dataesr/scientific-paragraphs-categorization huggingface dataset:
The EPC formalism was an original language, in fact based on the conceptual transaction model of MERISE, even if it did not say so. It linked input events (connected by the usual logical operators AND, OR and XOR) to 'activities', themselves producing output events that become input events for downstream activities of the process. ARIS was supported by ARIS ToolSet, the number one EM tool in terms of commercial sales, and it has for a long time been the modelling tool recommended by SAP for planning the implementation of its ERP product. ARIS ToolSet is now marketed as ARIS Architect & Designer by Software AG (www. softwareag. com), in which BPMN is an alternative to the EPC language and a Product/Service View has been added. A free-ofcharge tool named ARIS Express can be downloaded from the Net (www.
Resource inputs of activities refer to 'resources' required to carry out the activity function. Resources are enterprise objects that play the role of support in the execution of activities. They can be active resources (sometimes called 'functional entities' like in CIMOSA), i. e. entities able to send and receive messages and perform 'functional operations', or passive resources, i. e. simply inert components. Active resources can either be human agents, technical agents (i. e. machines with a controller) or IT-based agents (software packages, cyber agents or database systems). Resources are characterised by typical properties (such as availability, capacity or reliability features), the list of functional operations that they can execute and the set of capabilities or competencies that they can offer.
S1 , Supplementary Material online). We previously reported that these genes have probably been acquired horizontally by the virus from an ancestral insect before the Leptopilina diversification  (Lepetit et al. 2016; supplementary figs. S1 and S2A, Supplementary Material online). Two of them (ORFs 27 and 66) are predicted to encode inhibitors of apoptosis, whereas ORFs 11 and 13 encode a putative demethylase  (Lepetit et al. 2016). These two last genes may derive from a single horizontal transfer followed by a subsequent gene duplication  (Lepetit et al. 2016 ). In the following section, we will focus on the second class of genes identified by this BLAST analysis. Leptopilina Species Captured 13 Viral Genes from an LbFV-like Virus More surprisingly, we found clear evidence that a massive integration of viral DNA into wasp genomes occurred before the diversification of the Leptopilina genus and most likely after the divergence between Ganaspis and Leptopilina (Table  1 ).
boulardi (supplementary fig. S16A , Supplementary Material online) or the bacteria Wolbachia in L. heterotoma (supplementary fig. S16B , Supplementary Material online). In addition, several typical intron-containing eukaryotic genes were predicted in the vicinity of these genes (depicted in gray in fig. 1 ). Note that apart from these 13 loci specifically found in Leptopilina genomes, most flanking Leptopilina-predicted proteins were also detected in both The evolutionary history of the 13 genes is consistent with a horizontal transfer from an ancestor of the virus LbFV (or a virus closely related to this ancestor) to Leptopilina species (fig. 2 ). Indeed, when other sequences with homology to the proteins of interest were available in public databases, the three wasp genomes always formed a highly supported monophyletic clade with LbFV as a sister group of Leptopilina sequences  (ORFs 58, 78, 92, 60, 68, 85, 96).
In addition, for the six remaining phylogenies (for which no homologs were available in public databases), the midpoint rooting method always led to similar topologies with LbFV as the sister group of Leptopilina sequences. Furthermore, the divergence LbFV-Leptopilina relative to the divergence among Leptopilina species was identical for both types of loci (supplementary fig. S17 , Supplementary Material online), further suggesting that both loci have the same evolutionary history. Interestingly, it appeared from the analysis of ORF60, that before being transferred to Leptopilina wasps, the gene has probably been acquired by the donor virus from an ancestral bacterium (fig. 2 ). The clustering of most of these loci on the same scaffold in L. boulardi (8 out of 13 on scaffold 159, N ¼ 75,550 scaffolds, see fig.
S26 , Supplementary Material online). This strategy allowed the identification of a total of 383 proteins, of which 236 were found in both replicates. Among these proteins, as expected, we were able to reproducibly identify typical virulence proteins known to be part of VLP content (such as the RhoGAP LbGAP  [Colinet et al. 2007 ], superoxide dismutase  [Colinet et al. 2011] , serpin  [Colinet et al. 2008] , or calreticulin  [Zhang et al. 2006] ) confirming that we correctly purified the proteins (supplementary table S10, Supplementary Material online). We also reanalyzed a similar VLP proteomic data set obtained by others  (Heavner et al. 2017 ) on the related species L. heterotoma. First, both L. boulardi and L. heterotoma data sets indicated enrichment for similar gene ontology terms, further suggesting that we correctly purified the VLP proteins (supplementary tables S8 and S9, Supplementary Material online).
