dataesr/scientific-paragraphs-categorization huggingface dataset:
as a high and low precipitation indicator at Wonderkrater, South Africa  (Chevalier and Chase 2015) ). Finally, while this paper is dedicated to the analysis of southern African pollen types, all the diagnostic tools presented are transferable and applicable to other regions of the World and/or different ecosystems as they are based on the crestr R package (https://github. com/mchevalier2/ crestr) and can be generated using R scripts available at https://github. com/mchevalier2/Papers/ tree/master/2021_Chevalier_etal_Pollen_Atlas_SA. This technique will help to formalise and standardise pollen-climate interpretations and facilitate and refine interpretations of regional fossil pollen data.
ACKNOWLEDGEMENTS This work was supported by the  European Research Council (ERC)  under the European Union's  Seventh Framework Programme  (FP7/2007-2013)/ ERC Starting Grant 'HYRAX' , grant agreement no. 258657. The authors also acknowledge the support of the  South African National Botanical Institute (SANBI)  in sharing their botanical data. Lloyd Rossouw ,  Alma Fuller  and  Frederick Scott  for scanning and arranging negatives of the pollen reference collection of the  Department of Plant Sciences University of the Free State  in a database. LS was supported by the  National Research foundation (South Africa)  ( NRF Grant no. 85903 ). Any opinion, finding, and conclusion or recommendation expressed in this material is that of the authors, and the  NRF  does not accept any liability in this regard.
Some of the most popular methodologies in topology optimization include the homogenization method, solid isotropic material with penalization (SIMP) and level set methods, etc. Topology optimization has been applied in the design of automotive, aircraft and aerospace structures, for which mass constraints are frequently imposed. To date, commercial TO software, such as Altair, ANSYS, Autodesk Fusion 360, have gained popularity in various industrial applications. However, existing topology optimization methods still have several limitations that impede industrial application. Firstly, although topology optimization has great potential to exploit the design freedom provided by AM, AM processes cannot always print the obtained structures with successes. This is primarily because AM still has some manufacturing constraints which need to be considered in the topology defining process.
, of conventional TO methods as discussed above. Recently, a set of commercial software provides new functions of the generative design method for AM processes in their structure design module, such as Autodesk and Altair. However, these tools, based on traditional multi-objective topological optimization, only alters the way of removing materials from the design space to populate alternative solutions, most of which are invalid. Key manufacturing constraints of AM processes have been ignored in the material removing procedure. The result is that these commercial tools usually generate very complex geometries without validation for manufacturing. Hence, designers have to use their own knowledge to evaluate and select the optimal solution from the large number of populated non-valid alternatives, which is quite difficult for operation in design practice.
A tiny shell (7 mm length) of a juvenile Mollusc (supposed gastropod) was discovered enclosed within the packstone lled shell of a terebratellidine brachiopod (Zittelina hofmanni Bujtor and Vörös, 2020) from the Lower Cretaceous Apátvarasd Limestone Formation of Zengővárkony (Mecsek Mountains, South Hungary). Serial sectioning of the brachiopod shell revealed that in addition to the brachidium, a different and unusual shelly structure was preserved inside the brachiopod shell. 2D serial sections were digitalized and fed into Free-D imaging software to generate a 3D reconstruction of the entombed fossil, which is supposed a juvenile gastropod. Consideration of the emplacement, dimensions, and orientation of the shell suggests that it entered the cavity of the living brachiopod shell as an egg or larva and was trapped.
In this case the encapsulated strophomenid deviated the normal development of the crura and resulted an asymmetric brachial structure. 14 Other brachiopod -brachiopod encapsulation is reported  15  from the Jurassic of Romania. Other kind of co-existence from the Silurian of England is known, too. In that case an atrypid brachiopod attached to the shell of an other brachiopod (Bethia serraticulma), however this is a coexistence but without any co-actions, being epibiotic co-existence. 16 These authors serially ground at 20 μm intervals their specimens, digitally photographed then digitally reconstructed using custom SPIERS software suit. A surprising co-existence between living gastropods and brachiopods were reported very early  17  where a brachiopod larva entered in the mantle of the gastropod, attached and attained a considerable size in this unusual environment.
