dataesr/scientific-paragraphs-categorization huggingface dataset:
We identified, annotated and compared transcripts to existing databases (including the complete pea aphid genome), allowing to discover some phylloxera-specific gene families, reconstructed a large catalogue of predicted coding sequences, and analysed patterns of nucleotidic composition. We finally performed a differential expression analysis to compare transcript abundance in leaf and root-feeding forms and found significant changes in expression among the two forms. We also identified i) a gene family that is extremely highly expressed in both morphs and appears to be associated with oviparity, illustrating major changes in expression associated with change in life-traits between phylloxera and the true aphids ii) a gene family containing two closely related copies characterized by opposite patterns of expression bias among morphs, showing a case of rapid switch in the specificity of expression following duplication.
8 and 7. 4. The cDNA libraries -Truseq, v3 chemistry, with poly-A selection, were performed according to the manufacturer's instructions (Illumina, San Diego, CA, USA), then sequencing was done on the Hiseq2000. The five cDNA libraries were sequenced in pair-ends, with reads of 101 bp, by the GATC company (Germany). Samples were sequenced in two different runs (GA and RA on one run, while the egg sample was sequenced in another run). The raw sequence data has been deposited in the SRA division of Genbank (project accession: PRJNA294954).
Cleaning of sequences and assembly Analyzing the GC content and the over-representation of sequences with the fastqc software (http://www. bioinformatics. babraham. ac. uk/projects/fastqc/), we did not see any evidence of contamination, nor unexpected presence of adapters in any library. Low quality parts of the reads were trimmed from the right when the mean of phred score in a 20 bp window was below 20, with prinseqlite (http://prinseq. sourceforge. net/). The reads larger than 20 bp after trimming were re-organized by pairs and assembled with Trinity with the jaccard_clip option to limit fusion transcripts  [23]  and default parameters for other options.
Annotation Contig sequences were compared by blastx (blastall program  [24] , version 2. 2. 28+) to the complete genome of the pea aphid Acyrthosiphon pisum (using the version 2. 1 of predicted proteins, www. aphidbase. com). In parallel, a blastx search of similarity was performed against public general databases (nr, with an e-value cutoff of 1e-8). Also, completeness of the assembled transcriptome was assessed using the BUSCO software  [25] : the method searches homologies to a core set of 2,712 highly conserved genes in all arthropods (we used the Drosophila melanogaster sequences). Finally, a blastn search was performed against potentially contaminant sequences, i. e. ribosomal RNA or mitochondrial sequences (using sequences from A. pisum). Then a BLAST2GO annotation helped by blastx results against nr and by an interproscan search (v4.
Genomic features Prediction of coding sequences (CDSs and protein sequences) was performed using the Transdecoder tool from the Trinity package  [23] , which uses a self-training procedure and a Hidden-Markov model approach for ORF detection. This allowed a comparison of coding sequences with the nearest completely sequenced taxon, the pea aphid. Such comparison, aimed at identifying potential orthologs and gene families that would be specific to phylloxera, was done with OrthoMCL  [26]. Then the predicted CDSs sequences allowed us to evaluate compositional patterns in the phylloxera, measuring nucleotide frequencies at the three codon positions. Read mapping to contigs and counts of expression per library-Phylogeny of the most abundantly transcribed gene family RNA-seq allows to capture the digital gene expression information in the form of relative read coverage.
For this, the reads were aligned by pairs and by library back to the contigs with bowtie2  [27]  with the non-deterministic parameter (only the best alignment is reported, or a random hit among the best if the read maps in many places). The counts of reads by contigs and library were then obtained with the samtools idxstats program  [28]. To also get insight on the most expressed transcripts across all libraries (which could be linked with specificities of the phylloxera biology), we investigated the potential phylogenetic relationships among the corresponding genes, in particular for a 6-gene family and for their orthologs in other insect species. A phylogenetic study of this gene family was performed: the proteic alignment was obtained with T-coffee  [29]  then trimmed with Gblocks  [30].