Wasp Genome Sequences and Annotation We previously reported the genome of L. boulardi, strain Sienna (accession number: PQAT00000000) which has been obtained from the sequencing of a single female  (Varaldi and Lepetit 2018). Although this female was infected by LbFV, the draft genome does not contain contigs belonging to the virus genome as we removed them by comparison to the published virus genome sequence  (Lepetit et al. 2016). The assembly was performed using IDBA_ud  (Peng et al. 2012)  followed by a scaffolding step with assembled RNAseq reads using the software L_RNA_scaffolder  (Xue et al. 2013). We sequenced the genomes of the related L. heterotoma (Gotheron strain, accession number RICB00000000), the more distantly related G. brasiliensis (Va strain, accession number RJVV00000000), and an uncharacterized G.
sp emerged from Drosophila collected in Brazil (Cabo Frio, RJ, accession number WNHD00000000). Leptopilina heterotoma is refractory to infection by LbFV  (Patot et al. 2012) , and no reads mapping to LbFV genome have been found neither in L. heterotoma nor in G. brasiliensis or G. sp data sets. We extracted the DNA of a single female abdomen using Macherey-Nagel columns, similarly to what was performed for L. boulardi  (Varaldi and Lepetit 2018). The DNAs were then used to prepare paired-end Illumina libraries using standard protocols  (TruSeq PE Cluster v3, TruSeq SBS 200 cycles v3, TruSeq Multiplex Primer). The libraries were then sequenced on a Hiseq2500 (for Lh, 2 Â 100 bp, insert size ¼ 418 bp) or Hiseq3000 (2 Â 150 bp; for Gb: insert size ¼ 427 bp, for G. sp: insert size ¼ 438 bp) machine on the Genotoul sequencing platform.
Similarly to what was done for L. boulardi, the drafts of L. heterotoma, G. brasiliensis, and G. sp were obtained after assembling genomic DNA reads with IDBA_ud  (Peng et al. 2012). For L. heterotoma assembly, this was followed by scaffolding using publicly available assembled RNAseq reads  (Goecks et al. 2013 ) by running the software L_RNA_scaffolder  (Xue et al. 2013). This RNAseq scaffolding step was not performed for Ganaspis species because no RNAseq reads were available for these species in public databases. The genome of an asexual strain of L. clavipes (strain GBW) which is not infected by LbFV was obtained and is described in  Kraaijeveld et al. (2016)  (accession number JUFY00000000). To have comparable assembly strategies, we included an additional RNA scaffolding step using publicly available sequences  (Misof et al.
3. 4. 1  (Langmead and Salzberg 2012)  and samtools version 1. 8  (Li et al. 2009) , removing contaminant reads (from viruses, prokaryotes, and microbial eukaryotes) with Kaiju 1. 6. 2 used with the NRþeuk 2018-02-23 database  (Menzel et al. 2016) , k-mer frequencies were established from the remaining reads for each species using Jellyfish 2. 2. 9 (Marcais and Kingsford 2011) and k ¼ 21 (default value). From these 21-mers distributions, genome size was estimated with findGSE  (Sun et al. 2018 ) used with default parameters. These estimates were then used to run DNAPipeTE version 1. 3  (Goubert et al. 2015)  (two samples per run, 0. 1Â coverage per sample) in order to assess the repetitive fraction of the genomes. Finally, independent estimates from flow cytometry experiments were obtained for L.
Species Tree Based on 541 "universal arthropod" genes identified by the BUSCO pipeline  (Simão et al. 2015) , a species tree was constructed for L. heterotoma, L. boulardi, L. clavipes, G. brasiliensis, and G. sp, using Apis mellifera as outgroup. The protein sequences were aligned using the bioconductor msa package  (Bodenhofer et al. 2015). Individual alignments were concatenated and a phylogenetic reconstruction was then performed using PhyML (parameters: -d aa -m LG -b -4 -v e -c 4 -a e -f m)  (Guindon et al. 2010). In total, 248,282 variable sites were found and the branch supports were computed using approximate likelihood ratio test (aLRT). We also constructed a tree for ten Leptopilina species and G. brasiliensis using publicly available sequences of ITS2. Alignment was performed with muscle and a phylogeny was obtained with PhyML (parameters: -d nt -m GTR -b -4 -v 0.
dN/dS Calculation The coding sequences of "universal arthropod" BUSCO genes identified in the three Leptopilina species were extracted and we first aligned the corresponding proteins using MUSCLE v3. 8. 1551  (Edgar 2004 ). Then, the sequences were reversealigned using the protein alignments as a guide (pal2nal v14;  Suyama et al. 2006). We then computed the value of x (dN/dS) in all branches of the species tree using CodeML  (Yang 2007)  as implemented in the Python package ete3  (Huerta-Cepas et al. 2016). We used the free-ratio model to estimate the x ratio for tree branches. Each model was run three times with different starting values and we selected the model with the highest likelihood (starting x values ¼ 0. 2, 0. 7, 1. 2). Then, a global x ratio for all the tree was calculated as the tree length for dN divided by the tree length for dS.
