dataesr/scientific-paragraphs-categorization huggingface dataset:
Methods study design and patients ECLIPSE (ClinicalTrials. gov, NCT00292552) was a multicenter, observational and longitudinal study to identify surrogate markers of COPD progression. 11 It enrolled 2,164 current or ex-smokers ($10 pack-years) with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2-4, 337 smokers with normal lung function and 245 neversmokers. 12 All ECLIPSE participants underwent a low-dose volumetric computed tomography (CT) scan of the chest at baseline. In a subset of them that constitutes the population for the current report, a valid CT scan slice at L2-L3 could be identified, allowing to assess body composition from which fat and muscle densities, a reflection of tissue fatty infiltration, could be accurately quantified. 13 atients' characteristics (age, race, sex, smoking history), chest CT scan, pulmonary function tests, St Georges' Respiratory Questionnaire (SGRQ) score and 6-minute walking distance (6MWD) were obtained at baseline and yearly for the 3-year study duration as previously reported.
A total of 1,661 moderate-to-severe exacerbations were reported in patients with COPD, with a mean exacerbation rate of 1. 28±0. 06/year/patient (range: 0-9/year/patient). The Pearson's coefficient and ICC for each body composition parameter are reported in Table  2  and show an excellent intra-and inter-observer reproducibility of our body composition measurements. CT body composition data adjusted for age, sex, smoker status and BMI are presented in Figure  2. For a similar BMI (Figure  2A ), patients with COPD exhibited higher CSA of VAT (Figure  2B ), lower MT attenuation (Figure  2C ) and a tendency to have lower CSA of MT (Figure  2D ) than controls. CSA of SCAT could be quantified in 384 subjects (327 COPD subjects and 57 controls) in whom the abdomen external wall body composition parameters were particularly notable in patients with GOLD 4 COPD.
Acknowledgments The authors thank  Véronic Tremblay  for the body composition analysis platform of the  Institut universitaire de cardiologie et de pneumologie de Québec  for ensuring standardization of the CT images analyses and  Gaétan Daigle  for statistical assistance. They also thank all the subjects, investigators and study site staff who participated in ECLIPSE. This study was funded by  GlaxoSmith-Kline (GSK). MM was a recipient of a research training award from the  Fonds de la recherche Québec -Santé. FM holds a GSK/ Canadian Institute of Health Research (CIHR)  Research Chair on COPD at  Université Laval. J-PD  is the scientific director of the  International Chair on Cardiometabolic Risk , which is based at the  Faculty of medicine, Université Laval. This work has been presented as an abstract at the 2015 meeting of the American Thoracic society.
The gaseous mixtures of MTG and Ar in different proportions were prepared by standard manometric methods. The matrices were formed by pulsed depositions  [6, 7]  of the gas mixtures onto a cold CsI window (~10 K) of a Displex closed-cycle refrigerator (SHI-APD Cryogenics, model DE-202). In our experimental conditions, the IR spectra of the matrices were measured with a resolution of 0. 125 and 0. 5 cm À1 , with 256 and 64 scans, respectively. All quantum chemical calculations were performed using the Gaussian 03 program package  [8]. Geometry optimizations and transition state calculations were sought using standard gradient techniques by simultaneous relaxation of all geometrical parameters. The vibrational properties were calculated to characterize the structures as true minima, with no imaginary vibrational frequency, or as transition states.
Acknowledgements This work was supported by funds from the  International cooperation program ECOS-MinCyT  ( A13E05 ),  Agencia Nacional Científica y Tecnol ogica ANPCyT  ( PICT11-0647  and  PICT14-3266 ),  Facultad de Ciencias Exactas of the Universidad Nacional de La Plata  ( UNLP-11/X684 ),  Consejo Nacional de Investigaciones Científicas y T ecnicas CONICET  ( PIP-0352 )) and the  LABEXCaPPA PIA Program  (contract  ANR-11-LABX-0005-01 ).
Measurements of differential cross-sections of top-quark pair production in fiducial phasespaces are presented as a function of top-quark and t t system kinematic observables in proton-proton collisions at a centre-of-mass energy of √ s = 13 TeV. The data set corresponds to an integrated luminosity of 3. 2 fb -1 , recorded in 2015 with the ATLAS detector at the CERN Large Hadron Collider. Events with exactly one electron or muon and at least two jets in the final state are used for the measurement. Two separate selections are applied that each focus on different top-quark momentum regions, referred to as resolved and boosted topologies of the t t final state. The measured spectra are corrected for detector effects and are compared to several Monte Carlo simulations by means of calculated χ 2 and p-values.
