dataesr/scientific-paragraphs-categorization huggingface dataset:
EMG pre-processing A notch-filter was used to reduce 50 Hz line noise when present (quality factor 35; Matlab iirnotch function). The EMGs for each trial were digitally full-wave rectified, low pass filtered (20th order FIR filter; 50 Hz cutoff; zero phase distortion; Matlab fir1 and filtfilt functions) and resampled at 200 Hz. Diagnostic screening of EMG signal quality was performed by checking the maximum level of activation, the activation level before the launch time (i. e. , with the arm at rest), and the power spectral density of each channel. Eighteen trials (out of a total of 581 trials) that showed high pre-launch activity or abrupt change in signal amplitude, likely resulting from a partial detachment of the electrode from the skin, were excluded. Presence of significant cross-talk was assessed by computing the mean cross-correlation between pairs of channels across trials.
Statistical analysis To explain the effect on the synergies recruiting parameters of experimental condition (three ball flight times and two ball arrival heights), the synergy amplitude and timing coefficients were submitted to either a Two-Way ANOVA test (3 arrival times × 2 height conditions) or to a multiple linear regression analysis according to the model: y = α + βT + γZ d + δ(T, Z d ) + ε where T is the time variable, i. e. , the ball flight time, Z d is a dummy variable for the ball arrival height Z, i. e. , Z d = 1 for low launches and Z d = 2 for high launches. Statistical analyses were performed in the R software environment (R Development Core Team, 2011). The level of significance was set at p < 0. 05. wrist trajectories, filtered EMGs, and wrist speed profiles averaged across multiple trials of subject S 1 in the condition (T 1 ,Z 1 ).
While we plan to test a more diverse set of experimental conditions in the future, the synergy decomposition approach was used here as a tool to identify spatiotemporal components in the muscle patterns independent of temporal constraints, such as flight duration. Thus, the synergies identified from this dataset might be composed by the combination of a larger number of more fundamental building blocks modulated by the spatial demands of the task, such as ball arrival locations at different medio-lateral coordinates. Our observation of the modulation of the onset time of the second synergy by the temporal demands of the task, i. e. , the duration of the ball flight and of the ball arrival at the interception point, may be contrasted with the timing modulation of the synergies for reaching a stationary target.
XRF scanning A series of element abundances -including K, Ti, Zr, Al -were measured on U-channels using the Avaatech core scanner from the EPOC laboratory at the University of Bordeaux. The sediment was protected with Ultralene during Xray transmission foil in order to avoid contamination. The data were acquired at a 30 s count time, using 10 kV voltage and 400 mA intensity. Richter et al. (2006)  give technical details on the XRF scanning technique. The results are expressed in counts per second, with a 2 % precision according to standard samples. The Zr/Al, Ti/Al and K/Al ratios as used in the text refer to Zr XRF /Al XRF , Ti XRF /Al XRF , and K XRF /Al XRF ratios respectively. Trace elements are normalized to Al  (Tribovillard et al. , 2008) , in order to avoid dilution effect by carbonates.
Acknowledgements. This study was funded by the  ANR LAMA. This manuscript benefits from thorough reviews from one anonymous referee and from  Nejib Kallel. Thomas Richter  is thanked for his advice on the use of presentation of XRF data. Philippe Martinez  ( EPOC -University of Bordeaux ) is thanked for producing XRF analysis of the core. Léa-Marie Bernard Emaille ,  Deny Malengros  and  Romain Abraham  are thanked for technical assistance for XRD analysis and laser grain size measurements. This is LSCE contribution no. 4586. Edited by:  D. -D. Rousseau The publication of this article is financed by  CNRS-INSU.
PDE-5 inhibitors may also increase the risk of central nervous system (CNS) oxygen toxicity by enhancing cerebral blood flow under conditions that can occur in diving or during hyperbaric oxygen administration  [23]. Based on its properties, sildenafil could have a beneficial role on decompression by reducing bubble formation. On the other hand, its vascular impact on the central nervous system is not known in the context of diving and severe decompression. To our knowledge, there are no reported data on the occurrence of DCS in divers taking sildenafil. The purpose of the present study was to evaluate the clinical effects of sildenafil pre-treatment on DCS in a rat model. To complete this analysis, we also determined the level of circulating vascular bubbles in the right cavities and counted blood cells.