Protein Sequencing Proteins extracted from purified VLPs were stacked in the top of an SDS-PAGE gel (4-12% NuPAGE, Life Technologies), stained with Coomassie blue R-250 and in-gel digested using modified trypsin (Promega, sequencing grade) as previously described  (Salvetti et al. 2016). Resulting peptides were analyzed by online nanoliquid chromatography coupled to tandem mass spectrometry (UltiMate 3000 RSLCnano and Q-Exactive HF, Thermo Scientific). Peptides were sampled on a 300 lm Â 5 mm PepMap C18 precolumn and separated on a 75 lm Â 250 mm C18 column (Reprosil-Pur 120 C18-AQ, 1. 9 lm, Dr Maisch) using a 120-min gradient. MS and MS/ MS data were acquired using Xcalibur (Thermo Scientific). Peptides and proteins were identified using Mascot (version 2. 6) through concomitant searches against the homemade L.
boulardi database (see above for details), classical contaminant database, and the corresponding reversed databases. The Proline software (http://proline. profiproteomics. fr) was used to filter the results: conservation of rank 1 peptides, DiGiovanni et al. doi:10. 1093/molbev/msaa030 MBE peptide identification false discovery rate < 1% as calculated on peptide scores by employing the reverse database strategy and minimum of one specific peptide per identified protein group. Proline was then used to perform a compilation, grouping, and spectral counting-based comparison of the protein groups identified in the different samples. Proteins from the contaminant database were discarded from the final list of identified proteins.
Annotation of Viral Genes We used a PSI-BLAST approach (BLOSUM45) using the 13 LbFV proteins as queries, on refseq (accessed July 15, 2019). In case no hit was found, a second round was performed using nr as database. In addition, we searched for the presence of conserved domains in the 13 LbFV proteins horizontally transferred to Leptopilina species using the hmmer webserver (https://www. ebi. ac. uk/Tools/hmmer/, accessed May 5, 2018).
Acknowledgments This work was supported by a grant from the  Agence Nationale de la Recherche (ANR)  to J. V. ( 11-JSV7-0011  Viromics). We thank the  LABEX ECOFECT  ( ANR-11-LABX-0048 ) for financial support for the internship of D. D. G. and  B. Bitner-Mathe  ´and the Brazilian programs  FAPERJ  and  CAPES/ PVE-2012  for visits to UFRJ. Proteomic experiments were partly supported by the  Agence Nationale de la Recherche  ( ProFI  Grant  ANR-10-INBSQ6 ). The bioinformatic work was performed using the computing facilities of the  CC LBBE/ PRABI. We thank  Shubha Govind  for kindly providing the Ganaspis brasiliensis strain,  Elzemiek Geuverink  for providing Leptopilina clavipes samples,  Ken Kraaijeveld  for providing access to raw Illumina reads of L. clavipes,  D. Colinet  and  N. Mortimer  for sharing mass-spec data and analysis,  D.
Kahn  for advices on data analysis, and  N. Burlet  for help in the lab. We also thank  PCI Evol Biol reviewers  for helpful comments on an earlier draft which has been reviewed and recommended by  Peer Community in Evolutionary Biology  (https://dx. doi. org/10. 24072/pci. evolbiol. 100062). Scripts used for this publication are available at https://doi. org/10. 5281/zenodo. 1889392.
99 0. 99 HspNPV SjNPV 0. 87 Lc 0. 99 0. 89 0. 89 Lb Lh Lc 0. 92 Lb 0. 99 0. 78 0. 99 MdSGHV Lb 0. 84 Lc 0. 97 Lh LbFV PoGV 0. 1 Lb 0. 5 LbFV 0. 2 Lh 0. 2 GpSGHV ORF87 ORF92 ORF94 ORF96 LbFV GpSGHV Lb 0. 5 LbFV 1 GpSGHV MdSGHV Lh 1 Lc Lb 0. 94 Lc Lc Lc 0. 96 Lh Lh 1 Lb 0. 2 Lb LbFV 0. 2 Lh 0. 2 LbFV ORF107 LbFV Lb Lc 0. 88 0. 2 Lh FIG. 2. Phylogenetic evidence for a massive horizontal transfer of 13 viral genes into the genome of Leptopilina wasps. The names of the ORFs refer to the ORF number in LbFV genome. Blue, red, and green colors represent, respectively (supposedly), eukaryotic, viral or bacterial branches. Only aLRT supports P 0:7 are shown. The midpoint rooting method was used. Accession numbers of the corresponding sequences are available in supplementary table S5, Supplementary Material online.