7. 1 inventory number at the palaeontological collection of the Hungarian Natural History Museum, Budapest. Sixty-four serial section drawings were digitalized by ABBYY FineReader OCR software run on an OpticPlus 4800 scanner and stored as TIFF images. The TIFF images were imported into the Free-D software  25  for 3D reconstruction. 26 Each image was assigned a z-position corresponding to its position during the grinding process. The Free-D registration module was used to manually align the images of consecutive sections, using a combination of translations and rotations. In parallel, the Free-D automatic thresholding and contour following tool was used on each section to extract polygonal representations (sets of connected 2D vertices) of the drawings of the different structures (brachiopod crura, valves, entombed fossil).
When this not the case, as in the present study, manual contouring followed by contour triangulation may be the only feasible option, which comes at the cost of an increased complexity compared with isosurface extraction when facing complex topological changes. The third constraint is that the serial sectioning has to be performed at a constant spacing. This in turn generally imposes a small spacing to ensure the recovery of details in some regions, even though some regions could be reconstructed using a larger spacing. The number of images to be registered and segmented can become very large. Here, we took advantage of the 3D reconstruction and modelling software Free-D, initially developed for neuroanatomy then cell biology studies  26, 27  to propose an alternative approach avoiding all these constraints.
Acknowledgements The rst of the authors (LB) acknowledge the nancial support of the  Bolyai János Research Grant  of the  Hungarian Academy of Sciences  that nanced the eld work in 2010 [grant number  484/10 ]; and indebted to  Attila Vörös  ( Hungary ) for co-working on brachiopods from this locality. Fruitful comments on the nature of the entombed fossil with  Franz Fürsich  (Germany) is highly appreciated. The authors are indebted to  Michael Sandy  ( USA ) for the thorough discussions, comments and linguistic emendations of the draft that greatly improved the quality of the paper. The IJPB bene ts from the support of  Saclay Plant Sciences-SPS  ( ANR-17-EUR-0007 ).
The Mutational Spectrum in Orthocoronavirinae Is AU-Biased Since variation in GC3 content is the main individual driver of the variation in CUB between CoVs, we investigated next whether mutational biases are the underlying main force driving nucleotide content. Population genetics studies show that in order to explore mutational biases independently of the effect of natural selection, one should work at shallow, short-term evolutionary periods, where natural selection is less powerful to impact nucleotide polymorphism patterns  [45]. Consequently, we estimated the frequencies of individual transition and transversions by narrowing down our analysis to a subset of 16 different CoV metapopulations. From the public databases (see Methods), we downloaded a total of 12,102 different viral genome entries to construct these 16 different metapopulations (Supplementary Table  S2 ).
Prior to the identification of SNPs for each metapopulation, we carefully preprocessed each dataset by removing putative recombinant sequences (see Methods, Supplementary Figure  S3A ), as recombinant sequences violate the assumptions for phylogenetic inference methods used downstream. For each viral metapopulation, we removed further the effect of population structure by phylogenydriven selection of one single homogeneous population per viral species (Supplementary Figure  S3B ). Our final dataset was composed of a total of 10,373 viral genomes for the 16 metapopulations (median number of genomes per metapopulation 31; range 9-9588), for which a total of 57,059 SNPs were called (median number of SNPs called per metapopulation 3037; range 253-7778; Supplementary Table  S2 ). Despite the heterogeneous sampling size across our metapopulations, the number of SNPs called was highly comparable, the exceptions being SARS-CoV-1 sequences from humans and MERS sequences from humans and from camels, which exhibited a low number of sequence polymorphisms, albeit large enough to grant sound analyses (respectively 716, 621 and 253).
Indeed, at the short time scale that our analyses can explore for the SARS-CoV-2 epidemics in humans, we verify a small albeit significant trend towards GC reduction (Figure  2C ). Similar trends have also been reported when analyzing different datasets  [95, 96]. Future work will benefit from accessing a sufficient number of SARS-CoV-2 non-human strains collected from different hosts (bats and pangolins in first instance, given the current knowledge) to assess the population-level characteristics of the direction and intensity of mutational bias in endemic host species. Additionally, endemic hCoVs exhibit a large variation in observed synonymous GC3-content, ranging from 18. 7% to 30. 6%, which suggests that the strength of the mutational bias causing C->U changes is not similar among all hCoVs.
