dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from CERN FIG. 28. Measured values of LU observables in B þ → K þ l þ l -and B 0 → K Ã0 l þ l -decays and their overall compatibility with the SM. TABLE XI. SM predictions and uncertainties from the FLAVIO software package  [71]. The dominant QED uncertainty from Ref. [14]  is quoted separately. The results obtained using the RUN 1, RUN 2P1, RUN 2P2 datasets alone for R K and R K Ã in the low-and central-q 2 regions are shown together with their likelihood profiles including all systematic uncertainties. The results obtained from the best fit in individual run periods are shown in Table  XII  and the corresponding one-dimensional likelihood scans are shown in Fig.
This work has been partially funded by the  French Agence Nationale de la Recherche  ( ANR-20-CE24-0001   DALHAI  and  ISITE-BFC ANR-15-IDEX-0003 ), the  EIPHI Graduate School  ( ANR-17-EURE-0002 ), and the  European Union  through the  PO FEDER-FSE Bourgogne 2014/2020 programs. Device characterization was performed at the technological platforms SMARTLIGHT and  ARCEN Carnot  with the support of the  French Agence Nationale de la Recherche  under program  Investment for the Future  ( ANR-21-ESRE-0040 ), the  Région de Bourgogne Franche-Comté , the  CNRS , and the  French Renatech+ network.
Acknowledgements Funding information The authors would like to express special thanks to the  Mainz Institute for Theoretical   Physics (MITP)  of the Cluster of Excellence PRISMA+ (Project  ID 39083149 ), for its hospitality and support. OM, FM and RW acknowledge support by  FRS-FNRS  ( Belgian National Scientific Research Fund)   IISN  projects  4. 4503. 16. CK was supported by  DOE  grant  DOE-SC0010008. AB, CK, and TP would like to thank the  Baden-Württemberg-Stiftung  for funding through the program  Internationale Spitzenforschung , project  Uncertainties -Teaching AI its Limits  ( BWST_IF2020-010 ). AB would like to acknowledge support by the  BMBF  for the AI junior group  01IS22079. TH is supported by the  DFG Research Training Group   GK-1940 ,  Particle Physics Beyond the Standard Model.
TH's contribution to this project was made possible by funding from the  Carl-Zeiss-Stiftung. Computational resources have been provided by the supercomputing facilities of the  Université catholique de Louvain (CISM/UCL)  and the  Consortium des Équipements de Calcul Intensif en Fédération Wallonie Bruxelles (CÉCI)  funded by the  Fond de la Recherche Scientifique de Belgique (F. R. S. -FNRS ) under convention  2. 5020. 11  and by the  Walloon Region. The work of JI was supported by the  Fermi National Accelerator Laboratory (Fermilab) , a  U. S. Department of Energy, Office of Science, HEP User Facility. Fermilab is managed by  Fermi Research Alliance, LLC (FRA) , acting under Contract No. DE-AC02-07CH11359. This project was supported by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)  under grant  396021762 -TRR 257   Particle Physics Phenomenology after the   Higgs Discovery and through Germany's Excellence Strategy   EXC 2181/1 -390900948  The  Heidelberg STRUCTURES Excellence Cluster.
Acknowledgement None In the general case of a circular loop of radius a and at an arbitrary distance from the origin O (which is located on its symmetry axis x), the magnetic field along the Ox axis can be calculated by means of the following expansion  [23]  B SL 1;axial ¼ where I is the current intensity in the loop and l 0 the air permeability. The various quantities in (A1) are defined in Fig. 1  of the main text; P 1 nþ1 ðcos aÞ is the associated Legendre polynomial. Consider now the system of three coaxial circular loops in the co-current mode (Fig. 2  in the main text). The resulting magnetic field can be expressed as where X i ¼ cos a i and where loops are numbered so that The polynomial expressions of b ni =ðl 0 IÞ are listed up to n ¼ 6 in Table  A1  below. The classical method for producing a uniform gradient consists in the cancellation of derivatives calculated from the B 1 expression, starting from order 2 up to the maximum order which can lead to a derivative equal to zero.