ORF Query Representative Description n Sequences Domains Dom. Name Dom. Pos Dom. e-Value Length (min e-value with this description) ORF5 696 - None ORF58 1,308 DNA polymerase (4e-72) >500 DNA_pol_B PF00136. 20 639-870 1:4310 À24 ORF60 362 Lecithin-cholesterol acyltransferase >500 LCAT PF02450. 14 76-172 6:7310 À11 (LCAT) (10 À55 ) ORF68 645 ATP-dependent DNA helicase >500 PIF1-like helicase PF05970. 13 124-167; 3:3310 À8 ; (2310 À35 ) 248-320 3:5310 À6 ORF72 106 Toll-like receptor (2310 À27 ) 5 7 ORF78 676 DNA-directed RNA polymerase sub- >500 RNA_pol_Rpb1_2 PF00623. 19 358-415 5:4310 À7 unit (4310 À54 ) ORF83 433 - None ORF85 215 Ac81 (1310 À62 ) 41 Ac81 PF05820. 10 56-201 1:3310 À25 ORF87 176 FAD-containing oxidoreductase >500 (nr) (1310 À29 ) ORF92 1,593 DNA primase/helicase (4310 À35 Þ 206 ORF94 182 N-acetyl-D-glucosamine kinase 418 (5310 À51 ) ORF96 1,049 Lef-8 like protein (DNA-directed RNA 3 (nr) polymerase subunit) (3310 À26 ) ORF107 625 - None NOTE.
Their contribution to the diagnosis of the pulmonary function remains to be elaborated. Results obtained here for a healthy subject are instructive in terms of pulmonary mechanics, and this is well illustrated in the trajectories shown in Fig. 2. If we assume that normal breathing results from the concurrent action of the diaphragm and the intercostal muscles, the normal trajectories are expected to stand between the two extreme diaphragmatic and thoracic cases. In normal breathing, trajectories are indeed diagonally oriented and they show, as a result, very little amount of motion hysteresis. The latter could also be explained by the fact that total ventilation volumes were experimentally lower during the normal breathing experiment than during the thoracic and diaphragmatic ones. Axial, sagittal and coronal views from the 3D UTE dataset at the end of expiration, and over which are superimposed the regional flow-volume loops estimated with 3D MR Spirometry (only one every 20 th ) for thoracic breathing.
For each local loop, the global loop representing the flow-volume for the entire lung is also drawn for reference (green). In the bottom right-hand corner, we showed the color and axis conventions for the local and global loops. The main strength of the technique is to be based on 3D motion corrected MR images, namely on complete 4D MR dataset. As seen above, the parameters we have explored can be quantified, first, everywhere in the lung, second upon the actual 3D motion field of the lung parenchyma. The latter is very important because, from a Lagrangian point of view, each elementary volume of lung tissue follows a trajectory in a 3D space. If this trajectory is extracted from a space with a lower number of dimensions (2D MR images or 2D projection images, for example), the information is inherently incomplete and leads to quantification biases.
In any case, an MRI system is far more cumbersome and expensive than a standard spirometer. It is not available today in any pulmonology department and might not be in the near future. Three-dimensional MR Spirometry was performed here with data acquired over 11 min. This total acquisition time may be reduced either by future improvements of the image acquisition procedure or by compromises with the final image quality (voxel size, SNR, under-sampling artifacts, …). Yet, it will be difficult to soon achieve the acquisition of a sufficient amount of data in less than several tens of seconds. This minimal acquisition time covers several quasi-periods of nominal respiratory motion, which requires averaging of data from different respiratory cycles. Even though respiratory motion is not fully repeatable from one motion period to the other, if inspiration and expiration phases are separated and if the outlying motion states are discarded in the post-processing steps as implemented in this work, the motion can fairly be considered repeated for any given MR-gate and time averaged, while spatial resolution can be degraded above the millimeter scale.
