dataesr/scientific-paragraphs-categorization huggingface dataset:
Archaeological samples The various tarry lumps and fragments from the Sutton Hoo burial that were re-examined in this study are listed in Table  1. The primary focus of the work was the fragments that had been previously identified as tar (BM Reg nos. one metre diameter, with 76 LED lights (Bridgelux BXRA-56C1000-A-00 LEDs, with a colour temperature of 5600K) arranged inside four quadrants. Each LED is illuminated in turn, with a separate image of the object recorded each time. Images were recorded using a Nikon 800D camera positioned at the apex of the dome, giving a maximum field of view of 20 by 30 cm. The images were recorded using a procedure developed by Klaus Wagensonner  [22]. The 76 images were compiled into the polynomial texture map (ptm) file using RTI Builder software, which was developed by Universidade do Minho and Cultural Heritage Imaging.
5 min. Acquisition was performed in selected ion monitoring (SIM) mode after a solvent delay of 6 min. The following m/z ions were selected to target terpanes and steranes characteristic of bitumen  [23] : 83. 10, 85. 10, 113. 10, 125. 10, 133. 10, 134. 10, 142. 10 177. 20, 178. 10, 183. 20, 191. 20, 192. 20, 205. 20, 217. 20, 218. 20, 221. 20, 231. 20 and 259. 20. G1701EA Chemstation (G1701EA) software was used for system control and data collection/manipulation. Mass spectral data were interpreted manually with the aid of retention time data from previously analysed bitumen specimens, the NIST/EPA/NIH Mass Spectral Library version 2. 0 and comparison with published data  [24]. Isotopy. EA-IRMS analyses were performed using a Europa Scientific elemental analyser with 20-20 Europa Scientific IRMS.
The Middle Eastern comparators are all known or reputed to be in active exploitation in the 1 st millennium AD and earlier (Table  2 )  [37]. The Sutton Hoo extracts appear richer in polar compounds and poorer in saturates relative to the native Pitchford bitumen, although this alone would not rule out a correlation. However, it is notable that its gross composition is very similar to published data from Middle Eastern bitumen of the geochemically well-described Dead Sea family  [37] [38] [39] [40]. More compelling evidence for a Middle Eastern origin comes from the asphaltene carbon stable isotope composition (δ 13 C) and petroleum biomarker parameters. These are considered reliable indicators for the origin of archaeological bitumen providing they have not been severely affected by weathering, which can modify gross and molecular compositions  [30, 41].
Acknowledgments We would like to thank  Antony Simpson  for formatting the figures for publication. We are indebted to  Dr Sonja Marzinzik  and  Dr Sue Brunning , former and current curators of the  Department of Britain, Europe  and  Prehistory at the British Museum , for facilitating access to the Sutton Hoo finds. Carbon and hydrogen isotopic measurements were carried out by  Iso-Analytical Limited. We are grateful to colleagues and others who read and commented on the manuscript in draft.
This research was supported by funding from the  European Commission Research Executive Agency (REA)  via the  Marie Curie Actions -Intra-European Fellowships for Career Development funding  scheme ( FP7-MC-IEF ), Grant Agreement No. 253942 , awarded to PB and RJS for project AMPT ( Ancient Maritime Pitch  and Tar: a multi- disciplinary study of sources , technology and preservation). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Whole blood assay Fresh heparinized blood from either SB or MV rabbits (12 mL/kg, ZEEP over a 48 hour-period) (n = 7 and 5, respectively), was obtained by venipuncture and diluted 1:2 with RPMI 1640. Blood was immediately plated at 120 μL/well in a 96-well plate and incubated for 15 minutes at 37°C. In some experiments, either mAb T2. 5 or IgG1κ were diluted with RPMI 1640 (10 μg/mL in 60 μL final volume) and added to rabbit whole blood at room temperature  [9]. One hour later 60 μL of Pam 3 CSK 4 (100 ng/mL) or heat-killed S. aureus (USA300 strain; 9 log CFU warmed at 90°C for 60') were added and the blood was then incubated for 24 hours at 37°C. This concentration corresponded to the maximal response observed with the TLR2 agonist in preliminary experiments (data not shown). Cell culture supernatants were finally removed and kept frozen at -80°C until IL-8 and TNF-α concentrations were determined.
