dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments The observer data analyzed in this study were collected by the  Institut de Recherche pour le Developpement (IRD)  part of the  Mixed Research Unit 212 'Exploited Marine Ecosystems' (IRD/ Ifremer/U. Montpellier 2),  Instituto Espan ˜ol de Oceanografı ´a , and AZTI-tecnalia through the  EU Research Bigeye Program  ( Reg 96/028 ) and the  EU-funded Data Collection Framework (DCF, Reg (EC)   1543/2000  and  199/2008 ). We wish to acknowledge the contributions of ORTHONGEL, the staff of the  Observatoire Thonier (IRD) , and all the technicians and fishermen that have been involved in data collection, processing, and management. This study was part of the Ph. D. thesis conducted by the first author (ETI) at the University of Montpellier 2 (ED SIBAGHE) and funded by  Consejo Nacional de Ciencia y Tecnologı ´a (CONACYT) ,  Mexico , Scholarship No.
Acknowledgements. The authors thank the "Conseil Général de l'Hérault" for providing the data of the 2005 Cent-Fonts resurgence, pumping test data, obtained under contract by BRGM. We also thank Alexander Calvin, Martin Saar and Andrew Luhmann for friendly and helpful discussions about heat transfers in karstic system. This work has benefited of a special grant of the organization of the International Workshop of Deep Geothermal Systems, Wuhan, China, 29-30 June 2012.
Accidental signals. In real events, a background of random accidental signals might appear. The most frequent source of random noise is created by single particles (generally isolated atmospheric muons) and, more rarely, by a bunch of particles arriving at the same time from a low-energy shower close to a SD station. In general, it is very difficult to identify and take into account all possible sources of accidental signals. They can appear at any time and at any location in the SD array, completely uncorrelated with the genuine primary shower signal. Random accidental signals can have a damaging effect on the data quality, since they can trigger some stations of the array, distorting the reconstruction of the showers. In our analysis, the main impact comes from a possible underestimation of the start time of the traces due to an accidental signal prior to the true one.
VI. RESULTS The data set used in this analysis comprises events recorded between 1 January 2004 and 31 December 2012. We compute the MPD distributions on an eventby-event basis. To guarantee an accurate reconstruction of the longitudinal profile, we impose the selection criteria described in Sec. V B. For the angular range and energy threshold set in this analysis, our initial sample contains 500 events. After our quality cuts, it is reduced to 481 events. The evolution of the measured X µ max as a function of the energy is shown in Figure  8. The data are grouped in five energy bins of width 0. 1 in log 10 (E/eV), except for the last bin, which contains all events with energy above log 10 (E/eV) = 19. 7 (E = 50 EeV). The sizes of error bars represent the standard deviation of the mean.
VII. DISCUSSION Under the assumption that air-shower simulations are a fair representation of reality, we can compare them to data in order to infer the mass composition of UHECRs. For interaction models (like those used for Figure  8 ) that assume that no new physics effects appear in hadronic interactions at the energy scales probed by Auger, the evolution of the mean   [38]  to ln A , as a function of energy. On the left (right) plot we use QGSJetII-04 (Epos-LHC) as the reference hadronic model. See text for a detailed discussion of the difference between models. Brackets correspond to the systematic uncertainties. X µ max values indicates a change in composition as the energy increases. Data show a flatter trend than pure proton or pure iron predictions (35. 9 ± 1. 2 and 48. 0 ± 1. 2 g/cm 2 /decade, respectively 5 ).
