dataesr/scientific-paragraphs-categorization huggingface dataset:
Stereotyped eyemovement artifacts (e. g. , blinks) were kept in the data to be removed in a later step by means of independent component analysis (ICA). Data were further preprocessed using custom routines and functions from the free and open source EEGLAB toolbox (v9, http://sccn. ucsd. edu/eeglab/;  Delorme and Makeig, 2004)  written in MATLAB (Math-Works). Signals were cut into time-segments from Ϫ1000 to 2000 ms with respect to reaching-movement onset and then downsampled to 256 Hz to be submitted to a temporal ICA using the infomax algorithm  (Bell and Sejnowski, 1995). The resulting 64 independent components (ICs) corresponding to the 64 input channels were visually screened to identify (based on their topographies and time courses) the ICs corresponding to eye-blinks. New EEG signals, exempt from these stereotyped artifacts, were obtained by backprojecting the ICs into the channel space removing the identified ICs; the latter data were used to compute the ERPs.
, 1997). Our aim was to first identify for each individual the IC(s) that would account for a substantial part of the ERP-K profiles, and then to quantify the proportion of the FRN that could be accounted for by the selected ICs. This procedure was intended to investigate the similarities between the ERP-K and the FRN  (Makeig et al. , 2004; Debener et al. , 2005a,b; Onton et al. , 2006; Gentsch et al. , 2009; Roger et al. , 2010; Wessel et al. , 2012). In this purpose, we used the automated ICs selection procedure proposed by  Wessel and Ullsperger (2011)  and implemented as the free and open source MATLAB toolbox COMPASS (http://jrw. lima-city. de/e_compass. htm). Before being submitted to the COMPASS algorithm, ICs (that were obtained from the EEG-preprocessing step) were screened as recommended by  Wessel et al.
We used head meshes describing the boundaries of different head compartments (scalp, inner skull, and cortical sheet) based on the MNI template provided with SPM8  (Mattout et al. , 2007). The EEG data and the MNI templates were coregistered using the nasion and preauricular fiducials, as well as the recorded electrode locations. Group inverse solutions were obtained using the empirical Bayesian approach implemented in SPM8  (Mattout et al. , 2006) , using the multiple sparse prior model  (Friston et al. , 2008). For the ERP-Ks, inversion for all three difference curves (corresponding to the different types of trials) was performed together; only the results for the Large_PD Ϫ No_PD curve will be presented here. Following inversion, for each individual and each ERP type a 150-mswide time window (centered in the inversion window) was extracted.
Assuming a given cosmological scenario and standard BBN dynamics, it is now possible to infer indirectly from Planck data the abundance of primordial nuclides with exquisite precision. For example, assuming ΛCDM, the Planck constraint on the baryon density, Ω b h 2 = 0. 02207 ± 0. 00027, can be translated into a prediction for the primordial deuterium fraction using the public BBN code PArthENoPE  [3] [33] 2 H/H = (2. 65 ± 0. 07) • 10 -5 (68% C. L. ) , This constraint is competitive with the most recent and precise direct observations. Recently, the authors of Ref. [4]  (see also  [5] ) presented a new analysis of all known deuterium absorption-line systems, including some new data from very metal-poor Lyman-alpha systems at redshift z = 3. 06726 (visible in the spectrum of the quasar QSO SDSS J1358+6522) and at redshift z = 3.
4% level with the best-fit result of  [6] ). Further data on this crucial cross section in the relevant energy range might be expected from experiments such as LUNA. While waiting for such measurements one can find out to which extent the deuterium measurement of  [4]  can be made even more compatible with Planck predictions when the rate of the reaction d(p, γ) 3 He is treated as a free input parameter. We will address this issue assuming different cosmological models: the minimal ΛCDM model, ΛCDM plus extra radiation, a non spatially-flat universe, etc. This simple exercise points out that, remarkably, present CMB data are powerful enough to provide information on nuclear rates. Moreover, we will see that our results give independent support to the theoretical calculation of  [10]. Of course, this close interplay between astrophysical observations and nuclear physics is not new.
