dataesr/scientific-paragraphs-categorization huggingface dataset:
Finally, values for approximately one-third of creatinine clearance measurements were missing (in cases where measurements were not recorded on the CRF, concerted efforts were made to determine whether the measurements had not been taken, or they had been taken but not recorded on the CRF by the investigator). Therefore, safety data must be assessed cautiously, as both LMWH and rivaroxaban are renally excreted; however, as we have discussed previously, this is not unexpected in a noninterventional study. 21 n summary, this substudy of the noninterventional XALIA study provides evidence that physicians treat cancer-associated thrombosis with different anticoagulant regimens. The most commonly prescribed treatment regimen was LMWH. The high mortality in the LMWH cohort suggests that physicians administer LMWH to patients with the most advanced cancer.
Photoemission spectroscopies Most of the photoemission data were collected at TEMPO beamline, SOLEIL synchrotron, France. The synchrotron light spot of the TEMPO beamline is defocused to 1 mm × 2 mm purposely to decrease the photon flux, and to avoid beam damage, without losing photoelectron count rate. The electron analyzer is a modified SCIENTA200 machine fitted with a delay line detector. All photoemission spectra are taken with a take-off angle of 0° with respect to the surface normal. Valence band spectra and shallow corelevels (Sn 4d, In 4d) are recorded at ℎߥ = 60 eV in surface sensitive conditions. The In 4d and Sn 4d spectra are also recorded in more bulk sensitive conditions at 825 eV to profile out the Sn distribution in the material. In 3d core-levels were measured at 600 eV. C 1s, O 1s core-level XPS spectra were respectively recorded at ℎߥ = 340 eV and ℎߥ = 600 eV with an overall experimental resolution better than 100 meV.
The SEEDC of the deposits 10 15 , 2×10  15  and 3×10 15 molecule•cm -2 give a Φ value of 3. 90 eV, independent of coverage (in the thick limit). The slight decrease in work-function associated to molecular adsorption can be attributed to the formation of cationic species at the ITO/DIPO-Ph 4 interface. 16  present in Figure  6 , the electron energy level scheme of the ITO/DIPO-Ph This is entirely true for molecules in the neutral ground state, and therefore the measured HOMO binding energies are relevant to discuss transport properties, in particular the transport gap of molecular solids, when inverse photoemission spectroscopy data about the lowest unoccupied molecular orbital (LUMO) energy are also available. However, as ‫ܧ‬ ி approaches the HOMO this molecular level is partly emptied due to a charge transfer to the substrate, but the spectroscopic level H(+) (a doubly ionized final state) will appear below the HOMO due to the strong hole-hole interaction.
0001; Figures  1d  and e ), and more specifically with a high expression level (91% of SLY-associated genes are among the 50% most expressed genes, χ 2 , Po0. 0001; 36% among the 10% most expressed genes, χ 2 , Po0. 0001). Interestingly, SLY was found to bind to the TSS of master genes of spermatid transcriptional regulation such as Crem, Creb1, Crebbp, Kif17, Taf7l, Terf2, Tbpl1, Papolb, Piwil1 or Brd4. 1, 2, 19 SLY presence appears as an excellent marker of genes essential Figure  1  SLY marks the sperm differentiation program and co-localizes with active epigenetic marks. (a) Annotation of SLY-enriched genomic regions (right) compared to whole genome (left), using Cis-regulatory Element Annotation System (CEAS). (b) Graphic representation of the percentage of genes found occupied by SLY protein by ChIP-Seq on each chromosome.
Extensive acetylation of histone H4 (acH4) is a hallmark of chromatin remodeling during spermatid differentiation and is detected at the same postmeiotic stages than H3K79 dimethylation, just prior to nucleosome eviction. 31, 32 It has recently been demonstrated that DOT1L-mediated H3K79me2 facilitates acH4. 34 We therefore tested whether acH4 was impacted by Figure  3  DOT1L is highly expressed in postmeiotic germ cells. (a) Schematic of Dot1l expression as found by RNA-Seq on Sertoli cells (SE) and mouse purified germ cells fractions (SG: spermatogonia; SC: spermatocytes; rST: round spermatids; eST: elongating spermatids) (analysis of GSE35005  18  ). (b) Schematic diagram of DOT1L expression in humans as found by micro-array analyses of testicular biopsies with different germ cell contents (SG, SC, rST, eST) (analysis of Affymetrix HG-U133_Plus_2 probe no.
