dataesr/scientific-paragraphs-categorization huggingface dataset:
VI. EVENT CATEGORIZATION Gluon fusion is expected to be the dominant production mode of Higgs bosons at the LHC, contributing about 87% of the predicted total production cross section at m H = 125. 4 GeV and √ s = 7-8 TeV, while VBF and the associated production processes V H and t tH are predicted to contribute only 7%, 5%, and 1%, respectively. Based on their properties, the selected diphoton events (Sec. V) are divided into 12 categories, separately for each of the 7 TeV and 8 TeV datasets, that are optimized for sensitivity to the Higgs boson production modes studied here, for a Higgs boson mass of m H = 125 GeV. The event selections are applied to the initial diphoton sample in sequence, as illustrated in Fig. 3. Only events that fail all the previous event selections are candidates for a given category, to ensure that the events are grouped into exclusive categories.
The sequence of categories is chosen to give precedence to the production mechanisms that are expected to have the lowest signal yields. Each category is optimized by adjusting the event selection criteria to minimize the expected uncertainty in the signal strength of the targeted production process. Although the measurements are dominated by statistical uncertainties with the present dataset, systematic uncertainties are taken into account during the optimization. The 12 exclusive categories, whose events have different signal invariant mass resolutions and signal-tobackground ratios, can be logically grouped into four sets depending on the production processes they are expected to be most sensitive to, as described in the following subsections. Comparisons between signal MC samples, background MC samples, and data in the sidebands of the m γγ distribution are shown for the main kinematic quantities used to define several of the categories.
at least six jets with p T > 30 GeV out of which one is b-tagged using the 60% WP; 3. at least five jets with p T > 30 GeV out of which two are b-tagged using the 70% WP. Only the first set of criteria above is applied to the 7 TeV data but with a working point efficiency of 85%. The fraction of t tH events relative to all signal production passing this selection in the hadronic category is larger than 80% while in the leptonic category it ranges from 73% to 84% depending on the center-of-mass energy; the numbers are reported in Tables  II  and III. Contributions of about 10% from ggF events in the hadronic category and 10% from W H events in the leptonic category remain. The remaining 10% in each of the two categories is accounted for by tHW and tHbj events.
E. Summary of categories The predicted signal efficiencies, which include geometrical and kinematic acceptances, and event fractions per production mode in each event category for m H = 125. 4 GeV are listed in Tables II and III for the 7 TeV and 8 TeV data, respectively. The total expected numbers of signal events per event category N S are also shown, normalized as discussed in Sec. III. The dependence of the yield for each production process on the Higgs boson mass is parameterized in each category with simple polynomials that are used to build the statistical model described in Sec. IX. As discussed in Sec. III, the detection efficiency for b bH events is assumed to be the same as for ggF events. The expected contamination of ggF and VBF in the V H E miss T category is larger in 7 TeV data than in 8 TeV data due to the poorer resolution of the E miss T reconstruction algorithm used in the 7 TeV analysis.
The number of events observed in data in each category is reported in Table IV separately for the 7 TeV and 8 TeV data. The impact of the event categorization described in the previous sections on the uncertainty in the combined signal strength is estimated on a representative TABLE II. Signal efficiencies , which include geometrical and kinematic acceptances, and expected signal event fractions f per production mode in each event category for √ s = 7 TeV and mH = 125. 4 GeV. The second-to-last row shows the total efficiency per production process summed over the categories and the overall average efficiency in the far right column. The total number of selected signal events expected in each category NS is reported in the last column while the total number of selected events expected from each production mode is given in the last row.
The bias criteria in Eq. (  2 ) are indicated by the dashed lines. TABLE VI. List of the functions chosen to model the background distributions of mγγ and the associated systematic uncertainties on the signal amplitudes in terms of spurious signal (Nspur) and its ratio to the predicted number of signal events in each category (µspur) for the 12 categories and the 7 TeV and 8 TeV datasets. Model exp1 (exp2) is the exponential of a first-order (second-order) polynomial.