We measure a value of d X µ max /d log 10 E = -25 ± 22 (stat. ) ± 21 (syst. ) g/cm 2 /decade. This value deviates from a pure proton (iron) composition by 1. 8 (2. 3) σ. In Figure  8  we observe how QGSJetII-04 and Epos-LHC estimate, for both protons and iron, a similar muonic elongation rate (evolution of X µ max with energy) but with considerable differences in the absolute value of X µ max. While the Auger data are bracketed by QGSJetII-04, they fall below the Epos-LHC estimation for iron. Therefore, the study of the MPD profile can also be used as a tool to constrain hadronic interaction models. X max and X µ max are strongly correlated, mainly by the depth of first interaction  [29, 36]. According to simulations the correlation factor between these two observables is ≥ 0. 8. Therefore, similarly to X max , X µ max is correlated with the mass of the incident cosmic ray particle.
Acknowledgments The successful installation, commissioning, and operation of the  Pierre Auger Observatory  would not have been possible without the strong commitment and effort from the technical and administrative staff in Malarg üe. We are very grateful to the following agencies and organizations for financial support:  Comisi ón Nacional de Energía At ómica, Fundaci ón Antorchas, Gobierno De La Provincia de Mendoza, Municipalidad de Malarg üe, NDM Holdings  and  Valle Las Le  ñas, in gratitude for their continuing cooperation over land access, Argentina; the  Australian Research Council ;  Conselho Nacional de Desenvolvimento Científico e Tecnol ógico (CNPq) ,  Financiadora de Estudos e Projetos (FINEP) ,  Fundacão de Amparo à Pesquisa do Estado de Rio de Janeiro (FAPERJ) ,  São Paulo Research Foundation (FAPESP)  Grants #  2010/07359-6 , #  1999/05404-3 ,  Ministério de Ciência e Tecnologia (MCT) ,  Brazil ;  MSMT-CR LG13007 ,  7AMB14AR005 ,  CZ.
1. 05/2. 1. 00/03. 0058and the  Czech Science Foundation  grant  14-17501S ,  Czech Republic ;  Centre de Calcul IN2P3/CNRS ,  Centre National de la Recherche Scientifique (CNRS) ,  Conseil Régional Ile-de-France ,  Département Physique Nucléaire et Corpusculaire  ( PNC-IN2P3/CNRS ),  Département Sciences de l'Univers (SDU-INSU/CNRS) ,  Institut Lagrange de Paris ,  ILP LABEX ANR-10-LABX-63 , within the  Investissements d'Avenir Programme   ANR-11-IDEX-0004-02 ,  French National Research Agency  under grant no. ANR-2010-COSI-002 , France;  Bundesministerium f ür Bildung und Forschung (BMBF) ,  Deutsche Forschungsgemeinschaft (DFG) ,  Finanzministerium Baden-W ürttemberg, Helmholtz-Gemeinschaft Deutscher Forschungszentren (HGF) ,  Ministerium f ür Wissenschaft und Forschung ,  Nordrhein Westfalen, Ministerium f ür Wissenschaft, Forschung und Kunst, Baden-W ürttemberg, Germany ;  Istituto Nazionale di Fisica Nucleare (INFN), Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR) ,  Gran Sasso Center for Astroparticle Physics (CFA) ,  CETEMPS Center of Excellence, Italy ;  Consejo Nacional de Ciencia y Tecnología (CONACYT) ,  Mexico ;  Ministerie van Onderwijs, Cultuur en Wetenschap ,  Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) ,  Stichting voor Fundamenteel Onderzoek der Materie (FOM) ,  Netherlands ;  National Centre for Research and Development , Grant Nos.
It should be mentioned here that when a trigger is issued on a PDM, the data of the neighboring PDMs are also retrieved. Another important consideration is that more inclined EASs give brighter signals at EAS maximum and total integrated light. This can be used to extend the energy range of measurement to lower energies by simple geometrical cuts. Moreover, inclined showers allow almost fully calorimetric measurement of the EAS because the entire profile is visible. This is generally not the case of groundbased detectors, which typically select events up to 60 • in zenith angles, and for which the EAS is truncated at ground in many cases.
