dataesr/scientific-paragraphs-categorization huggingface dataset:
Signal and background predictions depend on systematic uncertainties that are parameterised by nuisance parameters, θ, which in turn are constrained using Gaussian functions, F G , so that L (µ, θ) = j = bin and category F P (N j | µ • s j + b j ) θ i F G (θ i | 0, 1) , (8. 1) where F P (N j | µ • s j + b j ) denotes the Poisson distribution with mean µ • s j + b j for variable N j. The correlations of the systematic uncertainties across categories are taken into account. The expected signal and background event counts in each bin are functions of θ. The parameterisation is chosen such that the rates in each channel are log-normally distributed for a normally distributed θ. To calculate the upper limit on µ for a given signal hypothesis, the compatibility of the observed or expected dataset with the signal-plus-background prediction is checked following the modified frequentist method known as CL s  [69].
Summary A search is presented for the neutral Higgs bosons of the Minimal Supersymmetric Standard Model in proton-proton collisions at a centre-of-mass energy of 7 TeV with the ATLAS experiment at the LHC. A significant portion of the available MSSM parameter space is consistent with the assumption that the newly discovered particle at the LHC is one of the neutral CP-even MSSM Higgs bosons. The study is based on a data sample that corresponds to an integrated luminosity of 4. 7 fb -1 to 4. 8 fb -1. The decay modes of the Higgs bosons considered are h/A/H → µ + µ -, h/A/H → τ e τ µ , h/A/H → τ lep τ had and h/A/H → τ had τ had. The analysis selection criteria exploit the two main production mechanisms in the MSSM, the gluon-fusion and b-associated production modes, by introducing categories for event samples with and without an identified b-jet.
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, 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 MVZT, 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.
Study Population A total of 4335 patients from the IHWG database met the following criteria and were included in the current analysis: 1) transplantation from an HLA-A, B, C, DRB1, and DQB1 allele compatible unrelated donor; 2) patient diagnosis of acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML) or chronic myeloid leukemia (CML) and 3) non-T cell depleted stem cell source without use of anti-thymocyte globulin (ATG) for GVHD prophylaxis. Patient characteristics by ethnicity are described in Table  1. Among these subjects, 1232 patients carried the diagnosis of ALL, 1758 AML and 1345 CML. Low-risk disease was defined as a CML chronic phase (CP) at the time of transplantation. The definition of disease risk was comparable among clinical centers within IHWG. Intermediate-risk was defined as transplantation in the first or second complete remission (CR) of ALL, AML, or the second CP or accelerated phase (AP) of CML.
High-risk was defined as transplantation in a more advanced stage than intermediate risk. Early status of disease included patients in first and second complete remission (CR) of acute lymphoblastic leukemia or acute myeloid leukemia at transplantation, first chronic phase of chronic myeloid leukemia at transplantation. For GVHD prophylaxis, a tacrolimus-based regimen was employed in 1536 patients, a cyclosporine-based regimen in 2593 and other regimens in 78. Patients were conditioned for transplantation using either a myeloablative (N=3687) or a nonmyeloablative/reduced-intensity regimen (n=381). A total of 3481 patients were transplanted with bone marrow and 854 with peripheral blood stem cells (PBSCs). Informed consent was obtained from patients and donors in accordance with the Declaration of Helsinki in each registry or institution, and consent of participation with the IHWG was obtained from each participating registry or institution before registration of the data or materials.
HLA antigens and haplotypes are population specific. The IHWG database is a unique resource for the comparative analysis of transplant outcomes and HLA genetics. In order to analyze acute GVHD and GVL effects clinically, it is essential that non-genetic factors that also influence these transplant-related immunological events are taken into consideration. As HLA compatibility between the patient and donor is a well-recognized risk factor for acute GVHD and leukemia relapse in unrelated donor HCT  [1] [2] [3] [4] [5] [6] 17, 18] , we restricted the study population to HLA-A, B, C, DRB1, and DQB1 allele-matched pairs. GVHD prophylaxis is also another important factor for acute GVHD. Therefore, only leukemia patients transplanted from non-T cell depleted stem cell sources without ATG were included in the analysis.