The program used to control decompression rate was designed on DasyLab (DasyLab National Instrument, USA) by our engineer. Compressed air was generated using a diving compressor (Mini Verticus III, Bauer Comp, Germany) coupled to a 100-liter tank at 300 bars. The oxygen analyzer was based on a MicroFuel electrochemical cell (G18007 Teledyne Electronic Technologies/ Analytical Instruments, USA). Water vapor and CO 2 produced by the animals were respectively captured with seccagel (relative humidity: 40-60%) and soda lime (,300 ppm captured by the soda lime), respectively. Gases were mixed by an electric fan. The day-night cycle was respected throughout. The temperature inside the tank was measured using a platinum-resistance temperature probe (Pt 100, Eurotherm, France). All these variables were controlled by a dedicated computer.
Statistical Analyses For statistical processing, we used Sigmastat 3. 0 (SPSS inc. , Chicago, Illinois). Numerical results were expressed as median and interquartile range. A contingency table was used for independence and association tests, coupled with a Fisher Exact or Chi 2 test of significance. Differences between two groups were analysed by a Mann-Whitney test, whereas matched comparisons within groups used a Wilcoxon test. A difference was considered as significant for p-values ,0. 05.
Event selection Events are required to be identified by the trigger system as containing at least one electron or one muon. In order to control the data-taking bandwidth, the trigger system imposed a minimum transverse energy threshold on electrons of 20 GeV or 22 GeV (depending on the data-taking period), and a minimum p T threshold on muons of 18 GeV. For the highest luminosities towards the end of the data-taking period, the muon trigger is required to be accompanied by a jet that passes the first-level trigger p T threshold of 10 GeV. All data events are required to be recorded during stable LHC running conditions and with all relevant sub-detectors functioning normally. Events are cleaned for instrumental effects, such as sporadic noise bursts  [46]. Events are required to have exactly one reconstructed electron (muon) with p T > 25  (20)  GeV.
425. In addition, the CTEQ6L1 PDF set is used instead of CT10 which is used in the nominal t t sample. The total background yield is found to differ by 1. 5% with respect to the nominal samples. The uncertainty on the signal and the top-quark background due to initial-state radiation (ISR) and final-state radiation (FSR) is evaluated using the AcerMC generator interfaced to the PYTHIA 6. 425 shower model with the parameters controlling ISR and FSR varied in a range consistent with experimental data  [54]. The event yields are found to agree with nominal values within statistical uncertainties. MC@NLO events with top-quark masses of 170 GeV and 175 GeV are used to assess the top-quark mass dependence, which is added in quadrature to the uncertainty related to the choice of event generator and PDF set.
Conclusions A search for pair production of third generation scalar leptoquarks has been performed with the ATLAS detector at the LHC, using a data sample corresponding to an integrated luminosity of 4. 7 fb -1. No significant excess over the SM background expectation is observed in the data. The assumption is made that BR(LQ → τb) = 1. 0 and third generation scalar leptoquarks with masses up to m LQ < 534 GeV are excluded at 95% CL. The cross-section for leptoquark pair-production increases with centre-of-mass collision energy. At √ s = 8 TeV the production rate for leptoquarks with m LQ = 700 GeV is enhanced by a factor of two, providing scope for setting stronger limits using data from the 2012 LHC run. Meanwhile, this result is the most stringent limit arising from direct searches for third generation scalar leptoquarks to-date.
Acknowledgements 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 ;  COL-CIENCIAS, 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, DIP and Benoziyo Center, Israel ;  INFN, Italy ;  MEXT  and  JSPS, Japan ; CNRST, Morocco; FOM and  NWO, Netherlands ;  BRF  and  RCN, Norway ;  MNiSW , Poland; GRICES and FCT, Portugal; MERYS (MECTS), Romania; MES of Russia and ROSATOM, Russian Federation; JINR; MSTD, Serbia; MSSR, Slovakia; ARRS and MIZ Š, Slovenia; DST/NRF, South Africa; MICINN, Spain;  SRC and Wallenberg Foundation, Sweden ;  SER ,  SNSF  and  Cantons of Bern and Geneva, Switzerland ;  NSC, Taiwan ;  TAEK, Turkey ;  STFC , the  Royal Society and Leverhulme Trust ,  United Kingdom ;  DOE  and  NSF ,  United States of America.