Acknowledgments This work was partially supported by  Basic Science Interdisciplinary Research Projects of RIKEN  and  JSPS KAKENHI  Grant ( 22340063 ,  23340081 , and  24244042 ), by the  Italian Ministry of Foreign Affairs, General Direction for the Cultural Promotion and Cooperation , by the  Deutsches Zentrum fuer Luft-und Raumfahrt , by the  'Helmholtz Alliance for Astroparticle Physics HAP ' funded by the  Initiative and Networking Fund of the Helmholtz Association (Germany) , and by  Slovak Academy of Sciences  MVTS JEM-EUSO as well as  VEGA  grant agency project  2/0076/13.
The complex consists of an on-axis detector (INGRID) and a suite of off-axis detectors (ND280) that reside within a 0. 2 T magnet  [2]. The Super-Kamiokande (SK) 50 kt water Cherenkov detector, situated 295 km away, is used to detect the oscillated neutrinos. The results presented here are based on data taken from January 2010 to May 2013. During this period the proton beam power has steadily increased and reached 220 kW continuous operation with a world record of 1. 2 × 10 14 protons per pulse. The total neutrino beam exposure at SK corresponds to 6. 57 × 10 20 POT. Neutrino Beam Flux-The neutrino beam flux  [13]  is predicted by modeling interactions of the primary beam protons in a graphite target using external hadron production data from the CERN NA61/SHINE experiment  [14, 15]  and the FLUKA2008 package  [16, 17].
Parameters in the first category comprise the axial masses for CCQE (M QE A ) and single resonant pion production (M RES A ), and normalizations for CCQE, CC single pion, and neutral current (NC) 1π 0 interactions. Parameters in the second category are typically related to the interaction target-primarily carbon at ND280 and oxygen at SK-and include Fermi momentum, binding energy, and spectral function modeling for the CCQE nuclear model. Also in this category are normalizations for other CC and NC cross sections, the ν e /ν µ CC cross section ratio, pion production parameters, and final state interactions of pions exiting the nucleus. External data sets, primarily from  [22] [23] [24] , are used to determine the initial values and prior uncertainties of the parameters  [4]. ND280 Measurements, Flux and Common Cross Section fits-The energy spectrum of the neutrino beam and the neutrino cross section parameters are constrained using ν µ CC interactions in ND280.
A χ 2 goodness-of-fit test returns a p-value of 0. 66, indicating no disagreement between the data and the prediction using best-fit parameters. Figure  1  shows the muon momentum distribution of the CC-0π sample, and the improvement in data and MC agreement when using the best-fit parameters. The fit to the ND280 data gives estimates for 22 beam flux parameters at SK, the 5 common cross section parameters, and their covariance. Using the ND280 information reduces the uncertainty on the expected number of electron-like events at SK due to the propagated parameters from 25. 9% to 2. 9%. SK Measurements-The SK detector is composed of an inner detector (ID) and an outer detector (OD). The ID has a water fiducial volume (FV) of 22. 5 kt that is equipped with 11129 photomultiplier tubes (PMT) and is surrounded by the 2 m wide OD.
3σ over the hypothesis of sin 2 2θ 13 = 0. When combining the T2K result with the world average value of θ 13 from reactor experiments, some values of δ CP are disfavored at the 90% CL. T2K will continue to take data to measure the neutrino oscillation parameters more precisely and to further explore CP violation in the lepton sector. We thank the J-PARC staff for superb accelerator performance and the CERN NA61 collaboration for providing valuable particle production data. We acknowledge the support of MEXT, Japan; NSERC, NRC and CFI, Canada; CEA and CNRS/IN2P3, France; DFG, Germany; INFN, Italy; Ministry of Science and Higher Edu- 32. The solid (dotted) line with markers corresponds to the 90% CL limits for normal (inverted) hierarchy, evaluated by using the Feldman-Cousins method. The δCP regions with values above the lines are excluded at 90% CL.
cation, Poland; RAS, RFBR and MES, Russia; MICINN and CPAN, Spain; SNSF and SER, Switzerland; STFC, U. K. ; and DOE, U. S. A. We also thank CERN for the UA1/NOMAD magnet, DESY for the HERA-B magnet mover system, NII for SINET4, the WestGrid and SciNet consortia in Compute Canada, and GridPP, UK. In addition participation of individual researchers and institutions has been further supported by funds from: ERC (FP7), EU; JSPS, Japan; Royal Society, UK; DOE Early Career program, U. S. A.
