dataesr/scientific-paragraphs-categorization huggingface dataset:
Spectroscopic dataset The rationale of our selection is illustrated in Fig. 1. Figure  1a  shows the CMD of a circular region within 1. 0 • from the centre of Sgr (coinciding with the centre of the massive globular cluster M 54). The innermost 11. 5 is excised to minimise the contamination by the compact stellar nucleus  (Bellazzini et al. 2008; Carlberg & Grillmair 2022) , according to the 2010 version of the  Harris (1996)  catalogue, where the tidal radius of M 54 is r t = 9. 9 , while  Bellazzini et al. (2008)  reported r l 10. 5 as the limiting radius of the metal-rich component of the stellar nucleus. While part of the horizontal branch (at G 18. 3 and G BP -G RP < 0. 7) and the bright asymptotic giant branch (AGB) sequence of Sgr, bending to the red from (G, G BP -G RP ) (14. 6, 2. 3), are relatively clean, its red clump (G, G BP -G RP ) (17.
2008; Majewski et al. 2013, hereafter M13) , thus ensuring that no significant bias on the MDF can arise from kinematic cuts. The second criterion removes most of the foreground stars that happen to have proper motions within the adopted selection window, and it is justified by the fact that the parallax corresponding to the distance to the core of Sgr dSph (which we assume throughout the paper to be D = 26. 3, from  Monaco et al. 2004 ) is ω 0. 04 mas, virtually indistinguishable from zero, within the typical uncertainty of the considered data (err ω 0. 08 mas). From this sample, is easy to select stars that sample the entire colour range spanned by the Sgr RGB, thus avoiding the biases against metal-poor stars that affected previous analyses. We also selected our targets only in the magnitude range 16.
Metallicity The chemical abundances were then derived using our own code SALVADOR, which performs a χ 2 minimisation between the observed line and a grid of suitable synthetic spectra calcu-lated on the fly using the code SYNTHE  (Kurucz 2005 ) and varying only the abundance of the corresponding element. Model atmospheres were calculated for each star with the code ATLAS9  (Kurucz 1993 (Kurucz , 2005)). The lines were selected in order to avoid blended or saturated lines, and we kept only transitions that were not affected by residuals of the sky subtraction. The number of Fe lines we used changed with the metallicity, atmospheric parameters, and noise of the spectra. We used from 2 (1% of the sample) to 19 lines (0. 5% of the sample). The median value of the number of Fe lines is 15. To determine the uncertainty, two main sources of error were taken into account: the error arising from the measurement procedure, and that arising from the uncertainty in atmospheric parameters.
All the marginalised PDFs are bell-shaped and remarkably symmetric. We used our new dataset to follow this result up. With respect to M13, our sample is slightly larger and confined to a more restricted radial range. However, as expected, it provides a significantly extended sampling of the metal-poor population because only six of the stars analysed by M13 reach [Fe/H] < -1. 0 (see their Fig. 2h ). As a first step, we compared the RV distributions of the subsamples with a metallicity above or below a certain threshold [Fe/H] tresh using the Kolmogorov-Smirnov (KS) statistical test. The probability that the two sub-samples are extracted from the same parent RV distribution is lower than 5. 0% for thresholds in the range -0. 6 ≤ [Fe/H] tresh ≤ -1. 0, with a minimum of P KS < 0. 5% at [Fe/H] tresh = -0.
Acknowledgements. The data presented and analysed in this paper were collected under the  ESO program   105. 20AH. 001. MB acknowledge the financial support to this research by the  PRIN-INAF  Grant  1. 05. 01. 85. 14 Building up the halo: chemo-dynamical tagging in the age of large surveys ( P. I. Sara Lucatello ). This work has made use of data from the  European Space Agency (ESA) mission Gaia  (https://www. cosmos. esa. int/gaia),processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement. This work has made use of  Sloan Digital Sky Survey IV (SDSS-IV ) data. Funding for the SDSS-IV has been provided by the  Alfred P.