It has three normal modes (n modes = 3): The symmetric (q 4 , ω 4 ) and asymmetric stretching (q 3 , ω 3 ) and the doubly degenerate bending (q 1, 2 , ω 1, 2 ). Table  1  contains the relevant output of the electron structure calculations we have performed on the target by using the Molpro program suite  [45]  in the framework of the normal mode approximation. Using cc-pVTZ basis functions at different levels of theory, we have calculated the ground state energy in the optimized equilibrium geometry, the normal mode frequencies and the permanent dipole moments. The characterization of the target is followed by electron scattering calculations performed on the "elec-tron+target" system. This part is the bottleneck of our method, since most of the higher level theories and bases functions are not tractable for the scattering calculations performed with UK R-matrix-based Quantemol-N programme suite  [46, 47].
This study originates in the very stimulating scientific environment of the French consortium GdR THEMS. The authors acknowledge support from Fédération de Recherche Fusion par Confinement Magnétique (CNRS and CEA), La Région Normandie, FEDER, and LabEx EMC3 via the projects PTOLEMEE, Bioengine COMUE Normandie Université, the Institute for Energy, Propulsion and Environment (FR-IEPE), the European Union via COST (European Cooperation in Science and Technology) actions TUMIEE (CA17126), MW-Gaia (CA18104) and MD-GAS (CA18212). The authors are indebted to Agence Nationale de la Recherche (ANR) via the project MONA. This work was supported by the Programme National "Physique et Chimie du Milieu Interstellaire" (PCMI) of CNRS/INSU with INC/INP co-funded by CEA and CNES. MAA and VK acknowledge support from the Thomas Jefferson Fund of the Office for Science and Technology of the Embassy of France in the United States and the National Science Foundation, Grant No.
PHY-2102188 and the program "Accueil des chercheurs étrangers" of CentraleSupélec. JZsM. and OA thank the financial support of the National Research, Development and Innovation Fund of Hungary, under the K18 and FK19 funding schemes with project no. K 128621 and FK 132989. JZsM, OA and IFS are grateful for the support of the NKFIH-2019-2. 1. 11-T ÉT-2020-00100 and Campus France-Programme Hubert Curien+BALATON+46909PM Projects. JZsM is grateful for IEPE for a Visiting Professor Fellowship. Open access funding provided by ELKH Institute for Nuclear Research.
Funding This study originates in the very stimulating scientific environment of the French consortium GdR THEMS. The authors acknowledge support from Fédération de Recherche Fusion par Confinement Magnétique (CNRS and CEA), La Région Normandie, FEDER, and LabEx EMC3 via the projects PTOLEMEE, Bioengine COMUE Normandie Université, the Institute for Energy, Propulsion and Environment (FR-IEPE), the European Union via COST (European Cooperation in Science and Technology) actions TUMIEE (CA17126), MW-Gaia (CA18104) and MD-GAS (CA18212). The authors are indebted to Agence Nationale de la Recherche (ANR) via the project MONA. This work was supported by the Programme National "Physique et Chimie du Milieu Interstellaire" (PCMI) of CNRS/INSU with INC/INP co-funded by CEA and CNES. MAA and VK acknowledge support from the Thomas Jefferson Fund of the Office for Science and Technology of the Embassy of France in the United States and the National Science Foundation, Grant No.
Data analysis The data sets were analyzed using the standard photometry procedures of the Platform for Reduction of Astronomical Images Automatically (PRAIA,  Assafin et al. 2011). The flux of the occulted star was corrected by the flux of nearby reference stars to account for sky transparency variations and was normalized to the total star+Quaoar flux outside the occultation. The Stellar Occultation Reduction and Analysis package (SORA,  Gomes-Júnior et al. 2022 ) was used to derive the ingress and egress instants of the occultation by the main body, assuming an opaque body without atmosphere. More details are presented in Appendix A. The extremities of the resulting chords were finally used to fit an elliptical model to Quaoar's limb at the moment of the occultation. (1)  δ = -15 • 12 45.
