dataesr/scientific-paragraphs-categorization huggingface dataset:
The primary end point was analyzed in both the intention-to-treat (ITT; primary analysis) and per-protocol (PP) populations. Secondary and post hoc efficacy variables were analyzed in the ITT population only. The ITT population was defined as all randomized patients who received at least one dose of study medication and with available efficacy data (primary or secondary efficacy variables) in at least two treatment periods. The PP population was defined as all patients from the ITT population without any major protocol deviations (ie, wrong inclusions, poor compliance and non-permitted medications). The safety population comprised all randomized patients who received at least one dose of study medication.
50% of patients responded. Dose-response to bronchodilators in COPD is typically assessed using FEV 1 analyses. However, given one of the classic features of COPD is hyperinflation, it is also useful to consider the effects of a bronchodilator on measures such as IC. In this study, all the four GB doses provided  statistically significant improvements versus placebo in pre-dose IC. The greatest improvement in IC was observed with the two higher GB doses, which provided differences from placebo consistent with those seen previously with tiotropium and aclidinium. 7, 8 These data therefore provide further support to the selection of 25 µg BID as the minimal effective dose of this formulation of GB. Of note, GB 25 µg BID is also the minimal effective dose for the extrafine pMDI formulation, in terms of both comparisons with placebo and as an add-on to BDP/FF.
Acknowledgments The authors would like to thank the investigators and patients at the investigative sites for their support of this study. Writing support was provided by  David Young  of  Young Medical Communications and Consulting Ltd. This support was funded by  Chiesi Farmaceutici SpA. This study was funded by  Chiesi Farmaceutici SpA. Employees of the sponsor were involved in study design, oversaw the conduct and analysis of the study and (as authors) took part in the decision to submit the manuscript.
The expression of the SNR is then used to simplify equation 1: SNR = S δ S (2) into: P Mie = 1 - 1 2 er f c( SNR -1 √ 2 ) (3) The complementary er f c function being monotonic, applying a threshold on P Mie is the same as applying a threshold on the Mie SNR. From a database of simulated scenarios, the SNR value enabling a high detection score has been determined.
The paper is organized as follows. Section 2 describes the framework for the standard, two-subevent and three-subevent four-particle cumulant methods used in this analysis. Details of the detector, trigger, datasets, as well as event and track selections are provided in Sections 3 to 5. The correlation analysis and systematic uncertainties are described in Sections 6 and 7, respectively. The measured cumulants from the three datasets are provided in Section 8. A summary is given in Section 9. 2 Four-particle cumulants The multi-particle cumulant method  [20]  is used to extract the amplitude of long-range azimuthal correlations of particles produced in high-energy collisions. This method has the advantage of suppressing correlations from jets and dijets, instead of relying on an explicit procedure to correct v n harmonics for dijet contributions in the 2PC approach, as done in Refs.
Detector and trigger The ATLAS detector  [27]  provides nearly full solid-angle coverage around the collision point with tracking detectors, calorimeters, and muon chambers, and is well suited for measurement of multi-particle correlations over a large pseudorapidity range  1. The measurements were performed primarily using the inner detector (ID), minimum-bias trigger scintillators (MBTS) and the zero-degree calorimeters (ZDC). The ID detects charged particles within η < 2. 5 using a combination of silicon pixel detector, a silicon microstrip detector (SCT), and a straw-tube transition radiation tracker, all immersed in a 2 T axial magnetic field  [28]. An additional pixel layer, the "insertable B-layer" (IBL)  [29]  installed between Run 1 (2010-2013) and Run 2 (2015-2018), is available for the Run-2 datasets.
Datasets and Monte Carlo simulations This analysis uses integrated luminosities of 28 nb -1 of p+Pb data recorded at √ s NN = 5. 02 TeV, 0. 17 pb -1 of pp data recorded at √ s = 5. 02 TeV, and 0. 9 pb -1 of pp data recorded at √ s = 13 TeV, all taken by the ATLAS experiment at the LHC. The p+Pb data were mainly collected in 2013, but also include 0. 3 nb -1 data collected in November 2016 which increases the number of events at moderate multiplicity (see  Section 5). During both p+Pb runs, the LHC was configured with a 4 TeV proton beam and a 1. 57 TeV per-nucleon Pb beam that together produced collisions at √ s NN = 5. 02 TeV, with a rapidity shift of 0. 465 of the nucleon-nucleon center-of-mass frame towards the proton beam direction relative to the ATLAS rest frame. The direction of the Pb beam is always defined to have negative pseudorapidity.