Data Collection and Processing To access the diversity of coronavirus species we downloaded sequences classified within the Coronaviridae families from the virus-host database (https://www. genome. jp/ virushostdb/, accessed on 19 March 2021). Because the 212 viral entries present in the database are composed of a mixture of sequence classified at different taxonomy levels, i. e. , species (HKU1, HKU4, HKU5,. ) or strains (HKU4-1, HKU4-2, HKU4-3,. ), we used CD-HIT (option-c 0. 95-n 5) to cluster together sequences sharing over 95% of identify. A total of 82 distinct groups of complete genomes were identified, from which we manually choose one single representative member, preferentially selecting the NCBI manually curated genomic sequence. For the intra-species diversity, we downloaded strain sequences from the Virus Pathogen Resource database (VIRP).
Unusually long or short sequences (>130% or <70% of the median length of the reference sequence of a species) were filtered out. In addition, the complete genomic sequences of SARS-CoV-2 isolates were obtained from GISAID (available at https://www. gisaid. org/epiflu-applications/nexthcov-19-app/), accessed on 6 May 2020 to collect the sequences for our metapopulation analysis. SARS-CoV2 sequences bellow 29,000 bp were automatically discarded. Detailed accession ID for both datasets are provided in Supplementary Tables  S1  and S2.
Nucleotide Composition Analysis From the NCBI Genbank files of the previously selected 82 complete genomes, we used BIOPYTHON to concatenate the coding sequences of each CoV genome, and then compute the total synonymous codon frequencies for each genome. Only ORFs from the orf1ab, spike glycoprotein (S), envelope small membrane protein (E), membrane protein (M), and nucleoprotein (N) were considered for our downstream analysis, as those ORFs were presumably the best annotated ones across CoVs. We want to raise a word of caution, as we have analyzed the complete coding genomes of the different viral taxa without individual focus on the different genome regions that may be differentially transcribed and replicated and present local peculiarities in nucleotide composition and/or synonymous codon usage.
Thus, our results refer to overall trends for the complete genomes and do not exclude the possibility of the presence of local compositional anomalies. A matrix of 82 (CoVs) × 59 (synonymous codons) was created, which served as input for either our PCA analysis (FactoMineR) and correspondence analysis (run with R package ade4). In parallel, we calculated the dinucleotide observed/expected abundances in coding sequences by calculating the ratio rXY = fXY/fXfY, where fXY denotes the observed frequency of the dinucleotide XY and fXfY the product of the individual frequencies of the nucleotides X and Y in a sequence. We used as significant lower and upper boundaries the thresholds of 0. 78 and 1. 25, corresponding to p < 0. 001 for sufficiently long (>20 kb) random sequences  [99].
SNP Calling To identify intra-species polymorphisms, we used MUMMER  [100]  to perform a genome-to-genome alignment of our 16 metapopulations against its corresponding reference sequence, to then call SNPs using the program SHOW-SNPS from the MUMMER TOOLS suite. Multi-allelic sites and structural variants were filtered out to only consider bi-allelic variants. In order to differentiate synonymous to non-synonymous mutations, using BIOPYTHON we annotated each variant based on the CDS annotation provided within the corresponding Genbank reference sequence.
Site Frequency Spectrum Assessment Mutational Equilibrium Prior to the inference the site frequency spectrum (SFS), the population structure of each metapopulation was characterized. Using BIOPYTHON, we first transformed our multisample VCF file into a multi-alignment (MSA) file, which served as input file for the identification of population sub-structure and recombinant sequences using FASTGEAR  [101]. FASTGEAR presents the advantage of identifying population genetic structure from an alignment, as well as detecting recombination between the inferred lineages. Complete genomes presenting long recombining segments (>200 bp) were removed from each dataset, while short recombination segments were masked for the downstream analysis. From the VCF file of each metapopulation, the allele frequency of each variant was computed using VCFTOOLS (-freq).