(  4 ) Renormalized unit weight error  (Lindegren et al. 2021 ). (5) Obtained from the Numerical Integration of the Motion of an Asteroid (NIMA,  Desmars et al. 2015) , based on astrometric positions derived from previous stellar occultations and the Minor Planet Center (MPC) database, available at https: //lesia. obspm. fr/lucky-star/obj. php?p=958 (6) Obtained from the method of  Vachier et al. (2012). (7) Assuming the double-peaked light curve from  Ortiz et al. (2003). In the case of rings, the events were fitted using the square box model described in Appendix E and pipelines based on the SORA package. This provides the radial width of the ring W r (assuming a circular ring), its normal opacity, p N , and normal optical depth, τ N , from which the equivalent width, E p = W r p N , and equivalent depth, A τ = W r τ N , are derived.
4 × 10 -3 , with p approaching zero for values larger than E p. While the two light curves of the Gemini instrument may be correlated as they were taken at the same telescope, the Gemini and CFHT data are independent in terms of fast-seeing fluctuations. Using Poisson statistics, we estimate that the probability that the simultaneous events in the Gemini and CFHT data occur randomly due to the seeing fluctuations is very low, with p ≈ 10 -6. Some dips in flux were observed in the vicinity of Q2R detection in the region after the closest approach (Fig. 3 ). These detections are at the detection limit of our data, so we cannot say whether these are due to seeing variations or additional structures. Furthermore, we do not observe counterparts of these dips in the region before the closest approach.
Based on observations obtained at the international Gemini Observatory, a program of NSF's NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation on behalf of the Gemini Observatory partnership: the National Science Foundation (United States), National Research Council (Canada), Agencia Nacional de Investigación y Desarrollo (Chile), Ministerio de Ciencia, Tecnología e Innovación (Argentina), Ministério da Ciência, Tecnologia, Inovações e Comunicações (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). This work made use of data from GN-2022B-DD-101 observing program and were obtained with the High-Resolution Imaging instrument(s) 'Alopeke (and/or Zorro). 'Alopeke (and/or Zorro) was funded by the NASA Exoplanet Exploration Program and built at the NASA Ames Research Center by Steve B.
This work profited from unpublished occultations by Quaoar made at SOAR L4, page 5 of 14 (SO2019A-003) and the Pico dos Dias Observatory (OP2019A-004) to improve the accuracy of the ephemeris NIMAv16. With the limb-darkened angular diameter of the star estimated and considering the observation band pass and its FWHM, we also fit the local normal velocity (v ⊥ ). By minimizing the χ 2 statistic, we found the velocity and the ingress (egress) time that best explained the observed light curve. This was applied to the Gemini z'-band data since this was our best light curve. The radial velocities obtained are v ⊥ = 10. 2 km s -1 and v ⊥ = 16. 6 km s -1 for ingress and egress instants, respectively. The separation between the chords obtained from the Gemini and CFHT when projected onto the sky plane was about 160 meters, a value smaller than the star's apparent diameter.
Stacking was performed using Python routines built from the astropy library as described in  Morgado et al. (2019) , where each new image is the average of six original images, resulting in a temporal resolution of 1. 2 seconds for each stacked image. Notes. The normal opacity, p N , and normal optical depth, τ N , were calculated from the ring opening angle, B, and position angle, P, on August 9, 2022, derived from the orientation of the body obtained from the 2018-2022 data. The other parameters are: Mid-time in UT and the error bars in parentheses given in seconds; r, the radial distance from Quaoar's center in kilometers; W r , the radial width in kilometers; E p and A τ , the equivalent width and equivalent depth in kilometers respectively. The terms "ing" and "egr" stand for ingress and egress, respectively, and refer to the fact that the detection occurred before and after the occultation by Quaoar's main body, respectively.
