dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements The authors thank  Dunming Wu ,  David Beckers , and  Arndt Ziemons  for their help in sample preparation,  Martin Heller  and  Risheng Pei  for their help in focused ion beam milling,  James Best  for the help in nanoindentation,  Stefanie Sandlöbes-Haut  for fruitful discussions, and  Mattis Seehaus  for his help during the revision of this paper. This project has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 Research and Innovation Programme  (Grant Agreement No. 852096  FunBlocks). Funding by the  Deutsche Forschungsgemeinschaft (DFG)  in Projects  KO 4603/2-2 (Project ID 437514011 ) and SFB1394 Structural and chemical atomic complexity -from defect phase diagrams to material properties (Project  ID   409476157 ) is gratefully acknowledged.
, 2019). Some UCXBs may contain BHs as well. The first strong globular cluster BH candidate  (Maccarone et al. , 2007)  in NGC 4472 is an ultracompact system  (Zepf et al. , 2008) , probably with an orbital period near 5 minutes, and 47 Tuc X-9  (Miller-Jones et al. , 2015; Bahramian et al. , 2017)  is also a strong candidate ultracompact BH X-ray binary. At the shortest orbital periods, BH+WD binaries should be detectable by LISA to distances of a few megaparsecs. For these cases, imaging X-ray data would be needed, along with follow-up optical spectroscopy to look for [O III] nebulae as well as hydrogen emission similar to that in the globular cluster RZ 2109 in NGC 4472  (Zepf et al. , 2008; Steele et al. , 2014; Dage et al. , 2019). In the Milky Way, UCXBs with BH accretors at relatively long orbital periods could be quite faint X-ray sources in quiescence (being considerably fainter than accreting NSs at the same mass transfer rate due to advection dominated accretion,  Narayan and Yi 1994).
By performing synergistic observations that combine low-frequency GW signals with EM signals from the same source, we will uncover previously unavailable information. These combined observations will precede, accompany, or follow, the MBH merger events, helping us to constrain MBH activity, understand their immediate surroundings (e. g. the nature of the accretion disc, jets, and the accreted/ejected material), and its relation with the host galaxy. One challenge of multimessenger observations is the localization of the sources, and the confirmation that they are indeed MBH binaries. Before the launch of LISA, we will have to better understand, among other aspects, how the different potential observational EM signatures of coalescing systems are originated, and develop new analysis tools to identify these GW source candidates in large datasets.
Therefore, future improvements should take into account magnetic fields, employ at least some approximate radiative transfer, and consider more realistic models of stellar feedback and of the clumpy, multi-phase interstellar medium (e. g. Hopkins et al. , 2018; Marinacci et al. , 2019). One key aspect is the connection between AGN feedback and the spin of MBHs. Given that LISA will provide us with spin distribution of the merging systems, this is a direction that we need to address in the coming years. The strength of AGN feedback scales with the radiative efficiency, which is closely tied to MBH spin. Therefore, a self-consistent treatment of AGN feedback should account for the effect of spin on radiative efficiency (as in  Trebitsch et al. , 2020; Dubois et al. , 2020, for example) , which could become feasible if the spin distribution will be robustly constrained by future GW datasets.
There are also other subtleties that enter the models. For instance, the spins and mass ratios of the binaries at the time of coalescence, which are determined by formation, growth, and dynamical evolution all together, influence the speed of recoil kicks (e. g. Peres, 1962; Damour and Gopakumar, 2006) , which in turn modulate further the merger rate by ejecting MBHs from galaxies. Thus, not only the merger rates but also mass and spin distributions of merging MBHs depend sensitively on the specific assumptions of the models in terms of seeding, accretion, feedback, and spin evolution, which are largely unconstrained by available observational datasets. The details of these physical aspects are described in Section 2. 2 and Section 2. 3 of this paper and below we discuss how they influence the statistics of LISA's merging MBHs also in dependence of the technique used.