We used broad terms to classify Caucasian, Hispanic and African Americans; however, each of these populations may include individuals of very different ethnic backgrounds, and is one limitation of our study at present. Critical to achieving this goal is the need to define the genetic diversity of all human populations given the highly polymorphic nature of the HLA system. In the US, a larger clinical experience will aid our understanding of the immunogenicity of specific HLA phenotypes representing African American, Hispanic and Native Americans  [13, 32]. As most Asian/Pacific Islander pairs in our current study (1734 out of 1753) were Japanese pairs registered from the JMDP, the data are representative of the Japanese population rather than Asian/Pacific ethnicities as a whole. Contribution of data from other populations in the future will aid in the effort to mapping transplantation determinants, information that will benefit all patients.
Acknowledgments We thank all the members of the IHWG hematopoietic-cell transplantation component who contributed data to this publication (Supplemental Table  S6 ). We are grateful for support from the following agencies: Grant ( H23-Immunology-010 ) from the  Ministry of Health, Labor and Welfare, Japan , Grant ( 3224-22133011 ) from the  Ministry of Education, Culture, Sports, Science and Technology, Japan ; Grants  AI069197 ,  CA100019 , and  CA18029  (EWP, MM), and  CA76518  (SS) from the  National Institutes of Health, USA. HHSH234200637015C  (SS) from the  Health Resources and Services Administration, USA ;  N00014-10-1-0204  and  N00014-1-1-0339  (SS) from the  Office of Naval Research, USA.
8 g/L, or CSF PMN ≥1000/mm 3. The BMS has undergone external validation on the large database of the French national registry for childhood bacterial meningitis (ACTIV-GPIP)  [51]. Of 889 children with confirmed bacterial meningitis, 884 were correctly identified by the BMS rule (sensitivity = 99. 6%; 95% confidence interval (CI) 98. 9-99. 8) with a specificity >60%. Thus, despite these near-perfect results, a few patients with bacterial meningitis (n = 5) were not detected by the BMS  [52] ; that the BMS can have a few false-negatives also was confirmed by a recent meta-analysis  [53]. The Meningitest® (European patent EP1977244) has been subsequently proposed to refine the BMS and avoid these false-negatives, by omitting some variables of poor discriminatory power and introducing the serum PCT level  [45, 54].
The Meningitest® rule suggests initiating antibiotic therapy if at least one of the following criteria is present: seizures, toxic appearance, purpura, PCT level ≥0. 5 ng/mL, positive CSF Gram stain, or CSF protein level ≥0. 5 g/L. External validation of the Meningitest® has been performed on an European database of 198 patients (including 96 with bacterial meningitis), where its sensitivity and specificity were respectively of 100% (95% CI 96-100) and 36% (95% CI  [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46]  for the diagnosis of bacterial meningitis, whereas corresponding values for the BMS were 100% (95% CI 96-100) and 52% (95% CI 42-62)  [55]. A single serum PCT level ≥0. 5 ng/mL has similar sensitivity and specificity as the BMS, whereas combining CRP with CSF protein levels provided lower performances.
When can biomarkers help the decision to stop antibiotic therapy? Given the number of studies examining this question and the high level of evidence generated, investigating this question was limited to examining randomized, controlled studies having tested a strategy based on biomarker measurement(s), to the exclusion of all other study designs. All studies in hospitalised patients used serum PCT level measurements, as there is no study testing the impact of using another biomarker in this specific indication; whereas several studies have tested the value of CRP for initiating antibiotics in pre-hospital care  [24, [66] [67] [68] , none examined its potential impact on discontinuation of antibiotics, although several studies are ongoing (see http:// www. clinicaltrials. gov/ct2/results?term=c+reactive+protein+ and+duration&recr=&rslt=&type=&cond=&intr=&outc=& spons=&lead=&id=&state1=&cntry1=&state2=&cntry2=&st-ate3=&cntry3=&locn=&gndr=&rcv_s=&rcv_e=&lup_s=&-lup_e=).
