dataesr/scientific-paragraphs-categorization huggingface dataset:
Identification of binaries We identify binaries in the mock data by measuring the observed RV for each star at different observational epochs, i. e. different observations with time scales of hours, weeks or months 1. We do not evolve the simulations between epochs; therefore, the positions and velocities of single stars, and the centre of mass position and velocity of binary systems remain fixed 2. Any variation on the RV 1 We use 19 epochs given by  epoch  = [0, 6, 15, 24, 33, 360, 375, 384, 384. 03, 384. 06, 384. 09, 384. 12, 384. 15, 384. 93, 384. 96, 384. 99, 385. 02, 385. 05, 393]  days. 2 Single stars and the centre of mass of binary systems would not significantly move in this time range since it is much smaller than the dynamical time. 1. 0 10. 0 R h [pc] 0. 1 1. 0 10. 0 R c [pc] Harris+(2010) simulated GCs Figure  1.
However, they did not detect this in HST observations for NGC 7078, which is consistent with the low binary fraction of the cluster. In general, it is challenging to disentangle this effect, as it depends on the binary fraction and level of energy equipartition in the cluster. The second effect is an increase in the observed velocity dispersion due to the measured line-of-sight velocity of the binaries. For binaries that have a large velocity amplitude, the orbital motion around their centre of mass will dominate the observed line-of-sight velocity, introducing a bias to larger velocity dispersion measurements. To show this effect, we construct velocity dispersion profiles from the mock data with all the stars (single+binaries) and compare it with a sample that only includes stars with a low probability of being a binary ( bin < 0.
SUMMARY In this work, we explored the dynamical effects of a central IMBH on the binary population of GCs. We used a sample of simulated GCs from the MOCCA-Survey Database I  (Askar et al. 2017 ) and applied the method proposed by  Giesers et al. (2019)  to identify binaries through multi-epoch radial velocity (RV) observations. We have produced mock observations for each cluster considering velocity errors in RVs and proper motions; for these mock observations, we follow the radial velocities during many epochs, considering long-term observations spanning over months as well as multiple observations during a single night. This approach allows us to identify binaries in the simulated GCs in the same manner as done for real observations. Two-body relaxation drives the dynamical evolution of GCs; a consequence of this process is mass segregation.
(2012 Ferraro et al. ( , 2018)). By analysing the distribution of blue-straggler stars and their relation with the binary fraction, it will be possible to study another tracer for the dynamical effects of a central IMBH. Similarly, the distribution of X-ray binaries could help separate clusters with a central IMBH from those with a BHS. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 895174. AA is supported by the Swedish Research Council (grant 2017-04217) and also acknowledges partial support from the Royal Physiographic Society of Lund and the Walter Gyllenberg Foundation for the research grant: "Evolution of Binaries containing Massive Stars". This research made use of the NUMPY package (van der Walt et al.
2011), while all figures were made using MATPLOTLIB  (Hunter 2007). Table  A1. Initial conditions for the simulated GCs in our sample. is the initial number of objects (single+binaries),  t is the tidal radius,  0 is the King parameter and  the metallicity. Only one cluster is tidally filling. Natal kicks for neutron stars and stellar-mass black holes follow a mass fallback model  (Belczynski et al. 2002)   A1. For further details on the MOCCA-Survey Database I, we refer the reader to  Askar et al. (2017). In the simulated GCs, the velocity of stellar-mass black holes due to natal kicks can follow two distinct approaches. If the cluster has a "no Fallback" approach, then the natal kick velocities come from a Maxwellian velocity distribution with  = 265 km/s  (Hobbs et al. 2005). Alternatively, clusters can follow a "Fallback" approach, where stellar-mass black holes can have their masses and natal kick velocities modified by the mass fallback prescription provided by  Belczynski et al.
ACKNOWLEDGEMENTS We thank the anonymous referee for their constructive comments and suggestions, which helped us improve this manuscript. We thank the  MOCCA-Survey collaboration  for making their data available to us and answering all our questions. FIA also thanks  Sebastian Kamann  for constructive discussions regarding the MUSE data,  Alice Zocchi  for her helpful suggestions regarding the manuscript and  Nadine Neumayer  for helpful discussions and ideas. FIA and GvdV acknowledge funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  under grant agreement No  724857  ( Consolidator Grant ArcheoDyn ). ACS is supported by the  Deutsche Forchungsgemeinschaft (DFG, German Research Fundation ) -Project- ID 138713538 -SFB 881 ("The Milky Way System ", subproject  A08 ).