56 For reads with multiple good alignments, one alignment was reported at random. Alignments were extended in silico at their 3′-ends to a length of 200 bp, which is the average genomic fragment length in the size-selected library, and assigned to 32-nt bins along the genome. The resulting histograms (genomic 'signal maps') were stored in BAR and bigWig files. Data sets have been submitted to SRA http://www. ncbi. nlm. nih. gov/sra with accession number SRP055115. Sly peak locations were determined using the MACS algorithm (v1. 4. 2) 57 with a cutoff of P = 1e -7. Annotation of SLY-enriched genomic regions (Figure  1a  and Supplementary Figure  1A ) was performed using Cis-regulatory Element Annotation System available at http://liulab. dfci. harvard. edu/ CEAS/index. html. P-values for the significance of the relative enrichment with respect to the background were calculated using one-sided binomial test.
BED files containing SLY ChIP-Seq regions (WT and Sly-KD) were intersected with Ensembl80 gene coordinates (gene start, or gene start ± 1 kb). Graphical representation of enrichment around the start of genes (expressed and not expressed in round spermatids) was done using Profiler and ComputeMatrix tools  58  available at the Galaxy website https://mississippi. snv. jussieu. fr/. 0] [21]  All data sets were re-analyzed using the last version of the mouse genome (GRCm38/mm10) as described in Moretti et al. 38  Overlap comparison was achieved by intersecting the intervals of two ChIP-Seq data sets. Graphic representations of ChIP-Seq data were performed using IGV (Integrative Genomics Viewer, https://www. broadinstitute. org/igv/). Gene ontology analyses were performed using Genomatix (https://www.
Alterations in the spermatid chromatin structure affect the replacement of nucleosomes by protamines and lead to a higher proportion of nucleosomes and a decreased proportion of protamines. As a result, Sly-deficient spermatozoa are abnormally shaped, less compact and present a higher susceptibility to DNA damage than WT spermatozoa deregulated with a P-value ⩽ 0. 05 were converted to ENSEMBL ID using Biomart and mm10 version of the mouse genome. This gave a list of 1171 deregulated genes. Gene expression data from human testicular biopsies were obtained from published microarray data set (ArrayExpress: E-TABM-234). 61 Gene expression data of mouse purified germ cells were obtained from RNASeq data sets GSE35005 and GSE43717  6, 18  and analyzed by GenoSplice (http://www. genosplice. com) using the following parameters: reads were aligned onto the mouse genome (Ensembl 75, mm10) using STAR v.
2. 3. 0, with an exon-exon junction database built using annotations from Ensembl version 75. For each gene present in ENSEMBL, reads aligning on constitutive regions (that are not prone to alternative splicing) were counted. Based on these read counts, normalization and differential gene expression were performed using DESeq (v1. 12. 0 on R v3. 0. 0). Mice. All animals used in the present study were on 490% C57BL/6 background and processed at adult age (between 2-and 6-month old males). Sly-KD mice were obtained as described in Cocquet et al. 15  FLAG-SLY1 transgenic mice were obtained by pronuclear micro-injection of a linearized construct containing Sly1 open reading frame (i. e. , Sly long and main isoform, see Riel et al. 16  fused with Flag sequence, under the control of the spermatid-specific promoter SP-10 (aka ACRV1).
70  Spectra processing, peptide identification. The software Proteome discoverer 1. 3 was used to generate. mgf files. The threshold of signal to noise for extraction values was 3. MS/MS spectra were submitted to MASCOT version 2. 5. 1 and Maxquant version 1. 5. 2. 8. The database used was a concatenation of Mouse sequence of NCBI database. Oxidation of methionine was permitted partially, whereas carbamidomethylation of cysteine was considered complete. LFQ option without match between runs was used in Maxquant. Two anti-FLAG co-immunoprecipitation assays were performed respectively on whole testis and on transiently transfected GC1 cells. For whole-testis experiment, duplicate mass spectrometry analyses were performed and were independently analyzed with MASCOT; Table  3  shows the results of MASCOT analysis of the second experiment.