Acknowledgements The authors acknowledge support of the following institutions (and grants): the  Slovak Grant Agency   VEGA (2/0009/11 :  P. Bala  ´z ˇ, MB, ED;  2/0043/11 : MA), the  Slovak Agency for Science and Development APVV  ( VV-0189-10 :  P. Bala  ´z ˇ, MB, ED, MA;  VV-0528-11 :  P. Billik ),  Centre of Excellence of Slovak Academy of Sciences (CFNT-MVEP) ,  Slovenian Research Agency (TR) ,  Russian Foundation for Basic Research  ( 10-03-00942a : AS,  12-03-00651a : AS),  Ministry of Science and Higher education in Poland  ( CUT/c-1/DS/KWC/2008-2012 ,  PB1T09B02330 ,  NN209145136 ,  NN209148936 : KW), Alexander von Humboldt Foundation and EPFL (MS). This acknowledgement is also devoted to all the colleagues who have contributed to this review article, but are not listed as co-authors.
with the stacked pressure profile derived from the XMM-Newton data for the same sample (purple points). The dispersions about the SZ and X-ray profiles are depicted, respectively, by the red and purple shaded areas. Our best fit GNFW profile is shown as a solid black line and that of A10 as a solid green line. The lower panel shows the χ profile of these two best models taking into account the statistical errors and dispersion about the observed profile. Right: stacked profile from Planck and XMM-Newton for the sub-samples of cool-core (open circles) and non cool-core (open stars) clusters within the ESZ-XMM sample. The shaded areas are identical to the one shown in the left panel. Our best fit models for each sub-sample are shown as black solid and dashed lines for the cool-core and non cool-core clusters, respectively (see Table  1 ).
The best A10 fit for cool-core and non cool-core clusters are shown as green solid and dashed lines, respectively. The lower panel gives the χ profiles of our best fit models with respect to the measured profiles and associated errors (including dispersion). On both panels the Planck data points are correlated at about the 20% level (see Sect. 4. 3. 1). As for the stacked SZ profile, the error bars on the Planck points are purely statistical and correspond to the square root of the diagonal elements of the covariance matrix. For the XMM-Newton points they correspond to the statistical error on mean.
In parallel to our Planck SZ analysis, we have also derived the pressure profiles of our 62 clusters from the analysis of XMM-Newton data. We followed the method applied to the REXCESS sample and presented in A10. Details of the XMM-Newton analysis and results are provided in  Démocles (2012). The Planck and XMM-Newton stacked pressure profiles derived from our sample of 62 ESZ-XMM clusters, are displayed in Fig. 4. The two sets of data agree remarkably well. They are fully compatible within their respective dispersions, and they overlap in the radial range ∼ (0. 3-1) R 500. We recall that the points from the Planck data suffer a degree of correlation at about the 20% level, whereas all the points in the XMM-Newton profile can be considered as uncorrelated. These two independently derived pressure profiles are fully complementary.
Best-fit to the Generalised NFW profile We have combined the Planck and XMM-Newton pressure profiles into a joint fit to the generalised NFW model (Eq. 7). The pressure profiles derived over our sample from the Planck and XMM-Newton data cover a radial range from 0. 02 × R 500 to 3×R 500 , with an overlap in the radial interval of (0. 1-1)×R 500. In order to find the best parametric representation of our observed stacked profile, we ran a Monte Carlo Markov Chain analysis to find the maximum likelihood solution parametrising the GNFW profile. The Planck and XMM-Newton data are two different and fully independent observational data sets. We therefore computed the likelihood as the product of the two independent likelihoods: L = L X × L SZ. For the Planck data, we have accounted for the correlation between points through the use of the covariance matrix (see Sect.
The SPT team Planck Collaboration: Pressure profiles of galaxy clusters from the Sunyaev-Zeldovich effect found good agreement between the X-ray predicted signal and their SZ measurement within R 500. Similarly, in a recent study,  Bonamente et al. (2012)  used a sample of 25 clusters observed with SZA/CARMA  (Muchovej et al. 2007 ) and found an excellent agreement when modelling the SZ emission over their sample, either with the universal pressure profile from A10 or with the model from  Bulbul et al. (2010). Our SZ and X-ray data are in excellent agreement over the radial range (0. 1-1) R 500 , providing tighter observational constraints. Our results, together with the SPT, and ACT results, have to be compared with other works that reported a difference between SZ and X-ray measurements.