In order to work in a framework where population structure of our metapopulation does not interfere with the shape of the derived allele frequency counts, we focused for each viral entry on the single lineage per metapopulation, having the highest number of complete genomes (as previously identified by FASTGEAR). For each of the 18 viral metapopulations we calculated the derived allele frequency spectrum by comparing each extant sequence with the ancestral one. Previous studies have shown that the analysis of the derived allele frequency spectrum are sufficiently robust to demographic and/or sampling effects  [102, 103]. We constructed then the folded SFS by polarizing the derived allele frequency as AU-enriching or GC-enriching with respect to the ancestral sequence, as in  [56]  using the R script kindly provided by Dr.
Acknowledgments: The authors acknowledge the  IRD itrop HPC (South Green Platform) at IRD Montpellier  for providing HPC resources that have contributed to the research results reported within this paper. URL: https://bioinfo. ird. fr/-http://www. southgreen. fr. We warmly thank  Sylvain Glémin  for sharing with us R script function and helpful suggestions regarding our estimation of the mutational equilibrium.
Data Availability Statement: We acknowledge the three different sources of genomes that we employed: the virus-host database (https://www. genome. jp/virushostdb/, version of 19 March 2020), the Virus Pathogen Resource database (VIRP, https://www. viprbrc. org/brc/home. spg?decorator= vipr, version of 26 April 2020), and the GISAID database (https://www. gisaid. org/, version of 19 August 2020).
This lead to a lower limit on its luminosity: L UV-X ≥ 7×10 37 W. The detection of H 2 O maser spots provides a very reliable and precise measurement of the emitting medium. A line of maser spots, oriented along PA = 135 • is observed as far as 1. 1 pc from the nucleus. The analysis of their velocity profile indicates that they originate from a disk seen edge-on with an inner radius r i = 0. 6 pc and an outer radius r o = 1. 1 pc. This maser disk is counter-rotating with the molecular disk observed with ALMA. The maser disk appears contained within the molecular disk and surrounds the cloud of gas from which S1 originates. A study based on similar GRAVITY data was presented in Gravity  Collaboration et al. (2020) , focusing on the interpretation of a reconstructed image of the source and suggesting that the K-band emission originates from a thin ring-like structure with a radius r = 0.
Observation The GRAVITY observation on which this study is based on was made during the night of November 20th, 2018, under excellent atmospheric conditions. It is one of the two observations used in Gravity  Collaboration et al. (2020). However, NGC 1068 remains a challenging target to observe with GRAVITY due to its relatively low surface brightness and complex morphology. In order to achieve the observation, 100% of the flux from the source was injected in the fringe-tracker (FT) (see Gravity  Collaboration et al. 2020). This strategy made it possible to fringe track, however it means that only FT data are available, with a R ∼ 22 spectral resolution (K-band split in 5 spectral channels) and without any absolute phase measurements. Total integration time on the object is 45 minutes, and three reference stars have been observed, HIP 54, HIP 16739, and HIP 17272.
Geometrical approach As a first step, we used geometrical approaches to model the observables and derive images of the source: we used simple geometrical models fitted with the LITpro software 1  as well as image reconstructions using the software MiRa  (Thiébaut et al. 2003). The goal was to look for characteristic size measurements and hints on the morphology to guide our further radiative transfer modeling. All simple geometrical models converge toward a central elongated structure (see Table  2 ), with ∼ 4 × 6 mas (∼ 0. 28 × 0. 42 pc) dimensions and a major axis at PA ∼ 140 •. Also, all models agree on the significance of the diffuse flux, contributing to around 2/3 of the total flux. Out of the four simple models presented in Table  2 , the one which provides the best fit to the data is the elongated thick ring, whose K-band image image and associated visibility points are presented in Fig.
Physical modeling from radiative transfer simulations MontAGN In this section, we describe how we used radiative transfer simulations to derive a physically realistic 3D model of the source from the GRAVITY observables. We are trying here a new approach, using a model highly constrained from astrophysical considerations in order to produce physically realistic images, that will be then compared to the interferometric measurements in a second step. For this purpose, we are using the simulation code MontAGN  (Grosset et al. 2018; Grosset 2019)  to model a dusty disk heated by a central source of energetic photons. The images produced by each model are used to compute the various interferometric observables. We first give a description of MontAGN, and general considerations on the model that will be used.
