dataesr/scientific-paragraphs-categorization huggingface dataset:
For the predicted rotation profile, we also aim to make a comparison with observations. In Sect. 2, we describe the fundamentals of the ESTER code and the improvements made. In Sect. 3, we compare the predictions of the 2D models, especially the predicted rotation profile, with asteroseismic measurements of a massive star. We show that the predictions of the 2D model are consistent with the observations. In Sect. 4, we discuss the contribution of meridional circulation to nitrogen enrichment as predicted by 2D models. Finally, we conclude in Sect. 5.
ESTER models In this work, we make use of new ESTER models where time evolution has been implemented. We recall that ESTER models are 2D models of rotating stars that include the centrifugal distortion of the star and the associated baroclinic flows. These models therefore predict the structure (pressure, density, and temperature distributions) and the associated large-scale flows, namely the differential rotation and meridional circulations. The first version of the ESTER code, which computes the steady states of early-type star models (Espinosa Lara & Rieutord 2013), has now been completed with a time evolutive version that includes the unsteady terms needed to follow the thermal and nuclear evolution of a star. The code solves the set of equations given in Appendix A, still assuming the axisymmetry of the star.
Conclusions In this Letter, we present the first results of a 2D modelling of rotating stars including time evolution. These new models are an update of the 2D ESTER models designed by Espinosa Lara & Rieutord (2013), which compute steady 2D models of fast rotating stars. As in the steady models, the timedependent ones take into account the centrifugal flattening of the star as well as the large-scale flows (differential rotation and meridional circulation) driven by the baroclinicity of the star. We ran two 12 M models of a massive star with initial angular velocities of 15 and 50% of the critical one, respectively. The first model has a rather mild rotation rate but can be compared to the recent observation of a massive star, while the second model allowed us to test the performance of the code and revealed some new features of the internal dynamics of a massive star (see below).
Acknowledgements. The authors are grateful to the referee prof. Georges Meynet  for his comments and suggestions. The research leading to these results has received funding from the  French Agence Nationale de la Recherche (ANR) , under grant  MASSIF  ( ANR-21-CE31-0018-02 ). The authors thank  Siemen Burssens  for providing the MESA setup. Computations of ESTER 2D-models have been possible thanks to HPC resources from CALMIP supercomputing center (Grant  2023-P0107 ).
Introduction With over 15,000 living species, Decapoda represents a diverse order of Crustacea that includes lobsters, crayfish, crabs, prawns, and shrimps  [1]. They are a crucial component of marine and freshwater ecosystems  [2, 3]. The Decapoda order originated around 455 million years ago, in the Late Ordovician, and is divided into two suborders: the Dendrobranchiata (commonly known as prawns) and the Pleocyemata. The latter encompasses Caridea (swimming shrimps) and a crawling/walking group called Reptantia that consists of Achelata (spiny lobsters), Astacidea (true lobsters and crayfish), Anomura (hermit crabs), and Brachyura (short-tailed crabs)  [4]. Decapoda are characterized by highly variable genome sizes. According to the Animal Genome Size Database (https://www. genomesize. com, accessed on 17 May 2022), genome size estimates range from 2.
To address these limitations, we designed a standardized protocol for RE annotation that encompasses both TEs and satDNAs. This pipeline was used to establish the RE landscape of twenty Decapoda and six other Crustacea, enabling an objective comparison of the Decapoda repeatomes in terms of abundance, composition, and evolutionary dynamics. Our standardized approach allowed us to assess the contribution of REs to the evolution of the enigmatic Decapoda genomes. Furthermore, we explored the possibility of using the REs as reliable phylogenetic markers for Decapoda. Lastly, this study also provides a new library of REs in Decapoda genomes that extends the existing databases and can be used for future analyses.
Genomic Datasets Available assemblies for Decapoda species were downloaded from NCBI GenBank and RefSeq (last accessed 16 February 2022). Contig and scaffold N50 are useful values to estimate the contiguity of the genome by indicating the length of the shortest contig or scaffold that cover 50% of assembly. However, Decapoda genomes present variable N50 values (Table  S1 ). The BUSCO completeness score, which can be independent of the contiguity of the genome, was also determined for each genome to assess the completeness of the assemblies (Table  1 )  [45]. Only the 20 genomes with a BUSCO completeness score of at least 25% were selected. Considering the low number and fragmentation status of available Decapoda genomes, a lower BUSCO score threshold than usually used was chosen to retain at least one genome in all infraorders that had genome assemblies.