Acknowledgements. C. L. P is thankful for the support of the CAPES and FAPERJ/DSC-10 (E26/204. 141/2022). This work was carried out within the "Lucky Star" umbrella that agglomerates the efforts of the Paris, Granada, and Rio teams, funded by the European Research Council under the European Community's H2020(ERC Grant Agreement No. 669416). This study was financed in part by the National Institute of Science and Technology of the e-Universe project (INCT do e-Universo, CNPq grant 465376/2014-2). This study was financed in part by CAPES -Finance Code 001. The following authors acknowledge the respective CNPq grants: B. E. M. 150612/2020-6; F. B. R. 314772/2020-0; R. V. M. 307368/2021-1; M. A. 427700/2018-3, 310683/2017-3, 473002/2013-2; J. I. B. C. 308150/2016-3, 305917/2019-6. R. C. B acknowledges the FAPERJ grant E26/202.
125/2020. E. F. -V. acknowledges financial support from the Florida Space Institute and the Space Research Initiative. J. L. O. , P. S. -S. , M. V-L, and M. K. acknowledge financial support from the grant CEX2021-001131-S funded by MCIN/AEI/ 10. 13039/501100011033, they also acknowledge the financial support by the Spanish grants PID2020-112789GB-I00 from AEI and Proyecto de Excelencia de la Junta de Andalucía PY20-01309. Funding for RECON was provided by grants from USA: NSF AST-1413287, AST-1413072, AST-1848621, and AST-1212159. We thank RECON observers Doug Thompson, Ken Conway, Dorey Conway, Terry Miller, David Schulz, Michael von Schalscha, and Matt Christensen for their efforts in collecting data.
Acknowledgment We warmly thank  CERN  for the successful operation of the CNGS facility and  INFN  for the continuous support given by hosting the experiment in its  LNGS laboratory. Funding is gratefully acknowledged from national agencies and Institutions supporting us, namely:  Fonds de la Recherche Scientifique-FNRS  and  Institut Interuniversitaire des Sciences Nucléaires for Belgium ; MZO for Croatia; CNRS and IN2P3 for France; BMBF for Germany; INFN for Italy; JSPS,  MEXT , the  QFPUGlobal COE program  of  Nagoya University, and Promotion and Mutual Aid Corporation for Private Schools of Japan for Japan ;  SNF , the  University of Bern  and  ETH Zurich for Switzerland ; the  Programs of the Presidium of the Russian Academy of Sciences (Neutrino Physics and Experimental and Theoretical Researches of Fundamental Interactions) , and the  Ministry of Education and Science of the Russian Federation for Russia ; the  National Research Foundation of Korea (NRF)  grant funded by the  Korea government (MSIT)  (No.
A Dalitz plot analysis of the D + s → π -π + π + decay is presented. The analysis is based on proton-proton collision data recorded by the LHCb experiment at a centreof-mass energy of 8 TeV and corresponding to an integrated luminosity of 1. 5 fb -1. The resonant structure of the decay is obtained using a quasi-model-independent partial-wave analysis, in which the π + π -S-wave amplitude is parameterised as a generic complex function determined by a fit to the data. The S-wave component is found to be dominant, followed by the contribution from spin-2 resonances and a small contribution from spin-1 resonances. The latter includes the first observation of the D + s → ω(782)π + channel in the D + s → π -π + π + decay. The resonant structures of the D + s → π -π + π + and D + → π -π + π + decays are compared, providing information about the mechanisms for the hadron formation in these decays.
In this paper, the resonant structure of the D + s → π -π + π + decay is determined. 1 The analysis is based on proton-proton (pp) collision data collected by the LHCb experiment at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 1. 5 fb -1. The main purpose of this work is to determine the resonant structure of the decay and to measure the π + π -S-wave amplitude. The results are obtained using a quasi-modelindependent partial-wave analysis, in which the S-wave amplitude is parameterised as a generic complex function determined by a fit to the data. The resonant structure of the D + s → π -π + π + is compared to that of the D + → π -π + π + decay  [4]. A particular feature of the D + s → π -π + π + decay is that while D + s meson is a cs state and the decay occurs through the favoured transition c → s, there are no strange particles in the final state.