MontAGN MontAGN is a radiative transfer simulation code using Monte Carlo methods, developed to study AGN dusty tori, and more specifically the interpretation of polarimetric observations. It offers the possibility to model the diffusion, absorption, and emis-  MontAGN follows the path of photons, from their emission by a central source until the moment they exit the simulation grid, modeling all along the different interactions with the medium. In the following list, we succinctly describe the main steps of interest of a simulation: 1. Extinction and absorption coefficients, albedo, Mueller matrices, and phase functions are calculated on a wide range of wavelengths (from X to far-IR) and grain sizes for each of the "dust types" defined by the user 2. The 3D grid of cell is initialized with Cartesian coordinates, and is filled with dust by attributing a density value for each cell and each dust type.
MontAGN model 2 : accounting also for closure phase In a third model, we try to reproduce simultaneously the GRAV-ITY closure phase and visibility measurements. As already pointed out in Sect. 3. 3, the [UT1-UT2-UT3] triplet (in red in Fig. 4 ) contains the majority of the closure phase measurements and is moreover associated with the lowest uncertainties. The spatial frequencies probed by this triplet allow to constrain an important property of the model: the difference of luminosity between the northeast and the southwest regions of the structure. The closure phase is positive when the southwest edge is the most luminous, and negative in the other case. Their value is an indicator of the relative contrast between the two edges. The mean closure phase on the [UT1-UT2-UT3] triplet is 73 The first dataset of MontAGN simulations, which was used for model 1 in Sect.
Unified model of the dataset In the previous sections, we described several methods to interpret and model the GRAVITY data. Despite some diversity in the resulting parameters, recurrent features allow us to draw a synthetic description of the nuclear structures, that we present below before discussion and comparison with previous studies. First, the flux of the compact object represents around onethird of the total flux detected in the field of view of GRAVITY (56 mas or 3. 9 pc), the remaining is considered as a diffuse component distributed on larger spatial scales. All the models agree on the characteristic size of this structure which is less than one parsec. More precisely, the different methods converge toward an elongated structure with a major axis of around 7 mas (0. 5 pc) oriented northwest/southeast and with an elongation ration e ∼ 3/2.
Acknowledgements. We thank the anonymous referee for its constructive comments. This work was made possible by the doctoral school ED 127  Astronomie et Astrophysique d'Ile de France  which funded and accompanied with care the first author during its PhD. The last steps of the publication process were done while he was starting a position at the  Astronomical Institute of the Czech Academy of Sciences , where he was supported by  Czech Science Foundation  Grant  19-15480S  and by the project RVO:67985815. The Gravity data analyzed in this paper have been obtained thanks to  ESO Large Programs IDs   0102. B-0667 ,  0102. C-0205  and  0102. C-0211. We would like to thank the Gravity collaboration, and more particularly our colleagues from  Max Planck Institute for extraterrestrial Physics , for the fruitful discussions that allowed to improve our data analysis.
Formally, if we encode the mapping between A 1 and A 2 into a boolean matrix M A 1 →A 2 such that M A 1 →A 2 ii = 1 if and only if function i in A 1 is paired with function i in A 2 , then, our extrapolating scheme simply consists in computing the diffing correspondence between A k and A n as follows: M A k →A n = n-1 i=k M A i →A i+1. We applied this extraction protocol to three well known open source programs, namely Zlib 3  , Libsodium  4  and OpenSSL 5  from which we collected respectively 18, 33 and 17 different binary versions and therefore 153, 528 and 136 diffing instances. Statistics describing our evaluation dataset are given in Table  3. As a baseline, we chose to compare to the two most common diffing tools: BinDiff and Diaphora. BinDiff uses a matching algorithm close to VF2  [8]  originally introduced to approximate the MCS whereas Diaphora proposes a different greedy assignment strategy that first matches the most similar functions and then searches for potential correspondences in the remaining ones.