dataesr/scientific-paragraphs-categorization huggingface dataset:
Magellan To observe most of our targets in the South Galactic Cap (SGC), and most of the relatively high-redshift targets, we used the Magellan Clay 6. 5m telescope with the Low Dispersion Survey Spectrograph 3 (LDSS3)-C spectrograph. Observations were carried out over the nights 2016 July 26-29. The LDSS3-C instrument consists of a grism situated behind an aperture plate; we opted to use the VPH-All grism (covering 4250-10000 Å) with the standard 1. 0 × 4. 0 center long slit mask. The LDSS3-C spectrograph has better efficiency toward redder wavelengths (7000 < λ < 10000 Å) than the MMT's Blue Channel, so we preferred it for higher-redshift objects. Reductions were carried out both using standard IRAF techniques, and the pydis software adapted for use with LDSS3 data.
Spectral Decomposition We use the QSfit spectral decomposition code from  Calderone et al. (2017)  to analyze the SDSS and follow-up spectra. We fit simple power-law continuum components, iron optical and UV templates, Balmer continuum, broad emission line, narrow emission line, and host galaxy components. The Fe II templates are based on the narrow-line Seyfert 1 (NLS1) AGN I Zw 1  (Vestergaard & Wilkes 2001; Véron-Cetty et al. 2004) , with the UV iron equivalent 2 http://jradavenport. github. io/2015/04/01/spectra. html width (EW) fixed to avoid a degeneracy with the continuum slope. The host galaxy template is a typical AGN host  (Silva et al. 1998; Polletta et al. 2007 ). We adopt the redshifts and E(B -V ) values from the DR7Q catalog. We exclude spectra where the median S/N is 2. For an example spectral decomposition near Hβ, see Figure  1.
The CRTS data resolve the time of transition more often than the SDSS/PS1 light curves, but due to the unfiltered bandpass, the CRTS light curves are less sensitive than the g-band to blue continuum variability. The results from light curve modeling (following  Koz lowski et al. 2010; MacLeod et al. 2010 ) and characterization (following  Kim et al. 2011 ) of the SDSS/PS1 or CRTS photometry essentially confirm our selection of CLQ candidates: that they have a large change in flux at some point between the SDSS and Pan-STARRS data (leading to longer characteristic timescales, e. g. ). Among those CLQ candidates that we followed up spectroscopically, we notice no overall difference between the light curves of CLQs versus non-CLQs.
Predictive modeling, where the expected variability is predicted either for a given night or over a particular timeframe, could prove useful here (see  Graham et al. , 2019, PASP). It is unclear whether the same physical processes are occurring in/around the accretion disks in extremely variable quasars. But there are some hints of outliers and interesting objects; this problem will also be easier to solve with larger datasets of repeat quasar spectroscopy. Samples have recently grown substantially in the SDSS-IV TDSS  (Morganson et al. 2015; MacLeod et al. 2018) , forming a pilot to even larger spectroscopic surveys upcoming in SDSS-V  (Kollmeier et al. 2017). A sample of newly discovered CLQs from SDSS-IV will be presented in  MacLeod et al. (2019). The ideal survey would provide dense cadence repeat spectroscopy of a large sample of quasars, e.
This material is based upon work supported by the  National Science Foundation  under Grants No. AST-1715763  and  AST-1715121. The work of DS was carried out at the  Jet Propulsion Laboratory, California Institute of Technology , under a contract with  NASA. We thank  Marco Lam  and  Nigel Hambly  for assistance with the PS1 DVO database hosted at Edinburgh. We thank  Peter Blanchard  for assistance in carrying out Blue Channel observations. CLM would like to acknowledge  Zeljko Ivezic ,  Martin Elvis  and  Fabrizio Nicastro  for useful discussions regarding the Eddington ratio and disk-wind model. We thank an anonymous referee for their very helpful and thorough comments. Funding for the SDSS and SDSS-II has been provided by the  Alfred P. Sloan Foundation , the Participating Institutions, the  National Science Foundation , the  U.
The Pan-STARRS1 Surveys (PS1) have been made possible through contributions of the  Institute for Astronomy , the  University of Hawaii , the Pan- STARRS  Project Office, the  Max-Planck Society  and its participating institutes, the  Max Planck Institute for Astronomy, Heidelberg  and the  Max Planck Institute for Extraterrestrial Physics, Garching , The  Johns Hopkins University, Durham University , the  University of Edinburgh, Queen's University Belfast , the  Harvard-Smithsonian Center for Astrophysics , the  Las Cumbres Observatory Global Telescope Network Incorporated , the  National Central University of Taiwan , the  Space Telescope Science Institute , the  National Aeronautics and Space Administration  under Grant No. NNX08AR22G  issued through the  Planetary Science Division of the NASA Science Mission Directorate , the  National Science Foundation  under Grant No.
