dataesr/scientific-paragraphs-categorization huggingface dataset:
This type of approach can be applied to detect peaks in diversity and evaluate the genetic divergence of the environmental sequences as compared to reference databases ('genetic novelty';  Mahé et al. , 2017). It provides therefore the needed information on where to look for undescribed organisms. In the case of the Trebouxiophyceae, given the size of the reference database and the fact that many deposited strains have been barcoded, it can be safely assumed that most novel sequences correspond to potentially undescribed organisms. Here, we applied an environmental DNA approach based on the V9 variable region of the gene coding for the SSU rRNA to a wide sampling design including samples taken from freshwater (FW) and soil (SO) samples, plus all sequences obtained in the course of the TARA Oceans expedition  (de Vargas et al.
Phylogenetic tree construction and annotation In total, we extracted 2018 sequences from the public databases SILVA and NCBI that belonged unambiguously to Trebouxiophyceae (Table  S1 ). Amongst them, we used 1814 high quality (no errors or ambiguous nucleotides), long (i. e. >1000 nt) and non-redundant sequences to build the reference phylogenetic tree. Most of the main Trebouxiophyceae clades were supported with high bootstrap values (>70%) and annotated at the genus level. Those that have bootstrap values lower than 70% were annotated at the order level according to the bibliography  (Leliaert et al. , 2012; Lemieux et al. , 2014). Three formerly uncharacterized deep clades were retrieved and annotated as TREB01-TREB03 (Fig. 1 ). These clades were composed exclusively by environmental sequences that had been already published previously.
Genetic novelty About 80% of all OTUs shared more than 95% identity with published sequences in the PR 2 eukaryotic ribosomal database  (Guillou et al. , 2013). However, present knowledge on Trebouxiophyceae genetic diversity was not evenly distributed. Only 20% of MA OTUs had more than 95% of identity with PR 2 reference sequences. In contrast, this percentage rose above 89% in FW and SO (Fig. 4 , Table  S3 ).
Discussion A reference phylogenetic tree to classify Trebouxiophyceae environmental molecular diversity Our reference phylogenetic tree is a compilation of all knowledge on Trebouxiophyceae diversity available on public databases; indeed, all genera described to date have at least one representative species barcoded for the 18S SSU rRNA gene  (Leliaert et al. , 2012; Lemieux et al. , 2014). Leliaert et al. (2012)  predicted the existence of seven major groups amongst Trebouxiophyceae. Even if the limitation of the SSU rRNA gene for phylogenetic Trebouxiophyceae studies has been previously reported  (Neustupa et al. , 2013; Fu cíková et al. , 2014) , our analysis retrieved the seven predicted groups as well-supported clades most often with high bootstrap values (>70%). Moreover, our study reveal three uncharacterized clades from soil, evidencing the existence of an unsuspected deep diversity (i.
We consider unlikely that these sequences correspond to organisms of edaphic origin brought in the sea as we systematically removed rare sequences. Moreover, the marine sampling was performed far away from the coast  (de Vargas et al. , 2015). Some of these organisms may possibly be free-living forms from these groups or, perhaps, free-living stages of symbiotic organisms. In support for this hypothesis, two OTUs (OTU_59ee09bd8eccf066d00d 755548d60655 and OTU_a0cbafb71d700506213b5e4b3c3 870dc) were classified within Elliptochloris; a future expansion of the trebouxiophyceaen genetic database will help determine how far these organisms are related to Elliptochloris marina or if they constitute a new symbiotic lineage. Althogether, these findings open the way for an accurate assessment of Trebouxiophycean symbiotic associations in marine systems, their range of possible hosts and the relevance of these associations at ecosystem level.
Curated database and the reference phylogenetic tree reconstruction The reference phylogenetic tree was built with a similar pipeline as proposed by del  Campo et al. (2018). Briefly, sequences related to Trebouxiophyceae were extracted from SILVA v132 database  (Quast et al. , 2012). They were aligned with MAFFT v7. 123  (Katoh and Standley, 2013). Introns and intergenic regions were excluded using Geneious v9. 0. 5 (Biomatters, Auckland, New Zealand). Sequences were clustered at 99% of identity with USEARCH v10. 0. 24  (Edgar, 2010). The centroids for each cluster were aligned with MAFFT and a phylogenetic tree inference with RaxML v8. 2. 8  (Stamatakis, 2014)  using GTR + GAMMA model and 100 bootstraps, after the noninformative regions of the alignment excluded by trimAL v1. 4. rev22  (Capella-Gutierrez et al.