For the generation of t t samples and those with a single top quark from the Wt and s-channel samples, the Powheg-Box v2  [23]  event generator with the CT10 PDF set  [24]  in the matrix element calculations is used  [25]. Events where both top quarks decay into hadronically decaying W bosons are not included. The overlap between the Wt and t t samples is handled using the diagram removal scheme  [26]. The top-quark mass is set to 172. 5 GeV. The EvtGen v1. 2. 0 program  [27]  is used to simulate the decay of bottom and charm hadrons. The h damp parameter, which controls the p T of the first additional emission beyond the Born configuration in Powheg, is set to the mass of the top quark. The main effect of this is to regulate the high-p T emission against which the t t system recoils. Signal t t events generated with these settings are referred to as the nominal signal MC sample.
In the second sample the factorisation and hadronisation scales are varied upward by a factor of 2. 0, the h damp parameter is unchanged and the 'radLo' tune variation from the Perugia2012 tune set is used. The unfolded data are compared to three additional t t simulated samples  [25]  which use the NNPDF3. 0NLO PDF set  [38]  for the ME: a MadGraph5_aMC@NLO+Pythia8 sample using the A14 tune, a Powheg+Pythia8 sample simulated with the h damp parameter set to the top-quark mass, also using the A14 tune and a Powheg+Herwig7 sample generated with the h damp parameter set to 1. 5 times the top-quark mass, using the H7-UE-MMHT tune. The t t samples are normalised using σ tt = 832 +46 -51 pb where the uncertainty includes effects due to scale, PDF and α S variations, evaluated using the Top++2. 0 program  [39].
Muons are required to have p T > 25 GeV and to be within |η| < 2. 5. To reduce the background from muons originating from heavy-flavour decays inside jets, muons are required to be separated by ∆R > 0. 4 from the nearest jet and to be isolated using track quality and isolation criteria similar those applied for the electrons. If a muon shares a track with an electron, it is likely to have undergone bremsstrahlung and hence the electron is not selected. Jets are reconstructed using the anti-k t algorithm  [59]  implemented in the FastJet package  [60]. Two types of anti-k t jets are considered: so-called small-R jets with radius parameter R = 0. 4 and large-R jets with radius parameter R = 1. 0. Jet reconstruction in the calorimeter starts from topological clusters calibrated to be consistent with expected electromagnetic or hadronic cluster shapes using corrections determined in simulation and inferred from test beam data.
Multijet production processes, including all-hadronic t t production, have a large cross-section and mimic the lepton+jets signature due to jets misidentified as prompt leptons (fake leptons) or to semileptonic decays of heavy-flavour hadrons (non-prompt real leptons). The multijet background is estimated directly from data by using a matrix-method  [70]. The number of background events in the signal region is evaluated by applying efficiency factors (fake-lepton and real-lepton efficiencies) to the number of events satisfying a tight (signal) as well as a looser lepton selection. The fake-lepton efficiency is measured using data in control regions dominated by the multijet background with the real-lepton contribution subtracted using MC simulation. The real-lepton efficiency is extracted from a tag-and-probe technique using leptons from Z boson decays.
Conclusions Kinematic distributions of hadronically decaying top quarks in both resolved and boosted topologies, and of top-quark pairs in the resolved topology are measured in a fiducial phase-space, using events from the lepton+jets channel using data from 13 TeV proton-proton collisions collected by the ATLAS detector at the CERN Large Hadron Collider, corresponding to an integrated luminosity of 3. 2 fb -1. Absolute as well as relative differential cross-sections are measured as a function of the hadronic top-quark transverse momentum and rapidity. For the resolved topology, the differential cross-sections are also measured as a function of the mass, transverse momentum and rapidity of the t t system. In general, the Monte Carlo predictions agree with data in a wide kinematic region. However, the shape of the transverse momentum distribution of hadronically decaying top quarks is poorly modelled by all NLO+PS predictions, where the disagreement is largest at high transverse momentum.