Multimessenger astrophysics • The Legacy Survey of Space and Time of Vera Rubin observatory to detect AGN binaries through photometric variability The Vera C. Rubin Observatory will perform the Legacy Survey of Space and Time (LSST), which will provide time-domain observations of unprecedented quality and quantity (LSST Science  Collaboration et al. , 2009). This is particularly significant for EM searches of MBHBs, since they can be detected as AGN with periodic variability. LSST will monitor a large number of quasars (of order one million) providing multi-band observations with high cadence, and long baselines, extending up to 10 yr. Therefore, it is perfectly suited to detect the relatively short-lived and short-period MBHBs emitting GWs in the LISA band. Already large numbers of binary candidates are identified in existing photometric datasets from the Catalina Real-time Transient Survey (CRTS;  Graham et al.
If one of the MBHs in a binary system is surrounded by enough gas to produce a prominent broad line region, the motion of the MBH will result in detectable Doppler shifts in the broad emission lines  (Nguyen et al. 2020 and references therein). The spectroscopic database of SDSS has already provided significant samples for spectroscopic searches of MBHBs and dozens of binary candidates have been identified from their large broad-line offsets  (Eracleous et al. , 2012). However, these are not unique signatures for binaries, and long-term spectroscopic follow-up is necessary in order to observe coherent changes in the broad emission lines and confirm the binary nature of the sources  (Runnoe et al. , 2017). SDSS-V will provide a promising sample for this type of search, since the BH mapper program will spectroscopically monitor thousands of AGN over multiple epochs  (Kollmeier et al.
Acknowledgements  P. Dayal  acknowledges support from the  European Research council  ( ERC-717001 ) and from the  Netherlands Research Council NWO  ( 016. VIDI. 189. 162 ). P. H. Johansson  acknowledges the support from the  European Research Council  ( ERC-818930 ). S. Toonen  acknowledges support from the  Netherlands Research Council NWO  ( VENI 639. 041. 645  grants)  C. Unal  is supported by  European Structural and Investment Funds  and the  Czech Ministry of Education, Youth and Sports  (Project  CoGraDS -CZ. 02. 1. 01/0. 0/0. 0/15_003/0000437 ). S. Chaty  acknowledges the  LabEx UnivEarthS  for the funding of Interface project  I10 «  From binary evolution towards merging of compact objects ». A. De Rosa  acknowledges financial contribution from the agreement  ASI-INAF  n. 2017-14-H.
O E. Berti  is supported by  NSF  Grants No. PHY-1912550  and  AST-2006538 ,  NASA   ATP  Grants No. 17-ATP17-0225  and  19-ATP19-0051 ,  NSF-XSEDE  Grant No. PHY-090003 , and  NSF  Grant  PHY-20043. D. Gerosa  is supported by  European Union 's  H2020   ERC Starting  Grant No. 945155-GWmining ,  Leverhulme Trust  Grant No. RPG-2019-350  and  Royal Society  Grant No. RGS-R2-202004. T. Bogdanovic  acknowledges support by the  NASA  award No. 80NSSC19K0319  and by the  NSF  award  AST-1908042. D. Porquet acknowledges funding support from  CNES. C. Danielski  acknowledges financial support from the  State Agency for Research of the Spanish MCIU  through the " Center of Excellence Severo Ochoa " award to the  Instituto de Astrofísica de Andalucía  ( SEV-2017-0709 ) B. L. Davis acknowledges support from  Tamkeen  under the  NYU Abu Dhabi Research Institute  grant CAP3.