D. Parameter Evaluation The Fe-rich intermetallic particles are considered as an initial porosity. To estimate the volume fraction occupied by these particles, we applied a thresholding method to ten SEM images, obtained in the same conditions. To avoid subjectivity in the choice of the threshold, an automatic method based on entropy maximization was chosen (from the ImageJ image analysis software). With this method, a value of 0. 7 pct of surface fraction was found. It is assumed that the volume fraction is equivalent to the surface fraction. The coalescence parameters were then adjusted through a parametric study of their influence on the 7-mm-width flat sample. According to the literature,  [12, 13]  the calibration of the void growth model [3]  accounts for the limits for f c in the range 1 to 15 pct and f u in the range 15 to 25 pct.
The absence of functional Rag1 protein precludes IgL chain gene rearrangement and cells are completely arrested at the small pre-B cell stage (Figure  1A ). We performed genome-wide expression profiling of FACSpurified B220 + CD19 + pre-B cell fractions from wild-type (WT), Btk, and Slp65 single-and double-deficient VH81x transgenic Rag1 2/2 mice (Figure  1A ). In these experiments non-VH81x transgenic Rag1 2/2 pro-B cells served as controls. One-way ANOVA analysis using MeV software (p,0. 01) [45]  revealed that 266 genes were differentially expressed between the five groups of pro-B/pre-B cells (Figure  1B ). When compared with WT VH81x transgenic Rag1 2/2 pre-B cells, 174 genes were up-regulated, whereby the average values of the fold increase were ,1. 70, ,3. 28, ,3. 36, and ,3. 47 for Btk 2/2 , Slp65 2/2 , Btk 2/2 Slp65 2/2 VH81x transgenic Rag1 2/2 pre-B cells and non-VH81x transgenic Rag1 2/2 pro-B cells, respectively (see Table  S1 ).
Pre-BCR Signaling Enhances Interactions of 39Ek and Sis, But Not iEk, with V k + Fragments The differential effects of pre-BCR signaling on long-range chromatin interactions of the iEk, 39Ek, and Sis elements clearly emerged in a quantitative analysis of the 3C-seq datasets (Figure  4A ; see Materials and Methods for a detailed description of the quantification methods used). When pre-BCR signaling was absent (Rag1 2/2 pro-B cells) or very low (Btk 2/2 Slp65 2/2 pre-B cells), the average interaction frequencies were similar within the ,3. 2 Mb V k region and the ,3. 2 Mb downstream flanking region, for all three regulatory elements. Interaction frequencies with the upstream flanking region were lower, consistent with the larger chromosomal distance to the three viewpoints. The presence of increasing levels of Btk/Slp65-mediated pre-BCR signaling was associated with reduced interaction of iEk and 39Ek with the Igk flanking regions and with increased interaction of the Sis element and (to a lesser extent) 39Ek with the V k region (Figure  4A ).
3C-Seq analyses in wild-type and Btk/Slp65 single-and double-deficient pre-B cells demonstrated that pre-BCR signaling significantly affects Igk locus topology. First, pre-BCR signaling Quantitative analysis of 3C-Seq datasets using the three indicated k regulatory elements as viewpoints. (A) Average long-range chromatin interaction frequencies (from two replicate 3C-seq experiments) with upstream (,2. 0 Mb), V k (,3. 2 Mb), and downstream (,3. 2 Mb) regions, as defined in Figure  3A , for the five B-cell precursor fractions representing a pre-BCR signaling gradient. Average interaction frequencies per region were calculated as the average number of 3C-Seq reads per restriction fragment within that region. See Materials and Methods section for more details. (B) Average interaction frequencies within the V k region were determined for fragments that do not (2) contain a functional V k gene and for those that do contain a functional V k gene (+).
