dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors gratefully acknowledge financial support provided by the  STSE WACMOS-MED (Water Cycle Multimission Observation Strategy for the Mediterranean) project  under  ESA  (Grant No. 4000114770/15/I-SBo ) and the  Earth2Observe  ( Global Earth Observation for Integrated Water Resource Assessment)  project of the  FP7  (Grant No. 603608 ). We also thank  GRDC  for providing the river discharge observations. The  ESPRI (Ensemble de  services pour la recherche à l'IPSL) computational facilities of IPSL were used to perform all calculations and this work is a contribution to the  HyMeX program.
The Double Focusing Mass Spectrometer DFMS embarked on the European Space Agency's Rosetta mission as part of the ROSINA instrument suite. It boasts a high mass resolution and a high sensitivity, which have guaranteed spectacular discoveries during Rosetta's rendez-vous with comet 67P/Churyumov-Gerasimenko. This paper describes the DFMS data calibration procedure for determining the parent and fragment ion count rates in the neutral mode, which serve as the basis for retrieving the neutral gas densities. A new approach to computing secondary electron yields is presented. Attention is given to an analysis of the mass peak shapes, which change with magnet temperature. Discrete counting statistical effects also affect the peak shape at low counts. If not accounted for, changes of mass peak shape can induce errors of up to 20% on the determination of the ion fluxes.
Option 2 is therefore a necessity for establishing long-term averages. It has therefore been used for the provision of the ROSINA DFMS Level 5 data in ESA's Planetary Science Archive. Relative ion count rates are often directly proportional to the relative abundances of the corresponding parent species. When computing such relative quantities, several systematic errors disappear, such as the uncertainty on the gain associated with the definition of J Ã. Because the trends of the J variation with temperature may have opposite directions for different ions, the net effect on ion count rate ratios can be considerable. Fig. 8  shows the ratios relative to H 2 O þ.
In that case, the uncertainties associated with the Poisson counting error, the position-dependent gain, the sensitivity and the fragmentation pattern all combine to determine the uncertainty on the parent densities. An important part of this uncertainty can be removed by rescaling the densities relative to the total density as determined by the ROSINA COPS sensor. the many engineers, technicians, and scientists involved in the mission and in the ROSINA instrument team over the past 20 years, whose contributions are gratefully acknowledged. Rosetta is an ESA mission with contributions from its member states and NASA. All ROSINA data are available from the PSA archive of ESA and the PDS archive of NASA. Data and software used to produce the tables and figures in this manuscript are available from the authors upon request.
, 2013; Vinck et al. , 2015; Dadarlat and Stryker, 2017; Pachitariu et al. , 2019). These findings complicate the comparisons of dLGN and V1 representations in different animals or recording sessions, as differences in neural activity could be caused by changes in the internal or behavioural state. To address this, we recorded simultaneously from populations of neurons in dLGN and V1 of mice that were presented with gratings of varying spatial and temporal frequencies. Leveraging this dataset, we compared the population code in each of these areas, and how trial-to-trial spiking covariability changed the representation of visual information from dLGN to V1 within the same animal.
Data acquisition Neurophysiological signals were amplified (400x), bandpass filtered (0. 3-10 kHz), and acquired continuously at 20 kHz at 16-bit resolution using an Amplipex system (http://www. amplipex. com/). The spike sorting procedure was described in detail previously  (Mizuseki et al. , 2009). In brief, extracellular action potentials were extracted from the recorded broadband signal after high pass filtering (>800Hz) by a threshold crossing-based algorithm. Based on principal component analysis, individual spikes were automatically clustered into groups using the KlustaKwik program  (Harris et al. , 2000) , followed by manual adjustment of the clusters using the Klusters software package (http://klusters. sourceforge. net) (Hazan et al. , 2006). Only units with clear refractory periods and well-defined cluster boundaries were included in the analyses  (Harris et al.
Visual stimuli Stimuli were generated in Python, using the Psychopy toolbox  (Peirce, 2007) , and were shown on an Asus PB238 screen (1920 x 1080 pixels, 51 cm wide, 60 Hz refresh rate) adjusted with a flexible arm to be 45° from the anteroposterior axis, 11 cm from the mouse's eye, thus subtending 133° of visual field. The monitor was gamma corrected to linearize luminance. All stimuli were presented full screen.
