dataesr/scientific-paragraphs-categorization huggingface dataset:
The atomic line data for the bound-bound transitions, which constitutes the main and most important source of opacity in SNe Ia, are taken from the extended set of lines by Kurucz 14. Following a bound-bound interaction, most photons (a fraction ϵ, which is a global parameter of the simulation; see  Kasen et al. 2006 ) are thermalised and re-emitted at a different wavelength with a distribution set by the emissivity. The rest of the photons (fraction 1 -ϵ) are re-emitted at the same wavelength (within the line width). As in  Wygoda et al. (2019) , we used ϵ = 0. 8 in the runs performed here. The runs here use 162 spatial cells for the toy01 and toy06 models and 115 spatial cells for the DDC10 and DDC25 models. All models are run with 128 time steps logarithmically spaced between 2 and 210 days, and a uniform spectrum resolution of 10 Å between 100 and 30 000 Å.
Delayed-detonation model files The two delayed-detonation model files DDC10_0. 976d. dat and DDC25_1. 300d. dat represent a snapshot of the ejecta at 0. 976 days and 1. 3 days, respectively, with 115 shells with the following 50 columns 17 : (1) Velocity at shell centre (km s -1 ) (2) Radius at shell centre (cm) = velocity at shell centre × the time post explosion 15 https://github. com/sn-rad-trans/data1 16 For the STELLA runs, the files snia_toy01_1h_lowres. dat and snia_toy06_1h_lowres. dat represent a snapshot of the ejecta at 1 h post explosion and include 202 shells (rows) with the same structure. 17 For the STELLA runs, the files DDC10_29. 29s_highres. dat and DDC25_62. 60s_highres. dat represent a snapshot of the ejecta at ∼29 s and ∼63 s post explosion, respectively, with 399 shells.
Output file names The name of each file has the following structure: <output type>_<model>_<code name>. txt where -<output type> represents the type of output (described below) and can take one of six values: lbol_edep, edep, phys, ionfrac_<element> (where <element> is the name of a given element, e. g. ca for calcium), spectra, and wsynphot_mags, -<model> represents one of the models and can take one of four values: toy06, toy01, ddc10, and ddc25, -<code name> represents the code name with an optional additional descriptor (useful to distinguish between different code settings when applied to a given model) and can take one of 12 values: artis, artisnebular, cmfgen, crab, kepler, sedona, stella, stella_fr600 (for the STELLA runs for the toy06 models that use 629 frequency bins instead of the default 129), supernu, sumo, tardis, and urilight.
Example results In this section, we provide example results that are extracted from the outputs of the different simulations. The purpose of this section is to illustrate the contents of the data repository and comparisons that can be made using it. No comparison to observations or in-depth investigations of the sources of differences in   10 ) (the normalisation allows differences to be seen more clearly). results are made here. We note that while some groups provided a few sets of results for different physical approximations that appear in the repository, only one set of results is shown for each code in this set of examples. One exception is ARTIS, for which both the regular (artis) and nebular (artisnebular) versions are included for each model in order to present results for this code from early to late times.
Multi-band light curves and colours In this section, multi-band properties are shown for the different codes for different models. The photometry is extracted from the spectra reported in the spectra output files using the wsynphot package 19 (using the Vega calibration spectrum alpha_lyr_stis_003. fits 20 and a third-order spline interpolation). In Fig. 8 , the U BVRI JHK light curves are shown for model toy06 up to 100 days after explosion. The B-band rise times (from explosion to peak) are extracted by fitting a high-order polynomial around maximum light and shown for all models in Fig. 9. The B -V and V -R colour curves for model toy06 are shown in Fig. 10.
Discussion and outlook In this paper, we present an online public data repository that includes test models for radiative-transfer (RT) calculations of emission from SNe and standardised simulation outputs by ten different groups that allows direct comparison. Python scripts that generate the analytic toy models and read the different formats are provided as well. The main purpose of the repository is to allow studies of the different physical approximations involved in the different codes and to assess the robustness of different predictions of radiation transfer. In addition, the repository can be used for finding bugs in the codes or can provide checks in the development of new codes. We plan to extend the set of test models to include other SN types, as well as multi-dimensional models.