Besides, XNCD in the inorganic non-centrosymmetric LiIO 3 crystal was measured  [49] , and it was also attributed to the interference of electric dipole -electric quadrupole transitions  [49, 56]. As an addition, we can evaluate the Kuhn dissymmetry factor  [57] , g = (∆A/A), which is equal to ∼20% and satisfactorily explained by the E1:E2 mechanism. To better understand the observed XNCD signal, we performed a theoretical analysis of the XNCD features at the 1s-3d transitions. Numerical calculations of the absorption energy spectra and circular dichroism have been performed using the finite difference method realized in the program FDMNES  [62, 63]. Comparison of experimental and calculated spectra is shown in Figure  5. The calculations did not reveal any significant E1:M1 contribution to the dichroism spectra, which confirms the assumption that the circular dichroism in this structure is only due to the contribution E1:E2.
Acknowledgments: This research used the ID12 beamline of the  European Synchrotron Radiation Facility. The authors are very grateful to  P. Voisin  ( ESRF ) for his assistance during the experiment. M. S. P. acknowledges support from the  Russian Science Foundation  [grant  19-72-00002]. K. A. K. acknowledges support from the  Russian Foundation for Basic Research  (project no. 19-52-12029  and project no. 19-02-00483 ). V. E. D. was partly supported by the  Ministry of Science and Higher Education of the Russian Federation within the State assignment FSRC "Crystallography and Photonics" RAS. V. Y. I. and A. A. M. were supported by the  Russian Science Foundation  [grant  16-12-10531 ]. The authors acknowledge  M. Molokeev  ( Kirensky Institute of Physics ) for fruitful discussions.
Results of chemical analysis of the samples are presented in Section 3. 3. SANS results are unambiguous. They are directly used for the simulation of neutron scattering in DND powders. SANS measure both individual DNDs and the clusters. SANS data are given in Section 3. 5. In order to extrapolate the results to other neutron velocities, we applied the model of discrete-sized diamond nanospheres, which was introduced in  [40]  and mentioned briefly in Section 2. 3. A more detailed description of the method will be published elsewhere. XRD is sensitive to the crystal structure of DNDs. It is useful to verify that the deagglomeration procedure does not affect the sizes of crystalline cores of DNDs and sp 2 shells; otherwise, there would be two contributions to the change in SANS results, and it would be more difficult to interpret the data.
Our conclusion (from studies on non-fluorinated samples) strongly supports that deagglomeration does not increase the amount of non-H impurities sufficient to affect neutron elastic scattering. Consequently, our DF-DNDs sample was characterized solely with IR spectroscopy sensitive only to H. According to the results of Raman scattering, the fraction of H does not increase during the F-DNDs deagglomeration. Therefore, we are confident that a possible change in impurities during deagglomeration cannot be so large as to affect the neutron scattering on DNDs. In all studied powders and after various stages of their deagglomeration and chemical treatment, the fraction of N is 0. 4-2. 0%, which corresponds to the data available in the literature indicating that N is located inside diamond crystals in the form of impurity atoms  [47].
XRD X-ray diffraction was measured at the ID28 instrument at ESRF with PILATUS3 1M area detector with X-ray wavelengths of 0. 697 Å and 0. 980 Å. DNDs were inserted in quartz capillaries with the diameter of 200 µm. Data were evaluated using SNBL Toolbox  [49, 50]  software. No significant difference between the peak shape before and after deagglomeration treatment is observed, as shown in Figure  5 , in line with the expectations.
XRD X-ray diffraction was measured at the ID28 instrument at ESRF with PILATUS3 1M area detector with X-ray wavelengths of 0. 697 Å and 0. 980 Å. DNDs were inserted in quartz capillaries with the diameter of 200 μm. Data were evaluated using SNBL Toolbox  [49]  and  [50]  software. No significant difference between the peak shape before and after deagglomeration treatment is observed, as shown in Figure  5 , in line with the expectations.
Size Distribution of Nanoparticles The size distribution of DNDs were characterized with the optical methods, which do not contradict each other, but their results' interpretation is somewhat ambiguous and is more of a complementary nature in relation to the neutron elastic scattering. The SANS data are more relevant for us; therefore, we used the model of discrete-sized diamond nanospheres to extract the size distribution of scatterers in the samples. The fitting procedure is stable against the initial parameter choice (populations, binning of radii, the radii range; it is wide enough). Here, we used 20 radii values per decade uniformly distributed on a logarithmic scale. The radii range was selected based on the following arguments. The minimum radius is 0. 6 nm; at this value, it is still energetically more advantageous for C atoms to form a diamond lattice  [57].