Gratings We presented an extensive matrix of stimuli consisting of drifting gratings. We aimed to explore a broad range of spatial and temporal frequencies  (Niell and Stryker, 2008; Andermann et al. , 2011; Piscopo et al. , 2013). This stimulus set consisted of gratings with eight directions (4 orientations) spaced uniformly between 0 deg and 360 deg, six spatial frequencies (0. 02, 0. 04, 0. 08, 0. 16, 0. 32 and 0. 64 cycles per degree), and five temporal frequencies (1, 2, 4, 8, 15 Hz) with contrast fixed at 80%. We analyzed data only from the 3 lower spatial frequencies, because the neural responses recorded at the 3 higher spatial frequencies showed unstable inter-neuronal correlations (i. e. , the correlations differed substantially between different portions of the dataset, precluding accurate statistical models to be fit to the population activity).
Correlated v. independent decoding Population decoding was assessed as two-alternative forced choice accuracy of a maximum likelihood estimation. That is, given neural activity pattern x at a single snapshot in time, the decoder chooses direction θ 1 if P(x|θ 1 ) > P(x|θ 2 ). To test the impact of correlations on decoding, we compared two models of the conditional distribution P(x|θ): one that only reproduces the firing rates of the neurons (the 'independent' decoder), and one that also reproduces the pairwise noise correlations (the 'correlated' decoder). Specifically, we used maximum entropy models to fit the joint spiking activity of populations of either dLGN or V1 neurons  (Gardella et al. , 2019). Maximum entropy models are useful because they can fit specified statistics of the data (such as correlations and firing rates) while making no additional assumptions on the rest of the structure of the data.
Acknowledgements We thank the many staff members of the  Allen Institute  and especially the  In Vivo Sciences team  for surgeries, the Engineering team, the  Imaging Team  and  Naveen Ouellette  for expert assistance; and  Allen Institute  founder,  Paul G. Allen , for his vision, encouragement and support. JZ is an Associate Fellow of CIFAR, in the Learning in Machines and  Brain Program , and gratefully acknowledges the following funding sources: Sloan Fellowship;  Canada   Research Chairs program ;  NSF-DMS Grant 1056125 , and  National Science and Engineering Research Council of Canada (NSERC).
Plasmodiophora brassicae is an obligate biotrophic pathogenic protist responsible for clubroot, a root gall disease of Brassicaceae species. In addition to the reference genome of the P. brassicae European e3 isolate and the draft genomes of Canadian or Chinese isolates, we present the genome of eH, a second European isolate. Refinement of the annotation of the eH genome led to the identification of the mitochondrial genome sequence, which was found to be bigger than that of Spongospora subterranea, another plant parasitic Plasmodiophorid phylogenetically related to P. brassicae. New pathways were also predicted, such as those for the synthesis of spermidine, a polyamine up-regulated in clubbed regions of roots. A P. brassicae pathway genome database was created to facilitate the functional study of metabolic pathways in transcriptomics approaches.
Genome sequencing and assembly For de novo sequencing of the eH genome, different libraries were sequenced using 40 µg DNA with Illumina HiSeq 2500 technology (Genoscreen, Lille, France). Three libraries were sequenced: a paired-end shotgun library with an insert size of 430 bp, a 3 kb insert mate-pair Illumina library, and a 5 kb insert mate-pair Illumina library. Paired-end reads were cleaned (N-trimming) and reads shorter than 50 bp were removed. The eH genome was de novo assembled (86 bases k-mer) using SOAPdenovo. Gaps were trimmed and gap-closed using GapCloser, scaffolds were filtered (500 nt in size) and redundancy was removed. For scaffold #43, identified as the mitochondrial genome, assembly was performed with appropriate software, such as MITObim  (Hahn et al. , 2013) , NOVOPlasty  (Dierckxsens et al.