, 2009)  was performed. The phylogenetic tree was manually curated and these steps were iteratively repeated until obtaining a consistent database with sequences that represent most of the clades  (Leliaert et al. , 2012). Sequences belonging to Trebouxiophyceae but not assigned as such in GenBank (like unassigned environmental clones) were searched into the NCBI database (September 2017). The search was performed with BLAST v 2. 6. 0  (Altschul et al. , 1997). For each sequence, 100 hits with more than 97% sequence identity, e-value less than 1E-6 and bit-score higher than 1000 were retrieved. This step was repeated until no new sequences were obtained. Sequences with 18S mark region length shorter than 500 nucleotides were excluded using the filtration step proposed by  Logares (2017). New sequences were manually revised using web BLAST with standard parameters in order to exclude non-Trebouxiophyceae sequences.
Phylogenetic tree annotation The names of clades from the reference tree were assigned according to the bibliography  (Leliaert et al. , 2012; Fu cíková et al. , 2014; Hoda c et al. , 2016). We defined new environmental clades (designed as TREBXX) when environmental sequenced clustered together in a robust clade supported by a bootstrap value of at least 70%. We annotated original environment type (FW, MA or SO) and lifestyle (photosymbionts/parasites) based on information retrieved from Genbank and on the bibliography. Organisms found in brackish environments were classified as marine as the salinity barrier is considered as the greatest divide in microbial diversity  (Logares et al. , 2009). This information was deposited in Table  S1. OTUs were added to the Trebouxiophyceae reference alignment using PaPaRa v2.
5  (Berger and Stamatakis, 2011)  and placed in the reference phylogenetic tree with EPA implemented in RaxML v 8. 2 and epa-accumulated-threshold = 0. 999 command  (Zhang et al. , 2013; Mahé et al. , 2017). The best placements for each OTU were selected using Gappa (https://github. com/ lczech/gappa) and corroborated using BLASTN web service tool  (Altschul et al. , 1997). New clades obtained in this study were annotated as TREBXXHTS. The phylogenetic tree figure was performed using Itool  (Letunic and Bork, 2007)  and edited with inkscape 0. 48. 4 (https://inkscape. org). Sampling, DNA extraction, amplification and sequencing SO samples (0. 5 g) were stored in a buffer appropriate for environmental nucleic acids preservation (Life Guard, Qiagen) prior to DNA extraction (see  Seppey et al.
Bioinformatic analysis Our initial data set was constituted of 435 samples distributed in different three different environments: 36 Soil (SO), 65 Freshwater (FW) and 334 Marine (MA). For details about the geographical distribution and the reference of each sample see Table  S2  for SO and FW, and supplementary material from  de Vargas et al. (2015)  for MA; all these correspond to open ocean samples. The data set and the sequences of  de Vargas et al. (2015)  are available in http://taraoceans. sb-roscoff. fr/EukDiv/. In order to compare the three environments, we processed the FW and the SO samples bioinformatically (i. e. assembling, curation, parsing) with the same pipeline developed by  de Vargas et al. (2015)  and already applied in  (Singer et al. , 2016). Likewise, Tara Ocean and our own samples were clustered with Swarm v2.
5-3, only variables with significant p-value (p-value<0. 01) were shown in Fig. 3. To assess the global distribution of Trebouxiophyceae, we calculated the specific richness of each samples, here defined as the total number of OTUs. We plotted the three environment independently on a world map, to see in which environment the samples were more diverse. We used GGMAP version 2. 6. 1 and GGPLOT version 3. 1. 0 package from R to compute the analysis. To determine the representation of the OTUs in references databases and in each environment, OTUs were separated according to their distribution, forming four classifications  (Freshwater, Soil, Freshwater and Soil, and Marine). For each OTU we extracted the percentage of identity assigned in the classification step explained before using PR 2  (Guillou et al.