In addition, we intend to produce more specialised test cases for which exact solutions can be found and agreed upon; these will provide benchmarks for RT code development. We also aim to include models with standardised atomic data sets that will allow the study of the effects of atomic physics on the emission for the different approximations. Other groups that are developing RT codes are encouraged to add their results to the repository in the standardised format. Information for this purpose is provided in the README. md file in the repository. Notes: Due to a g f cut (level dependent, g f > 10 -4 ) only 1 292 015 lines were included in the non-LTE calculations of the level populations. 2 082 610 lines were included when computing the observed spectrum. Prior to 4. 25 days post explosion a higher cut was used (g f > 10 -3 ) in order to ease convergence.
Acknowledgements. The results presented in this paper are based on work performed before February 24, 2022. We thank the  Schwartz/Reisman Institute for Theoretical Physics at the Weizmann institute of science  and the  Max Plank Institute for Astrophysics  for hosting the workshops during 2018-2019 which lead to this collaboration. This work was supported by the  'Programme National de Physique Stellaire' (PNPS)  of  CNRS/INSU  co-funded by  CEA  and  CNES. This research was supported by the  Excellence Cluster ORIGINS  which is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation ) under Germany's Excellence Strategy EXC-2094-390783311. SB acknowledges support from the  ESO Scientific Visitor Programme in Garching. CC acknowledges support by the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  under grant agreement no.
S. A. S. acknowledges funding from the  UKRI STFC  Grant  ST/T000198/1. Part of this work was performed using the Cambridge Service for Data Driven Discovery ( CSD3 ), part of which is operated by the  University of Cambridge Research Computing  on behalf of the  STFC DiRAC HPC Facility  (www. dirac. ac. uk). The DiRAC component of CSD3 was funded by  BEIS  capital funding via STFC capital grants  ST/P002307/1  and  ST/R002452/1  and  STFC  operations grant  ST/R00689X/1. DiRAC is part of the  National e-Infrastructure. M. W. acknowledges support from the  NASA   Future Investigators in NASA Earth and Space Science and Technology grant  ( 80NSSC21K1849 ) and support from the Thomas J. Moore Fellowship at  New York University. Los Alamos National Laboratory  is operated by  Triad National Security, LLC , for the  National Nuclear Security Administration of U.
19 https://github. com/starkit/wsynphot 20 https://archive. stsci. edu/hlsps/reference-atlases/ cdbs/calspec/alpha_lyr_stis_003. fits 21 SEDONA also has non-LTE capabilities but these were not used here. A&A 668, A163 (2022) 1. 0 0. 20 ARTIS -1 Å-1 ] 0. 8 ] -1 Å-1 0. 15 CMFGEN SUMO erg s 0. 6 erg s 0. 10 L λ [10 39 0. 2 0. 4 L λ [10 39 0. 05 0. 0 4000 6000 8000 10000 0. 00 4000 6000 8000 10000 Wavelength [ Å] Wavelength [ Å] A163, page 17 of 25.
Study Design and Patient Selection This pilot, prospective and bicentric study was approved by the Ethics Committee (Comitede Protection des Personnes, Ile de France V, France) and was registered on Clini-calTrials. gov (NCT04230642). The inclusion criteria were percutaneous ablation under CT guidance validated by a multidisciplinary tumor board targeting one or two liver tumors in adult patients who have the ability to understand and sign the informed consent. Exclusion criteria were pregnancy, breast-feeding women, patients unable to undergo general anesthesia, patients unable to tolerate CT contrast agent, or participating to another clinical study.
Post-operative Assessment and Ablation Success A CT-scan acquisition was performed at the end of the intervention to ensure the absence of complication, and to assess whether the tumor was completely ablated or not. The patients were then reviewed periodically every 3 months using either CT-scan or MRI to assess LTP, as per standard practice guidelines  [13]. The follow-up performed after a minimal 6-month period was to collect data to assess the local tumor control rate, as routine follow-up.
Ablation Feasibility Feasibility was defined as a needle placement judged by the operator as adequate to perform ablation. The operator visually estimated on the post-insertion CT-scan if the needle was positioned accurately enough compared to the planned trajectory. To confirm feasibility assessment, the post-insertion CT-scan was ultimately reviewed by the Data and Safety Monitoring Board (DSMB), constituted of 2 experts in interventional radiology and one expert in digestive surgery who worked in different institutions.
Statistical Analysis All statistical analyses were performed using SASÒ 9. 4 software (Cary, NC, USA). Description of relevant study variables was: n (total number of data), number of missing data, mean, standard deviation (SD), median, min and max for quantitative variables and using number of missing data, frequency and percentage of non-missing for qualitative variables. The statistical analysis took into account data clustering (several ablations for a given patient) in case of inferential statistics. Data were analyzed according to both the intention-to-treat (ITT) and per protocol (PP) principles.