Transcriptome sequencing and functional annotation RNA from eH non-germinating resting spores was used for RNA sequencing using 1x100 bp Illumina HiSeq2500. The oriented single end reads were trimmed and cleaned. All non-redundant generated sequences were processed using Velvet for transcriptome assembling and Gmap for alignment to the eH genome sequence. Genome annotation was conducted using EuGene prediction software  (Foissac et al. , 2008)  trained on P. brassicae data. The annotation pipeline included in EuGene certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. integrates various sources of evidence, such as high throughput strand-specific RNA-Seq data, intrinsic information provided by coding potential (Interpolated Markov Models), stop and start codon analysis (using a dedicated RBS alignment tool), similarities with known proteins (SwissProt), high quality CDS predictions and ncRNA predictions (tRNAscan-SE, RNAmmer and Rfam-scan softwares).
Putative transcript function and Gene Ontology (GO) analyses were performed using Blast2GO  (Conesa et al. , 2005)  with default settings. For more detailed genome annotation and to retrieve information (Enzyme Commission numbers (EC), GO terms, InterPro and pathways), several external databases were interrogated: Reactome  (Fabregat et al. , 2016) , KEGG  (Kanehisa et al. , 2017) , MetaCyc  (Caspi et al. , 2016) , EupathDB  (Aurrecoechea et al. , 2017) , Uniprot (The UniProt Consortium, 2017), Gene Ontology  (Ashburner et al. , 2000; The Gene Ontology Consortium, 2017) , and ECDomainMiner to link known Pfam domains to EC numbers  (Alborzi et al. , 2017). Carbohydrateactive enzymes (CAZymes) were predicted using the dbCAN pipeline  (Yin et al. , 2012). SignalP  (Petersen et al. , 2011)  was used to detect secretion signals in protein sequences.
All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018. ; https://doi. org/10. 1101/335406 doi: bioRxiv preprint 10 Gene annotation of scaffold #43 was performed with the automated MFannot tool  (Burger et al. , 2013)  that predicts group I and group II introns, tRNAs, RNase P-RNA, and 5S ribosomal RNA (rRNA). The annotation was verified with Blastn and Blastp by quering the NCBI databases.
Metabolic pathway database A GenBank file was created containing detailed DNA sequence information and used to run Pathway Tools version 21  (Karp et al. , 2011). This allowed a Pathway Genome DataBase (PGDB) to be created for P. brassicae: ClubrootCyc. Pathways were predicted with MetaCyc database version 20. 5  (Caspi et al. , 2016). PGDB functionalities were validated using data from the transcriptomics analysis of lipid droplets by  Bi et al. (2016).
Data Availability The eH P. brassicae genome sequence has been deposited in the public domain in GenBank Data Librairies under accessions SRR6395507, SRR6395506 and SRR6395505 for raw data sequences, and POCA00000000 for the genomic data. The Pathway Genome DataBase ClubrootCyc is available online at https://pathway-tools. toulouse. inra. fr/CLUBROOT.
(2016)  were not included because data are not available). The gene density, calculated as the number of genes every 20 kb, was nine on average. This gene density is relatively high as previously described  (Schwelm et al. , 2015; Rolfe et al. , 2016) , and contributes to the small genome size compared to the two known genomes of free-living Rhizaria, Bigelowiella natans certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018. ; https://doi. org/10. 1101/335406 doi: bioRxiv preprint (~100 Mb)  (Curtis et al. , 2012)  and Reticulomyxa filosa (~320 Mb)  (Glöckner et al. , 2014). Gene similarity between the eH and e3 isolates was studied by comparing the gene sequences of both genomes.
Genome annotation The RNAseq of resting spores, used for annotation, resulted in 23,540,954 reads. The genome annotation was improved compared to the e3 reference genome by interrogating several external databases as described in the materials and methods. The annotation data predicted 12,591 protein-coding genes in eH genome (Table  1 ). In total, 7,420 genes were associated with GO terms, 4,379 with EC certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. numbers and 8,081 with InterPro signatures. In rare cases of conflicting annotation, the results from manual annotation and Blast2Go were favored. Carbohydrate-active enzyme sequences of both the e3 and eH genomes were compared using dbCAN, a web server and DataBase for automated Carbohydrateactive enzyme ANnotation.