Differential expression analyses Normalization of read counts and statistical comparison of expression of the contigs were performed using DESeq2  [32] , focusing on the comparison between GA and RA libraries, for which two replicates were available. Adjusted p-values indicated levels of significance of an expression bias among the two conditions (the software using information on the variability between replicates and between conditions). The log2-fold ratio of the normalized expressions of GA (mean of the two replicates) versus RA libraries was also used to determine lists of genes that showed a morph-biased expression pattern. Differentially expressed (DE) transcripts were defined as genes with a significant difference in expression (to further decrease the risk of false positives, we selected an adjusted p-value threshold of 0.
Quantitative RT-PCR For the qRT-PCR validation step, independent aphid samples were prepared and corresponding RNAs were extracted for respectively leaf-gall and root-feeding adults. Total RNAs extractions were performed according to the RNeasy Mini Kit (Qiagen) protocol. RNA samples purity and quality was checked with a Bioanalyser 2100 (Agilent) and quantified by spectrophotometery (Nanodrop Technologies). Before reverse transcription, a DNAse I treatement was performed (Sigma Aldrich). One microgram of total RNA was used for cDNA synthesis using Superscript III (ThermoScientific) and oligo dT (Promega). Primer sequences used for qRT-PCR were designed using Primer 3 software; sequences are available in Additional file 1. Quantitative PCR was performed on cDNAs products with the LightCycler 480 Real-Time PCR System using the SYBR Green I Master mix (Roche) according to the manufacturer's instructions.
pisum and phylloxera data are respectively based on a complete genome and on a de novo transcriptome. A significant number of families (683), totaling 3,047 genes, were found to be specific to phylloxera (Table  4 ). Since our comparison involved only two species (grapevine phylloxera and the pea aphid) this does not imply that all of these genes are "specific" in a broader sense (some of these genes could be similar to other genes from different organisms). However, we found that a majority of these genes (78. 2 %) had not hit to the nr database. This is the case of the two largest phylloxeraspecific families which comprised 69 and 63 peptides respectively. Therefore gene families truly specific of D. vitifoliae appear to represent a significant fraction of this transcriptome-based gene collection.
Identification of very abundant transcripts, phylogenetic study of their gene family We examined the characteristics of the most abundant transcripts, whether or not they showed a biased expression among morphs. In particular, the most supported transcript in RA represented more than 5 % of the mapped reads (Table  5 ). We checked CDS predictions for that transcript and for potential related sequences in the transcriptome (paralogs). We found a total of six gene copies with predicted full length peptide (sequence length of ca 470 amino-acids). Several of these copies have a high expression in GA and RA (totaling more than 1 % of the mapped reads)but not in the egg Table  3  Results of the blastx comparisons between contigs from the grapevine phylloxera transcriptome and proteins from the nr bank, ordered by the number of contigs which have a given species as best hit.
The numbers of families of each type are given, along with the number of predicted genes from each species for each category library. This gene family for which we predicted a signal peptide (SignalP analysis  [36] ) showed no similarity outside aphids. However, these genes had hits to three weakly similar copies in the pea aphidall hypothetical proteins -and also to three transcripts from the transcriptome of Acyrthosiphon svalbardicum (a transcriptome recently obtained by our group for sexual oviparae females, unpublished data). The phylogenetic analysis of this family shows two sub-groups (corresponding to an ancient duplication, preceding the phylloxera-true aphid divergence) -Fig. 2. In sub-group 1, lineage-specific duplications further occurred either in true aphids or in the phylloxera lineage.
Differential expression analyses The change in expression level among the two conditions (log2fold change), for every contig, is represented in Fig. 3. This figure shows that the distribution of genes that are more expressed in RA or GA were markedly different. GA-biased genes tended to represent abundant transcripts, with a moderate ratio increase of expression compared to RA. By contrast, RA-biased represented less abundant transcripts overall, with a high ratio increase of expression compared to GA. If we consider genes that are significantly biased at the p = 0. 01 level and show a log2fold of absolute value > 1 (meaning that absolute number of reads in normalized counts changes at least twofold among conditions), many more genes appeared to be RA-biased (n = 3,566) than GA-biased (n = 883).
