dataesr/scientific-paragraphs-categorization huggingface dataset:
Signal extraction and unfolding The number of signal events in data is extracted by subtracting the expected number of background events from the observed number of events for each bin of the observables. All expected background numbers are obtained directly from the MC simulations (see Section 3) except for tt final states other than the signal. The latter are dominated by events in which one or both of the intermediate W bosons decay into τ leptons with subsequent decay into an electron or muon. These events arise from the same tt production process as the signal and thus the normalisation of this background is fixed to that of the signal. For each bin the number of events obtained after the subtraction of other background sources is multiplied by the ratio of the number of selected tt signal events to the total number of selected tt events (i.
Cross section determination The normalised cross sections for tt production are measured in the full tt kinematic phase space at parton level. The number of unfolded signal events Munf i in bins i of kinematic variables is used to define the normalised cross sections as a function of several (two or three) variables σ i σ = 1 σ Munf i B L , (1) where the total cross section σ is evaluated by summing σ i over all bins, B is the branching ratio of tt into e + e -, µ + µ -, and e ± µ ∓ final states and L is the integrated luminosity of the data sample. For presentation purposes, the measured cross sections are divided by the bin width of the first variable. They present single-differential cross sections as a function of the first variable in different ranges of the second or second and third variables and are referred to as double-or triple-differential cross sections, respectively.
Experimental uncertainties To account for the pileup uncertainty, the value of the total pp inelastic cross section, which is used to estimate the mean number of additional pp interactions, is varied by ±4. 6%, corre-sponding to the uncertainty in the measurement of this cross section  [61]. The efficiencies of the dilepton triggers are measured with independent triggers based on a p miss T requirement. Scale factors, defined as the ratio of the trigger efficiencies in data and simulation, are calculated in bins of lepton η and p T. They are applied to the simulation and varied within their uncertainties. The uncertainties from the modelling of lepton identification and isolation efficiencies are determined using the "tag-and-probe" method with Z +jets event samples  [73, 74]. The differences of these efficiencies between data and simulation in bins of η and p T are generally less than 10% for electrons, and negligible for muons.
(tt)] cross sections using external PDFs To extract α S and m pole t , the measured triple-differential cross sections are compared to fixedorder NLO predictions that do not have variable parameters, except for the factorisation and renormalisation scales. These predictions provide a simpler assessment of theoretical uncertainties than predictions from MC event generators. The latter complement fixed-order computations with parton showers, thus accounting for important QCD corrections beyond fixed order, but complicating thereby the interpretation of the extracted parameters, because the modelling of the showers can involve different PDFs and α S values. Furthermore, for PDF fits using these data (to be discussed in Section 10), fast computation techniques are required that are currently available only for fixed-order calculations.
The measured cross sections for N jet ≥ 1 are compared to the NLO calculation for inclusive tt + 1 jet production, while those for N jet = 0 are compared to the difference of the NLO calculations for inclusive tt and inclusive tt + 1 jet production. The normalisation cross section is evaluated by integrating the differential cross sections over all bins, i. e. it is given by the inclusive tt cross section. As discussed below, χ 2 values are calculated for the comparisons of data and NLO predictions and are also used for the extraction of parameter values. The total χ 2 values obtained are identical for the comparisons based on inclusive tt and tt + 1 jet production cross sections and the ones based on the [N 0,1+ jet , M(tt ), y(tt )] results, shown in Figs. [14] [15] [16] , because the χ 2 values are invariant under invertible linear transformations of the set of cross section values.
The NLO predictions are obtained using the MG5 aMC@NLO framework running in the fixedorder mode. A number of the latest proton NLO PDF sets are used, namely: ABMP16  [87] , CJ15  [88] , CT14  [60] , HERAPDF2. 0 [89] , JR14  [90] , MMHT2014  [91] , and NNPDF3. 1  [92] , available via the LHAPDF interface (version 6. 1. 5) [93]. No tt data were used in the determination of the CJ15, CT14, HERAPDF2. 0 and JR14 PDF sets; only total tt production cross section measurements were used to determine the ABMP16 and MMHT2014 PDFs, and both total and differential (from LHC Run 1) tt cross sections were used in the NNPDF3. 1 extraction. The number of active flavours is set to n f = 5, an m pole t = 172. 5 GeV is used, and α S is set to the value used for the corresponding PDF extraction. The renormalisation and factorisation scales are chosen to be µ r = µ f = H /2, H = ∑ i m t,i.