To obtain a broader perspective of the landscape of Decapoda REs compared to crustaceans, we added 6 non-Decapoda crustaceans (Table  1 ). This allowed us to see if Decapoda species have a different or similar trend in terms of the proportion of the individual repeat families, the presence/absence of RE families, and finally their evolutionary trajectories in comparison to six other Crustacea. For each species, a set of Illumina paired-end reads was randomly chosen in the SRA database (Table  1 ). Reads that mapped to the mitochondrial genome were discarded, and the remaining reads were sampled to represent 1. 6% of estimated genome size. Genome size estimations were retrieved for all genomes, except for Chionoecetes opilio (Table  1 ). For this genome, all short paired-end reads corresponding to the assembly were downloaded and the genome size was estimated using KmerGenie version 1.
Statistical Analysis In order to test for correlation between genome size, assembly size, repeats, or TE load (number of copies) or percentage, we used a linear regression model and the Spearman rank sum method with α = 0. 005 using R package ggplot2 with lm method. A dendrogram was produced by calculating pairwise distances between repeat profiles (the pattern of presence and absence of repetitive elements) using hclust with the Euclidean method, and the heatmap was plotted using Orange3  [68]. The sequence divergence distribution was calculated as Kimura distances (rates of transitions and transversions) using the RepeatMasker tools "calcDivergenceFromAlign. pl" and "createRepeatLandscape. pl".
Construction of Repetitive Elements Reference To obtain a comprehensive view of REs in Decapoda and reduce the number of elements classified as "unknown", we developed a standardized protocol to annotate TEs and satDNAs at the genomic level (see Methods and Figure  1 ). This pipeline integrates the consensus sequences of the Arthropoda section of the RepBase database and the de novo identification of REs in all species by a combination of RepeatModeler2 and the TAREAN pipeline, in order to generate an extensive library of consensus sequences. The TAREAN pipeline was used to specifically identify satDNAs. Due to their structure and high sequence homogeneity, satDNAs are extremely difficult to assemble and are often excluded from the assembly  [12]. Therefore, we searched for satDNAs in Illumina raw reads paired-end sequences using the TAREAN pipeline to construct the "Satellite libraries".
(2007)   [35]  is widely used, but new TEs have been characterized since the establishment of the classification in 2007, resulting in conflicts in TE databases. Kojima (2019)   [37]  improved the classification of the RepBase database  [40] , but TE annotations can differ between RepBase, RepeatModeler2 database, and DFAM due to capital letters or multiple naming of the same element, for example. A manual correction of repeat names was thus applied when needed in order to obtain a clear annotation. All libraries generated by RepeatModeler2, the TAREAN pipeline, and RepBase were merged into a single library. This extensive database contains a total of 71,601 sequences including sequences from RepBase. Among these families, known TEs represent 31,579 sequences. With this new merged library, we considerably extended the number of annotated families compared to the RepBase database of Arthropoda REs.
Indeed, RepBase provides consensus sequences of 13,906 repetitive elements in Arthropoda, including 109 satDNAs. These elements are distributed in 218 Arthropoda species and in Eukaryota or Metazoa common ancestors. However, only sixteen Crustacea and six Decapoda species are represented, with 1419 and 328 sequences, respectively. Moreover, most Decapoda sequences (320) are from a single species, P. vannamei, as repeats from other species have not been submitted to RepBase. This shows the lack of knowledge of REs in Decapoda species in established databases. Our work also extended the number of known satDNA families in Decapoda species, with 405 consensus sequences compared to the 109 present in RepBase. The new REs identified in this study are provided in Supplementary Materials (Figure  S1 ).