This behaviour is consistent between the resolved and boosted topologies, and also with the results at lower centre-of-mass energies. In the resolved topology, the precision of the measurement of the transverse momentum of the t t system makes it possible to distinguish between different settings in the NLO+PS calculations, indicating that the data have discriminating power sufficient to allow parameter values for these generators to be improved. For the relative differential cross-section results, the transverse momentum of hadronically decaying top quarks is the most poorly modelled observable. erva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers.
In addition, individual groups and members have received support from  BCKDF , the  Canada Council, CANARIE ,  CRC ,  Compute Canada, FQRNT , and the  Ontario Innovation Trust ,  Canada ; EPLANET,  ERC ,  ERDF ,  FP7 ,  Horizon 2020  and  Marie Skłodowska-Curie Actions ,  European Union ;  Investissements d'Avenir Labex and Idex ,  ANR ,  Région Auvergne  and  Fondation Partager le Savoir, France ;  DFG and AvH Foundation ,  Germany; Herakleitos ,  Thales  and  Aristeia  programmes co-financed by  EU-ESF  and the  Greek NSRF; BSF, GIF and Min-.
The mean pitch interval within pseudo-words was significantly different from the mean interval between the pseudo-words (P = 0. 02). Moreover, pitch-contour changes could be used to segment the stream, as this cue was consistent and no other acoustic cues were inserted at word boundaries. The four learning streams were built by a random concatenation of the four words (without repetition of the same item twice in a row). All the stimuli were synthesized using Mbrola (http://tcts. fpms. ac. be/synthesis/mbrola. html) with the Spanish es2 database and thus were only built with syllables that were part of the Spanish-Catalan phonetic repertoire. The transitional probability between the syllables forming a word was 1. 0, while the transitional probability between syllables spanning word boundaries was 0.
EEG was recorded from 16 scalp electrodes (Biosemi ActiveTwo system, Amsterdam University) located at standard positions (International 10/20 system sites: Fp1, Fp2, F3, F4, T7, C3, C4, T8, P3, P4, O1, O2, Fz, Cz, Pz and Oz). The data of three newborns had to be discarded due to excessive movements inducing major EEG artifacts. The EEG was amplified by Biosemi amplifiers with a band-pass of 0-102. 4 Hz and was digitized at 250 Hz. Vocabulary and cognitive measures. At 18 months, parents of the participants were contacted again and asked to come to the Lab for a language and cognitive development assessment. Parents were requested to fill out the expressive vocabulary checklist form the Spanish version of the MacArthur-Bates Communicative Development Inventory 75 (MCDI). This questionnaire provided us with a parental estimate of expressive vocabulary size.
EEG data analyses. All the EEG data were processed and analyzed using custom scripts programmed in Matlab (version R2008b) and with functions of the EEGLAB toolbox. For the learning phases, EEG data were re-referenced offline to the left and right mastoidal electrodes and were filtered offline using a 0. 5-20 Hz bandpass filter (FIR, Hamming window, max stopband attenuation = -53 dB, Max passband deviation = 0. 0063; as done in previous reports studying the EEG correlates of the learning phases  24, 25, 30, 32  ). Continuous EEG data were then split into epochs from -50 ms to 1050 ms from word onset, baseline-corrected and epochs containing external artifacts exceeding ±120 μV were automatically removed from analyses. ERP data were analyzed by computing the mean amplitudes between 200 and 500 ms post word-onset independently of the sleep stage of the newborns.
For the test phase, because significant MMR were found in the melodically enriched condition only, we considered the two MMR occurring at each syllabic violation (difference illegal minus legal words in the 300-400 and 800-900 ms time-windows averaged across all EEG channels). Following this analysis, we explicitly quantified the predictive power of the significant EEG features using a machine learning evaluation framework  80. For this, we removed two subjects from the dataset, fitted the same model on the eleven other subjects and used it to obtain a predicted MCDI value from the EEG features of the two left-out subjects. This procedure was repeated throughout a cross-validation procedure  81  (leave-two-subjects-out) where all 78 combinations of two-out-of-thirteen newborns were used to obtain out-of-sample predicted MCDI scores -thus allowing to obtain a more robust result than with a leave-one-subject-out scheme.