III. DATA ANALYSIS METHOD Our main dataset consists in the Planck public data release of March 2013  [17] , based on Planck temperature completed by WMAP9 polarization at low. We also consider the recent B modes polarization data (5 bins) from the BICEP2 experiment  [18]. We combine these two CMB datasets (referred as Planck+WP and Planck+WP+BICEP2 respectively) with the deuterium abundance likelihood function L(Ω b h 2 , A 2 ) (referred as BBN). Occasionally, we will also include the direct measurement of the Hubble constant by  [19]  (referred as HST), and information on Baryon Acoustic Oscillations by SDSS-DR7 at redshift z = 0. 35  [20] , by SDSS-DR9 at z = 0. 57  [21] , and by WiggleZ at z = 0. 44, 0. 60, 0. 73  [22]  (referred alltogether as BAO). For the data analysis method, we will use indifferently the publicly available Monte Carlo Markov Chain packages CosmoMC  [23]  (http://cosmologist.
info/cosmomc/) and Monte Python  [24]  (http: //montepyhton. net), which rely on the Metropolis-Hastings algorithm for exploring the parameter space, and on a convergence diagnostic based on the Gelman and Rubin statistics. We use the latest version of the two codes (April 201a), which include the support for the Planck Likelihood Code v1. 0 (see http://www. sciops. esa. int/wikiSI/planckpla/) and implement an efficient sampling of the parameter space using a fast/slow parameter decorrelation  [25]. We checked that the results from the two codes were identical. To evaluate the deuterium abundance produced during the Big Bang Nucleosynthesis, we use the PArthENoPE code, minimally modified in order to account for the global rescaling factor A 2. We will first consider the Planck+WP dataset assuming the minimal ΛCDM model with six free parameters: the density of baryons and cold dark matter Ω b h 2 and Ω c h 2 , the ratio θ of the sound horizon to the angular diameter distance at decoupling, the optical depth to reionization τ , the amplitude A S of the primordial scalar fluctuation spectrum at k = 0.
In this case we include the BICEP2 dataset, assuming the B mode signal claimed by this experiment to be the genuine signature of primordial inflationary tensor modes. Since the amplitude of tensor modes measured by BICEP2 is in tension with the upper limit on r coming from the Planck experiment, we also consider two further extensions that could in principle solve the tension: an extra number of relativistic particles parametrized by N eff (see e. g. [27] ) and a running of the spectral index dn S /dlnk  [18].
IV. RESULTS In Table  II , we report our results for the parameters of the minimal ΛCDM model (plus the nuclear rate parameter A 2 and the derived cosmological parameter H 0 ), using the data combinations Planck+WP+BBN and PLANCK+WP+BBN+BAO. As expected from the discussion of sections I and II, we find that the data provides an indication for A 2 being greater than one, roughly at the level of two standard deviations, even when adding the BAO dataset. We can also check explicitly in Figure  2  (top panel) that there is a clear anti-correlation between A 2 and Ω b h 2 : in order to improve the agreement between Planck data and deuterium abundance measurements, one needs either a value of the nuclear rate rescaling factor A 2 higher than one, or a value of the baryon density larger than the Planck mean value.
When the direct measurement of the Hubble parameter is included (case Planck+WP+BBN+HST), the indication for A 2 > 1 is even stronger, at the 2. 5σ level. We can conclude that the preference for a large d(p, γ) 3 He reaction rate is robust against the extension of the minimal cosmological model to a free N eff. It is interesting to note that in Table  III , the preferred value for the neutrino effective number N eff is always larger than the standard value 3. 046. As reported in section 6. 4. 4. of Ref. [2] , the "standard" Planck+WP+BBN analysis (assuming A 2 = 1) gives N eff = 3. 02 ± 0. 27 (68% C. L. ), while the CMB only result is N eff = 3. 36 ± 0. 34 (to be precise, in these results, the CMB dataset includes high-data from ACT and SPT, but the same trend is observed with only Planck+WP).
With the present analysis, it becomes clear that this shift of N eff towards its standard value is mostly driven by the low experimental value of R 2. When A 2 is let free, the preference for N eff > 3. 046 persists even when deuterium measurements are included. This can also be checked in Fig. 3 , where we report the two dimensional likelihood contours in the N ef f vs. A 2 plane for the three different datasets: Planck+WP+BBN, Planck+WP+BBN+HST, and Planck+WP+BBN+BAO. A correlation between A 2 and N eff is clearly present: large values of A 2 remain compatible with Planck+WP+BBN data, provided that at the same time N eff is larger than three. Such considerations reinforce the motivations for future experimental campaign to collect further data on the d(p, γ) 3 He cross section in the few hundred keV range.