Annotation of Repetitive Elements in Decapoda Genomes With our new extensive database, we performed two rounds of annotation using RepeatMasker. In the first round we only used known TEs in order to have a better characterization and reduce the proportion of unknown TEs, and in the second we used all the remaining REs. We identified between 6805 and 31,798 consensus RE sequences in the different assemblies (Table  2 ). This represents an increase of approximately 16,500 families on average in Decapoda compared to previous annotations and 6500 for the other Crustacea. Moreover, our standardized protocol successfully identified the type of REs that were previously unclassified for most species (now between 4. 40% and 24. 15%). This represents a considerable improvement over the results obtained with the widely used species-specific databases.
3%. Unclassified elements were less frequent in the Dendrobranchiata suborder, with around 3. 5%, probably because of the better characterization of REs in this suborder in the RepBase database, with the almost exclusive presence of annotations derived from P. vannamei. Therefore, more divergent species present a higher proportion of unclassified elements, such as E. affinis with 24. 15%. The content variability suggests that the different suborders of the studied crustacean species have specific major REs present in their genomes. According to RE studies of Decapoda species included in assembly publications, the proportion of REs varies from 8% to 82%  [48] [49] [50] [51] [53] [54] [55] [76] [77] [78] [79] [80] [81] [82] [83] [84]. Tan et al. (2020)  annotated the repeatome of eight decapod species and estimated repetitive content between 27% and 50%, with the majority of the genomes having more LINEs, except for P.
vannamei, which had more DNA transposons  [54]. Compared to these studies, we annotated approximately 10% more repeats with our pipeline. For the P. virginalis genome, 8. 8% of repetitive elements were retrieved in the assembly Pvir0. 4 (GenBank accession: GCA_002838885. 1) and 27. 52% in the study of  Tan et al. (2020)   [54]. However, in the assembly DKFZ_Pvir_1. 0 (GenBank accession: GCA_020271785. 1), the new assembly version used in this study, we annotated 57. 87% of repetitive elements  [51, 55]. In the assembly of P. clarkii, Xu et al. (2021) annotated 82. 42% of repeats, while in our study, we observed only 71. 26% (Figure  2 ). For the P. platypus genome, we observed similar overall results to Tang et al. (2021) (Figure  2 )  [56]. However, the percentages of LINEs and LTRs are increased by almost 10% each, while unknown TEs were reduced to 17%.
Compared to non-Decapoda Crustacea, Decapoda have a higher proportion and number of REs in their genome. Moreover, the pattern of RE families present in Decapoda is well-conserved across species. With our protocol, we showed that the combination of repeat libraries of all species provides an excellent tool to analyse content and diversification of repetitive elements with on average 8% more categorized elements. The new consensus sequences can improve the annotation of TEs in other Crustacea or Arthropoda species by increasing the number of consensuses for homology searches. We suggest using this two-step pipeline for all repeatome studies on non-model organisms that are often underrepresented in public databases. Our pipeline provides a baseline for future genomic analysis, producing standardized and reproducible analyses that will allow for much more rigorous and complete comparative analysis of repeats in non-model organisms.
4 (GenBank accession: GCA_002838885. 1) an 27. 52% in the study of Tan et al. (2020)   [54]. However, in the assembly DKFZ_Pvir_1 (GenBank accession: GCA_020271785. 1), the new assembly version used in this study, w annotated 57. 87% of repetitive elements [51, 55]. In the assembly of P. clarkii, Xu et al. (202 annotated 82. 42% of repeats, while in our study, we observed only 71. 26% (Figure2). F the P. platypus genome, we observed similar overall results to Tang et al. (2021) (Figure [56]. However, the percentages of LINEs and LTRs are increased by almost 10% eac while unknown TEs were reduced to 17%. The percentage of REs in E. sinensis w.
GenBank accession: GCA_002838885. 1) an 27. 52% in the study of Tan et al. (2020) [54]. However, in the assembly DKFZ_Pvir_1 (GenBank accession: GCA_020271785. 1), the new assembly version used in this study, w annotated 57. 87% of repetitive elements [51,55]. In the assembly of P. clarkii, Xu et al. (202 annotated 82. 42% of repeats, while in our study, we observed only 71. 26% (Figure 2). F the P. platypus genome, we observed similar overall results to Tang et al. (2021) (Figure [56]. However, the percentages of LINEs and LTRs are increased by almost 10% eac while unknown TEs were reduced to 17%. The percentage of REs in E. sinensis w.