To this aim, we genotyped at least 30 individual workers per sampled native and introduced population at 12 microsatellite markers  (Fournier et al. 2005b ) and added this new data set to a previous data set investigating the worldwide genetic variation of W. auropunctata  (Foucaud et al. 2010). We performed three distinct population genetics analyses using this global microsatellite data set. We first used the software POPULATIONS  (Langella 2002)  to construct a dendrogram connecting worker populations using the Neighbor-Joining (NJ) algorithm  (Saitou and Nei 1987). The genetic distance used was Chakraborty and Jin's alleleshared distance  (Chakraborty and Jin 1993). This distance was averaged over all pairs of individuals belonging to pairwise populations in order to obtain the genetic distances between populations.
Bootstrap values (with the locus as a unit) were calculated over 1000 iterations. Extended majority rule was applied to reconstruct the consensus tree. Similar results were obtained using other genetic distances (including Nei's chord distance, Cavalli-Sforza & Edwards distance and the proportion of shared alleles;  Bowcock et al. 1994; Cavalli-Sforza and Edwards 1967; Nei et al. 1983 ) and reconstruction algorithms (UPGMA and BioNJ;  Gascuel 1997 ). These additional phylogenetic reconstructions were obtained using MSA 4. 05 for the computation of 10 000 bootstrapped distance matrices  (Dieringer and Schl€ otterer 2003)  and the neighbor and consense programs of the PHYLIP package v3. 69 for the tree reconstruction (Felsenstein 2004). As second analysis, we computed a matrix including pairwise F ST values between all sampled populations using the estimator h of the parameter F ST  (Weir and Cockerham 1984).
We therefore used Penalized Quasi-Likelihood methods (PQL;  Breslow and Clayton 1993) , as implemented in SAS 9. 1, to fit the model (PROC GLIM-MIX, SAS Institute, Cary, NC, USA). PQL methods may yield biased estimates of variance components in some situations  (Lin and Breslow 1996). However, on the basis of previous work  (Breslow and Clayton 1993; Breslow and Lin 1995; Bolker et al. 2009) , we conclude that our estimates may only be subject to a negligible bias, given that (i) the data were only slightly unbalanced, (ii) all fixed effects reached high levels of significance, and (iii) all variance component estimates were small (<0. 36) and the overdispersion coefficient was moderate (1. 53, see below). The significance of fixed effects was assessed through approximate F-tests and the number of denominator degrees of freedom for each test was computed using the Kenward-Roger approximation  (Bolker et al.
Effect of body size on thermotolerance We tested for a possible effect of body size on our thermotolerance results, by investigating worker body size in five native populationstwo from natural habitats (M3-F and M11) and three from human-modified habitats (Ker, P2-2 and Cay)and two introduced populations (New Caledonia and Australia). The introduced Australian population, which was not tested in our main thermotolerance assay, has previously been shown to be clonal  Foucaud et al. 2010 , and subsequently to exhibit thermotolerance levels similar to those of other introduced populations (results not shown). We collected and point-mounted 20 foraging workers from each population. Multifocus images (x40) of worker heads were acquired with a GT Entovision System and Archime-dTM software (Microvision Instruments, Evry, France).
Four morphological parameters of the head were measured on each worker (maximum head width, maximum head length, and head width in front of and behind the eyes) with Cartograph software (Microvision Instruments). Preliminary analysis showed that all morphometric measurements were highly correlated (all Pearson's productmoment correlations > 0. 66). Thus, as maximum head width is often considered a standard proxy for body size (H€ olldobler and Wilson 1990), we used only this morphological variable for subsequent analyses. After testing for normality and variance homogeneity, we investigated putative differences in body size between populations originating from different habitats in both ranges (native natural, native human-modified, and introduced human-modified), by fitting a linear mixed model implemented in R (R Development Core Team 2005) and including the following factors: 'type' (fixed factor corresponding to our three types of population) and 'pop' (random factor corresponding to the sampled population, nested within 'type').