2010)  or the WMAP statistical analysis over ∼ 700 clusters by  Atrio-Barandela et al. (2008) , though the latter is affected by the limited resolution and sensitivity of the survey. Conversely, from the tentative analysis of WMAP-3 data for 193 clusters with X-ray temperature above 3 keV,  Afshordi et al. (2007)  provided constraints for the cluster pressure profile (significant out to ∼ 1. 3 R 500 ). In agreement with these earlier works, the Planck measurements of the present study are the first to allow a precise description of the thermal pressure distribution out to the cluster outskirts. As shown in App. C, Planck also resolves some individual pressure profiles. The work presented by the Planck Collaboration X (2012) on the Coma cluster is even more striking, as the SZ profile detection reaches beyond 3 × R 500 , i.
Sets of numerical data We have investigated three sets of simulated clusters in order to compare to our combined Planck and XMM-Newton pressure profile. All are taken from numerical simulations of structure formation in a ΛCDM cosmology: 1. We first compared to the set of combined simulations used by A10 to derive their universal pressure profile together with the REXCESS data. They comprise 93, 14, and 88 simulated clusters with M > 10 14 M ⊙ , from  Borgani et al. (2004) ,  Nagai et al. (2007a)  and  Piffaretti & Valdarnini (2008) , respectively. We refer to this set of simulations as B04+N07+P08 hereafter. 2. The second set is built from the pressure profiles of 64 massive clusters with M > 3 × 10 14 M ⊙ from a simulation by Dolag (2012). 3. The third comprises the 40 most massive clusters (i.
These components and their spectral signatures are then recovered by minimising the number of significant coefficients in Ψ. Recently, L-GMCA has been further introduced to analyse the CMB data in a local and multi-scale manner  (Bobin et al. 2012 ). More precisely, the multi-channel data are analysed in four frequency bands in spherical harmonics (i. e. , wavelet bands). In each wavelet band, GMCA is applied locally on small patches with band-dependent sizes. In each band, the observations are analysed at the same banddependent resolution. In  Bobin et al. (2012) , it was shown this local analysis approach enhances the separation quality. The spectral signatures of CMB, free-free and SZ are assumed to be known. the aforementioned R 500 and Y 500 values from the MCXC prescription. The resulting stacked profiles are displayed in Fig.
Acknowledgements. The development of Planck has been supported by:  ESA ;  CNES  and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MICINN  and  JA (Spain) ;  Tekes, AoF  and  CSC (Finland) ;  DLR  and  MPG (Germany) ;  CSA (Canada) ;  DTU Space (Denmark) ;  SER/SSO (Switzerland) ;  RCN (Norway) ;  SFI (Ireland) ;  FCT/MCTES (Portugal) ; and  DEISA (EU). We acknowledge the use of the Healpix software. Villanueva de la Cañada ,  Madrid, Spain European Space Agency ,  ESTEC , Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands  GEPI, Observatoire de Paris, Section de Meudon , 5  Place J. Janssen , 92195  Meudon Cedex ,  France Helsinki Institute of Physics, Gustaf Hällströmin katu 2, University of Helsinki, Helsinki, Finland INAF -Osservatorio Astronomico di Padova, Vicolo dell'Osservatorio 5, Padova, Italy INAF -Osservatorio Astronomico di Roma, via di Frascati 33, Monte Porzio Catone, Italy INAF -Osservatorio Astronomico di Trieste, Via G.
Note that this conclusion is an additional argument for a separated examination of summer and winter trends extracted from the CDD ice records. Table  1  summarizes the available various seasonally resolved records covering changes from before World War II to the recent decades. Investigated chemical species are present The open points correspond to samples from the C11 ice core (see Sect. 2. 1). The thick solid lines are robust spline smoothing  (Bloomfield and Steiger, 1983). Black dots and lines refer to raw data, red ones to data after having discarded Saharan dust events (see Sect. 3. 1). in the atmosphere as either aerosol or gases, or both. In the following we critically review all investigated species in order to select those contributing to the atmospheric aerosol load.