Quantitative RT-PCR and DNA Microarray Analysis Extraction of total RNA, reverse-transcription procedures, design of primers, and cDNA amplification have been described previously  [21]. Gene expression was analyzed using an ABI Prism 7300 Sequence Detector and ABI Prism Sequence Detection Software version 1. 4 (Applied Biosystems). All PCR primers used for quantitative RT-PCR of TFs or k 0 , l 0 , and V k GLT are described in  [21] , except for Obf1 (forward 59-CCTGGCCACC-TACAGCAC-39, reverse 59-GTGGAAGCAGAAA CCTCCAT-39, obtained from the Roche Universal Probe Library). Biotin-labeled cRNA was hybridized to the Mouse Gene 1. 0 ST Array according to the manufacturer's instructions (Affymetrix); data were analyzed with BRB-ArrayTools (version 3. 7. 0, National Cancer Institute) using Affymetrix CEL files obtained from GCOS (Affymetrix).
The RMA approach was used for normalization. The TIGR MultiExperiment Viewer software package (MeV version 4. 8. 1) was used to perform data analysis and visualize results  [45]. One-way ANOVA analysis of the five experimental groups of B Figure  7. Proximity of V k genes to E2a binding sites correlates with frequencies of long-range interactions. (A) Schematic representation of the Igk locus, showing the location of all functional V k (grey, top), J k and C k gene segments, and the k regulatory elements Sis, iEk, and 39Ek. MAR, matrix attachment region. V k genes within close proximity (as defined by colocalization on the same 3C-Seq restriction fragment) to the indicated TFs or H3K4 hypermethylation (as detected by previous ChIP-seq studies; see Materials and Methods for references) are shown.
In total, between 1 and 8 million cells were used for 3C-seq analysis. Primers for the Sis, iEk, and 39Ek viewpointspecific inverse PCR were described previously  [21]. 3C-seq libraries were sequenced on an Illumina Hi-Seq 2000 platform. 3C-Seq data processing was performed as described elsewhere  [41, 77]. Two replicate experiments were sequenced for each genotype and viewpoint, and normalized interaction frequencies per BglII restriction fragment were averaged between the two experiments. For quantitative analysis, the Igk locus and surrounding sequences were divided into three parts (mm9 genome build): a ,2 Mb upstream region (chr6:65,441,978-67,443,029; 759 fragments), a ,3. 2 Mb V k region (chr6:67,443,034-70,801,754; 1,290 fragments) and a downstream ,3. 2 Mb region (chr6:70,801,759-73,993,074; 1,143 fragments).
For each cell type (as described above) sequence read counts within individual BglII restriction fragments were normalized for differences in library size (expressed as ''reads per million''; see  [74] ) and averaged between the two replicates before further use in the various calculations. Very small BglII fragments (,100 bp) were excluded from the analysis. Fragments in the immediate vicinity of the regulatory elements (chr6:70,659,392-70,693,183; 10 fragments) were also excluded because of high levels of noise around the viewpoint, a characteristic of all 3C-based experiments. V k gene coordinates (both functional genes and pseudogenes) were obtained from IMGT  [11]  and NCBI (Gene ID: 243469) databases. V k gene usage data (C57BL/6 strain, bone marrow) were obtained from  [54]. ChIP-seq datasets were obtained from  [21]  (Ctcf),  [55]  (Ikaros), and  [56]  (E2a, H3K4Me2, and H3K4Me3).