Acknowledgements We thank all the families and their babies for participating in the study. We also thank the medical staff from the maternal care unit in Sant Joan de  Déu Hospital. We thank  R. de Diego Balaguer ,  T. Cunillera  for their constructive comments on the manuscript; and  D. Cucurell  and  J. Solé  for their help in different steps of the study. This research has been supported by a grant from  FYSSEN foundation (post-doctoral grant ) as well as a Spanish  MINECO  project ( PSI2015-69132P ) and the  Catalan government  ( PERIS2017 ) to CF, and  Spanish MINECO  projects ( PSI2011-25376  and  PSI2014-55105P ) to LB.
Surprisingly, we found that the homeodomain TFs, Retinal Homeobox (Rx) and Ultrabithorax (Ubx) are also required for upd3-lacZ activity, primarily upon infection (Fig 3C ), suggesting these TFs could be involved in tissue repair. Among these TFs, Sna, Mad, Rx and Ubx were not found to bind to the upd3 promoter by the yeast one-hybrid assay, although there are some binding sites in the upd3 promoter region for these TFs according to the JASPAR database (Fig  3C ). This suggests that there is a possibility that they could act directly. Finally, global regulators of transcription such as the transcriptional corepressor CtBP, the H3K4 methyltransferase Trithorax-Related (Trr) and MBD-like, a member of the NuRD complex also influenced the regulation of upd3-lacZ (Fig  3C ). On the opposite side of the spectrum, we also identified TFs that cause increased upd3-lacZ expression when knocked-down.
Plate images were analyzed using the R package Gitter, that estimates colony surface and circularity. Sets of quadruplicate colonies that showed growth above background levels were deduced to have a direct interaction between the TF prey and the DNA bait, and the strength of the interaction was estimated and ranked (from +/-to +++) by the ability of each yeast colony to grow on increasing concentrations of the HIS3 inhibitor 3AT as previously described  [27, 79].
Acknowledgments We would like to thank  Florence Janody ,  Bruce Edgar ,  Jean-Paul Vincent ,  Matthew Freeman  and  Tian Xu  for stocks and reagents. We also thank members of the  Buchon lab  for helpful comments on the manuscript. We thank the  TRiP at Harvard Medical School  ( NIH/NIGMS   R01-GM084947 ) for providing transgenic RNAi fly stocks and/or plasmid vectors used in this study. Stocks obtained from the  Bloomington Drosophila Stock Center  ( NIH P40OD018537 ) were used in this study.
Sequence reads were aligned to the GRCm38/mm10 build of the Mus musculus genome using the Subread aligner  (Liao et al. , 2013). Only uniquely mapped reads were retained. Genewise counts were obtained using featureCounts  (Liao et al. , 2014). RNA sequencing data have been deposited in the National Center for Biotechnology Information's Gene Expression Omnibus and are accessible under accession number GSE97354.
statistical analysis For all experiments, the difference between two groups was calculated with the Student t test using GraphPad Software Prism 4. ANO VA and Bonferroni's test were used for multiple comparisons (*, P ≤ 0. 05; **, P < 0. 01; ***, P < 0. 001; ns, not significant). All graphs show mean and SEM. online supplemental material Fig. S1  shows the assessment of cell death and apoptosis in lung ILC2s at steady state and after IL-33 administration. Fig. S2  shows the gating strategy for Ki67 staining in lung ILC2s. Fig. S3  show the gating strategies for the assessment of lung-infiltrating cells (ILC2s and eosinophils) in CD45. 1 (WT)/CD45. 2 (AR KO ) mixed bone marrow chimeras.
AcknowLedGMents We are indebted to the facilities of our institutes, particularly those responsible for animal husbandry and histopathology at  INS  ERM  UMS06 , and flow cytometry at the  Centre de Physiopathologie de Toulouse Purpan (CPTP ) and at the Walter and  Elisa Hall Institute (WEHI, Australia). We thank  S. Kato  and  P. Chambon  for providing AR KO and ERα fl/fl mice, respectively. We would also like to thank  Dr. Zúñiga-Pflücker  ( University of Toronto ) for kindly providing the OP9-DL1 cell line. We thank  A. Lum  and  G. K. Smyth  ( WEHI, Australia ) for their help in the analysis of RNA sequencing data. Work at CPTP was supported by grants from  Conseil Régional Midi-Pyrénées  and  Fondation pour la Recherche Médicale  (équipe labelisée  DEQ2000329169 ). Work at the Walter and  Elisa Hall Institute of Medical Research  was supported by a project and program grants of the  National Health and Medical Research Council (NHM RC) of Australia, Victorian State Government Operational Infrastructure Support , and  Australian Government NHM RC Independent Medical Research Institutes Infrastructure Support Scheme.