Patient Flow and Baseline Data From May 2020 to January 2021, 22 patients were enrolled with 26 liver tumors. Patients were either treated at the institution A (n = 16) or B (n = 6) (Fig. 1 ). During the study period, one patient (with two tumors) for which the ablation procedure was not maintained was considered as a screening failure and was therefore excluded from the study. Of the 21 patients with 24 tumors remaining in the ITT population, one patient (with one tumor) was excluded from the PP analysis due to protocol deviation (the CTscan was performed later than planned in the protocol). Baseline characteristics of the 21 patients (9 women, 12 men) of ITT analysis are given in Table  1. Patients had a mean body mass index of 23. 8 ± 5. kg/m 2 and a mean age of 64. 8 ± 11. 9 years. The liver targeted tumors were   MWA was used in 23 (95.
Conflict of interest The authors of this manuscript declare relationships with the following companies: Thierry de Baere is consultant for and receive research grant from Quantum Surgical, consultant and speaker for Boston Scientific, GE Healthcare, AstraZeneca and Boris Guiu is consultant for Quantum Surgical, Boston Scientific, Canon Medical, Roche, Ipsen, Terumo and received research grant from his work. Ethical Approval The present study was submitted and approved by the Ethics Committee (Comitede Protection des Personnes, Ile de France V, France) and was registered on ClinicalTrials. gov (NCT04230642). Informed Consent Informed consent was obtained from all individual participants included in the study. Consent for Publication Patients signed informed consent regarding publishing their data and photographs.
Acknowledgments We thank  OptiGrate Company  for making volume Bragg gratings, and  Dr. Peter J. Delfyett  and  Dr. Ivan Divliansky  for lending equipment. We thank  L. A. Hall ,  A. Shiri ,  K. L. Schepler ,  L. Mach ,  M. G. Vazimali ,  I. Hatipoglu , and  M. Eshaghi  for useful discussions. M. Y. and A. F. A. were supported by the  U. S. Office of Naval Research (ONR)  under contracts  N00014-17-1-2458 ,  N00014-19-1-2192 , and  N00014-20-1-2789. J. F. and E. G. J. were supported by  ONR  contract  N00014-20-1-2558. M. A. A. was funded by the  Excellence Initiative of Aix Marseille University  -A*MIDEX, a  French 'Investissements d'Avenir' programme.
The core of our study is a time-resolved structural characterization of the phases and phase transformations of a water-glycerol mixture obtained after a fast quench at low temperature. This is done mostly at the glycerol concentration c g = 0. 178 ± 0. 005 through polarized neutron scattering and selective deuterations. An extensive set of data already exists for this concentration or nearby ones  5, 6, 8, 10, 14, 15, 17, 25, 33  , but no detailed structural investigations have been provided so far. Through the time-resolved neutron-scattering experiment we are able to probe the kinetics of phase transformation at constant annealing temperature, which may be very long in the glassy regime (10 hours or more). We further complement our analysis by thermodynamic measurements made by differential scanning calorimetry (DSC) and dynamical measurements obtained by Nuclear Magnetic Resonance (NMR) and Neutron Spin Echo (NSE).
5 mm in order to maximize the transmission. A wavelength of 4. 8 Å was chosen to measure the structure factor in the Q-range 0. 1 Å-1 < Q < 2. 4 Å-1. The raw data obtained on D7, i. e. , measurements of the non-spin-flip scattered intensity and the spin-flip one, were corrected by using the standard reduction software developed at the ILL (https://www. ill. eu/users/instruments/instrumentslist/d7/characteristics). The data are first normalized by the monitor counts. The background, measured from the scattering of the empty cell and a black sample (Cadmium) with the same geometry, was subtracted after taking into account the appropriate self-absorption corrections (i. e. , the measured transmission of the sample). The flipping ratio was measured from a quartz rod of the same diameter, and the detectors' efficiency was corrected with a vanadium sample.