Acknowledgements. We thank  Monika Ward  for helpful discussions,  Aine Rattigan  and  Anne-Marie Lachages  for help with elutriation settings,  Sophie Wood  and other members of the  NIMR transgenesis facility  for pronuclear injections. We also thank  Matthieu Benard  and other staff members of the  Cochin Institute Mouse House Facility ,  Antoine Gueraud  for DNA extraction,  Franck Letourneur ,  Florent Dumont  and  Juliana Pipoli  from the  Genomic Facility ,  Evangeline Bennana  and  François Guillonneau  from the  3P5  proteomic facility, as well as the Histology, Immunostaining and  Laser Microdissection Facility , the  Cellular Imaging Facility  and the  Cytometry and Immunobiology Facility of the Cochin Institute  ( INSERM U1016 ,  CNRS UMR8104 ,  Université Paris Descartes). This work was supported by  Inserm  ( Institut National de la Sante et de la Recherche Medicale ), the  Agence Nationale de la Recherche  program  ANR-12-JSV2-0005-01  (to JC),  Labex  ' Who am I?' ( ANR-11-LABX-0071  under program  ANR-11-IDEX-0005-01 ) and a  Marie Curie  fellowship  FP7-PEOPLE-2010-IEF-273143  (to JC).
A search is presented for particles that decay producing a large jet multiplicity and invisible particles. The event selection applies a veto on the presence of isolated electrons or muons and additional requirements on the number of b-tagged jets and the scalar sum of masses of large-radius jets. Having explored the full ATLAS 2015-2016 dataset of LHC proton-proton collisions at √ s = 13 TeV, which corresponds to 36. 1 fb -1 of integrated luminosity, no evidence is found for physics beyond the Standard Model. The results are interpreted in the context of simplified models inspired by R-parity-conserving and R-parity-violating supersymmetry, where gluinos are pair-produced. More generic models within the phenomenological minimal supersymmetric Standard Model are also considered.
Due to the more modest selection on E miss T , the analysis reported in this paper is sensitive to classes of signals not excluded by related searches performed by ATLAS  [20] [21] [22] [23] [24]  and CMS  [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35]. In the next section the ATLAS detector is described, followed by a description of the accumulated data and simulated event samples in section 3. Then the event reconstruction and selection are explained in sections 4 and 5. The data-driven method to estimate the multijet background and the estimation of systematic errors are in sections 6 and 7. The result and interpretations are presented in section 8 followed by conclusions in section 9. -1 -JHEP12(2017)034.
JHEP12(2017)034 3 Collision data and simulated event samples Data recorded by ATLAS during 2015 and 2016 are used in this analysis for background estimation as well as in the final signal region (SR) selections. Simulated events produced with several Monte Carlo (MC) event generators provide predictions for subdominant background contributions from SM processes producing top quarks and vector bosons. The main source of background is multijet production, for which predictions are derived directly from data, as described in section 6. 1. Models of potential signals are likewise simulated for analysis optimisation and interpretation of the final results.
Data Collision events studied for this paper comprise 3. 21 ± 0. 07 fb -1 recorded with good data quality in 2015 with a further 32. 9±1. 1 fb -1 recorded during 2016, all with a bunch spacing of 25 ns. The luminosity uncertainty was derived using beam-separation scans, following a methodology similar to that detailed in ref. [38]. Pile-up, i. e. additional pp interactions in the same or adjacent bunch crossings, contribute to the signals registered by the detector. For this dataset, the average number of interactions per bunch crossing ranged up to 52, with a mean of 22. 9. Events were recorded with a variety of triggers. During both 2015 and 2016, events were selected by a trigger requiring at least six jets with p T > 45 GeV and central pseudorapidity, |η| < 2. 4. In addition, in 2015 events were triggered by requiring the presence of at least five jets with p T > 70 GeV, and in 2016 with a trigger requiring at least five jets with p T > 65 GeV and |η| < 2.