AST-1238877 , the  University of Maryland , and  Eotvos Lorand University (ELTE). The  CSS  survey is funded by the  National Aeronautics and Space Administration  under Grant No. NNG05GF22G  issued through the  Science Mission Directorate Near-Earth Objects Observations Program. The CRTS survey is supported by the  U. S. National Science Foundation  under grants  AST-0909182  and  AST-1313422.
2003) , with a spectral resolution R ∼ 230. Standard data processing is performed using the VIPGI environment  (Scodeggio et al. 2005) , followed by redshift measurement using the EZ package  (Garilli et al. 2010). The target selection produces a final VUDS sample representative of the starforming galaxy population in the redshift range 2 < z < 6. 5, flux-selected from the rest-frame continuum UV luminosity. An important aspect of the VUDS is the wide field (large volume) covered. A total of 1 deg 2 is covered in three fields including the COSMOS, ECDFS and VVDS-02h fields. This enables to reduce cosmic variance in the redshift range of interest, to below 10%  (Moster et al. 2011). We identify galaxies with Lyα in emission as well as in absorption  (Le Fèvre et al. 2015, e. g. Figure 19 and 20) , and the fraction of Lyα emitters with EW(Lyα)>25Å in the redshift range of this study is ∼ 11%  (Cassata et al.
2013). We conclude that the co-evolution of stellar populations and AGN is a key ingredient to the star formation evolution and mass build-up in galaxies at these early times. Future experiments assembling larger datasets will be necessary to investigate whether the AGN feedback and quenching identified in the redshift range of this paper and beyond is mass-dependent. The results presented here point to the need for large comprehensive spectroscopic surveys with the power to identify galaxy populations which may appear as rare but provide important clues on the first phases of galaxy assembly. Our study paves the way to a systematic use of spectral line properties and diagnostics from the UV to optical rest-frame for future investigations using next generation facilities like the James Webb Space Telescope and ELTs.
Acknowledgements. This work is supported by funding from the  European Research Council Advanced  Grant  ERC-2010-AdG-268107-EARLY  and by  INAF  Grants  PRIN 2010 ,  PRIN 2012  and  PICS 2013. AC, OC, MT and VS acknowledge the grant  MIUR PRIN 2015. This work is based on data products made available at the  CESAM data center, Laboratoire d'Astrophysique de Marseille, France.
Methods Forsterite Mg 2 SiO 4 is modelled using the so-called THB1 semi-empirical potential  [19] [20] [21]. This potential model is based on an ionic pair potential description using formal charges combined with classical Buckingham form at short range, supplemented by a harmonic three-body term to represent the directionality of O-Si-O bonds of SiO 4 tetrahedra  [22]  and a shell model  [23]  to account for oxygen polarizability. The parameterisation of the force field have been successfully used for modelling bulk, defect properties of forsterite  [20, [24] [25] [26] [27] [28]  and also olivine phase transformations  [29, 30]  emphasising the transferability of the parameterisation to high pressure calculations. In this work, all the simulations have been performed using the LAMMPS molecular simulation package  [31]  for which THB1 has been recently implemented as a potential library  [27].
Each resolved plate was scanned using a Chemidoc TM MP Imaging System (Bio-Rad), and densitometric analyses were performed using the ImageLab TM software version 5. 0 (Bio-Rad) to determine relative TAG content per sample. In graphs, histograms represented the mean ± standard deviation of at least two or three independent experiments. Differences were considered statistically significant when p-values tested ≤ 0. 05 with a one-way ANOVA. Nile Red staining and fluorescence microscopy. Mycobacterial cultures were assessed for ILI formation using Nile Red staining as previously described  28  with slight modifications. Approximately 7. 5 × 10 7 mycobacterial CFU were centrifuged in Eppendorf tubes for 5 min at 5,000 g. Pellets were washed twice with 500 µL PBS buffer and re-suspended in 300 µL of PBS.