Sizes of MC samples The finite size of the MC signal samples may induce non-negligible statistical uncertainties depending on the category and the production process. The impact of these uncertainties on the individual signal strength parameters is estimated for each event category by analyzing representative MC datasets containing both Higgs boson signal and continuum background: for the signal the sample size is fixed to the one expected in data by the SM predictions, and for the background to the observed numbers of events. The uncertainties that contribute more than 0. 1% in quadrature to the total expected uncertainties are retained. The 14 uncertainties that contribute more than 0. 1% in quadrature to the total expected uncertainties are propagated, but their contribution is at the level of 1% or less, which is much smaller than the expected statistical uncertainties on the individual signal strengths.
The uncertainties on the signal yield due to the uncertainty on the photon identification efficiency are 8. 4% for the 7 TeV data and 1. 0% for the 8 TeV data and are treated as uncorrelated. 4. The uncertainty on the isolation efficiency is conservatively taken as the full size of the applied correction described in Sec. IV A. The effect on the signal yield varies among categories (depending on their photon E T spectrum). These uncertainties, which range between 1. 3% and 2. 3%, are estimated with the 8 TeV dataset and are assumed to be the same in the 7 TeV data but uncorrelated between the two datasets. The estimated values of the experimental uncertainties for both datasets are summarized in Table  IX. Larger uncertainties, also shown in the table, on the photon identification and isolation selection efficiencies are assigned to the categories sensitive to t tH and V H production modes.
Tables X and XI show the impact of the jet and E miss T uncertainties. To simplify the presentation of the results, categories and processes for which each source of uncertainty has a similar impact are merged. These uncertainties are fully correlated between the 7 TeV and 8 TeV datasets. 2. The impact of the uncertainty in the b-tagging efficiency on the migration of events to and from the t tH categories is decomposed into 10 (3) independent contributions in the 8 TeV (7 TeV) data analysis. The uncertainty on the t tH yield in the t tH categories from the uncertainty on the b-tagging efficiency ranges from 1 to 3%. The uncertainties affecting other production processes that have the largest impact on the yield in the ttH categories are 20-30% of the ggF component in the hadronic category and 6-7% to the WH contribution in the leptonic channel.
g. the uncertainty on a measured integrated luminosity), F LN (σ, θ) = e √ ln(1+σ 2 )θ (4) for a log-normal pdf. In both cases the corresponding component of the constraint product G(θ) is a unit Gaussian centered at zero for θ. The systematic uncertainties affecting the yield and mass resolution use the lognormal form while a Gaussian form is used for all others. When two uncertainties are considered fully correlated they share the same nuisance parameter θ with different values of σ. Systematic uncertainties with partial correlations are decomposed into their uncorrelated and fully correlated components before being assigned to nuisance parameters. The likelihood for the combined signal strength is the product of 24 likelihoods, consisting of the 12 category likelihoods for each dataset (7 TeV and 8 TeV).
As can be seen in Table  XIII  there are 146 constrained nuisance parameters associated with systematic uncertainties. Twelve of these are associated with the spurious signal in each of the 12 event categories. There are 49 unconstrained nuisance parameters that describe the normalizations and shapes of the fitted backgrounds in the 12 categories for the 7 TeV and 8 TeV data. As at least 2 events are needed to constrain the slope of the exponential background model, the categories with low expected yields are assumed to have the same shape parameters for the 7 TeV and the 8 TeV data. The V H E miss T , one-lepton, and dilepton categories are defined to have low yield since the probabilities to observe 2 events in the 7 TeV data are less than 1% based on the numbers of events observed in the corresponding 8 TeV data categories.
X. RESULTS The observed diphoton invariant mass distribution for the sum of the 7 TeV and 8 TeV data is shown in Fig. 13  and in Fig. 14  for the sums of categories most sensitive to different production modes. In all cases, for illustration purposes, each event is weighted according to the expected signal-to-background ratio S 90 /B 90 for the relevant category and center-of-mass energy. The results of signal plus background fits to these spectra with m H set to 125. 4 GeV are shown together with the separate signal and background components. Both the signal plus background and background-only curves reported here are obtained from the sum of the individual curves in each category weighted in the same way as the data points. The signal strengths are measured with the extended likelihood analysis described in Sec.