Patients and methods All site RTQA approvals and ICRs are tracked on an individual trial basis. All QUARTET FQs, BOA certificates, and CDC reports submitted for the purposes of site RTQA approval within the European paediatric Soft tissue Sarcoma Group FaR-RMS 2 (EUDRACT 2018-000515-24); SIOP Europe Neuroblastoma group VERITAS 3  (EUDRACT 2015-003130-27) and HR-NBL2 4 (EUDRACT 2019-001068-31), and SIOP Brain Tumour Group HRMB 5 (EUDRACT 2018-004250-17) trials were collated, and a descriptive analysis of participating institutions performed. Institutions with site RTQA approval completed by 31/10/2022 were included. Individual trial trackers and database records for ICR case submission and review forms for all cases submitted for ICR between 01/05/2016 and 31/10/2022, within the HR-NBL1 6 (EUDRACT 2006-001489-17), LINES 7 (EUDRACT 2010-021396-81), HR-NBL2, VERITAS, HRMB, and FaR-RMS trials were reviewed and collated for descriptive analysis.
By comparison, 2017 is the earliest treatment year for all other QUARTET-affiliated trials and 3DCRT is rarely used. The rise in retrospective reviews in 2020 is also explained by the HR-NBL1 cohort because it was at this time that the radiotherapy committee made an additional effort to expand the dataset, profiting from the technical advantages of the QUARTET platform over the SIOPEN R-NET system  [3, 25]. The initial QUARTET ICR outcomes show that inconsistency in planning, particularly due to (target) delineation remains a challenge, impacting the quality of radiotherapy treatments for children. This echoes the previous reports of protocol noncompliance rates and the importance of peer-review  [5, 6, 13, 14, [26] [27] [28]  to this population of patients as well as adults. Prospective ICR will continue to be prioritised, but regular amendments to the RTQA guidelines and implementation of additional education resources will also be necessary to better support investigators to meet protocol requirements at first submission, and to monitor and standardise decision making in areas of conflict which result in justified variations.
Acknowledgements The authors would like to acknowledge the support of  Gilles Vassal ,  Pam Kearns , and others at SIOP Europe in establishing the  QUARTET  project, and the international trial sponsors who have integrated QUARTET into their clinical trials:  Dominique Valteau-Couanet  (CI) with  Habiba Lynda Attalah  and colleagues at  Gustave Roussy (France)  for the  High Risk Neuroblastoma 2 study ;  Meriel Jenney  (CI),  Nicola Fenwick  and colleagues at  CRCTU  and the  University of Birmingham (UK)  for the Frontline and  Relapsed Rhabdomyosarcoma  study,  Vanessa Segura  and  Instituto de Investigación Sanitaria La Fe de Valencia , and  St. Anna Kinderkrebsforschung. Thanks too to  Lorenza Gandola  for her contributions to  High Risk Medulloblastoma ,  Daniel Portik  for data collection relating to the beam output audits,  Nick Reynaert  for supporting site approval activities,  James Talbot  and all of the QUARTET reviewers, the SIOPEN and EpSSG radiotherapy committees, all QUARTET collaborators, and especially to all patients or parents for their consent to participate in these clinical trials.
Acknowledgements The authors acknowledge  IBA  for the support in using the machine in FLASH mode. This work was partly funded by the  European Union 's  Horizon 2020 research and innovation program  under grant agreement No. 730983  (INSPIRE). This work was partly done in the framework of the project  18HLT04   UHDpulse , which has received funding from the  EMPIR program , co-financed by the Participating States and from the  European Union 's  Horizon 2020 research and innovation program. The simulations for this work were carried out using the access to the HPC resources of TGCC under the allocation 2021-A0100312448 made by  GENCI.
Executive summary This paper provides updated world averages of measurements of b-hadron, c-hadron, and τ -lepton properties using results available by September 2018. In a few cases, later important results are included and clearly labelled as such. While new measurements since the previous version of this paper  [1]  have been dominated by the LHCb and the BESIII experiments, there are new results from many other experiments, and the older results from previous generations of experiments are still very important. The future will provide updated results, with the most important change being that Belle II has started data taking in 2019. Since the previous version of the paper, the b-hadron fraction, lifetime and mixing averages have mostly made small incremental progress in precision, with the most significant improvements in several effective B 0 s lifetimes.