51 K (NIH, USA). Analysis of average fluorescence intensity was calculated using ImageJ 1. 51 K software with five snapshots from two independent cultures stained on independent occasions. GraphPad Prism 4 was used for performing statistical analyses, where differences in fluorescence intensity were considered significant when the calculated P-values were smaller than 0. 05 using a two-tailed Mann-Whitney test. processing for electronic microscopy. Bacteria were fixed at room temperature with 2. 5% glutaraldehyde (Sigma) in Na-cacodylate buffer 0. 1 M (pH 7. 2) containing 0. 1 M sucrose, 5 mM CaCl 2 , and 5 mM MgCl 2 , washed with complete cacodylate buffer and post-fixed for 16 h at room temperature with 1% osmium tetroxide in the same buffer without sucrose  65. Finally, samples were washed twice in cacodylate buffer and dehydrated in a graded series of ethanol solutions and gradually incorporated in Spurr resin.
Thin sections (80 nm thick) were stained with 1% uranyl acetate in distilled water and then with lead citrate before being observed by electron microscopy. Image acquisition was performed with a FEI Tecnai G2 20 TWIN 200 kV Transmission Electron Microscope, using a Lab6 cathode and an Eagle 2k camera. Images were processed using the open source program ImageJ 1. 51 K (NIH, USA). Concerning statistical analysis, between 300 and 400 mycobacteria per sample were examined under a TEM to determine the percentage of each category of M. smegmatis or M. abscessus ILI profiles. Cells were examined at random, and care was taken to avoid serial sections. Mycobacteria were previously divided into 3 different categories, according to the number/size of ILI  8, 26. Bacteria displaying no or few small ILI (0.
For fluorometric MIC determinations, a background subtraction was performed on all wells with a mean of the M wells. Relative fluorescence units were defined as: RFU% = (test well FU/mean FU of B wells) × 100. MIC values were determined by fitting the RFU% sigmoidal dose-response curves in Kaleidagraph 4. 2 software (Synergy Software)  70, 72. The lowest drug concentrations inhibiting 90% of growth was defined as the MIC 90. phenotypic antibiotic resistance by plate count method (CFU counting). The phenotypic antibiotic resistance against different concentrations of RIF, INH and KAN was measured by the plate count method (CFU counting). A 24 h-logarithmic-phase M. smegmatis culture in either 7H9 or MSM NL Gly 1% medium was diluted to an OD of around 0. 05 (i. e. , 5 × 10 6 cells/mL) and split into 5 mL samples, then drugs were added at either 10 µg/ mL (KAN) (corresponding to 10× MIC) or 12 µg/mL (INH, RIF) (corresponding to 4 × MIC), with an untreated sample serving as a control.
Bacterial burden and granuloma quantification. For microscopy experiments, zebrafish embryos were anaesthetized in a tricaine solution and mounted in 3% methylcellulose (Sigma-Aldrich) for imaging on a Zeiss Axio Zoom. V16 coupled with an Axiocam 503 mono (Zeiss). Image acquisition and processing was completed using ZEN 2 software (blue edition). Bacterial burden was measured as the number of pixels contained within each embryo above the background fluorescence with the ImageJ software version 1. 51w (National Institutes of Health). Fluorescent pixels were counted using the ' Analyse particles' function with threshold settings kept consistent for the duration of each experiment. To enumerate granuloma abundance, bacterial (green) and macrophage (red) fluorescent signals were merged using ImageJ to identify infection foci.
Acknowledgements This work was supported by the  CNRS  and  Aix-Marseille Université. PS received financial support for his PhD fellowship from the  Ministère Français de l'Enseignement Supérieur, de la Recherche et de l'Innovation. MDJ received financial support for his post-doctoral fellowship granted by  Labex EpiGenMed , an  « Investissements d'avenir » program  (reference  ANR-10-LABX-12-01 ). AV's post-doctoral fellowship was granted by  Fondation pour la Recherche Médicale  ( FRM -grant   N° DEQ20150331719 ). Special thanks are addressed to  Dr. Chantal de Chastellier ,  Pr. Sophie Bleves  and  Dr. Eric Durand  for their advices and continuous supports. PS, JFC and SC would like to thank  Laura Gallorini  for technical assistance. This work has benefited from the facilities and expertise of the  Platform for Microscopy of the Institut de Microbiologie de la Méditerranée FR3479 CNRS.
The morphing induces a lock-in of the buffet's frequency with the actuating frequency, reduces the separated region of the boundary layer and the thinning of the wake's width. In addition, a slight deflection of the trailing-edge upward showed efficient lift to drag ratio compared to the classical fixed wing-flap. This study focuses on the understanding of the morphing effects on the flow around the two-element wing-flap system and the improvement of the aerodynamic forces in the take off position of a two-element wing flap of the Airbus A320 at a large scale. The objectives of the present paper are summarized as follows : • Explain the dynamic deformation of the structured multi-block grid using advanced numerical methods implemented in the NSMB code  [8]  with a conservation of the same mesh properties.