Notice that for A 2 = 1. 055, corresponding to the theoretical result of  [10]  a standard value of N eff is allowed at 68% C. L. If experiments would confirm the theoretical result R th 2 (T ) in the BBN energy range, the overall agreement of CMB and BBN data for a standard number of relativistic degrees of freedom would improve with respect to the A 2 = 1 case. This does not hold if the HST measurement of H 0 is included in the analysis. In Table  IV  we report the constraints on A 2 for further extensions of the minimal ΛCDM model, using the Planck+WP+BBN. We tried to vary the curvature parameter Ω k , despite the fact that Ω k = 0 is difficult to explain from a theoretical point of view, and almost excluded when BAO data is also included. With free spatial curvature and without BAO data, the evidence for A 2 > 1 is slightly weaker.
Finally, we considered the case of a free CMB lensing amplitude parameter A L. Strictly speaking, this is not a physical extension of the ΛCDM model. The Planck data prefers A L > 1, but as such, this result has no physical interpretation. It could be caused by a small and not yet identified systematic error affecting the Planck data (see the discussion in  [2] ), or alternatively, it may account in some approximate way for a non-standard growth rate of large scale structures  after recombination. We can see in Table  IV  that when A L is left free, the A 2 parameter is well compatible with one. Our results for the joint confidence limits on A 2 vs. Ω k and A 2 vs. A L are shown in Fig. 4. In summary, Planck+WP+BBN data consistently indicate that A 2 > 1 (suggesting a d(p, γ) 3 He reaction rate closer to theoretical predictions than to experimental results) in the minimal ΛCDM model, as well as in a model with free N eff.
The evidence for A 2 > 1 goes away when either Ω k or A L are promoted as free parameters (with N eff = 3. 046), but these scenarios are less theoretically motivated. Incidentally, Table IV also shows that with a free Ω k or A L , and at the same time a free N eff , the evidence for A 2 > 1 persists. Finally, we have considered the Planck+WP+BICEP2+BBN dataset as stated in the previous section. In Table  V  we report the constraints using this dataset, allowing for a gravitational wave background with tensor to scalar ratio r 0. 05 at scales of k = 0. 05 Mpc -1. As we can see the indication for A 2 > 1 is still present in this case. Allowing for a variation in N eff provides even further evidence for A 2 > 1 at more than two standard deviations. It is however interesting that when a running of the primordial spectral index is considered, A 2 is now compatible with one in between one standard devation.
In 5 we show the 2-D contour plots from the Planck+WP+BICEP2+BBN dataset in the r 0. 05 vs A 2 (top panel), N eff vs A 2 (center panel) and dn s /dlnk vs A 2 (bottom panel) planes showing probabilities at 68% and 95%. As we can see, while there is essentially no degeneracy between A 2 and r 0. 05 , a degeneracy is clearly present between A 2 and N eff and dn s /dlnk. In summary, the BICEP2 dataset, when combined with the Planck data, provides an evidence either for a larger N eff , either for a negative running of the spectral index dn s /dlnk. In the first case a value of A 2 strictly larger than one is needed in order to be in agreement with BBN. In the second case, when running is considered, A 2 is well compatible with one. A precise measurement of A 2 from laboratory experiments could in principle help in a significative way in discriminating between these two scenarios.
In the latter case, the global likelihood analysis of astrophysical and cosmological data shows a direct correlation between A 2 and N eff , so that higher values for A 2 are in better agreement with non standard scenarios with extra relativistic degrees of freedom. Finally, we have shown that the inclusion of the new BICEP2 dataset also points towards a larger value for A 2 , especially when N eff is left free to vary. However, a running of the spectral index could bring the value of A 2 back in agreement with one even when the BICEP2 dataset is considered. New experimental data on the d(p, γ) 3 He reaction rate will therefore have a significant impact on the knowledge of N eff and of dn s /dlnk as well.
Constraints on cosmological parameters (at the 68% confidence level) for the Planck+WP+BICEP2 dataset, with free parameters (r0. 05,N eff , dns/dlnk). We vary at most two of these extra parameters at the same time, and fix the other ones to their standard model value, indicated above between squared brackets. FIG. 3:2-D contour plots in the N eff vs A2 plane, showing preferred parameter regions at the 68% and 95% confidence levels in the case of the extended ΛCDM model with extra relativistic degrees of freedom.