Acknowledgements We are indebted to  Didier Debroas  for providing several freshwater samples from French lakes. EL wishes to acknowledge the program ' Atracción de talentos de la Comunidad de Madrid ' (grant  2017-T1/AMB-5210 4 ) and  Swiss National Fund project SNF   31003A_163254  for funding. The project was funding by the  ANPCyT 'Agencia Nacional de Promoción Científica y Tecnológica'  ( PICT-2014-1290 ;  PICT-2016-1079 ). The  Swiss NSF  ( P2NEP3_178543 ) to D. S. We would like to acknowledge also  Sergio Pérez Ortega  and  Raquel Pino  ( Real Jardín Botánico de Madrid, CSIC, Spain ) for the fruitful discussions on trebouxiophyceae and symbioses in lichens, and two anonymous reviewers for valuable comments on the manuscript.
Once registered, the patients were informed and consented to the collection, handling and keeping of their personal data, in particular of their health data. Carenity informs members of the purpose of the collection and processing of their personal data in a full and transparent way. The second step of the study involved organizing a forum discussion animated in the French and Spanish online platforms to collect patients' verbatim responses and identify the topics of interest for the patients' survey. For that purpose, four main specific discussions were managed by the community managers related to cNF description, their impact on quality of life, satisfaction of patients with laser and surgery treatments and expectation related to future treatments. Twenty-three patients participated; all the comments posted were extracted then selected and grouped by themes.
Data analysis Only the completed questionnaires were considered for the analysis. Participants data were kept pseudonymised during the analysis and only aggregated data were presented in the results. Excel 2013® was used to perform the different analyses and R studio (v3. 5. 0) was used to perform multiple correspondence analysis and statistical analysis. Overall analysis and per country analysis were performed for every question, multivariate analysis was performed to take into account several items and questions at the same time. For the purpose of the study, two scores were set up and validated with the Advisory Board (comprised of the two medical experts in neurofibromatosis, Pr Pierre Wolkenstein and Pr Ignacio Blanco [who also validated the survey questionnaire]) to characterize disease severity and visibility and to allow the analysis with multiple factors that may be influenced by the severity and visibility of the cNF.
Acknowledgments The authors would like to thank Carenity, in particular  Mrs. Eugenie Ullman ,  Mr. Pierre Legendre ,  Mrs. Lise Radoszycki  and  Roman Dos Santos  for the collaboration to design and follow up the patients' community and questionnaire results. The authors are grateful to the patients who answered the patient's survey and to the  French patient's association 'Association Neurofibromatoses et Recklinghausen'  for its support informing their patients of the online community in the Carenity platform. The authors acknowledge the contribution of  Mrs. Clelia Cahuzac  and  Olivia Menu  for development of the survey and analysis of the results. The authors acknowledge the contribution of Insight Medical Writing for the revision of the manuscript.
III. CASE STUDY This tutorial illustrates the application of the described techniques to a 2. 4 GHz Low Noise Amplifier (LNA) case study. Figure  1  shows the schematic of the LNA, which has been designed in a 90 nm CMOS technology. The envelope detector at the output of the LNA has been included as a built-in test instrument  [18]. Our initial set of signatures contains 42 features: the DC voltages in all the nodes of the LNA, the biasing current, and the output of the envelope detector. Additionally, all the features were measured under nominal and stressed power supplies since this may bring additional information. A population of 2000 instances of the LNA were generated using Monte Carlo simulation and 500 of them were set aside as validation set. In this case study we use a perceptron neural network in MATLAB to predict the gain of the LNA under test.
Three replicate measurements were made to confirm good reproducibility of the results. The deviation between various time and frequency sweeps on fresh samples was within the range of repeatability of rheometry data and lower than 5%. In the aim to checking the thermal stability of the specimens at these temperatures, analyses were started with time sweep tests at 1 rad/s with a deformation of 10%, which was also shown to be within the linear viscoelastic domain for these materials. The linear viscoelastic region was determined using strain sweep at a constant frequency of 1 rad/s. It was identified as the region in which is the elastic modulus G' of the sample experienced less than 5% reduction.