One important background from D + s → η (→ π + π -γ)π + decays, in which the photon is undetected, cannot be eliminated with PID requirements. This background affects mostly the region of the three-pion invariant mass region, m(π -π + π + ), below the D + s mass. A multivariate analysis (MVA) is performed to further reduce the combinatorial background. The MVA uses the gradient boosted decision tree BDTG classifier  [21, 22]. Only the quantities related to the three-track combinations described above are used in the BDTG classifier, keeping the overall signal efficiency over the Dalitz plot as uniform as possible. The BDTG classifier is trained using simulated D + s → π -π + π + decays for the signal, and data from the m(π -π + π + ) intervals 1920-1940 MeV and 2010-2030 MeV for the background.
Signal efficiency and background model The efficiency for reconstructing and selecting a D + s → π -π + π + candidate varies across the Dalitz plot. A combination of simulation and data-driven methods is used to determine this efficiency as a function of the Dalitz plot variables s 12 and s 13 , defined in section 5. Effects of the geometrical acceptance of the detector, reconstruction, trigger and selection are included in the simulation, except for the particle identification. The PID efficiency is determined from data calibration samples. Decays that can be reconstructed without particle identification, such as the D * + → D 0 (→ K -π + )π + chain, are used to determine the efficiency as a function of momentum and pseudorapidity for each decay product. The PID efficiency of the candidate is the product of the efficiency for each final-state particle and is used to weight the simulated events that pass the remainder of the selection.
Acknowledgments We express our gratitude to our colleagues in the CERN accelerator departments for the excellent performance of the LHC. We thank the technical and administrative staff at the LHCb institutes. We acknowledge support from  CERN  and from the national agencies: -24 -JHEP07(2023)204  CAPES ,  CNPq ,  FAPERJ  and  FINEP (Brazil) ;  MOST  and  NSFC (China) ;  CNRS/IN2P3  (France);  BMBF ,  DFG  and  MPG (Germany) ;  INFN (Italy) ;  NWO (Netherlands) ;  MNiSW  and  NCN (Poland) ;  MEN/IFA (Romania) ;  MICINN (Spain) ;  SNSF  and  SER (Switzerland) ;  NASU (Ukraine) ;  STFC  ( United Kingdom );  DOE NP  and  NSF (USA). We acknowledge the computing resources that are provided by  CERN ,  IN2P3 (France) ,  KIT  and  DESY (Germany) ,  INFN (Italy) ,  SURF (Netherlands) ,  PIC (Spain) ,  GridPP  ( United Kingdom ),  CSCS (Switzerland) ,  IFIN-HH (Romania), CBPF (Brazil) ,  Polish WLCG (Poland)  and  NERSC (USA).
Data reconstruction: Dell EMC PowerEdge R7525 Rack Server (operating system: Ubuntu 20. 04. 3 LTS; central processing unit: AMD EPYC 75F3 2. 95 GHz, 64 cores; memory: DDR4-3200 32 GB (32×); graphics processing unit: NVIDIA Ampere A40 ×2; hard drive: 2. 4 TB 10 K RPM SAS 12 Gbps) • Data visualization: Dell Precision 7920 Tower (operating system: Windows Server 2016; central processing unit: Intel Xeon Platinum 8160 M processor, 2. 10 GHz, 24 cores; memory: 1. 5 TB; graphics processing unit: NVIDIA Quadro P6000; hard drive: AVAGO MR9460-16i SCSI 4. 67 TB) • Reconstruction code written in house using MATLAB 2017 available on GitHub (https://github. com/ HiPCTProject/Tomo_Recon) • PyHST2 (3D tomographic reconstruction code, http://ftp. esrf. fr/scisoft/PYHST2, open source) developed by the ESRF • ImageJ/Fiji (data pre-and postprocessing, https://imagej.