F. Pacucci acknowledges support from a  Clay Fellowship  by the  SAO  and from the  Black Hole Initiative , which is funded by grants from the  John Templeton Foundation  and the  Gordon and Betty Moore Foundation. A. J. Ruiter  acknowledges support from the  Australian Research Council Future Fellowship  grant  FT170100243. V. Paschalidis is supported by  NSF  grant  PHY-1912619  and  NASA  grant  80NSSC20K1542  to the  University of Arizona , and  NSF-XSEDE  grant  TG-PHY190020. D. Haggard  acknowledges support from the  NSERC   Discovery Grant  and  Canada Research Chairs programs , and the  Bob Wares Science Innovation Prospectors Fund. M. Toscani acknowledges European Union's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie  grant agreement  NO 823823  ( RISE DUSTBUSTERS  project) and  COST  Action  CA16104  -Gravitational waves, black holes and fundamental physics, supported by  COST (European Cooperation in Science and Technology).
The GC content for all samples ranged from 44. 28 to 44. 66 (Table  1 ). These results indicated that the sequencing data were of high quality. We then de novo assembled the high-quality clean reads into unigenes using the Trinity software  [23, 24]. The transcripts and unigenes exhibited similar lengths (Supplementary Fig. 2 ), with an average length of 835 and 853, respectively, and an N50 value of 1,227 and 1,239, respectively. Sequence similarity analysis showed that 71. 21% (216,347) of unigenes were at least highly identical to known proteins in seven different databases. Particularly,  47. 47, 70. 45, 48. 04, 70. 21, 39. 33, 59. 83, and 37. 25% of the unigenes were annotated in the KEGG, NR, Swiss-Prot, Trembl, KOG, GO, and Pfam databases, respectively. Regarding other species, 60. 69% of the unigenes showed high similarity with sequences in Grossypium spp.
Plant material and growth condition The Cd-tolerant Hibiscus syriacus variety "Hongxing" identified previously was used in this study  [22]. The plant material is available at the Key Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China under the accession number: ZHY0045A22. The formal identification was conducted by Prof Lanlan Liu. No permission is required to collect and study the plant material. The experiment was conducted in a completely randomized manner in pots of 25 cm × 13 cm × 16 cm dimensions. The pots were filled with 2 kg of sterilized (at 121 °C for 60 min) soil taken from Hunan Forest Botanical Garden. Two-year-old plants were adequately isolated from the same forest and transplanted in the pots, one in each. The experiment was conducted from June to September 2021 on the roof of the Zhongnan Forestry Department, College of Landscape Architecture, University of Technology.
[12]. Briefly, the TRIzol kit (Invitrogen GA, USA) was used for total RNA extraction from samples following the instructions by the manufacturer. The quality, purity, and integrity were investigated using a NanoDrop ND-2000 spectrophotometer (Thermo Scientific, USA) at 260/280 nm. cDNA libraries were constructed from the leaf total RNA with the TruSeqTM RNA sample prep kit (Illumina, San Diego, USA) according to the manufacturer's instructions. Next, the libraries were sequenced on the Illumina Hiseq X ™ Ten platform by Shanghai Majorbio Biopharm Technology Corporation (Shanghai, China). Using the Seq-Prep program, the low-quality reads were discarded, and high-quality reads (clean reads) were generated. Finally, the clean reads were de novo assembled using the Trinity software  [23, 24]. The expression levels of genes were assessed by FPKM (Fragments per Kilobase of transcript per Million mapped reads) using RSEM (www.
biome dsear ch. com/ nih/ RSEMaccur ate-quant ifica tion-from/ 21816 040. html) and Bowtie software (http:// bowtie. cbcb. umd. edu). The DEGs were detected using DESeq software (https:// www. rdocu menta tion. org/ packa ges/ DESeq2). The applied criteria for DEGs identification were threshold |log2Fold Change|≥ 1 and p-value < 0. 5.
DEGs analysis and functional annotation BlastX (E-value > 10 -5 ) against Swiss Prot, Protein family (Pfam) database, NCBI non-redundant (Nr) databases, Cluster of Orthologous Groups databases (COG/KOG), Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG), Gene Ontology (GO), and Trembl was used for gene function annotation. To gain insights into the biological functions of DEGs, we conducted GO and KEGG pathway enrichment analyses through the Blast2GO  [46]  and KOBAS2. 0 [47]  programs, respectively.