Theoretical uncertainties from scale, α S (m Z ), and m pole t variations are not included in this χ 2 calculation. Sizeable differences of the χ 2 values are observed for the predictions obtained using different PDFs. These differences can be attributed to the different input data and methodologies that were used to extract these sets of PDFs as discussed elsewhere  [95, 96]. Among the PDF sets considered, the best description of the data is provided by the ABMP16 PDFs. This comparison also shows that the data prefer lower α S (m Z ) and m pole t value than in the nominal calculation using CT14. The largest sensitivity to m pole t is observed in the lowest M(tt ) region close to the threshold, while the sensitivity in the other M(tt ) bins occurs mainly because of the cross section normalisation.
The values of α S (m Z ) and m pole t are extracted by calculating a χ 2 between data and NLO predictions as a function of the input α S (m Z ) or m pole t value, and approximating the dependence with a parabola. The minimum of the parabola is taken as the extracted α S (m Z ) or m pole t value, while its uncertainty is estimated from the ∆χ 2 = 1 variation. This extraction is performed separately using different PDF sets, as well as different scale values. As for the additional χ 2 values in Fig. 14 , the PDF uncertainties in the predictions are taken into account in these χ 2 calculations. Among the available PDF sets, only CT14, HERAPDF2. 0, and ABMP16 provide PDF sets for enough different α S (m Z ) values and are suitable for α S (m Z ) extraction. Because the dependence of the measured [N The theoretical uncertainties for [N 0,1+ jet , M(tt ), y(tt )] (upper) and [N 0,1,2+ jet , M(tt ), y(tt )] (lower) cross sections, arising from PDF, α S (m Z ), and m pole t variations, as well as the total theoretical uncertainties, with their bin-averaged values shown in brackets.
Simultaneous PDF, α S , and m pole t fit The triple-differential normalised [N 0,1+ jet , M(tt ), y(tt )] cross sections are used in a simultaneous PDF, α S , and m pole t fit at NLO (also referred to as a QCD analysis, or PDF fit), together with the combined HERA inclusive deep inelastic scattering (DIS) data  [89]. The XFITTER program (version 2. 0. 0) [102] , an open-source QCD fit framework for PDF determination, is used. The precise HERA DIS data, obtained from the combination of individual H1 and ZEUS results, are directly sensitive to the valence and sea quark distributions and probe the gluon distribution through scaling violations. Therefore, these data form the core of all PDF fits. The measured tt cross sections are included in the fit to constrain α S , m pole t , and the gluon distribution at high values of x, where x is the fraction of the proton momentum carried by a parton.
Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440 and 765710 (European Union); the Leventis Foundation; the A. P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F. R. S. -FNRS and FWO (Belgium) under the "Excellence of Science -EOS" -be. h project n. 30820817; the Beijing Municipal Science & Technology Commission, No. Z181100004218003; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lend ület ("Momentum") Programme and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program ÚNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Scientific and Industrial Research, India; the HOMING PLUS programme of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus programme of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa de Excelencia María de Maeztu, and the Programa Severo Ochoa del Principado de Asturias; the Thalis and Aristeia programmes cofinanced by EU-ESF, and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University, and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Welch Foundation, contract C-1845; and the Weston Havens Foundation (USA).