Acknowledgements We thank  S. Bayat  ( INSERM ) for help during the test phase,  P. Masson  ( LADAF ) for dissections of donors' bodies,  H. Reichert  ( ESRF ) and  R. Tori  for general support of the project and  E. Boller ,  C. Muzelle ,  R. Homs ,  C. Jarnias ,  F. Cianciosi ,  P. Vieux ,  P. Cook ,  L. Capasso  and  A. Mirone  for their help in setup developments and improvements. We also thank  R. Engelhardt ,  A. Muller Brechlin ,  C. Petzold ,  N. Kroenke  and  M. Kuhel  for help with histology and autopsies. This project has been made possible in part by grant number  2020-225394  from the  Chan Zuckerberg Initiative DAF , an advised fund of  Silicon Valley Community Foundation  and grant number  CZIF2021-006424  from the  Chan Zuckerberg Initiative Foundation , The ESRF funding proposals md1252 and md1290, the  Royal Academy of Engineering  ( CiET1819/10 ).
• Data reconstruction: Dell EMC PowerEdge R7525 Rack Server (operating system: Ubuntu 20. 04. 3 LTS; central processing unit: AMD EPYC 75F3 2. 95 GHz, 64 cores; memory: DDR4-3200 32 GB (32×); graphics processing unit: NVIDIA Ampere A40 ×2; hard drive: 2. 4 TB 10 K RPM SAS 12 Gbps) • Data visualization: Dell Precision 7920 Tower (operating system: Windows Server 2016; central processing unit: Intel Xeon Platinum 8160 M processor, 2. 10 GHz, 24 cores; memory: 1. 5 TB; graphics processing unit: NVIDIA Quadro P6000; hard drive: AVAGO MR9460-16i SCSI 4. 67 TB) • Reconstruction code written in house using MATLAB 2017 available on GitHub (https://github. com/ HiPCTProject/Tomo_Recon) • PyHST2 (3D tomographic reconstruction code, http://ftp. esrf. fr/scisoft/PYHST2, open source) developed by the ESRF • ImageJ/Fiji (data pre-and postprocessing, https://imagej.
The 1D scattering profiles are further treated using the SAXSutilities2 software  (Sztucki, 2021). For XPCS, acquired speckle patterns are processed via the Dynamix package  (Paleo et al. , 2021)  to obtain the intensity-intensity autocorrelation function pixel by pixel. This quantity is then averaged over a desired azimuthal range to derive the time (t) and ensemble averaged intensity-intensity autocorrelation function, g 2 (q, t). Further visualization and analysis of g 2 (q, t) data can be carried out using the XPCSUtilities program (Chevremont, 2023).
The onset of damage is judged on the basis of a systematic change in the scattering profile with increasing X-ray exposure. Typically, in a SAXS setup, the focusing and collimation are adjusted such that the beam size is minimum on the detector and relatively large on the sample. This condition cannot be met when a small beam spot on the sample or a coherent beam is required. In that case, the flux, exposure time and delay between exposures need to be optimized to remain below the damage threshold. Fig. 6  displays the effect of radiation dose on the effective structure factor [S M (q)] peak of a concentrated suspension of charge-stabilized silica colloids (R S ' 126 nm and volume fraction ' 0. 43) for two different beam sizes. To facilitate the comparison of the S M (q) peak and the compressibility limit [S M (q ' 0)], data are presented with I(q) on a linear scale.
Acknowledgements The authors thank colleagues  M. Sztucki ,  L. Matthews ,  J. Kieffer ,  A. Homs-Puron ,  P. Van Vaerenbergh ,  P. Boesecke ,  J. Gorini ,  M. Ginet ,  P. Paleo  and  Y. Chushkin  for technical support, and collaborators  A. Petukhov ,  M. Linari ,  P. Fischer  and  T. Sottmann.