For temporally repeated data (i. e. for serum cytokine concentrations), changes over time were assessed in each group using one-way repeated-measures analysis of variance for normally distributed data. Differences between the times were identified using the Bonferroni multiple comparison test after repeated-measures analysis of variance when significance was reached. All test were two-tailed. A p value lower than 0. 05 was considered as statistically significant. GraphPad Prism software was used (GraphPad Software, San Diego California, USA).
However, the WW channel benefits from a significantly larger branching fraction and a lower threshold for off-shell H → WW production  [18]. To maximize sensitivity, the results of this analysis are combined with those obtained in the H → ZZ channel  [21, 22]. The WW and ZZ analyses are based on proton-proton (pp) collision data collected by the CMS experiment at the LHC in 2011 and 2012, corresponding to integrated luminosities of 4. 9 fb -1 and 19. 4 fb -1 at the center-of-mass energies 7 and 8 TeV, respectively  [25, 26]. The paper is organized as follows: after a brief description of the CMS detector in Section 2, event datasets and Monte Carlo (MC) simulation samples are presented in Section 3. The object reconstruction and event selection are described in Sections 4 and 5, respectively.
Event datasets and Monte Carlo simulation samples The explicit final state used is the different-flavor dilepton final state W + W -→ e ± νµ ∓ ν. The same-flavor dilepton final states W + W -→ e + νe -ν/µ + νµ -ν are not considered, as they are overwhelmed by background from the Drell-Yan Z/γ * → + -production. The events are triggered by requiring the presence of either one or two high-p T electrons or muons with tight lepton identification and isolation criteria and with |η| < 2. 4 (2. 5) for muon (electron)  [28, 29]. Triggers with a single lepton have electron (muon) p T thresholds ranging from 17 to 27  (24)  GeV. The higher thresholds are used for data taking periods with higher instantaneous luminosity. For the dilepton triggers, one lepton with p T > 17 GeV and another with p T > 8 GeV are required.
The average combined trigger efficiency for events that pass the full event selection is 96% as measured in independent datasets obtained using different triggers. This analysis uses the dominant SM Higgs boson production modes of GF and vector boson fusion (VBF). Other processes are not expected to contribute significantly to off-shell production  [21]. The analysis accounts for possible interference between the Higgs boson signal and background processes when both have identical initial and final states. Relevant leading order (LO) Feynman diagrams for GF and VBF processes for signal and background, which interfere with the signal, are depicted in Figs. 1  and 2 , respectively. Following the previous study in the ZZ channels  [21] , a Higgs boson mass of m H = 125. 6 GeV  [8] , with width Γ H = 4.
The application of the factor to the background and interference samples has a negligible effect on the results. The detector response is simulated using a detailed description of the CMS detector based on the GEANT4 package  [49]. Minimum bias events are merged into the simulated events to reproduce the additional pp interactions in each bunch crossing (pileup). The simulated samples are reweighted to represent the pileup distribution as measured in the data. The average numbers of pileup interactions per beam crossing in the 7 TeV and 8 TeV data are about 9 and 21, respectively.
The transverse mass is defined as m H T = √ 2p T E miss T (1 -cos ∆φ( p T , p miss T )) , where p T is the dilepton transverse momentum vector, p T is its magnitude, and ∆φ( p T , p miss T ) is the azimuthal angle between the dilepton momentum and p miss T. The m H T and the m are used to discriminate the Higgs boson signal from the dominant WW and top quark pair, W + jets, and W + γ ( * ) backgrounds. In order to enhance the sensitivity, a boosted decision tree  [62]  multivariate discriminator (MVA) is implemented with the toolkit for multivariate analysis (TMVA) package  [63]  and is trained to discriminate between the off-shell Higgs boson signal and the other SM backgrounds. Seven variables, m H T , m , the opening angle ∆φ between the two leptons, p T , E miss T in an event, p T 1 , and p T 2 , are used for the boosted decision tree training and enter into the MVA discriminant.
Systematic uncertainties The systematic uncertainties for this analysis, presented in Table  2 , are classified into three categories as described in detail in Ref. [37]  and include uncertainties in the background yield predictions derived from data, experimental uncertainties affecting normalisation and shapes of signal and backgrounds distributions obtained from simulation, and theoretical uncertainties affecting signal and background yields estimated using simulation. The dominant background for the 0-jet category is continuum qq → WW production. The normalization of the qq → WW background for the 0 (1)-jet categories is determined from the 2D binned template fit to the data with 8 (18)% uncertainty dominated by the statistical uncertainty in the number of observed events. The template 2D distribution obtained from the default generator is replaced by another one from POWHEG to estimate the shape uncertainty in the fit.