Results are illustrated for c g = 0. 28 in Sec. XI of the SI. Rietveld analysis. The Rietveld method allows an easy modelling of the peak shape, width and intensity of diffraction patterns in relation with the atomic structure of crystalline phases and their relative contribution  41. The Rietveld analysis of the polarized neutron scattering data was performed with the FullProf program (see https://www. ill. eu/sites/fullprof/ and [61]). The refinement of the scattered intensities was carried out as a function of the scattering angle 2θ, which is the experimental quantity for a monochromatic diffractometer as D7 (the wave vector Q is then defined as Q = 4π sin θ/λ where the wavelength λ is 4. 8 Å), by accounting for the instrumental resolution as detailed in [62]. The peak intensity and shape were fitted by taking into account an averaged crystal structure based on the hexagonal I h and cubic I c crystalline structures of pure D 2 O 63 and their possible combination.
cm -1 , the diffusion delay ∆ was adjusted between 50 ms and 1000 ms, and the gradient pulse length δ was set between 1 ms and 5 ms depending on the diffusion coefficient. The selfdiffusion coefficients were determined from the classical Stejskal-Tanner equation  68  , ln(I/I 0 ) = -DG 2 γ 2 δ 2 (∆δ/3), where G is the magnitude of the two applied gradient pulses, γ is the gyromagnetic ratio of the nucleus under study, and I and I 0 are the integrated intensities of the signal obtained with and without gradient pulses, respectively. Here, we used 16 equally spaced gradient steps for each experiment. Data acquisition and treatment were performed with the Bruker Topspin software. Thermal treatments. For the structural studies we quenched the liquid samples in liquid nitrogen from 295 K down to ∼ 80-90 K.
Acknowledgments We thank  I. Popov  et  Y. Feldman  for fruitful discussions and access to their dielectric data, A. Wildes who was the local contact on D7 at the ILL,  M. Hartmann  for discussion on the structural data,  F. Legendre  for technical support at the  LLB (Muses) , and  M. Bombled  for helping on the DSC experiments at the LLB. We also thank the eRMN team of  ICMMO (University Paris-Saclay ) for providing access to the NMR facility and  J. Texeira  for useful exchanges and a careful reading of the manuscript.
Corrections for these motions are important because they remove the virial velocities of galaxies relative to the group center. Group-averaged redshifts have been used for a fraction (∼ 10%) of the low redshifts in Pantheon based on a collection in the NASA/IPAC Extragalactic Database (NED) used by  Carrick et al. (2015). Qin et al. (2018)  also implement groups to compare the 2MASS Tully-Fisher Survey to the 6dF in order to average redshifts within groups and avoid using misclassified galaxies. Tully et al. (2016)  use groups assigned by  Tully (2015)  to obtain group-averaged distances and velocities, compare with other group catalogs, and improve upon previous large-scale flow studies. In these catalogs, no information is given on the probability of a galaxy being in a group -a galaxy is either in a group or not.
Group Identification Methods The process for identifying galaxy groups is depicted in Fig. 3. In order to use these grouping catalogs, we match the SNe (N = 584) to their host galaxies as determined by  Carr et al. (2021). Any galaxy labeled to be in a group in T15 or Lim17 has an identification in the Principal Galaxies Catalog (PGC), so we match our host galaxies to entries in the PGC using the Lyon Extragalactic Database 2. We then use the Extragalactic Maximizing groups with three or more galaxies  (Crook et al. 2007 ) 120 Note-Group acronyms are written with a short description and number of SNe matched. 2007 ) group assignments for the SNe found in groups. Left: Corresponding group richnesses for the galaxies matched in our sample on a logarithmic scale. Right: Histogram of the unweighted average redshifts of a group subtracted by the host galaxy's redshift for each group catalog.
Median differences (µ) and standard deviations (σ) are given in km s -1 in the legend. Distance Database 3 , which has taken a number of different catalogs and matched according to PGC numbers, to compare to T15 and Lim17. We successfully find 149 SNe that are in groups in T15 and 121 in Lim17. The corresponding number of matched galaxies for Lam20 is 124 (matching by 2MASS IDs), where groups are predefined as having three or more galaxies. We match 120 SNe to galaxies in C07 by minimizing coordinate distance (defining an appropriate host galaxy if the coordinate separation is < 0. 01 • ). We plot any SN host galaxy deemed to be in a group in T15, Lim17, Lam20, or C07 in Fig. 2  alongside galaxies that do not have any identified group. We determine that up to 30% (N = 174) of our low-z galaxies can be assigned to groups and note a selection bias toward the lowest redshifts due to the completeness of the catalogs used.