In this study, we characterized viral dissemination; changes in immune cell frequencies both in peripheral blood and lymphoid tissues; as well as changes in cytokine and liver enzyme levels in NHP infected with YFV-DakH1279. Data presented herein show that a profound loss of peripheral lymphocytes in the blood precedes characteristic liver pathology and provides an early indicator of fatal YF in this model. In addition, we examined the transcriptome in peripheral blood mononuclear cells (PBMC) collected 3 days after infection with YFV-DakH1279 compared with the attenuated vaccine strain, YFV-17D. This analysis revealed that striking changes in gene expression are evident at this early time point and provide glimpses into the molecular basis of YFV virulence.
Measuring frequency of immune cell subsets PBMC were surface stained with antibodies against CD8b (Beckman Coulter, Brea, CA), CD4 (eBioscience, San Diego, CA), CD20 (Beckman Coulter, Brea, CA), HLA-DR (eBioscience), and CD14 (Biolegend, San Diego, CA). Samples were fixed with 4% paraformaldehyde for 4 hrs before removal from the BSL-3. The samples were acquired using the LSRII instrument (Beckton Dickenson, San Jose, CA) and the data were analyzed using FlowJo software (TreeStar, Ashland, OR).
This array contains 52,024 probe sets interrogating over 47,000 M. mulatta transcripts. Arrays were scanned using the GeneChip Scanner 3000 7G and image quality was determined immediately following each scan. Image processing was performed with Affymetrix GeneChip Command Console v3. 1. 1 and probe set summarization and CHP file generation were performed using Affymetrix Expression Console v1. 1 software.
Microarray data analysis All microarray data analysis steps were performed in the statistical environment R, using Bioconductor packages (R Development Core Team, 2008). The probe set-to-gene mappings for the Rhesus chip were downloaded from the Affymetrix site. All ambiguous probe sets on this chip were treated in the gene enumeration steps of this study in the following manner: controls and probe sets matching no or several loci in the Macaca mulatta genome were ignored in the downstream analysis steps. In addition, redundant probe sets that represent the same locus several times were counted only once. The normalization of the raw data CEL files was performed with the Robust Multi-array Average (RMA) algorithm using the default settings of the corresponding R function  [24]. The quality of the Affymetrix Gene Chips was assessed with analysis routines provided by the affyPLM library  [25].
For each probe, log 2 fold change (log 2 FC) expression was calculated as the difference of log 2 expression at 3 days postinfection (dpi) relative to 0 dpi. Analysis of differentially expressed genes (DEGs) was performed with the LIMMA package using the normalized expression values  [26]. The Benjamini and Hochberg method was selected to adjust p-values for multiple testing and control false discovery rates (FDRs)  [27]. As confidence threshold for identifying DEGs we chose an adjusted p-value of , = 0. 05 and absolute log 2 FC superior to 1.
Functional enrichment and upstream regulator analysis Functional analysis of statistically significant gene expression changes was performed using Ingenuity Pathways Knowledge Base (IPA; Ingenuity Systems) and Gene Ontology (GO)  [28]. In addition, we also used previously published microarray data from resting and activated human immune cells (GSE22886; IRIS database) to define genes specific to each immune cell type as previously described  [29]. Genes specific to innate immune cells were further defined as the union of genes significantly upregulated in resting or activated dendritic cells, natural killer cells, monocytes or neutrophils. Genes specific to adaptive immune cells were defined as the union of genes significantly up-regulated in naı ¨ve or activated T or B cells. For all gene set enrichment analyses, a right-tailed Fisher's exact test was used to calculate a p-value determining the probability that each biological function assigned to that data set was due to chance alone.
Similarly, SerpinB2, believed to play a role in sculpting the adaptive immune response  [34]  is also downregulated and BTLA, a negative regulator of T and B cell responses is upregulated  [35]. Functional categories enriched only after YFV-17D infection included ubiquitination and ISGylation, cytoskeleton and cell adhesion, and epigenetic regulation (Figure  8 B-D ). Interestingly, among the 765 DEGs after YFV-DakH1279 infection, 115 had metal ion binding activity and over 80% of those genes are specifically involved in zinc ion binding (Figure  9B ). An additional 30 genes were involved in cell growth or apoptosis regulation (Figure  9C ) and 226 were related to transcription (GEO series accession number GSE51972). Finally, ingenuity pathway analysis revealed that the biological functions predicted to be the most activated after YFV-DakH1279 infection (based on gene ontology, literature and the Ingenuity knowledge database) were organismal death and cell death (z-score = 4.