Besides, many more genes had only support in the RA condition (n = 11,077) than genes that had only support in the GA condition (n = 4,054). To get insight into the functional characteristics of differentially-expressed (DE) transcripts (as defined above), we compared their GO annotation using enrichment-tests based on a Fisher-test with a False Discovery rate or FDR of 0. 05 (Fig. 4 , which details the GO-terms statistically  For the grapevine phylloxera percentages of read counts in GA, RA and egg libraries are given for the six paralogs identified. For the pea aphid, percentages of read counts in libraries obtained from three different reproductive morphs (whole bodies of oviparous sexual females, viviparous asexual females, males) are given for the three paralogs identified  [21]  more associated with respectively RA-biased or GA-biased transcripts).
For the Molecular function category, RAbiased were much richer in genes annotated as "structural component of the cuticle" (of note, the same genes were also often associated with the Cellular component term "integral to membrane"). To further confirm this we analysed the distribution of log2fold ratios of expression between RA and GA for all 60 contigs annotated as "cuticular protein" and found this distribution was heavily shifted to positive ratios (58/60 contigs having higher Fig. 2  ML phylogenetic tree (JTT model, with MEGA6) of the gene family containing some of the most highly abundant transcripts in the phylloxera transcriptome (both for radicicoles and gallicoles libraries). The phylogeny includes 6 identified copies from the phylloxera transcriptome ("comp" prefix), three homologs from the pea aphid genome ("ACYPI" prefix) and three homologs from a transcriptome of Acyrthosiphon svalbardicum ("ASV" prefix).
qPCR validation To validate RNAseq measures of expression and subsequent identification of statistically DE genes among leafgall and root-feeding forms, we independently measured expression using qPCR. For that purpose, we selected 6 Fig. 4  Gene ontology enrichment analysis (Fisher test, False Discovery Rate < 0. 05) between genes that are significantly over-expressed in gallicoles (RA) or in radicicoles (RA). In y-axis, frequency of terms in GA-and RA-over-expressed transcripts genes, based on RNAseq results. Two genes had been identified as significantly more expressed in root feeding forms (apyrase-1, take out), two other genes had been identified as significantly more expressed in leaf-gall feeding forms (apyrase-2, trypsin-like serine protease) while the last two genes, transaldolase-like and ATP-synthaselike showed a constant expression level (respectively at moderate and high levels) and were used to normalize qPCR measures of expression.
pisum (36,990;  [41] ), which along with daphnia  [42] , has an exceptionally duplication-rich genome for an arthropod. Although the exact timing of the vast gene expansion characterizing the pea aphid lineage is yet to be determined, the distribution of genetic distances among paralogs of A. pisum suggested that most duplications took place relatively recently in the evolution of aphids, and probably well after the divergence between true aphids and Phylloxeroidea  [18]. Therefore, we may expect that the number of different proteins for grapevine phylloxera would be closer to the average of other insect genomes, and thus that the transcriptome based predicted genes we obtained should represent a majority of the coding genome. As a first attempt to annotate and characterize this assembled phylloxera transcriptome, we analysed blast hits to the nr database.
Further, most of these genes had no similarity to any known protein. For example, the two largest gene families comprised each up to 60 genes. Analysing the complete peptides in these families, we found the presence of a signal peptide (according to SignalP prediction), which suggest they could be secreted proteins, possibly playing a role in nutrition or host plant interaction  [43]. We also analyzed the specificities of this grapevine phylloxera transcriptome in terms of global expression levels, comparing to available data for the pea aphid for which extensive transcriptomics data have been produced. We focused on the contigs with the highest level of support, and thus the transcripts which appear to be the most highly expressed, and examined the nature of genes predicted for these contigs.