JHEP12(2017)034 together with the fixed four-flavour PDF set CT10f4  [53] , and with top quark decays using MadSpin  [54] , preserving all spin correlations. The parton shower, fragmentation, and the underlying event were simulated using Pythia v6. 428  [55]  with the CTEQ6L1 PDF sets  [56]  and the Perugia 2012 tune (P2012)  [57]. The top quark mass was set to 172. 5 GeV. The EvtGen v1. 2. 0 program  [58]  was used to model the properties of the bottom and charm hadron decays. Simulated t t events were normalised to the cross-section calculated to nextto-next-to-leading order (NNLO) in perturbative QCD, including soft-gluon resummation to next-to-next-to-leading-logarithm (NNLL) order  [59]. Events containing t t and additional heavy particles -comprising three-top, four-top, t t+W , t t+Z and t t+W W production -were simulated at leading order (LO) in the strong coupling constant α S , using MadGraph5 v2.
Results and interpretation The expected and observed event counts in the leptonic control regions are evaluated and normalisation factors derived. In general, the t t normalisation is close to one for lower jet multiplicities but may be as small as 0. 71 for high jet multiplicities. For µ W , the range is typically 0. 3-0. 6. Correspondingly, µ multijet is corrected upwards by up to 24%. Signal region yields as observed in data are summarised in table 4. These are illustrated graphically in figure  4. The most significant difference from the SM prediction is a deficit in the 9j MJ500 region with a statistical significance of 1. 8σ and a corresponding p-value (1 -CL b ) of 0. 04. Similar deficits are observed in the other MJ SRs, but the large overlap between these SRs implies that the deficits are strongly correlated.
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 MIZ Š, 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.
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 Sk lodowska-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 Minerva, Israel ;.
Benchmark calculations The nuclear data evaluation procedure utilizes multifaceted tests of the results using both formal checkers for the correctness of the data and benchmark analyses of integral experiments to check the data quality in application calculations. The newly evaluated Cu data was tested against the integral benchmark experiment performed at FNG on a copper assembly including measurements of specific reaction rates, neutron and  photon flux spectra. Neutron induced reaction rates, neutron and photon spectra were measured at several positions inside the massive copper block. Shown in the Figs. 12 and 13 are the C/E ratios for 27 Al(n,α) rate and a neutron spectrum at ∼ 17 cm in the Cu block. The results obtained with the revised 63,65 Cu evaluation demonstrate better agreement with the measured data as compared with the previous evaluation included in the JEFF-3.
Due to sparse data coverage in the Southern Ocean, altimetry-based frontal definitions have been developed; SSH SAF = -0. 25 m and SSH PF = -0. 70 m are updated values from  Sallée et al. (2008). North of the SAF, water masses such as Subantarctic Mode water (SAMW) and Antarctic Intermediate water (AAIW), subduct along isopycnals at specific locations in the Southern Ocean, such as the Scotia Sea  (Sallée et al. 2010). The subducted pools of SAMW and AAIW observed north of the ACC contain high levels of anthropogenic CO 2  (Sabine et al. 2004; Pardo et al. 2014 ) and heat  (Frölicher et al. 2015). Currently, SAMW is thought to be transformed by air-sea buoyancy fluxes  (Cerovecki et al. 2013 ) and subsequently mixed and subducted with AAIW, σ θ 27. 2 , to the South Atlantic  (Sallée et al.
During a drifter-following crossfront survey, a northward meander of the SAF and PF (Figure  2 ) separated from the ACC and formed a cold-core mesoscale eddy. In this paper, we focus on the observed frontal circulation and submesoscale variability along the periphery of the newly-formed eddy. Data sources and processing methods are described in Section 2. Results from the drifter-following survey are presented as follows in Section 3: a) eddy formation, b) frontal circulation, c) cross-frontal variability, and d) water mass modification. Section 4 presents a submesoscale instability analysis and an estimation of vertical velocity. In Section 5, results are summarized and the implications of submesoscale processes during eddy formation in the Scotia Sea are discussed.
Ship-based data sources The field component of the SMILES project consisted of a Scotia Sea research cruise, 22 April -21 May 2015, performed aboard the British Antarctic Survey RRS James Clark Ross (JCR). Seasoar, a winged and towed CTD body equipped with a Seabird-Electronics Inc. SBE911, collected temperature, conductivity, and pressure measurements at 16 Hz. Seasoar data is collected in a saw-tooth pattern (Figure  3 ) at 8 knots (∼ 4 m s -1 ) with a horizontal spacing between apogees of 2 km for 200-m dives. Temperature and salinity variables were binned to 0. 5 dbar intervals. Binned data were gridded using a 2-dimensional Gaussian interpolation scheme  (Barnes 1964)  with regular spacing, 0. 5-km horizontal and 1-m vertical, and decorrelation radii of 1 km and 2 m (Figure  3c ). Horizontal water velocity data was collected in 8-m depth bins over 22 to 600 m of the water column by the ship-board RDI Ocean Sciences 75 kHz acoustic doppler current profiler (ADCP).