In some cases where the matrices are large, it is inconvenient to report them in this document, and they can instead be found on the HFLAV web pages. The value of χ 2 ( x) provides a measure of the consistency of the independent measurements of x after accounting for the number of degrees of freedom (dof), which is the difference between the number of measurements and the number of fitted parameters: N •n-n. The values of χ 2 ( x) and dof are typically converted to a confidence level (CL) and reported together with the averages. In cases where χ 2 /dof > 1, we do not usually scale the resulting uncertainty, in contrast to what is done by the Particle Data Group  [5]. Rather, we examine the systematic uncertainties of each measurement to better understand them. Unless we find systematic discrepancies among the measurements, we do not apply any additional correction to the calculated uncertainty.
While formally suppressed by inverse powers of p T , these effects may be sizable, especially when the fragmentation probabilities are small as e. g. in the case of b baryons. In fact, the available data show that the fractions depend on the kinematics of the produced b hadron. Both CDF and LHCb report a p T dependence of the fractions, with the fraction of 0 b baryons observed at low p T being enhanced with respect to that seen at LEP at higher p T. We present here two sets of averages: one set includes only measurements performed at LEP, and the second set includes only measurements performed by CDF at the Tevatron. 3  While the first set is well defined and is basically related to branching fractions of inclusive Z 0 decays, the other set is somewhat ill-defined, since it depends on the kinematic region covered by the experiment and over which the measurements are integrated.
B 0 and B + lifetimes and their ratio After a number of years of dominating these averages, the LEP experiments yielded the scene to the asymmetric B fac-  tories and the Tevatron experiments. The B factories have been very successful in utilizing their potential -in only a few years of running, BABAR and, to a greater extent, Belle, have struck a balance between the statistical and the systematic uncertainties, with both being close to (or even better than) an impressive 1% level. In the meanwhile, CDF and D0 have emerged as significant contributors to the field as the Tevatron Run II data flowed in. In more recent years, the LHCb experiment reached a further step in precision, improving by a factor ∼ 2 over the previous best measurements. At the present time we are in an interesting position of having three sets of measurements (from LEP/SLC, B facto-ries and Tevatron/LHC) that originate from different environments, are obtained using substantially different techniques and are precise enough for cross-checking and comparison.
Since then, both BABAR and Belle have published improved measurements and have observed the B → Dτ ν τ decays  [615, 616]. The most powerful way to study these decays at the B-Factories exploits the hadronic or semileptonic B tag. Using the full dataset and an improved hadronic B tag selection, BABAR measured [617]: R(D) = 0. 440 ± 0. 058 ± 0. 042, R(D * ) = 0. 332 ± 0. 024 ± 0. 018  (227)  where decays to both e ± and μ ± were summed, and results for B 0 and B -decays were combined in an isospinconstrained fit. The fact that the BABAR result exceeded SM predictions by 3. 4σ raised considerable interest. Belle, exploiting the full dataset, published measurements using both the hadronic [618] and the semileptonic tag  [619]. Belle also performed a combined measurement of R(D * ) and τ polarization by reconstructing the τ in the hadronic τ → πν and τ → ρν decay modes  [620].
Four of the five states have been confirmed by  Belle [1440]  and, although the Belle dataset is much smaller than that of LHCb, these mass measurements do contribute to the world averages. There is evidence for a further, wider, state at higher mass in the LHCb data. Belle data shows a small excess in the same region, but it is of low significance (Table  299 ). Figure  106  shows the levels of excited charm baryons along with corresponding transitions between them, and also transitions to the ground states. We note that Belle and BABAR discovered that transitions between families are possible, i. e. , between the c and + c families of excited charmed baryons  [738, 1428] , and that highly excited states are found to decay into a non-charmed baryon and a D meson  [1420, 1430].
Acknowledgements We are grateful for the strong support of the ATLAS, BABAR, Belle, BESIII, CLEO(c),  CDF , CMS, D0 and LHCb collaborations, without whom this compilation of results and world averages would not have been possible. The success of these experiments in turn would not have been possible without the excellent operations of the BEPC-II, CESR, KEKB,  LHC ,  PEP-II , and  Tevatron  accelerators. We also recognise the interplay between theoretical and experimental communities that has provided a stimulus for many of the measurements in this document. We thank the  SLAC National Acceler-ator Laboratory  for providing crucial computing resources and support to HFLAV in past years and  CERN  for taking this over from 2018. Our averages and this compilation have benefitted greatly from contributions to the Heavy Flavour Averaging Group from numerous individuals.