Motion correction and image reconstruction protocol. The respiratory self-navigator was extracted from the real and imaginary parts of the first point acquired at the beginning of each spoke, for each of the 30 channels of the thoracic reception coil array, thanks to a Principal Component Analysis (PCA). After being checked against the signal outcome from the respiratory belt, this self-navigator was taken as a surrogate signal for respiratory motion correction. This correction was retrospectively applied onto the MR dataset with 32 motion bins defined upon the intrinsic surrogate signal, with 16 bins for the inspiratory phase and 16 bins for the expiratory phase. During the binning process, a view sharing strategy  42  was performed; outlying respiratory periods were discarded; and spoke weights were computed with a soft-gating approach  43.
A time-stamp was given to each bin. It was computed as the average over the total acquisition duration of the acquisition times of every spoke within the bin, with respect to the time of the end of expiration for the same motion period, taken as the reference motion phase. The bins were then reconstructed with parallel imaging (iterative SENSE  44  ) and compressed sensing  45  (3D wavelet space L1 minimization) strategies proposed by the open Berkeley Advanced Reconstruction Toolbox (BART  46  ). Sensitivity maps for parallel reconstruction were estimated from the k-space data (autocalibration) through the ESPIRiT 47 method in BART.
Acknowledgements The PET/MR platform is affiliated to the  France Life Imaging network  (grant  ANR-11-INBS-0006 ). This work was partially supported by  NIH  grant  R01HL136965. We sincerely acknowledge  Dr. Jean-Luc Gennisson ,  Dr. Thomas Similowski ,  Dr. Pierantonio Laveneziana ,  Dr. Christian Straus ,  Dr. Dominique Chapelle  and  Dr. Martin Genet  for open fruitful discussions.
Therefore, the partitioning of U and Zr between the metal and oxide layers determines both position and thickness of the metal layer. Hence, in the context of the In-Vessel Retention (IVR) analysis, it is essential to be able to predict this partitioning. Further, because of the computational cost of thermochemical equilibrium calculations, it is interesting to have a fast-running model, to evaluate the composition of the metal phase and its relative mole fraction with respect to the oxide. This is the objective of the work presented in this paper. In a first part, some characteristic features of the two phases at equilibrium are identified, from the results of thermochemical calculations using the NUCLEA database. From those characteristic features, a simplified representation of the quaternary (U, Zr, F e, O) system is provided showing that it can be represented as two pseudo-binary systems, in each phase.
A set of non-ideal solution based thermodynamic database, called NUCLEA database. 2. A toolbox of computational thermodynamics, referred to as NUCLEA toolbox. Simply put, NUCLEA is a self-sufficient database cum computational tool designed for the calculation of thermochemical equilibria. It is specially developed for in-and ex-vessel nuclear applications, related to severe accident scenario. NUCLEA database contains 18 + 2 elements: O -U -Zr -Ag -In -B -C -F e -Cr -N i -Ba -La -Sr -Ru -Al -Ca -M g -Si + Ar -H and includes the following 15 oxide systems:   (2007). To supplement the database, NUCLEA also comes with a Gibbs function minimization solver. Such a solver with all its functionalities are integrated within NUCLEA toolbox in the form of a Python Application Program Interface (API).
C sz It is the global ratio of Fe to Zr atoms. Depending on local configurations and timing in the accident scenario, the value of C sz may vary between 0 and rather large values, although the global value is typically around 1 for many reactors designs and accident scenarios. N z = 1 (1) N u = N z C uz = C uz (2) N o = 2(C uz + C ox ) (3) N s = N z C sz = C sz (4) N tot = N z + N u + N o + N s (5) where N tot is the total number of moles and C sz is the global F e/Zr ratio. For all thermochemical analysis, the version of thermochemical database used is NUCLEA-17 1. The present study deals with the miscibility gap where two liquid phases (oxide + metal) coexist. NUCLEA-17 1 calculations show that two liquid phases are obtained only in the temperature range between 2900K and 3100K. Thus, this study is valid in this range of temperature.
Illustration of Fit to NUCLEA Thermochemical Calculations for Various Inventory Compositions In this section we show the quality of fit, made by the derived simplified model, for the NUCLEA calculations. Method of Least Squares have been used to fit the NUCLEA data by the derived simplified model, which has lead to the deduction of the values of fit parameter (m). Fig. 8 , shows fit data (coloured lines) to the NUCLEA data (coloured dots), corresponding to C uz = 1. 0 and C ox = 0. 3. It can be seen that the model fits quite well to the thermochemical calculations. The value of fit parameter (m) for this case is found to be 0. 0948. The value of other fit parameter (b) can be calculated from Eq. (  42 ). Similarly, fits for thermochemical calculations, obtained for other values of C uz and C ox , can be seen in Figs.