Entre 95 et 400 millions de dollars, évaluation à retrouver dans le rapport : U. S. Army Corps Of Engineers Alaska District, Alaska Baseline Erosion Assessment A Veta Report Summary-Kivalina, Alaska 2 (2009). 4 Requête consultable en ligne via la base de données du Sabin Center for Climate Change, http://blogs2. law. columbia. edu/climate-changelitigation/wp-content/uploads/sites/16/case-documents/2008/20080226_docket-408-cv-01138-SBA_complaint. pdf (consulté le 1er avril 2020). 5 D'autres moyens sont invoqués, notamment le « civil conspiracy », mais ils ne seront pas traités par les Cours en raison de l'irrecevabilité de la requête. Nous nous concentrerons dans ce commentaire sur une analyse et une description de l'argument structuré autour  de   Consultable en ligne sur la base de données du Sabin Center for Climate Change, http://blogs2.
Ainsi, après que l'appel fut interjeté par les représentants du village, les sociétés défenderesses ne manquèrent pas de soulever ce nouvel argument de poids devant la Cour d'appel du 9 e circuit. Les demandeurs 7Mémoire en réponse consultable en ligne via la base de données business-humanrights. org, https://turtletalk. files. wordpress. com/2008/12/ shell-reply-brief. pdf (consulté le 1 er avril 2020).
Ainsi, après que l'appel fut interjeté par les représentants du village, les sociétés défenderesses ne manquèrent pas de soulever ce nouvel argument de poids devant la Cour d'appel du 9 e circuit. Les demandeurs 7Mémoire en réponse consultable en ligne via la base de données business-humanrights. org, https://turtletalk. files. wordpress. com/2008/12/ shell-reply-brief. pdf (consulté le 1 er avril 2020). -par rapport aux conséquences du réchauffement climatique -les juges devaient se prononcer dans AEP sur une injonction de réduire les émissions de GES. Or, pour les demandeurs, il y a là une différence suffisante pour ne pas conclure au rejet complet de la Public Nuisance Doctrine, et ils demandèrent ainsi clarification sur ce point. Fin 2011, le panel de juges de la Cour d'appel du 9 e circuit 10 confirma unanimement la décision de la District Court, avec une argumentation néanmoins beaucoup moins détaillée.
Une pétition de « writ of certiriorari » 14 fut enfin déposée en 2013, en dernier ressort, auprès de la Cour Suprême. Dans cette dernière, la communauté de villageois argumenta en particulier de la 10 Native Village of Kivalina c. ExxonMobil Corporation and al. , 4 : 08-cv-01138-SBA (9th Cir. 2011) consultable en ligne via la base de données du Sabin Center for Climate Change, http://blogs2. law. columbia. edu/climate-change-litigation/wp-content/uploads/sites/16/case- documents/2012/20120921_docket-09-17490_opinion. pdf (consulté le 1 er avril 2020). 11 Article III, section 2,  §1 et 2 (extraits) : «  §1 The judicial Power shall extend to all Cases, in Law and Equity, arising under this Constitution, the Laws of the United States, and Treaties made, or which shall be made, under their Authority […].
La district Court l'estima « non-fairly traceable ». Dans le même temps, et parallèlement à cette procédure, la Cour suprême des États-Unis se prononça dans une autre affaire pendante depuis 2005, l'affaire Connecticut c. American Electric Power dite AEP 9. À l'instar de Kivalina, cette affaire opposait plusieurs collectivités publiques à cinq compagnies pétrolières sur le sujet de la régulation des émissions de gaz à effet de serre. Les plaignants fondaient également leur requête sur la théorie de la Public Nuisance. Dans cette affaire, la Cour suprême trancha en faveur du Clean Air Act et rejeta l'application de la théorie de la Public Nuisance. 8 Native Village of Kivalina c. ExxonMobil Corporation and al. , C 08-1138 SBA (N. D. Miss. , 2009) consultable en ligne via la base de données du Sabin Center for Climate Change, http://blogs2.
The VCS sources, still, had position uncertainties typically five times larger than the other sources due to being observed in survey mode and generally only in a single session. For this reason, they were categorized separately from the IVS sources in ICRF2. Since the release of ICRF2, the VLBI database has continued to expand thanks to ongoing observing programs run by the IVS but also through specific projects carried out independently, notably by using the VLBA. The latter includes a complete reobservation of all VCS sources in 2014-2015, which has brought an overall factor of five improvement in coordinate uncertainties, hence bringing position uncertainties for the VCS sources closer to those for the rest of the ICRF2 sources  (Gordon et al. 2016). A specific effort has also been made to strengthen observations of optically bright ICRF2 sources within IVS programs to facilitate the alignment of the optical reference frame which is being built by the Gaia space mission (Le  Bail et al.