The non-idempotent N-representable 1RDM space is spanned using the self-consistent protocol presented in  [32]. The various results pertain to the case of a single impurity. The generalization to multiple impurities, discussed in Section 2. 2, will not be covered in this paper. For comparison purposes, the standard BHt method (gray lines) and the various cost function-based methods in this work (colored lines) are compared at the same level of numerical complexity, meaning that the clusters contain the same number of orbitals. For example, the single impurity and three orbitals in the bath in our approach are compared to the two impurities BHt, the latter containing two orbitals in the bath. Additionally, the variational parameters are optimized using the numpy Python library  [39] , particularly with the L-BFGS-B method, which is similar to the conjugate gradient optimization method.
Today's situation at Jupiter is like the situation at Earth before SAMPEX. Even the instrumentation and orbits of the upcoming Jupiter missions Europa Clipper and JUICE are optimized to perform only outside of the most intense and energetic radiation, despite the general interest in Jupiter's radiation. We therefore still cannot even claim that we would reliably know how particles distribute in Jupiter's radiation belts, limiting our ability to understand their origins and physics at work. While a lot of effort is being put into cleaning, correcting, and processing this unique data as best as possible (e. g. Nenon+17, Roussos+21, Kollmann+21), these efforts remain severely limited by the data quality. While radiation models exist (e. g. de Soria-Santacruz+16), they serve mostly mission design and operations and despite best efforts remain as reliable as Earth's recent "AE9" model  (Johnston et al.
Discussion The introduction of the electromagnetic array increases the noise within kV-CBCT images, without significantly degrading the absolute contrast. The impact on the accuracy patient positioning should be limited. To date, our data are the first to evaluate the kV-CBCT image quality with the whole Calypso system (QFix kVue couch top and the electromagnetic array). Only Ye et al. [8]  exhibited an abstract about the assessment of the Calypso tabletop for CBCT imaging. They compared CBCT acquisitions between the carbon fiber tabletop and synthetic fiber tabletop. Imaging characteristics were equivalent for both designs. The dosimetric tests revealed an important attenuation for the fixed beams crossing the rails. However, the QFix kVue flat couch top and the electromagnetic array attenuate the 6MV FF and 6MV FFF beams less than 2%.
Molecular hydrogen clouds are a key component of the interstellar medium because they are the birthplaces for stars. However, the details of how molecular clouds assemble and interact are still largely unknown. Thanks to new observations of the 158 µm line of ionized carbon [C II] in the Cygnus region within Ionized carbon tracing the assembly of interstellar clouds the FEEDBACK program on SOFIA, we present for the first time compelling evidence that [C II] unveils dynamic interactions between cloud ensembles. This process is neither a head-on collision of fully molecular clouds nor a gentle merging of only atomic clouds. Moreover, we demonstrate that the dense molecular clouds associated with the DR21 and W75N star-forming regions and a cloud at higher velocity are embedded in atomic gas and all components interact over a large range of velocities (∼20 km s -1 ).
Observations and data reduction The Cygnus X region was observed during several flights in 11/2019, 2/2021, 11/2021 and 4/2022 for the legacy program FEEDBACK, using the 2. 7m telescope onboard the Stratospheric Observatory for Infrared Astronomy (SOFIA). The dualfrequency heterodyne array receiver upGREAT  [23]  was tuned to the [C II] 157. 7 µm line in the Low Frequency Array (LFA) 2×7 pixel array and the [O I] 63 µm line (not shown) was observed in the High Frequency Array (HFA) 7 pixel array. The LFA has an array size of 72. 6 ′′ , and a pixel spacing of 31. 8 ′′. The half-power beam width at 158 µm is 14. 1 ′′ , determined by the instrument and telescope optics, and confirmed by observations of planets. For each flight series, the main-beam efficiencies η mb for each pixel for the LFA and HFA channels were determined, the average value for the LFA is 0.
Using a linear combination of the strongest components, we reconstruct the ONOFF spectra with the best-fit coefficients for each component. We scale each component by the coefficients that were found and subtract those from the ONOFF spectra. This procedure removes the systematic variations found in the OFFOFF spectra but does make changes to the astronomical line in terms of intensity, width, position etc. in the ONOFF spectra. We further improve the data quality by using a sophisticated algorithm to determine a set of spectra that are free of emission from the PCA-corrected spectra for each frontend and SOFIA flight. With this set of emission free spectra we employ a second PCA-correction equal to the one described above, but using now these emission-free spectra to determine the baseline "components".
