron interaction volume, and planar cathodoluminescence (CL) micrographs of a 300 nm-thick GaAs layer grown on bulk Ge substrate, Ge/Si substrate, and the NVS at 5 keV (a-d) and 20 keV (e-h), respectively. The color scale bar in a, e shows the electron concentration. The CL micrographs in b-h show the emission and the recombination behavior at the surface (5 keV) and in the bulk (20 keV) of GaAs on each substrate. Scale bars 3 µm. Room temperature cathodoluminescence spectra recorded from i GaAs/Ge, j GaAs/Ge/Si with a TD density of ~10 7 cm -2 and k GaAs/NVS with a TD density of ~10 4 cm -2 , at 5 and 20 keV. CL measurements confirm that the dislocations were effectively blocked from propagating using nanovoids, which is reflected by an enhancement of the emission efficiency of GaAs grown upon the NVS the CL intensity, when compared with the GaAs/Ge/Si sample.