4 ( 4 GenBank accession: GCA_002838885. 1) an 27. 52% in the study of Tan et al. (2020) [54]. However, in the assembly DKFZ_Pvir_1 (GenBank accession: GCA_020271785. 1), the new assembly version used in this study, w annotated 57. 87% of repetitive elements [51,55]. In the assembly of P. clarkii, Xu et al. (202 annotated 82. 42% of repeats, while in our study, we observed only 71. 26% (Figure 2). F the P. platypus genome, we observed similar overall results to Tang et al. (2021) (Figure [56]. However, the percentages of LINEs and LTRs are increased by almost 10% eac while unknown TEs were reduced to 17%. The percentage of REs in E. sinensis w.
The DNA Features pipeline is the analysis pipeline at EMBL-EBI that annotates repeat elements, including transposable elements. With Ensembl's goal to stay at the cutting edge of genome annotation, we proved that this pipeline needed an update. We then created a new analysis that allowed the Ensembl database to store the repeat classification from the PGSB repeat classification (Recat). This new dataset was then fetched using Perl scripts and used to prove that the pipeline modification induced a gain in sensitivity. Finally, we performed a comparative analysis of transposable element distribution in all plant species available, raising new questions about transposable elements in certain branches of the taxonomic tree.
Quality control of repeat distribution tables All repeat distribution tables found using both of the methods described in the previous paragraph had to have a quality at least equivalent to the previous standard. A table could still pass quality control if in a repeat type a superfamily-related row was missing, but all other family rows for this type were present. In that particular case, statistics for the missing row were considered zero. The various classifications used in the articles were normalized using the PGSB repeat classification  (Nussbaumer et al. , 2013). Due to the quality control, processing of annotation statistics was only performed on eight of the 53 species (including a cultivar) present in the database: two genome-wide repeat distribution studies were found for Brachypodium distachyon  (Initiative, 2010)  and Amborella trichopoda  (Zuccolo et al.
Comparative analysis of repeat elements distributions The file containing all repeat element features extracted from the Ensembl database was post-processed by a Perl script to remove every line that was not a transposable element. All REcat keys that had four levels of classification (group, class, type, superfamily, or "unclassified") were then extended with an additional "unclassified" level, and every REcat key with six levels (group, class, type, superfamily, family, and "unclassified") was trimmed of their "unclassified" final classification level, using a second Perl script. This modification led to 100 unique REcat keys with five levels. Finally, the processed repeat feature data were treated by a third Perl script. This script used a multi-dimensional hash table as a data structure, with the REcat keys as keys and the species name as value, with this species name also a key for an array of four key metrics, as follows: a binary value for the presence or absence of a key in the given species, number of copies, feature coverage in bp, and feature coverage in the percentage of the genome covered.
To compute and visualize the distributions of repeat elements in plant species, all four types of values for every key/species couple were stored in four R vectors and then converted into four matrices of 53 (for 53 species) rows by 100 (for 100 unique REcat keys) columns. The dist R module set up distance matrices for the initial 53 by 100 matrices. This module was used with default parameters, except for the "presence/absence" matrix, where the distance parameter used was "binary", as the values for this particular matrix were binary. Then, the distance matrices were processed with the hclust module, also with default parameters, to build clusters from the distance values and then creating views in the form of dendrograms (Figure  2 ). The values of the distance matrices have also been visualized in a heatmap (Figure  3 ).