Data availability The calibrated and polynominal baseline-corrected [C II] data cubes at a velocity resolution of 0. 2 km s -1 are provided by the IRSA/IPAC archive and are found at https://irsa. ipac. caltech. edu/applications/sofia under the project Number 07 0077 (FEEDBACK, PIs are A. G. G. M. Tielens and N. Schneider).
Acknowledgments. This study was based on observations made with the  NASA/DLR Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is jointly operated by the  Universities Space Research Association Inc. (USRA) , under  NASA  contract  NNA17BF53C , and the  Deutsches SOFIA Institut (DSI) , under  DLR  contract  50 OK 0901  to the  University of Stuttgart. upGREAT is a development by the  MPIfR and University of Cologne , in cooperation with the  DLR Institut für Optische Sensorsysteme. Financial support for FEEDBACK at the  University of Maryland  was provided by  NASA  through award  SOF070077  issued by  USRA. The  FEEDBACK  project is supported by the  BMWI via DLR , Projekt Number  50 OR 1916. N. S. , S. B. , R. S. , and L. B. acknowledge support through the project " GENESIS"  ( ANR-16-CE92-0035-01/DFG1591/2-1 ).
IV. EXPERIMENTAL RESULTS Figure  3 (a) shows an example of the results that we obtained for a gate voltage of V g = 0 V. We can see a waterfall plot of the electrical signal measured on the n-InSb detector, each curve being recorded at a different magnetic field applied on the sample. Every curve features a peak at a defined energy, witnessing a Landau emission coming out of the QW. It seems that this emission energy is growing with the magnetic field applied. It is confirmed with Fig. 3(b) , which depicts a colormap of the complete dataset obtained for this particular gate voltage value. The emission energy evolves linearly with the magnetic field applied on the sample, in accordance with the semi-classical cyclotron formula (1). From a linear fit, one can extract the value of the cyclotron mass.
ACKNOWLEDGMENTS This work was supported by the  TeraHertz Occitanie Platform , the  CNRS  through  IRP  " TeraMIR " by the  French Agence Nationale pour la Recherche (ANR)  for  Equipex+ Hybat  ( ANR-21 -ESRE-0026 ) project, by the  European Union  and the  ANR for Flag-Era JTC 2019   DeMeGRaS  project ( ANR-19-GRF1-0006-03 ), and the  Center of Excellence (Center of Photonics) , funded by the  Ministry of Science and Higher Education of the Russian Federation  (Contract No. 075-15-2022-316 ; S. V. M. , V. I. G. ). We would like to thank  Laurent Bonnet  and  Nassim Mouelhi  for technical support.
In order to obtain a 4+1-dimensional collision, 2  we choose to work with nontrivial dependence along three of the n -1 horizon directions. The whole set of simulations where done using the code Chihuahua  [48] , written in the Julia language. It can use both pseudospectral FFT differentiation and finite differences for the spatial derivatives, with a fixed time step RK4 time evolution algorithm. In all simulations in this paper, we use single-domain FFT differentiation. We chose L x = L y = L z = 100, with N x = N y = 50 and N z = 150, and the time step is taken to be ∆t = 0. 1 in all cases. Running each simulation up to t end = 30 took about 20 minutes on a single Intel Core i7-10750H at 2. 60GHz CPU, a short time compared to the typical AdS 5 shock collision simulations, allowing for a scan over possible different scenarios.
Acknowledgments We thank  David Ramirez  and  Martin Sasieta  for useful discussions. We are grateful to  David Mateos  and  Roberto Emparan  and  Marija Tomašević  for their very useful comments on the first manuscript. We thank  David Licht ,  Ryotaku Suzuki  and  Roberto Emparan  for their early exploratory work in this line of research. RL acknowledges financial support provided by  Next Generation EU  through a  University of Barcelona Margarita Salas grant  from the  Spanish Ministry of Universities  under the  Plan de Recuperación , Transformación y Resiliencia and by  Generalitat Valenciana / Fons Social Europeu  through  APOSTD 2022 post-doctoral grant   CIAPOS/2021/150. Work supported by  Spanish Agencia Estatal de Investigación  (Grant  PID2021-125485NB-C21 ) funded by  MCIN/AEI/10.