The 5. 02 TeV pp data were collected in November 2015. The 13 TeV pp data were collected during several special low-luminosity runs of the LHC in 2015 and 2016. Monte Carlo (MC) simulated event samples are used to determine the track reconstruction efficiency (Section 5). The 13 TeV and 5. 02 TeV pp data were simulated by the Pythia8 MC event generator  [24]  using the A2 set of tuned parameters with MSTW2008LO parton distribution functions  [33]. The HIJING event generator  [34]  was used to produce p+Pb collisions with the same energy and the same boost of the center-of-mass system as in the data. The detector response was simulated using Geant4  [35, 36]  with detector conditions matching those during the data-taking. The simulated events and data events are reconstructed with the same algorithms, including those for track reconstruction.
5 < p T < 5 GeV. These two p T ranges are chosen because they were often used in previous ridge measurements at the LHC  [11, [14] [15] [16] 19]. However, to count the number of reconstructed charged particles for event-class definition (denoted by N rec ch ), tracks with p T > 0. 4 GeV and η < 2. 5 are used for compatibility with the requirements in the HLT selections described above. Due to different trigger requirements, most of the p+Pb events with N rec ch > 150 are provided by the 2013 dataset, while the 2016 dataset provides most of the events at lower N rec ch. The efficiency of the combined track reconstruction and selection requirements in data is estimated using the MC samples reconstructed with the same tracking algorithms and the same track selection requirements. Efficiencies, (η, p T ), are evaluated as a function of track η, p T and the number of reconstructed charged-particle tracks, but averaged over the full range in azimuth.
For all collision systems, the efficiency increases by about 4% as p T increases from 0. 3 GeV to 0. 6 GeV. Above 0. 6 GeV, the efficiency is independent of p T and reaches 86% (72%) at η ≈ 0 ( η > 2) for pp collisions and 83% (70%) for p+Pb collisions, respectively. The efficiency is independent of the event multiplicity for N rec ch > 40. For lower-multiplicity events the efficiency is smaller by up to a few percent due to broader d BL 0 and z 0 sin θ distributions. The rate of falsely reconstructed charged-particle tracks is also estimated and found to be negligibly small in all datasets. This rate decreases with increasing p T , and even at the lowest transverse momenta of 0. 2 GeV it is below 1% of the total number of tracks. Therefore, there is no correction for the presence of these tracks in the analysis.
The results are mostly consistent with the nominal results within statistical uncertainties. As a crosscheck, the multi-particle correlations are calculated using a mixed-event procedure, where each particle in a 2k-multiplet is selected from a different event with similar N rec ch ( ∆N rec ch < 10) and similar z vtx ( ∆z vtx < 10 mm). The particle weights defined in Eq. (  13 ) are applied for each particle forming the mixed event. The c 2 {4} signal obtained from the mixed events is less than 0. 2 × 10 -6 in all datasets. The systematic uncertainty associated with the track selection is estimated by tightening the d 0 and z 0 sin θ requirements. For each variation, the tracking efficiency is re-evaluated and the analysis is repeated. The maximum differences from the nominal results are observed to be less than 0.
The nominal analysis is performed using the 50% efficiency selection and the differences between the nominal results and those from the 80% efficiency selection are used as a systematic uncertainty. The change amounts to (0. 1-0. 7)×10 -6. In this analysis, a pileup rejection criterion is applied to reject events containing additional vertices. In order to check the impact of residual pileup, the analysis is repeated without the pileup rejection criterion, and no difference is observed. For the 5. 02 and 13 TeV pp datasets, which have relatively high pileup, the data is divided into two samples based on the µ value: µ > 0. 4 and µ < 0. 4, and the results are compared. The average µ values differ by a factor of two between the two samples, and the difference in c 2 {4} is found to be less than 0.
Figures 9 and 10 compare the c 3 {4} values between the three datasets for the standard cumulant method and the three-subevent method. The c 3 {4} values from the three-subevent method are close to zero in all three systems. For the standard method, the positive c 3 {4} values in the small ⟨N ch ⟩ region indicate the influence of non-flow correlations, but the influence is not as strong as that for c 2 {4}. Figure  11  shows the c 3 {4} values from p+Pb collisions in the two p T ranges, obtained with the threesubevent method; they are zoomed-in version of the p+Pb data shown in Figures  8  and 9. Within their large statistical and systematic uncertainties, the values of c 3 {4} are systematically below zero, especially for 0. 5 < p T < 5 GeV, where the c 3 {4} values are comparable to -0. 16 × 10 -6 , corresponding to a v 3 value.