11. Temporal changes of summer mass concentrations of different aerosols at the CDD site. For the  1921-1951 and 1971-1988  years, atmospheric concentrations were estimated by inverting ice concentrations (see Sect. 6), whereas the 2004 concentrations are data gained during a field atmospheric campaign conducted in summer 2004  (Legrand et al. 2007b; Preunkert et al. , 2007). site in summer 2004, a recent period over which DOC and WSOC snow deposit data are not available (see Sect. 2). Preunkert et al. (2002)  found that atmospheric sulfate levels of 800 ng m -3 STP in summer at the CDD site correspond to 650 ppb in corresponding snow layers. These values were used to invert sulfate ice concentrations into atmospheric concentrations. A similar firn-air relationship was also used for other water-soluble submicron aerosols like ammonium aerosols and WSOC.
Acknowledgements. Funding was provided by the  European Community  via contracts  ENV4-CT97  (ALPCLIM) and  ENV4-CT96-5051  ( Environment and Climate Research Training ), and by the  Ministry for Science and Research of Baden-Württemberg  within the collaboration program between  Region Rhône-Alpes and Baden-Württemberg. The drilling operation to extract the  CDK ice core at Col du Dôme  was supported by the  EU   CARBOSOL  project (contract  EVK2 CT2001-00113 ). Finally the study of organics in the CDK ice cores was funded by the  CNRS-DFG  bilateral project entitled "Secondary organic aerosol production in the lower free troposphere over western Europe". We would like to thank  Dietmar Wagenbach  from  IUP Heidelberg  for continuous steering activities and a close and fruitful collaboration through these Alpine ice core studies that started more than 30 years ago.
7). However, the braking rate in the present models increases more steeply than Kawaler's in the unsaturated regime (cf. Table  4 ) and the braking efficiency thus becomes larger than Kawaler's as soon as the angular velocity exceeds the solar value. As a result, shorter disk lifetimes are required for fast rotator models  (2. 5  Myr here compared to 5 Myr in the Bouvier (2008) models), in order to account for large velocities at the ZAMS. The shorter duration of the star-disk interaction in fast rotators is additionally supported by the newly available h Per dataset at 13 Myr  (Moraux et al. in press, see Fig. 3 in this paper). In addition, as the current models and those presented in  Bouvier (2008)  have similar core-envelope coupling timescales for fast rotators  (10 and 12 Myr, respectively) , the more efficient braking of the outer envelope also results in enhanced differential rotation at the core-envelope boundary in the present models.
Acknowledgements. This study was supported by the grant  ANR 2011  Blanc  SIMI5-6 020 01  " Toupies: Towards understanding the spin evolution of stars " (http://ipag. osug. fr/Anr_Toupies/). We thank our partners in the  ANR  project, especially  S. Matt  for enlightening discussions on stellar wind models, and  A. Palacios ,  C. Charbonnel ,  S. Brun ,  P. Petit ,  C. Zanni , and  J. Ferreira  for numerous discussions and comments on an early version of this work. We thank the anonymous referee for helpful comment. We acknowledge financial support from  CNRS-INSU's Programme National de Physique Stellaire.
Meteorological modelling in the planetary boundary layer (PBL) over Greater Paris is performed using the Weather Research and Forecast (WRF) numerical model. The simulated meteorological fields are evaluated by comparison with mean diurnal observational data or mean vertical profiles of temperature, wind speed, humidity and boundary-layer height from 6 to 27 May 2005. Different PBL schemes, which parametrize the atmospheric turbulence in the PBL using different turbulence closure schemes, may be used in the WRF model. The sensitivity of the results to four PBL schemes (two non-local closure schemes and two local closure schemes) is estimated. Uncertainties in the PBL schemes are compared to the influence of the urban canopy model (UCM) and the updated Coordination of Information on the Environment (CORINE) land-use data.
Using the UCM and the CORINE land-use data produces more realistic modelled meteorological fields. The wind speed, which is overestimated in the simulations without the UCM, is improved below 1,000 m height. Furthermore, the modelled PBL heights during nighttime are strongly modified, with an increase that may be as high as 200 %. At night, the impact of changing the PBL scheme is lower than the impact of using the UCM and the CORINE land-use data.