Acknowledgments We would like to thank the members of the nonhuman primate animal core (especially  Al Legasse ,  Shannon Planer ,  Sierra Paxton ,  Merete Ohm  and  Miranda Fischer ) for sample collection and assistance with necropsy; as well as the Division of Comparative Medicine (DCM) at the  Oregon National Primate Research Center  for superb animal care and husbandry. We also thank  Dr. Karla Fenton  ( University of Texas, Medical Branch, Galveston National Laboratories ) for input regarding the histopathology.
Immunofluorescence and Immunohistochemistry For immunofluorescent staining, cells were fixed with 4% formaldehyde and permeabilized in 0. 1% Triton X-100, then blocked with 0. 5% goat serum and incubated with primary antibody. Dissected muscle was snap frozen in liquid nitrogen, sectioned (7 mm thick), and stained with hematoxylin and eosin stain (H&E) or immunofluorescence using standard protocols. Alexa 595-conjugated secondary antibody was used. Images were acquired with an IX51 Olympus microscope and the Cell*F software. Images were assembled using Adobe Photoshop. Western blots were run in triplicate, and bands were quantitated in one representative gel.
Subjects and methods This open-label study (NCT00508677) was conducted from March 2008 to April 2009 at Robert Debré Hospital. Written informed consent was obtained from both parents/ guardians of each child. It was reviewed and approved by the ethical Committee (Comité de Protection des Personnes, Ile-de-france II, france), and was conducted in accordance with guidelines from the Declaration of Helsinki and the International Conference on Harmonisation guidelines for good clinical practice. Prior to study initiation and during each visit, children and their parents met with the investigators and the clinical staff of the Clinical Investigation Center. The study included 1) a screening visit (visit 1), 2) a 10-day drug washout of all ADHD treatments (methylphenidate, other psychostimulants, and wake-promoting agents), 3) a baseline visit (visit 2), 4) followed by 7 days of treatment with a single daily dose of 1 mg mazindol per day for 7 days (visit 3 at day 7), 5) and 3 weeks' follow-up (visit 4 between day 7 and day 28) for a total of 40 days.
Efficacy data Data are summarized as frequencies and percentages for categorical variables. Quantitative variables are presented as mean values ± standard deviation. Statistical analyses were carried out in children with ADHD RS-IV results at day 0 and day 7. It was planned to include 24 patients in order to obtain at least 20 patients test-worthy for statistical analysis, to show a difference of 11 in ADHD RS-IV mean score after 1 week of mazindol using the nonparametric Wilcoxon paired test with type I error 5% and power 80%. All comparisons between scores (ADHD RS-IV, CGIs, CPRS-R:L) were performed using nonparametric Wilcoxon paired tests. More specifically, a comparison was performed between baseline (day 0) and end of treatment (day 7), and then between end of treatment and last visit (visit 4).
Pharmacokinetic analysis Pharmacokinetic analysis was carried out using the nonlinear mixed-effect modeling program NONMeM VI (version 2. 0; Icon Development Solutions, San Antonio, TX, USA). The Laplacian estimation method with interaction option was used to estimate pharmacokinetic parameters and their variability. The M3 method was used to handle below-thelimit-of-quantification (BLQ) concentrations. 23 everal one-or two-compartment open models with firstorder elimination were compared, each with various models to describe the absorption phase. Interindividual variability of the pharmacokinetic parameters was estimated using an exponential model. A residual variability (additive, proportional, exponential, or mixed) model was selected according to improvement of objective function value (OfV) and visual inspection of routine diagnostic plots.
The stability and performance of the final model were assessed using a nonparametric bootstrap with 1,000 times resampling and replacement. The values of estimated parameters from the bootstrap procedure were compared with those from the original data set. The entire procedure was performed using Perl-speaks-NONMeN (PsN). 27 The final model was also assessed by a visual predictive check (VPC) and normalized prediction distribution error (NPDe). 28  total of 1,000 data sets were simulated using the final population model parameters. for VPC, the plot was processed by Xpose (version 4. 3. 0). 29 for NPDe, the plots were processed by the NPDe R package (version 1. 2). 30.