Additional Student's t-tests on pairs of population types revealed only a non-significant trend of this type in our own data set (results not shown). Most importantly, the goal of our morphological analysis was to assess the possible relationship between body size and levels of thermotolerance in population samples for which we had thermotolerance data. In that respect, we found no significant association between these two variables. Thermotolerance in W. auropunctata is therefore probably achieved through physiological, biochemical, or behavioral processes, or through a combination of such processes, rather than through an increase in body size. For example, in the small workers of thermophilic C. rosenhaueri, thermotolerance results partly from an increase in metabolic rate and a decrease in cuticular water loss, together with differences in body posture  (Cerda and Retana 2000).
Acknowledgements We thank  Gary Morton  for providing the W. auropunctata individuals from Australia used for morphological analyses. JF thanks  Aude Gilabert  for support. This study was supported by a grant from the  French Minist ere de l'Ecologie et du D eveloppement Durableappel d'offre ECOTROP  to AE and JO and from the  French Agropolis Foundation  ( RTRA -Montpellier ,  BIOFIS  project number  1001-001 ) to AE and BF.
Related literature For general background to hybrid materials, see:  Benali-Cherif et al. (2007) ;  Messai et al. (2009). For studies of amine salts, see:  Jayaraman et al. (2002) ;  Steiner (2002). For related structures, see:  Gilli et al. (1994) ;  Boenigk & Mootz (1988) ;  Jin et al. (2001). Hydrogen-bond geometry (A ˚, ). Data collection: KappaCCD Server Software  (Nonius, 1997) ; cell refinement: DENZO-SMN  (Otwinowski & Minor, 1997) ; data reduction: DENZO-SMN; program(s) used to solve structure: SIR97  (Altomare et al. , 1999) ; program(s) used to refine structure: SHELXL97  (Sheldrick, 2008) ; molecular graphics: ORTEPIII  (Burnett & Johnson, 1996) ; software used to prepare material for publication: SHELXL97 and WinGX  (Farrugia, 2012).
Computing details Data collection: KappaCCD Server Software  (Nonius, 1997) ; cell refinement: DENZO-SMN  (Otwinowski & Minor, 1997) ; data reduction: DENZO-SMN  (Otwinowski & Minor, 1997 ); program(s) used to solve structure: SIR97  (Altomare et al. , 1999) ; program(s) used to refine structure: SHELXL97  (Sheldrick, 2008) ; molecular graphics: ORTEPIII  (Burnett & Johnson, 1996) ; software used to prepare material for publication: SHELXL97  (Sheldrick, 2008)  and WinGX  (Farrugia, 2012). Refinement. Refinement of F 2 against ALL reflections. The weighted R-factor wR and goodness of fit S are based on F 2 , conventional R-factors R are based on F, with F set to zero for negative F 2. The threshold expression of F 2 > σ(F 2 ) is used only for calculating R-factors(gt) etc. and is not relevant to the choice of reflections for refinement.
JHEP06(2013)081 SM does not directly predict the values of the masses of the elementary particles, and in the same context there is no prediction for the Higgs boson mass. The particle masses are considered parameters to be determined experimentally. Nevertheless, a number of very general arguments  [14] [15] [16] [17]  have been used to narrow the range of possible values for the Higgs boson mass to below approximately 1 TeV. The wealth of electroweak precision data from the LEP and SLC colliders, the Tevatron, and other experiments predicted the Higgs boson mass to be at approximately 90 GeV, with an upper limit of 152 GeV at the 95% confidence level (CL)  [4]. Direct searches at LEP excluded values lower than 114. 4 GeV at 95% CL  [18] , and early Tevatron measurements excluded the mass range 162-166 GeV at 95% CL  [19].