The datasets used in the two analyses are highly correlated: 142681 events are selected in Ref. [13] , 111791 events are selected in the current analysis, and 104407 events are selected in both analyses. The significance of the 0. 4 difference between the combined signal strengths, including the effect of the 74% correlation between the two measurements, is calculated by applying the jackknife technique to the union of the two datasets and is found to be 2. 3 σ. An uncertainty of 0. 1 σ on the compatibility between the two measurements is estimated by varying the size of the jackknife sub-samples. The decrease in the observed signal significance (5. 2 σ) with respect to the one published in Ref. [13]  (7. 4 σ) is related to the reduction of the measured signal strength according to the asymptotic formula Z = µ/σ stat µ , where σ stat µ is the statistical component of the uncertainty on µ.
In other words, the observed reductions of the significance and signal strength are consistent with each other and consistent with a statistical fluctuation at the level of ∼ 2. 3 σ. As can be seen in Figs. 17 and 18, the observed signal strengths of the tagged categories, which are dominated by production processes other than ggF, tend to be lower than the signal strengths measured with the untagged categories, which are dominated by ggF production. This tendency, combined with the optimized sensitivity of this analysis to production processes other than ggF, results in a lower combined signal strength than those measured using alternative analyses of the same dataset (or where the datasets are largely overlapping) that are inclusive with respect to the production process. The compatibility of the combined signal strength obtained in this analysis with the signal strength µ = 1.
XI. CONCLUSION A refined measurement of Higgs boson signal strengths in the H → γγ decay channel is performed using the proton-proton collision data recorded by the ATLAS experiment at the CERN Large Hadron Collider at centerof-mass energies of √ s = 7 TeV and √ s = 8 TeV corresponding to a total integrated luminosity of 25 fb -1 (the LHC Run 1 dataset). The results are based on improved calibrations for photons, electrons and muons and on improved analysis techniques with respect to the previously published analysis of the same dataset. The strength of the signal relative to the SM expectation, measured at the combined ATLAS Higgs boson mass m H = 125. 4 GeV is found to be µ = 1. 17 ± 0. 27. The compatibility with the SM prediction of µ = 1 corresponds to 0. 7 σ. Signal strengths of the main production modes are measured separately by exploiting event categories that are designed to be sensitive to particular production modes.
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; BMWF 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,  DNSRC  and  Lundbeck Foundation , Denmark; EPLANET,  ERC  and  NSRF ,  European Union ;  IN2P3-CNRS ,  CEA-DSM/IRFU , France; GNSF, Georgia; BMBF,  DFG ,  HGF ,  MPG  and  AvH Foundation, Germany ;  GSRT  and  NSRF, Greece ;  ISF, MINERVA, GIF, I-CORE and Benoziyo Center, Israel ;  INFN, Italy ;  MEXT  and  JSPS, Japan ; CNRST, Morocco; FOM and  NWO, Netherlands ;.
Sequences with a minimum of fi ve repeats were selected. The bioinformatics program QDD version 1 with default parameters  ( Meglécz et al. , 2010 )  was used to fi lter for redundancy, resulting in a fi nal set of sequences from which it was possible to design primers. Finally, for a total of 43. 9 Mbp read in the run, 10,895 sequences comprised microsatellite motifs with an average length of 304 bp. A total of 1114 primer sets were designed with QDD using BLAST, ClustalW, and Primer3  ( Altschul et al. , 1990 ; Larkin et al. , 2007 ; Rozen and Skaletsky, 2000 ). A subgroup of 47 primer pairs was then tested for amplifi cation. Primer sets were discarded if they failed to amplify or led to multiple fragments. Each primer pair was assessed in eight individuals of P. judaica. Microsatellite loci were amplified in 25-μ L reactions containing 20 ng of template DNA, 1 unit of Taq polymerase (FastStart Taq DNA polymerase, Roche Diagnostics), 0.