In our study, we found few bacterial transcripts overall, with one exception (see below), and no contig of our assembled phylloxera transcriptome matched to Pantoea. We must remain cautious about the significance of this negative finding, given that our purification protocol using poly-A selection may have hindered detection of bacterial transcripts. Further studies with different protocols would be necessary to better evaluate the prevalence of P. agglomerans in that insect species. However, we found abundant traces of transcripts (135 different contigs) from a bacteria closely related with Propionibacterium acnes, normally known as a human opportunistic pathogen. Although we first thought of contamination to explain this presence, a recent study  [53]  has since brought biological and phylogenetic evidences for a recent association of this human pathogen with grapevine (V.
This ubiquist gene family is often associated in animals with development or with the metabolism of toxic compounds. At present, there is still no easy explanation for these differences between GA and RA with respect to potentially immune-related or detoxification systems. Another interesting result of this study is that paralogous sequences (gene copies that derive from duplication) may display sharp differences in expression specificity among conditions. We detected this at least for a pair of transcripts corresponding to two different copies of a gene similar to apyrase, an enzyme known to hydrolyse ATP (for phylloxera, these genes were named apyrase-1 and apyrase-2). These two copies were among the four target genes selected for the qPCR validation of RNAseq measures of expression. We found indeed that apyrase-1 and apyrase-2 which are 94.
SDHCAL simulation and digitization method The SDHCAL prototype simulation is performed with a program based on the GEANT4 toolkit  [5]  where each SDHCAL element is described using its composition, density, size and position. Pion, electron, proton and muon events are simulated using different physics lists prepared by the GEANT4 collaboration. A physics list defines the different GEANT4 models and their transitions used to simulate physical processes. In this paper, the QGSP_BERT_HP and FTFP_BERT_HP physics lists are used to simulate hadronic and electromagnetic showers in the SDHCAL prototype using the 9. 6 GEANT4 version. These two physics lists are those recommended by the GEANT4 collaboration. In addition to the GEANT4 based program, a new algorithm called SimDigital is developed to perform the digitization.
In GEANT4, the energy deposited in the gas is recorded whereas in data the induced charge is measured. The multiplicity effect is also not included in GEANT4. The SDHCAL simulation output contains the following information: the list of steps 2  inside the gas gaps; the deposited energy in these steps; the start and end point positions of each step in gas gaps; and the occurrence time of each step in the gap. It may happen that GEANT4 produces several steps for only one particle inside the gas gap. To avoid the simulation of several avalanches for only one particle in the gap, these steps are linked together before writing the simulation output. However, one may expect that for particles with large angle with respect to the normal to GRPC's, triggering multiple avalanches in the gas gap should be allowed.
This will be take into account by correcting the induced charge using the steps angle (see Eq. 3. 1 and section 4. 3). The SimDigital algorithm is implemented as a Marlin  [11]  processor in the MarlinReco  [12]  package of ILCSoft  [13]. The aim of the SimDigital algorithm is to determine the induced charge from each particle crossing a gas gap, to distribute this charge over the pick-up pads and to apply the thresholds. It is formulated according to the following sequence: 1-During beam tests, no external trigger system was used. The hits from showers incident particles, muons, cosmics and noise were recorded using a 200 ns clock and an event building procedure was needed. For each time slot that contains more than seven hits, hits belonging to neighbouring time slots are added to those of the central one to build one physics event.
The Monte Carlo simulation was able to predict the hadronic shower response of the ATLAS-TileCal prototype within a few percents in a wide energy range (20 : 350 GeV)  [6]. The agreement between data and the simulated hadronic shower response in the CALICE-AHCAL prototype was also found to be satisfactory  [7]. However, the CALICE-AHCAL simulated response was higher than that in data above 30 GeV whereas an opposite behavior is observed within the SDHCAL prototype (Fig. 13 ). Nevertheless, for the CALICE-AHCAL prototype as well as for the ATLAS-TileCal prototype, the deposited energy was measured (analog readout) while the SDHCAL response is defined by the number of hits. Moreover, the transversal segmentation in ATLAS-TileCal (∆φ × ∆η ≥ 0. 1 × 0. 1) and in CALICE-AHCAL (≥ 3 × 3 cm 2 ) is not as fine as in SDHCAL (1 cm 2 ).