The fraction of such particles was always equal to zero according to the fitting algorithm. The maximum radii are 200 nm for F-DNDs and 300 nm for DF-DNDs. These values describe the SANS data corresponding to the minimum transferred momentum Q min. They differ due to the different values of Q min for the samples. Figure  7  shows measured and simulated SANS curves for both samples and demonstrates the validity of our model. The radii range was selected based on the following arguments. The minimum radius is 0. 6 nm; at this value, it is still energetically more advantageous for C atoms to form a diamond lattice  [57]. The fraction of such particles was always equal to zero according to the fitting algorithm. The maximum radii are 200 nm for F-DNDs and 300 nm for DF-DNDs. These values describe the SANS data corresponding to the minimum transferred momentum Qmin.
Calculation Storage Times in Closed Nano-Diamond Traps While the performance of F-DNDs and DF-DNDs are similar for the flat reflector geometry, the situation changes dramatically when we consider a three-dimensional geometry of the reflector: an empty spherical cavity inside an infinite medium consisting of diamond nano-powder. To simulate neutron reflection in this geometry, we use the same SANS data and the same model of neutron interaction with powders. Figure  12  shows the albedo of neutrons from the cavity walls versus the neutron velocity and the cavity radius for both F-DND and DF-DND samples. For comparison, Figure  13  shows the albedo of neutrons from the cavity walls versus the neutron velocity and the cavity radius for DF-DND and DND samples. Note that a higher albedo value means a higher density of neutrons, which can be accumulated in the  DF-DNDs show much higher values than those for F-DNDs and DNDs for the entire range of neutron velocities and all cavity sizes.
Funding: This research was funded by grants  RFFI-18-29-19039 ,  ERC INFRASUP P-2019-1/871072 ,  CREMLINplus Grant  agreement  871072 ,  ANR-20-CE08-0034 , and  JINR  grant for young scientists No. 21-402-06. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable.
Acknowledgments: The authors are grateful to M. Mikhaylov (NRC "Kurchatov Institute"-CRISM "Prometey", St. Petersburg) for producing the TEM images of F-DND and DF-DND samples, to Olga Kristavchuk and Oleg Orelovich (Flerov Laboratory of Nuclear Reactions, JINR, Dubna) for their help with producing SEM images of F-DND and DF-DND samples, to C. Gagnon and CHRNS at NIST, and to V. A. Artem'ev for useful discussions. This work benefited from the use of the SASView (http://www. sasview. org/download/, accessed on 9 July 2021) application, originally developed under NSF award DMR-0520547. SasView contains code developed with funding from European Union's Horizon 2020 research and innovation program under the SINE2020 project, grant agreement.
After the main Enceladus phase, close flybys of Titan with atmospheric sampling will be performed (Titan science phase). During the Titan science phase, the spacecraft will provide in situ sampling of the upper atmosphere at a minimum altitude from Titan surface as low as 900 km using mass spectrometers. At the closest approach the velocity of the spacecraft with respect to Titan's surface will be ~7 km/s. Imaging data would be collected during inbound and outbound segments of each flyby. The duration of the tour from its arrival in the Saturn system to the end of the 17-flyby Titan phase is about 3. 5 years. Figure  3  shows a proposed interplanetary transfer to Saturn and Fig. 4  shows a proposed sample tour. Both Figs. 3  and 4  are based on a proposed E 2 T launch of 2029-2030  [102]. Figure  5  shows the proposed configuration of the spacecraft for the E 2 T project.
Option 2: Radar sounder The ice penetrating radar (IPR), following the heritage of JUICE RIME and Europa Clipper REASON, would be capable of both shallow and deep sounding to characterize the subsurface with a depth of 9 km and ~30 m vertical resolution at minimum. Both RIME and REASON are to operate at a high frequency (HF) band with a centerfrequency of 9 MHz and possess bandwidths between 1 MHz and 3 MHz while REASON operates at an additional VHF frequency with a center frequency of 60 MHz  [14, 44]. An IPR can characterize structural, compositional, and thermal variations occurring in the subsurface providing data that can correlate surface and subsurface features and processes, deformation in the upper ice shell, as well as global and local surface age. In addition, an IPR can also investigate the ice-ocean interface at Enceladus' SPT and brittle-ductile transition on Titan constraining the thickness and thermal evolution of the ice shells.