Morphological studies Figure  1a  shows an image of the untreated Alfa fibers obtained in optical microscopy and Figure  1b , 1c and 1d show SEM pictures of biocomposites with 20 wt% of untreated, 1% or 5% alkali treated fibers. Other pictures have been published in previous papers  [18, 19]. The optical micrographs of the Alfa fibers were processed using the ImageJ software to obtain the length and diameter distribution. The examination of the distributions reveals that the most of fibers lengths lay within the range of 20-2500 µm with an average of 680, 590 and 540 µm for untreated, 1 and 5 % alkali treated fibers, respectively. Most fibers diameters have the range of 5-200 µm with an average of 40, 31 and 26 µm and an aspect ratio of 17, 19 and 21 respectively for the untreated, 1 and 5 % alkali treated fibers.
The Illumina HiSeq 2000 system was used to conduct 50 bp long single-end deep sequencing. The FASTX-Toolkit was used to remove the adaptor sequence and filtering of low-quality base call and low-quality reads. The short filtered sequencing reads that were acquired were mapped to the human genome by the TopHat2 and Subreads package; the featureCounts function was used to quantify the gene expression values. These gene expression values were then used to calculate the size of the library and dataset dispersion for the analysis of differentially expressed genes  [15]. Differential gene expression was examined using the R/Bioconductor package edgeR and established by log fold change (LogFC) and false discovery rate (FDR) (LogFC ≥ 1 or ≤-1; FDR ≤ 0 05).
Acknowledgments The authors acknowledge the technical support from the  Deanship of Scientific Research, King Abdulaziz University, Jeddah , and  KFMRC  for providing the  RNA-Seq facility. This work was funded by the  Deanship of Scientific Research (DSR) ,  King Abdulaziz University, Jeddah , under grant no. RG-43-130-40. The authors, therefore, acknowledge with thanks  DSR  for the technical and financial support.
17. 67). The absence of opposition by a patient in the 15 days following the receipt of an information letter was considered as nonobjection to this study. The statistical analysis was performed with SAS software (version 9. 4). Quantitative variables were described by their count, average, standard deviation. The groups were compared using a Mann-Whitney Wilcoxon test since the length of stay data were not normally distributed. For the qualitative variables, the counts and percentages were determined for each modality. The groups were compared using the parametric χ2 or nonparametric Fisher test.
Psychophysical task Participants performed the size adjustment task implemented with the EventIDE software (OkazoLab) on a laptop computer (hp probook equipped with a Core i5 processor and running Windows7; screen diagonal length: 39. 6 cm; resolution: 1366 3 768 pixels). We positioned the screen of the laptop computer about 70 cm from our participants, who wore an occluding patch in front of the nondominant eye in order to discard binocular depth cues (stereopsis) and to potentiate monocular depth cues (the linear perspective of the pictorially defined corridor). Figure  1c  presents the four experimental conditions which were pseudorandomly interleaved across trials: two with a corridor receding either leftward or rightward in the background (''corridor'' conditions; 15 repetitions each) and two with a black background (''control'' conditions; 10 repetitions each).
Acknowledgments  S. Rima  and  J. -B. Durand  developed the study concept. All authors contributed to the study design. S. Rima  and  C. Khalil  did the testing and data collection. S. Rima  and  J. -B. Durand  performed the data analysis and interpretation under the supervision of B. R. Cottereau  and  Y. Trotter. J. -B. Durand  drafted the manuscript, and  S. Rima; B. R. Cottereau  and  Y. Trotter  provided critical revisions. All authors approved the final version of the manuscript for submission.
Reads were trimmed and assembled as previously described  [19]. Genomic data as multilocus sequence typing (MLST) type and resistance genes were detected from assembled sequences using web-tools (http://www. genomicepidemiology. org/). For each isolate, the paired-end reads were aligned against the S. Dublin str. 3246 reference genome (GenBank accession number: CM001151. 1) using Bowtie2 with default parameters  [20]. A coregenome multi-alignment of assembled genomes was also done using Harvest v1. 0. 1 f ParSNP function  [21]. For each approach, the resulting single nucleotide polymorphisms (SNPs) were concatenated to generate a filtered multiple alignment that was used as input for the construction of a phylogenetic tree using Molecular Evolutionary Genetics Analysis (MEGA)6  [22]  with a maximum-likelihood (ML) approach.