3  Flow chart of the dynamic morphing implemented in the NSMB solver grids, the first grid is the fluid domain including the wing and the second one is around the flap in Fig. 2  (left). This grid is used for optional configurations of Take-off and Landing where the flap changes its deflection angle from 10 • to 40 • degrees. The grids have been tested in the NSMB code and a mesh independence have been studies for the pressure coefficients with the experimental results is provided in Fig. 2  (right). The results show a very similar Pressure coefficient Cp for both grids. The refined single grid is selected to continue this study. The presence of the walls in the IMFT wind tunnel S4 has an effect on the pressure coefficient, the wing was mounted wall-to-wall in the wind tunnel and a good comparison of numerical experimental will be achieved in the future.
We compared for this present study the flow in 2D in the Fig. 2  (right) the numerical simulation to the results of GA(w)-2 airfoil-flap (W. LU  [9] ) which is almost similar airfoil properties as the A320, but with a smaller flap. The simulations have been carried out with the NSMB solver. The NSMB solver is the fruit of a European consortium that included Airbus from the beginning of '90s, as well as main European aeronautics research Institutes, as KTH, EPFL, IMFT, ICUBE, CERFACS, Univ. of Karlsruhe, ETH-Ecole Polytechnique de Zurich, among other. This consortium is coordinated by CFS Engineering in Lausanne, Switzerland. NSMB is a structured code that includes a variety of efficient high order numerical schemes and of turbulence modelling closures in the context of LES, URANS and of hybrid turbulence modelling.
A first description of the code can be found in Vos et al. (1998)  [8]  concerning the versions of this code in the decade of '90s. Since then, NSMB highly evolved up to now and includes an ensemble of the most efficient CFD methods, as well as adapted fluid-structure coupling for moving and deformable structures. These developments can be found in  Hoarau (2002)   [10]  and Hoarau et al (2016)  [11]  regarding URANS modelling for strongly detached flows,  Martinat et al. (2008)   [12] , in the area of moving body configurations, Barbut et al. (2010)  [13]  and Grossi et al. (2014)  [14]  allowing for Detached Eddy Simulation with the NSMB code. NSMB solves the compressible Navier-Stokes equations using a finite-volume formulation on multi-block structured grids. In the present work, a fourth-order central scheme is used for the spatial scheme and an upwind second order for the temporal scheme.
E. Morphing strategy Unsteady flow calculations for problems with deformable surface shapes is investigated using grid deformation for a multi-block, structured mesh. A polynomial second order equation is implemented in the NSMB code to calculate the time-dependant dynamic displacement. A frequency f a of actuation, an amplitude a and a displacement d are imposed for the the flap's trailing-edge as presented in the Fig. 1. The Figure  4  represents an example of actuation compared to the static case. This dynamic vibration modifies the flow in the shear-layer of the wake and changes the behaviour of the flow dynamics. Fast and reliable method for deforming the computational grid during each step of the time simulation is needed while maintaining a good mesh quality as the orthogonality and the smoothness.
The remeshing algorithm implemented in the code NSMB combining the Volume Spline Interpolation (VSI) and Transfinite Interpolation (TFI)  [18]. These methods collect at first the imposed displacement of the trailing-edge and creates a list of vortices. The Volume Spline Coefficients calculation requires a matrix inversion of a full square matrix N + 1 rows where N is the number of vertices on the configuration surface. Only moved block edges using VSI method are taken into account which is one of the advantages of the VSI method that does not require all the coordinates. Next, the Trans Finite Interpolation is used to generate the displacement of block faces coordinates in two-dimension or the volume in three-dimension. Finally, the new deformed grid is computed based on the imposed deformation fixed as an input as presented in the Fig.
Acknowledgments The authors are grateful to the  National Supercomputing centres CALMIP, CINES, HPC Strasbourg, IDRIS  for the Computer allocation and the  PRACE Supercomputing allocation   N°2017174208. This work has been carried out within the  Research programme N°723402: "Smart Morphing and Sensing " (SMS) http://smartwing. org/SMS/ EU. This project is funded from the  European Union 's  H2020 program  for research and development of technology.