Summary Measurements of the four-particle cumulants c n {4} and harmonic flow coefficients v n {4} for n = 2 and 3 are presented using 0. 17 pb -1 of pp data at √ s = 5. 02 TeV, 0. 9 pb -1 of pp data at √ s = 13 TeV and 28 nb -1 p+Pb of data at √ s NN = 5. 02 TeV. These measurements were performed with the ATLAS detector at the LHC. The c 2 {4} values are calculated using the standard cumulant method and the recently proposed two-subevent and three-subevent methods. They are all presented as a function of the average number of charged particles with p T > 0. 4 GeV, ⟨N ch ⟩. It is found that the c 2 {4} value from the standard method is sensitive to the choice of particles used to form the event classes used for averaging. This suggests that the previous c 2 {4} measurement in pp collisions  [16, 19] , based on the standard method, may be dominated by non-flow correlations instead of a long-range collective flow correlation.
In general, it is easy to obtain incorrect results from the standard cumulant method, depending on the nature of the non-flow fluctuations associated with the event class chosen for the analysis. On the other hand, the sensitivity of c 2 {4} on event class definition is greatly reduced in the two-subevent method and is almost fully removed in the three-subevent method, demonstrating that the three-subevent method is more robust against non-flow effects. Similarly, the values of c 3 {4} are found to differ in the three datasets using the standard method, but are consistent with each other and much closer to zero using the three-subevent method. This gives confidence that non-flow correlations make a much smaller contribution to the three-subevent results, and that this method is more appropriate for studying longrange collective behaviour than the standard cumulant method.
The three-subevent method provides a measurement of c 2 {4} that is negative in all three datasets over a broad range of ⟨N ch ⟩. The magnitude of c 2 {4} increases with p T and is nearly independent of ⟨N ch ⟩ but in p+Pb collisions the values become smaller at high multiplicities. These results provide direct evidence for the presence of long-range multi-particle azimuthal correlations in broad ⟨N ch ⟩ ranges in pp and p+Pb collisions, and these long-range multi-particle correlations persist even in events with rather low multiplicity of ⟨N ch ⟩ ∼ 40. The c 3 {4} values are consistent with zero in pp collisions, but are systematically below zero in p+Pb collisions, compatible with the presence of significant long-range multi-particle triangular flow in p+Pb collisions. The single-particle harmonic coefficient v 2 {4} = (-c 2 {4}) 1 4 is calculated and compared with v 2 {2} obtained previously using the two-particle correlation method, where the non-flow contributions were estimated and subtracted.
Acknowledgments We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaijan; SSTC, Belarus;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN; CONICYT, Chile; CAS,  MOST  and  NSFC, China ;  COLCIENCIAS, Colombia; MSMT CR, MPO CR  and  VSC CR, Czech Republic ;  DNRF  and  DNSRC, Denmark ;  IN2P3-CNRS ,  CEA-DSM/IRFU , France; SRNSF, Georgia; BMBF,  HGF , and  MPG, Germany ;  GSRT, Greece; RGC, Hong Kong SAR, China ;  ISF, I-CORE  and  Benoziyo Center , Israel; INFN, Italy;  MEXT  and  JSPS, Japan ; CNRST, Morocco; NWO, Netherlands; RCN, Norway;  MNiSW  and  NCN , Poland; FCT, Portugal; MNE/IFA, Romania;  MES of Russia  and  NRC KI , Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain;  SRC and Wallenberg Foundation, Sweden ;  SERI ,  SNSF  and  Cantons of Bern and Geneva, Switzerland; MOST, Taiwan ;  TAEK, Turkey; STFC, United Kingdom ;  DOE  and  NSF ,  United States of America.
4x coverage of the whole genome. In addition, a library of SP80-3280 published by  Figueira et al. (2012)  contains 36,864 clones with an average insert size of 125 kb, representing 0. 4 total genome equivalent coverage. Sugarcane and sorghum (Sorghum bicolor) share a high level of collinearity, gene structure and sequence conservation. de Setta et al. (2014)  contributed to understanding the euchromatic regions from R570 and a few repetitive-rich regions, such as centromeric and ribosomal regions, other than defining a basic transposable element dataset. The genomic similarity between sugarcane and sorghum has been frequently used to characterize the sugarcane genome  (Jannoo et al. , 2007; Garsmeur et al. , 2011; Vilela et al. , 2017 , Mancini et al. , 2018) , demonstrating the high synteny of sugarcane x sorghum and high gene structure retention among the different sugarcane homeologs.