Observations The VLBI data used to build ICRF3 were acquired by arrays of 2 to 20 radiotelescopes organized in their vast majority under the umbrella of the IVS, the VLBA, and the DSN. Over the years, a total of 167 telescopes, located on 126 different sites, participated in such VLBI sessions (Fig. 1 ). Observations were carried out using the so-called bandwidth synthesis mode, which permits the determination of precise group delay quantities by observing multiple channels spread out across a bandwidth of several hundred MHz, as originally devised by  Rogers (1970). Following acquisition, the data were processed at one of the IVS correlators (in Bonn, Haystack, Kashima, Shanghai, Vienna, or Washington), the VLBA correlator in Soccoro, the Australia Telescope National Facility correlator in Perth, or the DSN processor in Pasadena.
S/X band (2. 3/8. 4 GHz) The data used for ICRF3 in this frequency band include the entire pool of geodetic and astrometric VLBI sessions acquired and made available by the IVS with rare exceptions. The sessions range from August 3, 1979 to March 27, 2018 and come from a variety of programs dedicated to monitor the Earth orientation, establish the terrestrial and celestial reference frames, and maintain and expand these, according to the objectives of the IVS  (Schuh & Behrend 2012). Details on the current observing programs are given in  Nothnagel et al. (2017). Data acquired prior to the establishment of the IVS in 1999 had similar goals and were obtained through ad hoc arrays organized by cooperations between individual observatories or national agencies and are described in  Ma et al. (1998).
e. , when ICRF2 was delivered), (ii) had less than 50 observations, (iii) were observed in three or fewer sessions, or (iv) were among the weakest known opti-cally bright sources listed in Le  Bail et al. (2016). The goal here was to further enhance uniformity of the data sets for ICRF3. In all, the VLBA sessions constitute only a small portion of the entire set of S/X band sessions (200 sessions out of a total of 6206 sessions) but account for 26% of the data, while more than two-thirds (68%) of the sources have observations coming exclusively from the VLBA. See  Gordon (2017)  for further details on the impact of the VLBA observing on the celestial frame. A&A proofs: manuscript no. icrf3 -60°- 30°0 °+30°+ 60°- 120°-60°0°+60°+120°C.
The latest session incorporated in this work was conducted on May 5, 2018. Additionally, three archived VLBA sessions dedicated to observing sources in the Galactic plane  (Petrov et al. 2011)  were also included. Observations between Hartebeesthoek and Hobart were initiated at about the same time as the VLBA sessions restarted (first session run on May 4, 2014) to complete the sky coverage in the far south. One southern session also included the Tianma 65 m telescope near Shanghai (China) while another one included the Tidbinbilla 70 m telescope near Canberra (Australia). In all, the VLBA sessions account for 99% of the data while the Southern-Hemisphere sessions account for 1% of it, which leads to a majority of sources (66%) having only VLBA observations, a similar division as that at S/X band.
X/Ka band (8. 4/32 GHz) Observations at X/Ka band were initiated in 2005 with the primary goal of building a reference frame for spacecraft navigation, now conducted on the DSN using the Ka frequency band. The data set includes a total of 168 single-baseline sessions that involved seven telescopes at the three DSN sites in Goldstone (California), Robledo (Spain), and Tidbinbilla (Australia). The first of these sessions took place on July 9, 2005 while the most recent one incorporated was run on January 28, 2018. Occasionally (in about 10% of the sessions), the European Space Agency (ESA) telescope in Malargüe (Argentina) joined the observations, which was essential to improve the north-south geometry of the network and reduce systematics in the reference frame.