A high CO/N 2 ratio, for instance, would suggest a cometary-like source with only a moderate modification of the volatile inventory, whereas a low CO/N 2 ratio would indicate a significant internal reprocessing. In addition to these main volatile species, during some Cassini flybys, the INMS data also indicated the possible presence of trace quantities of C 2 H 2 , C 3 H 8 , C 4 , methanol, formaldehyde, and hydrogen sulfide. Organic species above the INMS mass range of 99 u are also present but could not be further constrained  [174]. The identification and the quantification of the abundances of these trace species remains very uncertain due to the limitations of the mass spectrometer on board Cassini. Except for the measurement of D/H in H 2 O on Enceladus (which has large uncertainty,  [174] ), no information is yet available for the isotopic ratio in Enceladus' plume gas.
Ice-to-vapor ratios can constrain how Enceladus' plume material is formed and transported to the surface. For example, ice-to-vapor ratios >0. 1-0. 2 would exclude plume generation mechanisms which require a large amount of ice grains to be condensed from vapor  [65, 124]. However, this ratio is poorly constrained with estimates ranging from 0. 05  [136]  to 0. 4  [124]  to 0. 35-0. 7  [65]. Imaging and spectral data from the proposed baseline mission could help constrain this important ratio. Cassini ISS images used to track plume brightness variation, which is proportional to the amount of grains in the plume, with the orbital position of Enceladus found more ice grains are emitted when Enceladus is near its farthest point from Saturn (apocenter). It is not understood if the plume vapor has such a variation.
Ice penetrating radar (IPR) The ice penetrating radar (IPR) would be capable of both shallow and deep sounding to characterize the subsurface with a depth of 9 km and ~30 m vertical resolution at minimum. An IPR can characterize structural, compositional, and thermal variations occurring in the subsurface providing data that can correlate surface and subsurface features and processes, deformation in the upper ice shell, as well as global and local surface age. On Titan, radar sounder observations with a penetration depth up to ~9 km with a vertical resolution of ~30 m, similar to JUICE RIME and Europa Clipper REASON, could directly determine the relict brittle-ductile transition of the ice shell revealing its thermal state, thus constraining its ice shell thickness and thermal evolution. Liu et al.
Acknowledgments We are grateful to  E. Dudas  for stimulating discussions, and also to  G. Bogna  and  Y. Tatsuta , who read an earlier version of the manuscript and made useful comments. The work of AS was supported in part by  Scuola Normale , by  INFN  ( IS GSS-Pi ) and by the  MIUR-PRIN  contract  2017CC72MK 003. JM is grateful to  Scuola Normale Superiore  for the kind hospitality extended to him while this work was in progress. AS is grateful to  U. Paris VII  and  DESY-Hamburg  for the kind hospitality, and to the Alexander von Humboldt foundation for the kind and generous support, while this work was in progress.
The proper filling of the loop, without the presence of gas bubbles, can be checked with the optical sensors presented in Section "Optical sensor". Their output voltage depends on the amount of light received by the phototransistor. Once calibrated, the presence of liquid leads to an output of roughly 5 V as our solvent refractive index is close to the one of the PTFE tubing used. The presence of air or helium gas will lead to a lower voltage of around 2. 6 V. Fig. 4  shows a typical output data set from an optical sensor when a 7 mL volume of water is pushed through it with 6 bar of helium gas. The data were recorded with an oscilloscope (DSOX1204A, 70 MHz, Keysight Technologies, Les Ulis, France). At t 1 , the front of the liquid plug is detected at the optical sensor position. One can see that the first part of the plug, from t 1 to t 2 (indicated in blue in Fig.
Acknowledgments This research was supported by  ENS-Lyon , the  French CNRS, Lyon 1 University , the  European Research Council  under the European Union's  Horizon 2020 research and innovation program  ( ERC Grant  Agreements No. 714519 / HP4all  and  Marie Skłodowska-Curie Grant  Agreement No. 766402 / ZULF ). The authors gratefully acknowledge  Bruker Biospin  for providing the prototype dDNP polarizer, and particularly  Roberto Melzi ,  Marc Rossire ,  Marco Sacher  and  Marc Schnell  for scientific and technical support. The authors graciously acknowledge  Frank Decker ,  Bruno Knittel  and  Venita Decker  for lending assistance with the operation of.