BAC annotation The gene HP600 was used as target gene and showed strong evidence of being a single-copy gene when the transcripts of HP600 of sorghum, rice and sugarcane was compared. Twenty-two BAC clones from the SP80-3280 library that had the target gene HP600 (NCBI from MH463467 to MH463488) and a previously sequenced BAC  (Mancini et al. , 2018; NCBI Accession Number MF737011)  were sequenced by Roche 454 sequencing (detailed assembly can be found in Supplemental Table  1 ). The BACs varied in size from 48 kb (Shy171E23) to 162 kb (Shy432H18), with a mean size of 109 kb. The BACs were compared, and BACs with at least 99% similarity were considered the same haplotype (Figure  1  and Figure  2 ), resulting in sixteen haplotypes. Indeed, the possibility of one homeolog being more than 99% similar to another exists, but a real haplotype cannot be distinguished from an assembly mismatch.
Genetic mapping For the genetic mapping, 44 SNPs (Supplemental Table  7 ) were used to develop molecular markers (Figure  5 ), and they were used to construct a genetic map. The SuperMASSA  (Serang et al. , 2012)  software calculates all possible ploidies for a locus and produces the most probable ploidy. Moreover, it is possible to define a fixed ploidy for a locus. The first option was used to call the dosages, which were ultimately used to construct the genetic map (Figure  6 ), and this map was compared with the fixed ploidy according to the BAC haplotype results (Figure  5 ). In fact, when using a Bayesian approach similar to that from the SuperMASSA, providing prior information about the ploidy level might improve the dosage estimates. The markers from introns and exons were drawn along Region01 (Figure  5 , "Location" column), including the duplicated region found in Region02.
In Region02, the haplotypes of HP600 were not found in the transcriptome dataset  (Cardoso-Silva et al. , 2014; Matiello et al. , 2015) , but at least two haplotypes of the gene CENP-C were expressed. The gene haplotypes of HP600 from Region01 exhibited unbalanced expression; i. e. , for some reason, some haplotypes were expressed at greater levels than others. These findings could mean that apart from the duplication, HP600 might be expressed as a single-copy gene wherein only the haplotypes of the HP600 in Region01 were expressed. In addition, we could not identify the mechanisms contributing to the unbalanced expression. Therefore, the transcripts from different tissues make us speculate that some kind of tissue-specific expression could be occurring. Numerous molecular mechanisms are involved in the creation of new genes, such as exon shuffling, retrotransposons and gene duplications (reviewed in  Long et al.
Moreover, the presence of large LTR retrotransposons in the intronic region of the CENP-C haplotypes in Region01 does not influence the gene expression. Furthermore, two studies  (Saze, et al. , 2013 and Wang, et al. , 2013)  identified the inactivation of the same gene, IBM2/ANTI-SILENCING 1 (ASI1), which causes gene transcripts with methylated intronic transposons that terminate within the elements. The complete mechanisms that control LTR retrotransposon methylation require further clarification  (Kim and Ziberman, 2014). These results have several implications for the integration of transcriptome data and genomic data. The SNPs were also used to compare the ploidy found in BACs with the results of SuperMASSA software  (Garcia et al. , 2013). SuperMASSA uses segregation ratios to estimate ploidy, which is not the same as estimating ploidy by chromosome counting because of the differences in estimation and the real ploidy visualized.
, Düren, Germany), according to the kit instructions. The sequencing reactions were performed according to the manufacturer's instructions for the BigDye Terminator Kit (Applied Biosystems, Foster City, CA, USA). The primers used in the reactions were T7 Forward (5' TAATACGACTCACTATAGG 3') and M13 Reverse (5' AACAGCTATGACCATG 3'). The PCR conditions were 95°C for 1 min followed by 90 cycles of 20 sec at 95°C, 20 sec at 50ºC and 4 min at 60°C. The samples were loaded on a 3730xl DNA Analyzer (Applied Biosystems). Sequence trimming was conducted by processing the traces using the base-calling software PHRED  (Ewing and Green, 1998; Ewing et al. , 1998) , and reads with phred score < 20 were trimmed. The sequences were compared by using BLASTN in the S. bicolor genome from Phytozome v10. 1  (Goodstein et al.