Constraints on Higgs width with WW and ZZ decay modes To exploit the full power of the Higgs boson width measurement technique based on the offshell Higgs boson production approach, the results using H → WW reported here are combined with those found using H → ZZ  [21, 22]. The H → ZZ results are obtained using datasets corresponding to an integrated luminosity of 5. 1 (19. 7) fb -1 at 7 (8) TeV. The statistical methodology used in this combination is the same as the one employed in Ref. [21]. The likelihood of the off-shell signal strength is scanned with the assumption of SU(2) custodial symmetry for the combination: µ ZZ GF /µ WW GF = µ ZZ VBF /µ WW VBF = Λ WZ = 1. The observed (expected) constraints on the off-shell signal strengths at 95% CL are µ off-shell GF < 2. 4 (6. 2) and µ off-shell VBF < 19.
e. sociocultural influences) that could affect contraceptive choice were studied. Participants were asked to rate each factor as important or not important in their choice of contraception. All statistical analyses were performed using IBM SPSS Statistics for Windows version 21. 0 (IBM Corp, Armonk, NY, USA). Univariate descriptive statistics were used for all study variables. Fisher's exact test was used to identify the predictors of good knowledge of each method of contraception. A p-value < 0. 05 was considered statistically significant.
Analysis of rearing behavior Thirty-one adult mice (cKO, n ϭ 14; control, n ϭ 17) were each placed in the center of a square Plexiglas arena (55 by 55 by 22 cm) and allowed to freely explore for 15 min. The mice were videorecorded, behavioral parameters were scored manually by an observer blinded to the genotype of the mouse, and the duration of each rearing type was analyzed using AniTracker software. Rearing behavior was subdivided into three types: wall rearing, an upright position with the fore-paws touching a vertical surface (Fig. 4A , left); seated rearing, a half-standing position using the tail for support (Fig. 4B , left); and free rearing, in which the mouse supports its weight freely on its hind legs without using its tail or forepaws (Fig. 4C , left), as previously described by  Waddington et al.
Total ion current normalization was performed on each spectrum, and data quality was assessed as previously described  (Karlsson et al. , 2014). A total of 5400 peaks with a signal-to-noise ratio Ͼ3 were selected, and peak borders were defined by binning analysis using mass spectrometry peak binning software pbin. The peak area was calculated for each peak using an R script developed in-house. Data are expressed as average peak area for 40 -50 mass spectra collected from the nucleus accumbens (NAc) of each mouse (761 spectra in total collected from NAc of six cKO and three control mice). To specify the anatomic localization of peptides, photomicrographs of matrix deposits were coregistered with histologic staining of the same sections. After mass spectrometry acquisition, the matrix was removed with 95% ethanol and the mouse brain sections were stained with toluidine blue (Göteborgs Termometerfabrik, Göteborg, Sweden).
treatment. DIG epitopes were detected with alkaline phosphatase coupled anti-DIG fab fragments at 1:1000 and revealed with TSA ™ Kit (Perkin Elmer) using Cy3 tyramide at 1:200. Nuclear staining was performed with DAPI. All slides were scanned on a 40ϫ resolution NanoZoomer 2. 0-HT (Hamamatsu, Japan). Cell size measurement, silver grain (mRNA expression), and cell counting were performed using ndp. view software (Hamamatsu). Histograms and scatter plots were produced with MATLAB plotting tools (Mathworks, Natick, MA).
Histologic analysis of STN structure Three-dimensional reconstruction was obtained with MATLAB 3D plotting tools. Sixteen sections for knockout mice and 27 for wild-type mice were used to draw contours of the STN. These images were adjusted so that adjacent sections best fitted the real spatial position. We applied 3D cubic spline interpolation for missing sections and standard box smoothing. Different transparency, light shedding, and shading options enabled visualization of the 3D shape of the STN.
Quality of data acquisition In this study, the quality of arrays was found to be good since the expression levels of the control spots present on each slide were similar to those expected and the background noise was relatively low. Furthermore, the arrays were not spotted with single probes and 11,409 of them were repeated at least once  (18 %). Most repeated probes corresponding to the same differentially expressed gene with the same annotation (Ensembl, GenBank, etc) were consistently regulated between treatments.