For the eH isolate, 287 enzymes were predicted (Figure  S2 ; Table  S1 ): 89 Glycoside Hydrolases (GH), 111 Glycosyltransferases, 47 Carbohydrate Esterases (CE), 7 Polysaccharide Lyases, 23 Carbohydrate-Binding Modules (CBM), and 10 Auxiliary Activities. GH18, CE4 and CBM18 were the most abundant enzymes (respectively 19, 21, 7 were predicted) within some of these groups. Amongst these 287 eH genes with predicted carbohydrate-active enzyme activity, 223 matched with e3 genes. The list of CAZymes was similar in both the eH and e3 genomes. Using SignalP and TMHMM to predict the secretome, 741 protein sequences were found to harbor a secretion signal prediction without transmembrane helix. Furthermore, 543 sequences corresponded to small proteins (less than 450 amino acids). Schwelm et al. (2015)  analyzed the e3 genome and predicted 553 secreted proteins including 416 with a length smaller than 450 amino acids.
Among the proteins with a signal prediction, 355 were common to e3 and eH genomes (Table  S2 ). The higher number of predicted proteins found in the eH genome could be due to the annotation using Eugene which probably created more gene sequences compatible with secretome pattern detection. In addition, the use of updated software versions may have also upgraded the secretome. An additional annotation was carried out by blasting eH data against clubroot published sequences. All available sequence data for concerning eH and other P. brassicae isolates are summarized in Table  S3. Ninety-nine percent and 100% certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018.
brassicae isolate may allow more precise diagnostic molecular tools than the current pathotyping systems to be developed. These annotations were added to the corresponding eH genes using python scripts querying the Uniprot database. Using this updated annotation, the genes were classified into subsystems whose main terms are described in Figure  2. Most of the annotated genes were classed in the protein-binding (1,433) GO term category. This class, not accurately defined for their function, still remained high because of the lack of functional data in Plasmodiophorid genomics resources. Ninety-six genes encoding potential RNA-binding proteins having at least one RNA-binding domain were identified. This protein family could play a role in P. brassicae pathogenicity, as described in Ustilago maydis, the basidiomycete causative agent of corn smut disease  (Becht et al.
, 2005). From the InterPro (IP) database, the ankyrin repeat (258 and 259) was found to be the major protein domain. The ankyrin repeat is the most common protein-protein interaction motif in nature. It is predominantly found in eukaryotic proteins, but also in many bacterial pathogens which employ various types certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018. ; https://doi. org/10. 1101/335406 doi: bioRxiv preprint of secretion systems to deliver ankyrin-containing proteins into eukaryotic cells where they mimic or manipulate various host functions  (Al-Khodor et al. , 2010). In eukaryotes, proteins with ankyrin repeats are involved in many cellular functions, such as transcriptional regulation, signal transduction, cell cycle but also in virulence in Amoebae, suggesting an adaptation to their intracellular localization  (Molmeret et al.
Mitochondrial genome sequence In the circular genome representation (Figure  1 ), scaffold #43 showed a low GC content and one match with a P. brassicae mitochondrial gene (Siemens 2002, Unpublished, NCBI ID: AF537102). In addition, as a high AT content was found in some Plasmodiophorid mitochondrial genomes, for example in S. subterranea  (Gutiérrez et al. , 2014) , these observations suggested that the scaffold #43 could correspond to the P. brassicae mitochondrial genome. To ensure that no errors occurred in its assembly, a new assembly of this scaffold #43 was performed using software specifically designed for organelle assembly (NOVOPlasty). Both assemblies were similar suggesting consistent results. The newly assembled sequence of eH scaffold #43 is 102,962 bp, with a 24. 67% GC content (Figure  3 ) and is very similar (Max score = 91831, Total score = 1.
Metabolic pathway prediction Pathway Tools Software was used to create a P. brassicae specific database. Taking advantage of the improved annotation described here and available databases To validate the relevance and functionality of the ClubrootCyc database, the metabolic reconstruction was tested with available published transcriptomics data described by  Bi et al. (2016). Visual analysis of omics gene-expression, highlighted in Figure  S5 , showed that the major pathway was involved in fatty acid and lipid biosynthesis and degradation, consistent with the results of  Bi et al (2016)  who showed that lipid metabolism is enriched in cortical infection stage of gall development. The development of this P. brassicae -specific database is thus a useful tool for integrating transcriptomics data, gene and metabolic networks and to gain further information than just a list of over-or under-expressed genes between experimental conditions.