Work at Institut de Génétique et de Biologie Moléculaire et Cellulaire  was supported by funds from the  Centre National de la Recherche Scientifique , the  Institut National de la Santé et de la Recherche Médicale , the  Université de Strasbourg , the  Agence Nationale de la Recherche  ( ANR-10-1108-01  Androgluco), and by  French  state funds through the  Agence Nationale de la Recherche  ( ANR-10-LABX-0030-INRT ) under the  frame program Investissements d'Avenir labeled   ANR-10-IDEX-0002-02. The authors declare no competing financial interests. Author contributions:  S. Laffont ,  E. Blanquart ,  M. Savignac ,  C. Cénac ,  G. T. Belz ,  L. Pelletier ,  C. Seillet , and  J. -C. Guéry  designed the research, performed experiments, and analyzed the data. G. Laverny and  D. Metzger  provided samples from AR KO mice and contributed to the design and interpretation of experiments.
To understand these results and to consider how they can be improved using elliptical nanochannels, we have performed numerical modelling of how the transverse cross-section of the channels impacts the stress distribution observed under bending for (b) circular and (c) elliptical nanochannels. This modelling used SolidWorks TM software with a channel diameter of 360 nm for the circular case and channel dimensions of 720 × 360 nm 2 for the elliptical case  26  , and considered a channel depth of 150 nm. The stress was calculated numerically from the (tensor) linear elasticity equation for conditions of static equilibrium with pressure uniformly applied along the centre-line of the sample with both side ends maintained fixed. Note that full modelling over the experimental channel depth of 150 µm is computationally prohibitive, but these modelling results at reduced depth clearly show the qualitative difference between the two cases.
After cleaving, we also showed that the edges are stronger in comparison to processing with symmetric Bessel beams. For the same inter-channel spacing (5 µm), highrepetition rate (100's kHz) industrial lasers are expected enable processing speeds exceeding 1 meter per second. We anticipate these results will impact on the field on laser nano-processing of transparent materials and will foster research on the understanding of material properties at nano-scales around the laser-processed nanochannels. The research leading to these results has received funding from the European Union Seventh Framework Programme [ICT 2013. 3. 2 Photonics] under grant agreement No 619177 TiSa-TD and from the European Research Council (ERC-CoG-682032-PULSAR). This work has been performed in cooperation with the Labex AC-TION program, contract ANR-11-LABX-0001-01 and was partly supported by the French RENATECH network.
All sequences were cleaned and analyzed using Mothur v. 1. 39. 5 following an adapted version of the MiSeq standard operation procedure available online 1  (accessed August 2015)  (Kozich et al. , 2013). First, the two complementary sets of reads were combined for each sample after removal of the primers. Sequences that were too long or that contained ambiguity were discarded. Identical sequences were grouped to reduce the necessary processing power. These unique sequences were then aligned using a Mothur adapted version of the SILVA database (silva. seed. v119). 2 Chimeras where removed using UCHIME 3. The sequences were clustered into operational taxonomic units (OTU) at genetic distance dissimilarity of 3% and then classified using the Mothur formatted Ribosome database project (RDP) trainset version 14.
4  Raw reads for each sow fecal microbiota analyzed in this study are available through the NCBI SRA database under accession SRP100939. For alpha diversity analysis, indexes were calculated in Mothur using a subsample size consisting of the lowest number of sequences in samples with 1000 iterations. The average number of OTUs, the estimation of the portion of the diversity covered by our subsampling (coverage), the diversity of the OTUs found in the samples (inverted Simpson's index) and their evenness (Shannon evenness) was measured. Results were compared between groups using ANOVA and Student's t-test and relation with parity rank using linear regression with a significance level of 0. 05. For beta diversity analysis, a distance matrix comparing all the samples was created with a subsample using the same number of sequences as previously used and using Jaccard and Bray-Curtis dissimilarity index.