2014; revision accepted 18 June 2014. This research was carried out as part of a Ph. D. thesis (PACA regional research grant no. 2011-019) and fi nancially supported by the Agence Nationale de la Recherche (ANR). This research is a contribution to the "Trame Verte Urbaine" (TVU, N VD08_321105) program entitled "Assessment of urban green corridors and development of a reference frame: An infrastructure between aesthetic and ecology for a new urbanity. " S. M. was supported by the Institut Universitaire de France. 5  Author for correspondence: angele. bossu@etu. univ-amu. fr.
Ratiometric Measurements Cells on coverslips were placed on a thermostatted (37 °C) inverted Leica AF6000 videomicroscope (Leica Microsystems, Wetzlar, Germany) with 63, 1. 3 numerical aperture (NA) glycerin-immersion objective. Fluorescence excitation was performed with a 427 ± 10 nm bandpass filter through a double band dichroic mirror (440/520 nm). To avoid displacements between donor and acceptor's fluorescence measurements, we used fast detection filter wheel (respectively with 472 ± 30 nm and 542 ± 27 nm bandpass filters). Images were acquired every two minutes. After 6 min, drugs were added to the cell medium by gentle pipetting. YFP/CFP ratio for cell by cell data analysis was realized with the ImageJ software as described in  [10]. Curves were obtained by subtracting the average of the baseline values (time points 0 to 6 min) from each time point.
Acknowledgments Pauline Vandame is funded by the  University of Lille  1 and the  Region Nord-Pas-de-Calais. This work has been supported by  ANR   G2  Progress. We also thank  Christophe Slommiany ,  Laurent Heliot  and the  BioImaging Center Lille-Nord de France (BICeL)  for the microscopy facilities. We also thank  Jin Zhang ,  Karel Svoboda ,  Jun-ichi Miyazaki , and  Kees Jalink  (The Nederlands Kanker Instituut) as sources for the material. We are also grateful to  Emanuele Biondi  and  Coralie Bompard  for discussion and comments.
Equipment and Software The bimanual coordination apparatus involved two plastic handles (i. e. , 12. 5 cm in height x 3 cm diameter) independently attached to linear sliding devices that glided horizontally over ball bearings encapsulated in metal casings (see Fig. 1 ). Limb movements were permitted in only the left-right orientation from midline. Attached in parallel to the slides were linear potentiometers (Duncan Electronics, DEL Elec 612R12KL. 08), which encoded the displacement of the slides over a 20-sec trial. Data were sampled using a microprocessor (80486) with a sampling rate of 200 Hz (i. e. , one sample each 5 msec). LabWindows software (National Instruments Corporation, version 2. 2. 1) initiated and terminated 20-sec trials and also provided data capture and recording of limb position over time.
Significance level was set at =. 05 and post hoc simple main effects were analyzed using the Bonferroni correction. Data collection involved a continuous estimate methodology in which limb position was sampled at a rate of 200 Hz (every 5 ms). This method allowed for finer-grained information about movement accuracy as compared with point estimates, which typically focus on two time-points per cycle  [28]. Relative phase difference for each time point was determined in the following way. For each time point sampled, the relative phase of the right limb in space was captured, relative to the left limb, where a reference of 0º indicated that both limbs were at the midline position. Each trial resulted in an average mean error (i. e. , an average of the mean relative phase error data points) and a within-trial standard of these data points.
Database Search and Protein Validation-Database searches were performed using the Mascot Daemon software (version 2. 3. 2 Matrix Science, London, UK) using procedures described in the supplementary Experimental Procedures. Quantification from Raw MS Data-Quantification was performed based on all peptide identifications derived from the 60 analytical runs, using the label-free quantitative module implemented in the MFPaQ v4. 0. 0 software (Mascot File Parsing and Quantification) (http://mfpaq. sourceforge. net/) as described in the supplementary Experimental Procedures. Quantification of peptide ions was performed based on calculated Extracted Ion Chromatogram (XIC) areas values. Data Processing and Statistical Analysis-Protein relative quantification was performed by pairwise comparisons of different groups, containing each five samples analyzed in triplicate.