In Appendix A, we discuss use of the additional information available in the posterior distribution. This variant includes the external CF from 2M++ C15. • 2M++ [Gr]: where we calculate the 2M++ C15 CF correction at the group location (where available) rather than the individual galaxy location. • 2M++/SDSS ilos : which is the same as 2M++/SDSS but integrating over all possible distances along the line of sight as in 2M++ ilos. • 2M++/SDSS/6dF: similar to 2M++/SDSS, but using the β and v ext. coh. determined with SDSS, 2M++, and 6dF data, as done in  Said et al. (2020). These are β = 0. 341, v ext. coh. = 94î -138 ĵ + 4 k. The second set of CF corrections is from Cf3 using the methodology of forward modeling the data set as described in  Graziani et al. (2019). This set of PVs was computed with T15 group information where available.
CF Catalog Comparison We compare five variant sets of CF corrections and fit a line to each to show differences in methodology and assumptions in Fig. 5. We compare two of the variant CF correction sets from 2M++ (with and without an external CF) and find a correlation, using an orthogonal distance regression, with a slope of 0. 95 ± 0. 02, as shown in the upper panel of Fig. 5. In the upper-middle panel of Fig. 5 , we find a correlation between the CF corrections reported by 2M++ C15 and the extracted CF corrections from Cf3 observing a slope of 1. 34 ± 0. 05 and an offset of 91 ± 10 km s -1. Some potential explanations for this offset between 2M++ and Cf3 CFs, which is worse at higher redshifts, are improper Malmquist Bias corrections at the large distances of the Cf3 data set, differences between methodologies based on redshift surveys and direct PV measurements, and asymmetry in the SN sample, which is dominated by the Northern Hemisphere.
Acknowledgment: We acknowledge  Ivaylo Nikolov ,  Michele Manfredda ,  Luca Giannessi , and  Giuseppe Penco  for their inestimable help to set up the FEL and the laser for our experiment. NJ would like to thanks  S. Flewett  for discussion on XRMS simulations. Financial supports from  FLAG-ERA SographMEM  ( ANR-15-GRFL-0005 ), funding from the  Agence Nationale de la Recherche, France , under grant agreement no. ANR-17-CE24-0025  (TOPSKY) and  18-CE24-0018-01  (SANTA), the  Horizon2020 Framework Program  of the  European Commission  under  FET-Proactive Grant  agreement.
Acknowledgments This research was supported by  Advanced Research Projects Agency - Energy (ARPA-E)  No. DE-AR000067 , the  U. S. Department of Energy  under Contract No. DE-AC04-94AL85000  and the  American Institute for Manufacturing (AIM) Integrated Photonics. This work was performed, in part, at the  Center for Integrated Nanotechnologies , an  Office of Science User Facility  operated for the  U. S. Department of Energy (DOE) Office of Science. We thank  C. Shen  and  L. Chang  for discussions. The authors declare no conflicts of interest.
2020). The first highly sensitive space X-ray polarimeter, the Imaging X-ray Polarimeter Explorer (IXPE;  Weisskopf et al. 2022) , was launched on 2021 December 9. The high-quality data allowed  Doroshenko et al. (2022)  to discover a significant polarization signal from Her X-1 in both the phase-averaged and phase-resolved data with PD varying from ∼5% to ∼15% over the rotational phase. Object Cen X-3 was also observed by IXPE as one of the first science targets. Coherent pulsations from the source with a period of about 4. 87 s were discovered by the first X-ray space observatory, Uhuru  (Giacconi et al. 1971 ). The binary nature of Cen X-3 was established by  Schreier et al. (1972) , who detected the occultations of the X-ray source by a 53 Deceased. Original content from this work may be used under the terms of the Creative Commons Attribution 4.
3. 1 54 using CalDB released on 2022 March 14. Before the scientific analysis, the position offset correction and energy calibration were applied. Source photons were collected in a circular region with radius R src of 70″ centered on the Cen X-3 position. Background counts were extracted from an annulus with inner and outer radii of 2R src and 4R src , respectively. In the 2-8 keV band, the background comprises about 10% and 0. 5% of the total count rate in the source region in the first and second observations, respectively. The event arrival times were corrected to the solar system barycenter using the standard barycorr tool from the FTOOLS package and accounting for the effects of binary motion using the orbital parameters from  Raichur & Paul (2010). For the second observation, we found residual regular variations of the spin frequency over the observation even after correction, so the mideclipse epoch was adjusted to improve the orbital solution as described in Appendix.