ACKNOWLEDGEMENTS We thank the referee for her/his comments, which helped to improve the paper. This research was supported by a  Newton Fund project ,  DARA (Development in Africa with Radio Astronomy ), and awarded by the  UK's Science and Technology Facilities Council (STFC)  -grant reference  ST/R001103/1. This research was supported by  European Commission   Horizon 2020 Research and Innovation Programme  under grant agreement No. 730884  ( JUMP-ING JIVE ). FS acknowledges support from a  Leverhulme Trust Research Fellowship. J. H. K. acknowledges support from the  European Union 's  Horizon 2020 research and innovation programme  under  Marie Skłodowska-Curie  grant agreement No  721463  to the SUNDIAL ITN network, from the  State Research Agency (AEI)  of the  Spanish Ministry of Science and Innovation  and the  European Regional Development Fund (FEDER)  under the grant with reference  PID2019-105602GB-I00 , and from  IAC  project  P/300724 , financed by the  Ministry of Science and Innovation, through the State Budget  and by the  Canary Islands Department of Economy , Knowledge and Employment, through the  Regional Budget of the Autonomous Community.
IMV thanks the  Generalitat Valenciana  (funding from the  GenT  Project  CIDEGENT/2018/021 ) and the  MICINN  (funding from the Research Project  PID2019-108995GB-C22 ). AA and MAPT acknowledge support from the  Spanish MCIU  through grant  PGC2018-098915-B-C21  and from the  State Agency for Research of the Spanish MCIU through the "Center of Excellence Severo Ochoa " award for the  Instituto de Astrofìsica de Andalucìa  ( SEV-2017-0709 ). B. T. D. acknowledges financial support from grant " Ayudas para la realización de proyectos de I+D para jóvenes doctores 2019. "funded by  Comunidad de Madrid  and  Universidad Complutense de Madrid  under grant No. PR65/19-22417. '.
Deviations have been also observed in the theoretically cleaner angular observables of the  0 →  * 0 µ + µ -decay  [2]. Measurements of Lepton Flavour Universality (LU) in the decays  + →  + ℓ + ℓ -and  0 →  * 0 ℓ + ℓ -, commonly referred to as   and   * 0 , performed by LHCb exploiting the dataset collected during Run 1 of the LHC, also showed intriguing deviations with respect to the SM predictions  [3] :   = 0. 745 +0. 090 -0. 074 ± 0. 036 for 1. 0 <  2 < 6. 0 GeV 2 / 4 ,   * 0 = 0. 66 +0. 11  -0. 07 ± 0. 03 for 0. 045 <  2 < 1. 1 GeV 2 / 4 ,   * 0 = 0. 69 +0. 11 -0. 07 ± 0. 05 for 1. 1 <  2 < 6. 0 GeV 2 / 4 , where the first uncertainty is statistical and the second systematic. These results are compatible with the SM at the level of 2. 6, 2. 1 -2. 3 and 2. 4 -2. 5 standard deviations, respectively.
(2013b)  estimates that 100-500 M yr -1 of molecular gas is expelled by this outflow. In this paper, we present high spatial resolution (∼ 50 milliarcsecond = 24. 5 parsec) maps of the inner few kiloparsecs of NGC 6240 highlighting key optical, near-infrared, and sub-millimeter emission lines, from narrowband imaging and 3D spectroscopy. This unique combined dataset offers the most comprehensive view to date of the structure of the ISM in a galaxy hosting AGN, star formation, outflows, and shocks. In Section 2, we describe our data and data processing techniques. We compare the fluxes and morphologies of emission lines in Section 3 and discuss their physical implications in Sections 4, 5, and 6. In Section 7, we summarize our conclusions. Throughout the paper we adopt H 0 = 70 km s -1 Mpc -1 , Ω m = 0.
Spectrograph on the ANU 2. 3-m Telescope We use observations of NGC 6240 from WiFeS on the ANU 2. 3-m Telescope at Siding Spring Observatory, taken in July 2014, with 10-minute frames taken at a ratio of approximately three target frames to one sky frame, totaling 120 minutes on source. WiFeS (Dopita et al. 2007 , 2010)  is a dual-arm image slicer that, in this mode, covers 3700-5700 Å at a spectral resolution of R∼3000 and 5700-7000 Å at R∼7000; WiFeS frames cover an area of 25 ×36 , with 1 spatial sampling. During these observing runs, the seeing was approximately 1. 5. Our WiFeS data were reduced using the standard PyWiFeS pipeline v0. 6. 0  (Childress et al. 2014). The resulting blue and red data cubes were median-combined and then analyzed using LZIFU  (Ho et al. 2016) , an IDL package that uses penalized pixel fitting (pPXF; Cappellari & Emsellem 2004) to fit the stellar continuum and then MPFIT  (Markwardt 2009)  to fit one, two, or three Gaussian components to each of 11 strong emission lines simultaneously.