15 mm. The datasets were deconvolved and analyzed with Huygens Professional software (Scientific Volume Imaging, Hilversum, the Netherlands). The 3D coordinates of the center of mass of each probe were transferred to Microsoft Excel, and the distances separating each probe were calculated using the equation: !(Xa2 Xb)2+(Ya2Yb)2+(Za2Zb)2, where X, Y, and Z are the coordinates of object a or b.
Accession Numbers 3C-seq and microarray expression datasets have been submitted to the Sequence Read Archive (SRA, accession number SRP032509) and Gene Expression Omnibus (GEO, accession number GSE53896), respectively. of long-range interactions revealed by 3C-Seq experiments performed on the indicated cell fractions, representing a gradient of pre-BCR signaling. Shown are the relative interaction frequencies (average of two replicate experiments) for the Sis viewpoint per 100 kb region across the Igk locus, plotted as line graphs. The bottom graph shows an overlay of the WT and Btk 2/2 Slp65 2/2 pre-B cell interaction frequencies. The ,8. 4 Mb region containing the Igk locus (yellow shading) and flanking regions (cyan shading) is depicted. Pre-B cell fractions were FACSpurified from the indicated mice on a VH81x transgenic Rag1 2/2 background (see Figure  1   Figure  S7  Pre-BCR signaling is associated with an increase in the ratio of interactions inside the Igk locus over interactions outside the Igk locus.
The differential effects of pre-BCR signaling on long-range chromatin interactions of the iEk, 39Ek, and Sis elements, as measured in 3C-seq datasets, were quantified (see Figure  4A ). For all three regulatory elements, the y-axis shows the ratio of the average interaction frequencies per BglII fragment inside the ,3. 2 Mb Igk locus over the average interaction frequencies per BglII fragment in the flanking regions (,2. 0 Mb upstream together with 3. 2 Mb downstream). Analyses of the five groups of B cell precursors, representing a gradient of pre-BCR signaling, are shown, revealing that pre-BCR signaling is associated with a preference for interaction with fragments inside the V k region over fragments outside the V k region. (TIF) Figure  S8  Interaction frequencies of k regulatory elements with nonfunctional V k genes as measured in B cell fractions representing a pre-BCR signaling gradient.
Quantitative analysis of 3C-Seq datasets obtained for the five B cell precursor fractions representing a pre-BCR signaling gradient, using the three indicated k regulatory elements as viewpoints. Average interaction frequencies within the V k region were determined for fragments that do not contain any V k gene (''no V k ''), those that contain a nonfunctional V k gene (''pseudo V k ''), and those that contain a functional V k gene (''functional V k ''). See Materials and Methods section for more details on analysis methods. Statistical significance was determined using a Mann-Whitney U test (n. s. , not significant, p$0. 05).
Acknowledgments We thank  H. Jumaa  ( Ulm, Germany ),  J. Kearney  ( Birmingham, AL ), and  C. Murre  ( San Diego, CA ) for kindly providing Slp65 2/2 , VH81x transgenic, and  E2a 2/2  mice, respectively. We thank  D. Nemazee  ( La Jolla ,  CA ) for providing detailed V k usage data. We also thank  Z. O ¨zgu ¨r ,  C. E. M. Kockx ,  Rutger Brouwer , and  Mirjam van den Hout (Biomics, Erasmus MC) ,  M. Pescatori  ( Bioinformatics, Erasmus MC ), and P. F. van Loo,  I. Bergen , and  V. Ta  ( Pulmonary Medicine, Erasmus MC)  for their contributions.
This work was partly supported by Fundaca ˜o para a Ciencia e a Tecnologia (to CRA), the  International Association for Cancer Research  ( AICR 10-0562 , to RWH),  EpiGenSys/ERASysBio +/FP7  (NL: NWO, UK:  BSRC, D: BMBF , to PK), the  Center of Biomedical Genetics  and the  EU   6th Framework Programme EuTRACC Consortium  (Project LSHG-CT-2007-037455; FG, ES, and RS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.