Target gene determination Transcripts of S. bicolor, Z. mays and O. sativa were obtained from Phytozome v10. 1  (Goodstein et al. , 2012). Each transcript was queried against itself, and orthologous genes that resulted in redundant sequences were eliminated. From the remaining genes, the gene Sobic. 003G221600 (Sorghum bicolor v3. 1. 1 -Phytozome v. 12) was chosen because it was inserted in a QTL for Brix from a study by  Murray et al. (2008) , which identified the QTL in the SB-03 genome (S. bicolor v3. 1. 1 -Phytozome v. 12). The sequence of the gene Sobic. 003G221600 was then used as query in the SUCEST-FUN database (http://sucest-fun. org/ -  Vettore et al. , 2003)  and the transcriptome obtained by  Cardoso-Silva et al. (2014)  to recover sugarcane transcripts. All the transcripts obtained were aligned (MAFFT;  Katoh et al.
Sequencing and assembly Twenty-two positive BAC clones were sequenced in pools of 10 clones. One microgram of each BAC clone was used to prepare individual tagged libraries with the GS FLX Titanium Rapid Library Preparation Kit (Roche, Branford, CT, USA). BAC inserts were sequenced by pyrosequencing with a Roche GS FLX Life Sciences instrument (Branford, CT, USA) in CNRGV, Toulouse, France. The sequences were trimmed with PHRED, vector pIndigoBAC-5 sequences and the Escherichia coli str. K12 substr. DH10B complete genome was masked using CROSS_MATCH, and the sequences were assembled with PHRAP  (Gordon et al. , 1998; Gordon et al. , 2001; Gordon, 2003)  as described by  de Setta et al. (2014). A BLASTN with the draft genome (Riaño-Pachón and  Mattiello, 2017)  was performed. A search was performed in the NCBI databank to find sugarcane BACs that could possibly have the target gene HP600.
Sequence analysis and gene annotation All the BACs were aligned to verify the presence of redundant sequences of homeologs. BAC clones with more than 99% similarity were considered the same homeolog. BACs that represented the same homeologs were not combined. The BACs were annotated with the gene prediction programs EUGENE  (Foissac et al. , 2008)  and Augustus  (Keller et al. , 2011). The BAC sequences were also searched for genes with BLASTN and BLASTX against the transcripts of SUCEST-FUN database (http://sucest-fun. org/; Vettore et al. , 2003) , the CDS of S. bicolor, Z. mays and O. sativa from Phytozome v12. 0 and the transcripts published by  Cardoso-Silva et al. (2014). The BACs were also subjected to BLASTX against Poaceae proteins. The candidate genes were manually annotated using S.
bicolor, O. sativa and Z. mays CDS. The sequences with more than 80% similarity and at least 90% coverage were annotated as genes. Repetitive content in the BAC clone sequences was identified with the web program LTR_FINDER  (Xu and Wang, 2007). Afterward, the BAC sequences were tested by CENSOR  (Kohany et al. , 2006)  against Poaceae. The phylogenic trees were built by the Neighbor-Joining method  (Saitou and Nei, 1987)  with nucleic distances calculated with the Jukes-Cantor model  (Jukes and Cantor, 1969)  in MEGA 7 software  (Kumar et al. , 2016). The Kimura 2parameter  (Kimura, 1980)  was used as the distance mode.
Duplication divergence time The gene contents of HP600 and CENP-C in the duplication regions were compared, and the distance "d" for coding regions was determined by Nei-Gojobori with Jukes-Cantor, available in MEGA 7 software  (Kumar et al. , 2016). The divergence times of the sequences shared by the duplicated regions in the BACs were estimated by T = d/2r. The duplicated sequences were used to calculate the pairwise distances (d), and "r" was replaced by the mutation rate of 6. 5 x 10-9 mutations per site per year as proposed by  Gaut et al. (1996). For the whole duplication, the distance "d" for noncoding regions was determined with the Kimura 2-parameter model and the mutation rate of 1. 3 x 10-8 mutations per site per year, as described by  Ma and Bennetzen (2004). The insertion ages of the LTR retrotransposons were estimated based on the accumulated number of substitutions between the two LTRs (d)  (SanMiguel et al.