The final trees were visualised in the interactive Tree Of Life  [23]. All reads generated in this study have been deposited in project PRJEB28817. Multilocus variable-number tandem repeat analysis ANSES used MLVA as described elsewhere  [11] , to analyse 241 isolates (including 148 human and 93 non-human), of which 110 corresponded to the outbreak period. The measured lengths for each fragment were obtained using an ABI3500 capillary electrophoresis system (Applied Biosystems, France). Data were imported into GeneMapper software (Applied Biosystems, France) where each fragment was identified according to colour and size. A normalisation of the results was done with the free access MLVA_ Normalizer software  [24].
Data collection Epidemiologists from the regional offices of SpFrance interviewed the cases by telephone using a trawling questionnaire on clinical symptoms, medical history, detailed food consumption, contact with other persons experiencing diarrhoea, travel history and contact with animals. Loyalty card information was collected to trace-back supermarket purchases. On week 8 (22-28 February), 2016, controls from the GrippeNet. fr cohort received a web link to complete an online questionnaire about health, travel history and food consumption during 11-17 January 2016 (a 7-day ordinary non-festive period).
Microbiological findings Among 241 MLVA performed for S. Dublin isolates, 49 different MLVA patterns were obtained and among these, seven gathered 10 or more isolates (Table  2 ). The WGS analysis of all the 289 S. Dublin isolates, including historical ones, indicated a unique MLST, ST10 that had previously been related to serotype Dublin in both the literature and public databases (https://enterobase. warwick. ac. uk/)  [27]. As the mapping against the S. Dublin str. 3246 reference genome (GenBank accession number: CM001151. 1) showed high divergence with 19,213 SNPs, the core-genome multialignment of assembled genomes using ParSNP function was preferred. A generated matrix file revealed that maximum divergence for all isolates sequenced during the outbreak including the reference strain was 791 SNPs suggesting a relative homogeneous population of S.
Limitations Our investigations suffered from several limitations. First, cases were interviewed by phone, while controls completed a shorter online questionnaire, which could have led to obtaining exposure data with different degrees of accuracy. To minimise this bias, we used the same questions for cases and controls. Second, age and sex distribution of controls differed from that of the cases. We thus included age and sex in the multivariable analysis to adjust for those characteristics. Third, it was difficult to identify the exact sources of contamination due to probably low levels of contamination by S. Dublin of the cheese batches. As the cattle contamination was diffuse, it was difficult to incriminate specific cheese producers in the Bourgogne-Franche-Comté region as sources of contamination.
Acknowledgements We are grateful to all the microbiological laboratories processing human and non-human samples, who participate in the Salmonella network for isolates processing. We acknowledge Santé publique France epidemiologists from the regional offices who conducted the interviews, Edith Laurent who performed the data entry and  Marie-José Letort  who helped contacting laboratories. We thank all the persons involved in the microbiological investigations in Institut Pasteur (in particular Vincent Enouf,  Estelle Serre  and  François Gravey ) and in the  French Agency for Food, Environmental and Occupational Health and Safety. We also thank the persons who conducted the food trace-back investigations in the  Ministry of Agriculture and Food. We are grateful for the persons in the  French National Institute of Health and Medical Research  in the GrippeNet.
Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption.
g. , neuro-Construct  [22] , PyNN  [23] , NetPyNE  [24] , Open Source Brain  [25] , and the Allen Institute's Brain Modeling ToolKit (BMTK, https://alleninstitute. github. io/bmtk/; [26] ) have been developed that allow users to interact with these engines without mastering the underlying programming environments of individual simulators. However, the utility of these tools is limited without a broadly applicable, flexible, and high-performance modeling data format. The current evolution of typical workstyles towards collaborative team projects demands standardized formats for model sharing and reproducibility, as well as for interoperability between tools. Meanwhile, high computational performance of such formats becomes increasingly important to enable efficient representation of the growing biological complexity of models.