RepeatMasker, with the default library, found too many repetitive structures when compared to what is considered standard. Worse still, this overabundance of detected repetitive structures provides masking that is below this very standard. The very high value for detected features is mostly due to the extremely high value of features detected for Z. mays, as the pipeline detects 490% more features than the literature used as standard. This fivefold increase in the number of reported features results in a genome coverage 20% higher than the standard (Figure  4A ). When Z. mays is removed from the dataset, the pipeline detects, on average, 48. 86% fewer features than the reports in the literature. In contrast to the extreme values, the genome coverage and the number of features detected for O.
sativa sp. indica cv. 93-11 are unexpectedly low, with 0. 25% of genome masking and 0. 74% of feature detection when compared to reports. There is a significant difference in O. sativa sp. indica between the pipeline statistics and the reference article and also between O. sativa sp. indica and O. sativa sp. japonica pipeline statistics. O. sativa sp. japonica and O. sativa sp. indica, being cultivars of the same species, should have highly similar repeat distributions. We suspect that these differences come from the Repbase speciesspecific annotation, meaning that if few repeats from the Repbase dataset are labeled in the EMBL file as having an "Oryza indica" species annotation, only a few of these repeats are mapped on the O. sativa sp. indica genome, leading to underestimated statistics.
Pipeline extension, test, and rerun This pipeline extension implemented a new RepeatMasker analysis, similar to the analysis with Repbase (or custom libraries). This new analysis used REdat as a repeat library. Then, the RepeatMasker output, when used with REdat, could be parsed to provide a TE classification. A new run was performed on the 53 species present in the Ensembl database, with the new analysis. RepeatMasker was used with low sensitivity. The intent was to determine if the implementation showed a significant improvement in the pipeline annotation capabilities. This run using the REdat library increased the average proximity to reference articles by 39% for genome coverage and by 13% for the number of features detected (Figure  4B ). When compared to the initial pipeline run, the mean genome coverage increased by 22.
7% (from 30. 16% to 39. 02%) and the average number of detected features by 55. 36% (from 276,714 to 619,930). This means that running RepeatMasker with REdat on low sensitivity gives better results than RepeatMasker with Repbase on medium sensitivity. If the extremely low values for Indian rice seem to have been solved, the extremely high values for maize remain after the update. This invalidates the hypothesis of the species-specific system in Repbase and raises a new hypothesis: it could be due to the variation in the number of reported transposable elements in a given species. This taxonomic tree was computed from the presence/absence binary matrix of 100 transposons types in the 53 plant species available in the Ensembl database. The top scale shows the relative distances (from 0 to 1) between these species.
These species are separated by many events of whole genome duplications  (Chalhoub et al. , 2014). This study asks questions about the impact of whole genome duplications on transposon distribution and activity. Another case worth investigating is the presence of H. vulgare and Gossypium raimondii among algae and mosses. If the dendrogram bootstrap has not been performed, its strength can nonetheless be assessed with the clusters from Figure  2. As grasses are grouped with eudicots, this branch Binary heatmap, where each red point represents the presence of a REcat key on the x-axis in a given species on the y-axis. Each REcat has its fivedigit code at the bottom. On the left side is the list of plant species in the Ensembl core database. The top and the left side are trees showing computed relations between keys and between species.
In this paper, we focus on behaviours as these are the frontline defences against parasites and pathogens  (Sarabian, Curtis, & McMullan, 2018). We propose to adapt the ART framework to better encapsulate the variation in (and levels of) behavioural immunity, based on the type (endo-vs. ecto-), timing (before vs. after), severity experiments in the above contexts. Finally, we promote the creation of a database gathering disease avoidance evidence in animals and its applications. of the fitness cost, and ecological context of infection/exposure/ intoxication (Figure  1 ). As such, avoidance occurs when parasites/ pathogens are detected through species-specific sensory modalities before infection and when the cost of the behavioural action is lower than the cost of acquiring the infection, or in other words net-beneficial (see  Oliva-Vidal et al.
, 2019). Both strategies are based on unpleasantness or a certain degree of illness, which confers on them their evolutionary relevance and effectiveness. The proposed experiments are not supposed to create habituation to the presented cues, except for the mild ones depending on the implied trade-offs. Researchers should ensure that non-target species have no or limited access to anything presented during experimentation  (Smith et al. , 2022) , which may have unwanted cascading effects, and the design should be as specific as possible to the diet and ecology of the species (e. g. drilled gum discs for slow lorises). Finally, we propose to create a database (e. g. "ManyPTA"-Parasites To Avoid), which would gather the existing literature (Table  S1 ) but also the pending experiments and the animal taxa from which we know very little (e.