Drogued drifters Semi-Lagrangian water velocity data was collected using a triplet of drogued drifters. The drifters consisted of a sealed buoy with GPS and satellite communications, a 'holey-sock' drogue 10-m long and 90-cm in diameter centered at 50-m depth, and 3. 5 mm Dyneema line. This de-sign provided a drag area ratio of 44 which is accurate to follow water parcels to within 1 cm s -1  (Sybrandy et al. 2009). Drifter location updates were received at 10-minute intervals. The drifters were released along the northern portion of the meander, approximately three minutes apart. The release location was inside (south) of the maximum jet velocity and temperature gradient as shown in Figure  3a  for the first Seasoar leg of the survey. The trajectory of the first drifter released, D16, was chosen to define the along-front direction, θ along (Table  1 ).
Remote data sources Satellite sea surface temperature (SST) and sea surface height (SSH) data were used during the cruise and analysis for frontal and eddy detection. Both data sets are available daily on a 0. 25 • grid. Figure  2  is an example of the remote sensing data available during the SMILES cruise. The daily, gridded microwave SST data was downloaded from Remote Sensing Systems, (http:// www. remss. com). SSH, or absolute dynamic topography, and altimetrically-derived geostrophic surface current data were downloaded from AVISO Cnes data center (www. aviso. altimetry. fr)  (Pujol et al. 2016). Subantarctic front and Polar front positions are defined using SSH contours of -0. 25 m and -0. 7 m, respectively, updated from the mean frontal position definitions in  Sallée et al. (2008).
a. Eddy formation A northward meander of the Subantarctic front (SAF) and Polar front (PF) developed along the Antarctic Circumpolar Current (ACC) (Figure  2 ) in late April 2015. This mesoscale, O(100 km), feature characterized by 4 • C SST and 0. 5-m SSH meridional changes in 50 km, formed just south of the North Scotia Ridge. Antarctic surface water, <2 • C south of the PF  (Orsi et al. 1995) , is observed in the center of the meander. The vorticity Rossby number, Ro = ζ f -1 , of the meander as calculated from altimetrically-derived geostrophic surface currents from 20 April is ∼ 0. 4, a very high value for the coarse altimetry data set compared to previous submesoscale-focused process studies, e. g. Ro ∼ 0. 1 in the North Pacific  (Hosegood et al. 2013). A triplet of drogued drifters released in the northwest sector of the meander on 08 May 2015 20:00 GMT was followed with the RRS JCR while towing the Seasoar CTD perpendicular to the drifter trajectories.
c. Frontal circulation The frontal circulation at the center of each Seasoar leg can be described using the co-located drifter and horizontal water velocity datasets. As shown in Figure  8a , the drifter and along-front water velocities at 50-m depth are in strong agreement. Drifters initially deployed in the northern sector of the cyclonic eddy decelerated around the eastern side toward the southern sector where the along-front velocity is minimum, after which the drifters accelerated around the western edge. Similar trends were observed in the measured along-front velocity. The cross-frontal gradient of cross-frontal velocity, was negative (confluent) during the along-front deceleration and positive (diffluent) during the along-front acceleration as shown in (Figure  8b ). In a horizontally nondivergent flow regime, cross-frontal confluence leads to along-front divergence and vice versa.
However, the deceleration of the drifters suggests convergent along-front flow in a region with convergent along-front flow and therefore the presence of a vertical circulation. These observations suggest downwelling occurred along the N -SE sectors and upwelling in the S survey sector. This will be quantified in Section 4b. S space are connected via σ θ 27 , the isopycnal that outcrops on either side of the dense filament at the front center in Leg N, previously presented in Figure  7. A similar connection along deeper isopycnals, such as σ θ 27. 2 , is not observed in Leg N (Figure  9 ). This is due to an unequal isopycnal upheaval across the Seasoar leg and the 200-m depth limit of the dataset.