Synthetic RNA (Two-Color RNA Spike-In Kit, Agilent Technologies) was added as an internal quality control. The cRNA obtained was purified using RNeasy Mini Spin columns (Qiagen) and subsequently run on a Bioanalyzer 2100 using RNA 6000 Nano chips (Agilent Technologies) to assess the profiles. Three hundred ng of Cy3-labeled cRNA (specific activity > 9) and 300 ng of Cy5-labeled cRNA (specific activity > 9) were combined for each single array, and the washing steps were then performed according to the manufacturer's recommendations. The slides were finally scanned using a G2565CA Scanner System (Agilent Technologies), The resulting. tiff images were analysed with Feature Extraction Software (Agilent Technologies) using the GE2_107_Sep09 protocol to obtain background-subtracted and spatially-detrended processed signal intensities.
Data analysis Genes differentially expressed (DE) between TM and C, TM and TMHC, C and CHC and TMHC and CHC were identified using a moderated t-test where variance was modelized using the shrinkage method in the Limma package under the R statistical environment (http://cran. rproject. org/) from Bioconductor project (http://www. bioconductor. org/). The raw p-value of each gene was adjusted according to the Benjamini-Hocheberg method to monitor the false discovery rate  [50]. Difference in gene expression was judged significant when its adjusted P-value was below 0. 05.
Real-time RT-PCR assay RNA samples were reverse-transcribed using RNase H-MMLV reverse transcriptase (Superscript II, Invitrogen, Illkirch, France) and random primers (Promega, Charbonnières les Bains, France). cDNA samples thus obtained were added to SYBR Green I qPCR Master Mix Plus (Eurogentec, Angers, France) as well as specific reverse and forward primers previously designed and validated by sequencing the end-point PCR product to quantify each target gene. Primers for DE genes originating from the microarray analyses are described in Additional file 2. The geNorm analysis was performed on the expression of a set of "standard genes" to find a reliable normalization factor in order to correct expression data of target genes relative to the initial RNA content of samples  [51]. In our study, this normalization factor was calculated from the threshold PCR cycles from the genes encoding β-actin, cytochrome B and 18S.
Functional annotation and promoter analysis The interpretation of microarray data was performed using Ingenuity Pathway Analysis 7. 0 (IPA, Ingenuity Systems Inc. , Redwood City, CA) and functional annotation was determined regarding Biological Processes (GO) from the ontology 'biological process' from the Gene Ontology Consortium (GO, http://www. geneontology. org/) using Genomatix software. The P-values reported were the probabilities (using Fisher's Exact Test) of finding at least m genes in an input list of length q having annotation A, with q being the number of genes in the input set, m the number of genes from the input set having annotation A assigned, under the assumption that belonging to the input list is independent of having this annotation. The genes included in the analyses were those identified as differentially expressed within one of the four comparisons tested.
Acknowledgements This study was performed with the financial support of the  French Agence Nationale de la Recherche , « Jeunes Chercheuses et Jeunes Chercheurs» Project ,  ANR-09-JCJC-0015-01 , THERMOCHICK. The author wish to thank  T. Bordeau ,  E. Godet ,  E. Baéza ,  M. Couty ,  L. Bouyer , ( URA, INRA, 37380 Nouzilly, France ),  F. Mercerand ,  J. Delaveau ,  C. Rat ,  H. Rigoreau  and  N. Sellier  ( PEAT, INRA, 37380 Nouzilly, France ) for their contribution to this work, and  D. Raine  for English revision. T. Loyau is a PhD student supported by a grant from the  Ministère de l'Enseignement Supérieur et de la Recherche  and  ANR.
Population sample This study was conducted from February to August 2015 on a sample of 1,000 individuals aged 20 and older. The sample was constructed using the combined quota method  [39]  (cross-section by age, gender and town of residence) in order to strive for representativeness of the population aged 20 and older living in the department of Dakar. Data from the Agence Nationale de la Statistique et de la Démographie dating from the last census (2013) were used. According to the last census, the population of the department of Dakar was 1,146,053 in 2013, including 725,373 adults aged 20 and over. The quota variables used were gender (male/female), age (20-29 / 30-39 / 40-49 / 50-59 / 60 and over, with an upper age limit of 100 years, but concretely, the oldest participant was aged 90) and town of residence.