This may explain why the number of hits (above 50 GeV) in the simulation was lower than that in the SDHCAL data while the agreement between data and simulation was better for the ATLAS-TileCal and CALICE-AHCAL prototype. The radial shower profile was also studied using the CALICE-AHCAL prototype in  [7]. The conclusion of this study was that GEANT4 physics lists underestimate the radial extent of hadronic showers. The radial shower profile is also studied in the SDHCAL prototype. To compute this profile, the shower main thrust is estimated using a straight line fit of the unweighted shower hit positions. Then, the intersection of the main axis and each layer is used to locate the shower  barycentre in each layer. Hits are then counted in 1 cm thick rings, using the center of pads, around the barycentre position.
Acknowledgements We would like to thank the  CERN-SPS  staff for their availability and precious help during the two beam test periods. We would like to acknowledge the important support provided by the  F. R. S. -FNRS, FWO (Belgium) ,  CNRS  and  ANR (France) ,  SEIDI  and  CPAN (Spain). This work was also supported by the  Bundesministerium für Bildung und Forschung (BMBF) ,  Germany ; by the  Deutsche Forschungsgemeinschaft (DFG) ,  Germany ; by the  Helmholtz-Gemeinschaft  (HGF), Germany; by the  Alexander von Humboldt Stiftung (AvH) ,  Germany.
Material Using the online software "google forms, " we created two questionnaires, each composed of 150 questions. The first questionnaire contained an adapted French version of a definition of LD ("During LD, one is-while dreaming-aware of the fact that one is dreaming. It is possible to deliberately wake up or to control the dream action or to observe passively the course of the dream with this awareness") and a frequency question, as used by  Schredl and Erlacher (2004). The second questionnaire contained two separate questions, one on the frequency of dream awareness and the other one on dream control: "While dreaming, have you ever been aware that you were actually dreaming?"; "While dreaming, have you ever been able to control the content of your dream?" These two questions were devised from existing formulations in English.
Data Acquisition and Pre-processing As a reminder, the purpose of the present study is (1) To investigate whether the prevalence of LD would vary depending on the type of methodology and (2) To study links between the prevalence of LD as assessed, respectively, by each questionnaire, with the following two factors: Vividness of Mental Imagery and Parasomnia. Analysis would thus concern only items of the Mental Imagery scale and the 10 questions on parasomnias that could be remembered by participants at wake. Exploratory items were not considered in the present statistical analysis (for example, questions on sleep position, consumptions, duration of sleep. ). For the questionnaire in which a definition of LD was presented (DefQuest), LD frequency per week was measured with an 8-point rating scale ranging from zero (never) to seven (several times).
RESULTS Data collection and processing was carried out using SPSS R version 20 for Windows. Non-parametric tests were conducted since the conditions of homogeneity and normality of variances were not met. After exclusion of contributions with missing answers, the statistical analyses concerned 309 participants out of the original sample of 315 individuals. As shown in Figure  1 , among participants who have answered the DefQuest (n = 153), 81. 05% reported having experienced LD at least once. Among participants who answered the AwarContQuest (n = 154), 73. 38% reported having experienced dream awareness at least once. Concerning the dream control question, 50. 65% reported dream control at least once. For the AwarContQuest, among the 113 participants who reported one dream or more with awareness, 79 reported a lower frequency for dream control.
Prevalence differences of lucid dreaming (LD) across studies. The purpose of this table is to illustrate how LD prevalence and methodology vary across studies focusing on LD prevalence evaluation. Titles and abstracts were searched in the electronic PubMED and PsycINFO databases and in google scholar search engine (limited to the 10 first pages) using the following search terms: lucid dream * /AND (frequency OR prevalence OR incidence). Only studies published after 2000 were examined.