, 2017). They represent well-known virulence factors for several pathogenic fungi  (Jacobson, 2000)  and for bacteria  (Nosanchuk and Casadevall, 2003). Metabolic pathway prediction in P. brassicae is still, however, incomplete and poorly annotated because there is still not enough information in the reference databases. To make further progress in metabolic network reconstruction and modelling, appropriate gap-filling methods are required. For this, software is being developed to identify and add lacking pathways, such as Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks  (Prigent et al. , 2017). certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018.
certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint (which was not this version posted May 31, 2018. ; https://doi. org/10. 1101/335406 doi: bioRxiv preprint (Uniprot, Gene Ontology and ECdomainMiner), a Genbank entry was created. Using this file as input, the PathoLogic component of Pathway Tools could be used to create a new Pathway Genome DataBase (PGDB) containing the predicted P. brassicae metabolic pathways. The database is called ClubrootCyc (Figures 4 and S4) and predicts 115 pathways, 1,938 enzymatic reactions, 71 transport reactions, 4,468 enzymes, 123 transporters, and 1,567 compounds (https://pathwaytools. toulouse. inra. fr/CLUBROOT). It links genomic data to additional information such as protein annotation, enzymatic reactions and pathways.
Local pig breeds are adapted to the specific local environment and fed with various locally available feedstuffs. Besides their genetic merit for agro-biodiversity, they represent the basis for sustainable local pork chains. The present chapter aims to present history and current status of the Basque pig breed, its exterior phenotypic characteristics, geographical location, production system and main products. This French autochthonous breed of pigs, which almost disappeared few decades ago, seems now consolidated, thanks to a chain organization and recognised high-quality products (Protected Designation of Origin). Reproductive performance data reviewed from the literature and estimated from the LIGERAL database (herdbook) are presented. Available data on production traits including growth (early, middle, late and overall growth), feed intake, body composition and carcass traits are also summarized.
Productive performance 5. 1 Reproductive traits Basic data obtained on reproductive traits in this review are presented in Table  3. Averages are calculated from data recorded in the LIGERAL database. For the last available 5-year period (2012-2016), the average age of sows at the first parturition is 16. 6 months. On average, sows of Basque pig breed have 1. 6 litters per year with 7. 5 piglets born alive  [9]. The death rate of piglets until weaning in the considered study (last 5 years available period) of Basque pig breed averages 18. 9%. Published data are also synthesised in Table  3. Without selection on reproductive performances, a progressive decline in litter size (born alive and weaned piglets) had been seen until 2003. Then, a slight improvement was observed  [3]. Most recent No.
= number, mth = month, d = days. 1 Litters per sow per year calculated as the average number of litters per sow having at least one litter in the year. 2 Least squares mean with a GLM model including breed ( five local breeds), parity season as a fixed effect, breed*parity interaction, the age of the sow and birth year as a covariate. TREASURE data confirm this tendency with +0. 5 born alive and +0. 6 weaned piglets in the last 10 years. Technical improvement of farming can explain this. Duration of lactation is prolonged in comparison to modern intensive systems to 38. 5 days, which is also reflected in the prolonged farrowing interval (228 days on average). Thus, it can be concluded that Basque pig breed has moderate fertility compared to the most prevalent breeds.
Meat and fat quality Basic data obtained in this review with some of the most commonly encountered meat and fat quality traits measured in longissimus muscle and subcutaneous back fat tissue that could be compared are presented in Table  7. In the studies reporting meat quality of Basque pigs, pH measured in longissimus muscle at 45 minutes and 24 h post-mortem was between 6. 27 and 6. 63 and between 5. 54 and 5. 76, respectively (n = 4 studies). Loin meat from Basque pigs also exhibited high intramuscular fat content (over 3. 3% and with a maximum of 5. 7%; n = 6) and a dark colour (high Minolta a* value over 9. 3 in four out of five studies and moderate lightness with L* value within the 43-52 interval). Big differences in the SFA, MUFA and PUFA content of intramuscular fat in longissimus muscle were observed between the considered studies (n = 5 studies).