Underweight was defined as BMI <18. 5; overweight was defined as 25 BMI < 30; obesity corresponded to a BMI of ! 30  [38]. Waist circumference (WC) was measured at the thinnest point of the abdomen at the end of a normal expiration. WC was measured using a measuring tape with 1-mm accuracy. WC of ! 102 cm in men and of ! 88 cm in women was considered central obesity  [42]. Waist-to-height ratio was used as another indicator of central obesity since it was demonstrated that this variable is a better predictor of cardiovascular risk than BMI and WC in SSA  [43]. WHtR was calculated using the formulae: WHtR = WC (cm)/ height (cm); the threshold of > 0. 5 was used, as recommended for Causasian, Asian and African populations  [44] [45] [46]  Socio-demographic variables. Among the socio-demographic data collected during the interviews, three variables were taken into account for this study: age, gender, and educational level.
Analysis To answer our research questions, we used Student t-tests, Chi-square tests, and logistic regressions. Results were expressed as mean ± standard deviation for continuous variables or as percentages for categorical variables. Bivariate comparisons were performed using Student t-tests for continuous variables, and Chi-square tests for categorical variables. Multivariate analyses were performed using binary logistic regression and results were expressed as odds ratios with 95% confidence intervals (CIs). In these binary logistic regression models, dichotomous outcome variables were: HTN, awareness and treatment; as well as general and central obesity. The software used for the statistical analysis was SPSS Statistics 22 for Windows.
Analyzing BOLD fMRI Data Functional images were acquired via a Siemens 3T Skyra (located at the Texas Tech Neuroimaging Institute; TR=2000ms; TE=20; FOV=240 mm; Flip angle=80; Voxel size: 3x3x4 mm; axial slices=34). Structural 3D high resolution T1 images were acquired using same orientation as the functional sequences (0. 9X0. 9X0. 9 mm). Functional data analyses were carried out using the fMRI Expert Analysis Tool (FEAT) in FSL. Imaging preprocessing involved removing non-brain structures by Brain Extraction Tool (BET), motion correction by using MCFLIRT, temporally high-pass filtered with a cutoff period of 100s, spatial smoothing with a 5mm Gaussian FWHM algorithm and coregistration of the fMRI data to anatomic images with each subject and MNI 152 standard brain space. The Child ANT paradigm was presented using ePrime with a random ordering of trials per session.
The cycle used was 56 °C during 30 min then 94 °C during 2 min followed by 40 cycles of 94 °C (15 s), 56 °C (30 s) and 68 °C (1 min 30). To finish, a final step of elongation at 68 °C during 5 min was performed. PCR products were sequenced by Beckman's Coulter Genomics, UK. The 15 E gene sequences are deposited in Genbank database under accession numbers listed as follows: KT187281, KT187282, KT187283, KT187284, KT187285, KT187286, KT187287, KT187288, KT187289, KT187290, KT187291, KT187292, KT187293, KT187294, KT187295 (Table  1 ).
Sequence dataset Different datasets were constructed to perform phylogenetic analyses. For the determination of the DENV-3 genotype of the 15 strains, panels of 101 DENV-3 GenBank E gene sequences of 1479 bp of all genotypes were selected according to their geographic origin and date of isolation (Table  1 ). To compare the genetic relatedness of the partial virus genome, phylogenetic analyses were performed with a panel of 84 published DENV-3 genotype III sequences from 1986 up to 2014, and a DENV-3 genotype IV isolated in Puerto Rico in 1963 (AY146762) was used as an out group to root the tree. Before phylogenetic inference, datasets and multiple sequence alignments were thoroughly examined to eliminate misalignments and ensure correct framing of coding sequences leading to a 1479 bp sequence.
Phylogenetic analyses The percentage of sequence identity was calculated using Bioedit v3. 6 program. Sequencher® version 5. 3 sequence analysis software (Gene Codes Corporation, Ann Arbor, MI USA) was used to analyze nucleotidic/amino-acid sequences. Maximum like hood phylogenetic tree was generated using the method implemented in the PAUP package  [33]. Model Test  [34]  was used to determine the best model of substitution. The best fit to DENV-3 was the General Time Reversible + I + Γ model of substitution. Parcimony phylogenetic tree was also estimated using PAUP package  [33].