Analysis The principle behind VLBI data analysis is to compare measured quantities with a priori theoretical modeling of the same quantities and to refine underlying models by estimating model parameter corrections that best fit the data. Depending on the objective pursued, such parameters may pertain to the entire data set (e. g. , station positions and velocities, source positions,. ) or only to individual sessions (e. g. , the Earth orientation parameters,. ) or even to a small portion of a session (e. g. , clock and troposphere parameters which vary on the order of hours). Leastsquares methods are generally employed for this estimation. The VLBI modeling, analysis configuration, and software packages used to produce ICRF3 are outlined in the following sections.
Added to the geometric delay were corrections for atmospheric propagation, including the contribution due to highaltitude charged particles (ionosphere) and that due to the neutral component (troposphere). Ionospheric delays are proportional to the inverse of the frequency-squared and were calibrated using the dual-frequency data collected at S/X band and X/Ka band, whereas they were modeled using total electron content maps for K band. Such ionospheric maps are produced daily from global navigation satellite systems and were retrieved from NASA's Crustal Dynamics Data Information System  (Noll 2010)  for the purpose of the K band analysis. Tropospheric delays were derived using the VMF1 mapping function  (Böhm et al. 2006)  to map zenith delay contributions to relevant elevations. It must be noted that observations below 5 • elevation were discarded due to inadequacies in modeling the troposphere at such low elevations.
The zenith delays themselves were estimated every 30 minutes at each site using a continuous piecewise linear function during the least-squares parameter adjustment. Additional east-west and north-south tropospheric gradients were also estimated. The interval between such estimates was six hours for the S/X band and K band analyses, whereas they were estimated only once for the entire data set at X/Ka band due to the more limited sky coverage above each site for the latter. Corrections for instrumental delays were further added to the above geometric and atmospheric VLBI delay components. These come from propagation delays in the cables (which have a different length at each telescope), lack of synchronization of the clocks between stations, and clock instabilities. In practice, since it is not possible to calibrate those instrumental delays precisely, they were treated altogether, assuming an overall clock-like behavior at each telescope.
Of these components, only the first is expected to induce significant acceleration on a timescale of a few decades such as that of our VLBI data set. It is thus solely considered in the rest of this section. Based on the rotational property of the Galaxy, the solar system barycenter is known to move around the Galactic center with an orbital period of about 200 million years. Assuming a purely circular rotation, the resulting acceleration vector, which reflects the curvature of the orbit, is directed toward the Galactic center. Classically, this acceleration translates into an aberration effect which takes the form of an apparent overall proper motion for the distant extragalactic radio sources. The amplitude A G of this proper motion (see, e. g. ,  Kovalevsky 2003 ) is given by A G = V 2 0 R 0 c , (1) where R 0 is the distance of the barycenter of the solar system to the Galactic center, V 0 is the linear speed along its orbit, and c is the speed of light.
For the present work, we decided to re-determine the amplitude of the Galactic acceleration because we saw no compelling evidence to adopt one or the other of the published values (nor any of the unpublished values known to us) at the time. Additionally, the data sets on which those previous determinations are based are only up to 2016 whereas the data sets for ICRF3 extend to 2018. Because of the high-quality data acquired in the period, we thought these additional two years could make a difference. We also thought that it was most appropriate to use a value determined from a data set that covers the same time span as that for ICRF3. A dedicated analysis estimating both the amplitude and direction of the acceleration vector of the solar system barycenter was thus performed, prior to constructing ICRF3, based on the almost 40-year long S/X data set in our hand.
These sources either had not been imaged at the time ICRF2 was built or were subject to structural evolution in the meantime. A notable case is the source 0805+406 which shows a double structure with a component separation of about 6 mas, as revealed by VLBI images from the Bordeaux VLBI Image Database (BVID) 5  over the period 2010-2016. Its X band structure index 6  in BVID has a median value of 5. 5, well above the upper limit of 3. 0 adopted for the selection of the ICRF2 defining sources. Such a source has very poor astrometric suitability and is improper as a defining source. Additionally, another six ICRF2 defining sources which have a structure index in BVID between 3. 5 and 4. 0 (0440+345, 1038+528, 1548+056, 1823+689, 2106-413, and 2326-477) were deemed to be not good enough either.