p values were adjusted for multiple testing using the Benjamini-Hochberg procedure  (23). All procedures were performed using R packages, which can be provided upon request. Targeted Mass Spectrometry Analysis-Multiple Reaction Monitoring (MRM) for Biomarker Verification-The design of MRM assays and urinary sample preparation for MRM analysis was performed as described in the supplementary Experimental Procedures. Each dried digested urinary sample spiked with yeast exogenous proteins was suspended with 14 l of a mixture of synthetic stable isotope-labeled peptides (partially purified PEPotec synthetic peptides or purified AQUA Ultimate peptides, Thermo Scientific, see the supplementary Experimental Procedures) in 2% acetonitrile, and 0. 05% trifluoroacetic acid. Half of the preparation was then loaded on the system and analyzed on the 5500 QTrap as described for the design of MRM assays (supplementary Experimental Procedures), using the optimized transitions list (supplemental Data S1).
Quantitative measurements were performed via time-scheduled MRM acquisition, using a 4 min retention time window and a cycle time of 3s. Details of the MRM acquisition method are given in supplemental Table  S1. For assessment of the repeatability of the entire analytical workflow (sample concentration on SDS-PAGE ϩ in-gel digestion ϩ LC-MRM analysis), replicate sample preparations and LC-MRM analysis were performed on aliquots of either a unique healthy urine sample from the cohort of the verification study or of a pooled urine sample from healthy donors (supplementary Experimental Procedures, supplemental Table  S2  and supplemental Data S2-S3 for details on these preliminary experiments). For the candidate proteins monitoring with purified AQUA peptides, response curves were generated by spiking in increasing amounts the heavy standards in a pooled urine sample from healthy donors, and the LOD/LLOQ of the assays was calculated using the QuaSAR software (24) (supplementary Experimental Procedures, supplemental Table  S3  and supplemental Data S4 -S5).
Assessment of the LC-MRM system performances during the clinical study itself was done through systematic injection of a quality control beta-galactosidase tryptic digest, interspersed between acquisition of the clinical samples from the verification cohort (supplemental Data S6), and through monitoring of the spiked-in yeast protein internal standards (supplemental Data S7). Injections corresponding to the three groups of samples from the verification cohort were randomized during LC-MRM analysis. The entire data set of the MRM analysis was loaded into PeptideAtlas/PASSEL (http://www. peptideatlas. org/PASS/PASS00454). All MRM data were analyzed with the Skyline software (http://proteome. gs. washington. edu/ software/skyline). Data were manually inspected to ensure correct peak detection and integration.
In addition, the AuDIT module  (25)  was used to assess the quality of the monitored transitions, by controlling the relative ratios between transitions in the light and heavy peptides in the preliminary triplicate test data set (supplemental Table  S2 ), and in the clinical data set itself (supplemental Table  S4 ). Endogenous protein amounts were estimated by QuaSAR from the calculation of peak area ratio (PAR) values between light and heavy peptides, and from the known spiked amounts of the heavy internal standard peptides (approximate amounts were used in the case of partially purified PEPotec peptides). Relative quantification and statistical analysis between sample groups was performed on one selected transition (the best) for each targeted peptide using unpaired t test assuming unequal variances (supplementary Experimental Procedures).
For each sample group comparison (Mild/Healthy, Severe-Bladder/Healthy and Severe-Bladder/Mild) p values were corrected for multiple testing using the Benjamini-Hochberg procedure (22 p values corrected corresponding to the 22 peptides quantified per comparison) (supplemental Data S8). Adjusted p values less than 0. 05 were considered statistically significant. Graphics were generated by Prism 5 GraphPad software. Adult Mouse Model of Obstructive Nephropathy-Animals-C57Bl/6J mice were purchased from Janvier SAS (CS 4105 Le Genest St Isle F-53941 St Berthevin Cedex). The mice were housed in a pathogen-free environment. All experiments reported were conducted in accordance with the NIH guide for the care and use of laboratory animals and were approved by a local animal care and use committee.