While bacteria, plants, and fungi are able to biosynthesize riboflavin, humans and animals must obtain it from their diet, positioning riboflavin biosynthetic enzymes and regulatory factors as promising specific targets for antimicrobial therapies  [11]. In fact, riboflavin biosynthesis has been shown to be essential in many pathogenic bacteria that lack riboflavin transporters, such as Mycobacterium tuberculosis, Brucella abortus and some Salmonella and Escherichia species  [12] [13] [14] [15] [16]. The biosynthetic riboflavin pathway has been described in detail [9,  [17] [18] [19]. lumazine synthase (LS, EC database: 2. 5. 1. 78) catalyzes the penultimate step, allowing the condensation of 5-amino-6-ribitylamino-2,4 (1H,3H)-pyrimidinedione with 3,4-dihydroxy-2-butanone-4-phosphate to generate 6,7-dimethyl-8-ribityllumazine.
Riboflavin synthase (RS, EC database: 2. 5. 1. 9) catalyzes the last step, which corresponds to the dismutation of two molecules of 6,7-dimethyl-8-ribityllumazine (a and b) to yield one molecule of riboflavin c, with the regeneration of one molecule of 5-amino-6-ribitylamino-2,4 (1H,3H)-pyrimidinedione d (Fig. 1A ). Our laboratory has studied in detail these enzymes from B. abortus. For the former, we have identified two isoenzymes (RibH1 and RibH2/BLS) and characterized their tertiary and quaternary structures as well as their biochemical properties  [20, 21]. We have also assayed the relevance of the RibH enzymes in bacterial infection and demonstrated that the presence of at least one functional LS enzyme is essential for intracellular survival and that RibH2/BLS is necessary for mice colonization.
Mobility shift-based screening assay (MSA) The MSA was performed on a Caliper LabChip 3000 Drug Discovery instrument (Caliper Life Sciences, Waltham, MA, USA) in an off-chip mode. The reaction buffer contained 50 mM HEPES, 0. 02% Tween 20, 1 mM DTT, 0. 02% BSA, 10 lM Na 3 VO 4 , and 10 mM b-Glycerophosphate, pH 7. 5. The NIBR Drug Discovery Incubator library for external collaborations comprises 44 000 pure chemical compounds accessible from the Hit Finding Unit of Novartis Pharma AG (Basel, Switzerland). The compounds were selected according to their chemical diversity and drug-like properties, and their purity was assessed by LC-MS (data not shown). A quantity of 90 nL of the compound stock solutions [at 10 mM in 90% (v/v) DMSO/water] was placed in a 384-well assay microtiter plate (Corning Inc.
Statistical analysis Statistical analyses were performed with One-way ANOVA with a Bonferroni's multiple comparison post hoc test using GRAPHPAD PRISM5 (GraphPad Software, San Diego, CA, USA). Data are presented as mean AE standard deviation (SD). P-values of 0. 05 or lower were considered as significant. Statistical significance levels were defined as follows: *P < 0. 05; **P < 0. 01; ***P < 0. 001.
Among the various tools, the framework offers a symbolic model checker called RGMEDD. This tool generates the state space of a Petri net using Multivalued Decision Diagrams (MDD) and implements a CTL model checker with counter-example generation. The implementation of the MDD data structure is based on the highly-optimized Meddly library  [7]. Main Features of GreatSPN. The symbolic model checker of GreatSPN participates in the MCC'2019 competition for StateSpace generation, deadlock search and CTL model checking for both P/T and colored nets. The model evaluation strategy consists of the following main steps: 1. Translation phase: a set of support tools convert the PNML model, the NUPN 4  metadata and the CTL formulas into the internal format of Great-SPN. Colored (symmetric) models are unfolded to their corresponding P/T models.
ITS-Tools ITS-tools  [34]  is a model-checker supporting both multiple solution engines and multiple formalisms using an intermediate pivot called the Guarded Action Language (GAL). Both colored models and P/T models are translated to GAL. GAL models are more expressive than Petri nets, and support arithmetic and hierarchical descriptions. ITS-Tools is composed of a user-friendly front-end embedded in Eclipse, and of a command line solution back-end. Main Features of ITS-Tools. ITS-Tools uses a powerful symbolic solution engine based on Hierarchical Set Decision Diagrams (SDD)  [16]. SDD are shared decision diagrams where edges are labeled with a set of values. Since decision diagrams compactly represent a set, this allows to introduce hierarchy in the representation, and enables sharing of substructures of the diagram (different edges of the SDD labeled by the same set share their representation).