The discovery or exclusion of the SM Higgs boson is one of the primary scientific goals of the LHC. Previous direct searches at the LHC were based on data from protonproton collisions corresponding to an integrated luminosity of 5. 1 fb -1 collected at a centreof-mass energy of 7 TeV. The CMS experiment excluded at 95% CL masses from 127 to 600 GeV  [20]. The ATLAS experiment excluded at 95% CL the ranges 111. 4-116. 4, 119. 4-122. 1, and 129. 2-541 GeV  [21]. Within the remaining allowed mass region, an excess of events between 2 and 3 standard deviations (σ) near  125  GeV was reported by both experiments. In 2012, the proton-proton centre-of-mass energy was increased to 8 TeV, and by the end of June, an additional integrated luminosity of more than 5. 3 fb -1 had been recorded by each of the two experiments, thereby enhancing significantly the sensitivity of the search for the Higgs boson.
In the endcaps, each muon station consists of six detection planes. The precision of the r-φ measurement is 100 µm in the drift tubes and varies from 60 to 140 µm in the cathode strip chambers, where r is the radial distance from the beamline and φ is the azimuthal angle. The CMS trigger and data acquisition systems ensure that data samples with potentially interesting events are recorded with high efficiency. The first-level (L1) trigger, composed of the calorimeter, muon, and global-trigger processors, uses coarse-granularity information to select the most interesting events in less than 4 µs. The detector data are pipelined to ensure negligible deadtime up to a L1 rate of 100 kHz. After L1 triggering, data are transferred from the readout electronics of all subdetectors through the readout network to the high-level-trigger (HLT) processor farm, which assembles the full event and executes global reconstruction algorithms.
The HLT filters the data, resulting in an event rate of ≈500 Hz stored for offline processing. All data recorded by the CMS experiment are accessible for offline analysis through the world-wide LHC computing grid. The CMS experiment employs a highly distributed computing infrastructure, with a primary Tier-0 centre at CERN, supplemented by seven Tier-1, more than 50 Tier-2, and over 100 Tier-3 centres at national laboratories and universities throughout the world. The CMS software running on this high-performance computing system executes a multitude of crucial tasks, including the reconstruction and analysis of the collected data, as well as the generation and detector modelling of MC simulation.
A second BDT, using the same input variables, is trained on a separate sample of simulated photons to provide an estimate of the uncertainty in the energy value provided by the first BDT. The width of the reconstructed Z resonance is used to quantify the ECAL performance, using decays to two electrons whose energies are measured using the ECAL alone, with their direction determined from the tracks. In the 7 TeV data set, the dielectron mass resolution at the Z boson mass, fitting for the measurement contribution separately from the natural width, is 1. 56 GeV in the barrel and 2. 57 GeV in the endcaps, while in the 8 TeV data sample, reconstructed with preliminary calibration constants, the corresponding values are 1. 61 GeV and 3. 75 GeV. Electron reconstruction is based on two methods: the first where an ECAL supercluster is used to seed the reconstruction of a charged-particle trajectory in the tracker  [41, 42] , and the second where a candidate track is used to reconstruct an ECAL supercluster  [43].
Data sample and analyses performance The data have been collected by the CMS experiment at a centre-of-mass energy of 7 TeV in the year 2011, corresponding to an integrated luminosity of about 5. 1 fb -1 , and a centre-ofmass energy of 8 TeV in the year 2012, corresponding to an integrated luminosity of about 5. 3 fb -1. A summary of all analyses described in this paper is presented in table  1 , where we list their main characteristics, namely: exclusive final states, Higgs boson mass range of the search, integrated luminosity used, and the approximate experimental mass resolution. The presence of a signal in one of the channels at a certain value of the Higgs boson mass, m H , should manifest itself as an excess in the corresponding invariant-mass distribution extending around that value for a range corresponding to the m H resolution.
Simulated samples MC simulation samples for the SM Higgs boson signal and background processes are used to optimize the event selection, evaluate the acceptance and systematic uncertainties, and predict the expected yields. They are processed through a detailed simulation of the CMS detector based on Geant4  [49]  and are reconstructed with the same algorithms used for the data. The simulations include pileup interactions properly reweighted to match the distribution of the number of such interactions observed in data. For leading-order generators the default set of parton distribution functions (PDF) used to produce these samples is CTEQ6L  [50] , while CT10  [51]  is employed for next-to-leading-order (NLO) generators. For all generated samples the hadronization is handled by pythia 6. 4  [52]  or herwig++  [53] , and the tauola  [54]  package is used for τ decays.