Statistical analysis Statistical analyses of all traits were conducted using R (www. r-proje ct. org), and the data are presented as the mean ± SD of three replicates. Statistical differences were performed by t-test at P < 0. 05. GraphPad Prism v9. 0. 0121 (GraphPad 159 Software Inc. , La Jolla, CA, USA) was used to construct bar graphs and pies. The prcomp and pheatmap functions in R were used for PCA (principal component analysis) and HCA (hierarchical cluster analysis) analysis, respectively.
manuscript submitted to Journal of Advances in Modeling Earth Systems (JAMES) Acknowledgments This work was granted access to the HPC resources of TGCC under the allocation 2092 made by  GENCI. CR. CM. and FV. acknowledge the national french program  INSU-LEFE  for the funding of the SAM-iso proposal at the AO LEFE 2021. C. M. gratefully acknowledges funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme (Project CLUSTER , grant agreement No  805041 ). P. B. was supported by the  National Science Foundation  under Grant No. AGS-1938108. G. V. contributed as part of his internship as a Master student at  Sorbonne Université , with a funding from  Paris Sciences & Lettres  " ANR-10-IDEX-0001-02 ". C. D. contributed as part of her internship as a Bachelor student at  Sorbonne Université.
Population genetic models only provide coarse representations of real-world ancestry. We use a pedigree compiled from four million parish records and genotype data from 2,276 French and 20,451 French Canadian (FC) individuals, to finely model and trace FC ancestry through space and time. The loss of ancestral French population structure and the appearance of spatial and regional structure highlights a wide range of population expansion models. Geographic features shaped migrations throughout, and we find enrichments for migration, genetic and genealogical relatedness patterns within river networks across Quebec regions. Finally, we provide a freely accessible simulated whole-genome sequence dataset with spatiotemporal metadata for 1,426,749 individuals reflecting intricate FC population structure.
Such realistic populations-scale simulations provide new opportunities to investigate population genetics at an unprecedented resolution. Lay Summary : We all share common ancestors ranging from a couple generations ago to hundreds of thousands of years ago. The genetic differences between individuals today mostly depends on how closely related they are. The only problem is that the actual genealogies that relate all of us are often forgotten over time. Some geneticists have tried to come up with simple models of our shared ancestry but they don't really explain the full, rich history of humanity. Our study uses a multi-institutional project in Quebec that has digitized parish records into a single unified genealogical database that dates back to the arrival of the first French settlers four hundred years ago.
Simulated genomes with known transmission histories To assess how much of the FC population structure can be accounted for by events following the arrival of French settlers, we generalized the msprime software (28-30) to perform genome-wide coalescent simulations conditioning on the known pedigree of the FC population. We defined the FixedPedigree ancestry simulation model in msprime version 1. 2 to trace the ancestry of samples back through the genealogy accounting for coalescence and recombination (Fig. S4 ). To account for relatedness beyond the founders of the known pedigree, we modelled coalescence under a demographic model for European ancestry  (31)  (see Methods 2 for details). We compared the simulations to ascertained data with a subset of 4,882 individuals who were both genotyped and linked to the pedigree.
The PCA and UMAP of the simulations show clear qualitative agreement with the fine scale structure of ascertained genotype data (Fig. 2  and Fig. S3 ) as is evident from the first six PCs showing strong correlation (Fig. 2C ). Thus, leading axes of Following this, we simulated whole genomes of 1. 4M present day individuals with at least four grandparents linked to the pedigree. (see Fig. S5  for UMAP and PCA). Tree sequences of these simulations are freely available on Zenodo (https://doi. org/10. 5281/zenodo.
Finally, the strong correlation between empirical and simulated genetic data provides evidence that the structure within the FC population can largely be attributed to events in North America, while the population kept a genetic signature of the regions in France contributing more early French settlers. We describe how geological, social, historical effects, as well as idiosyncratic events, translated in genetic variation patterns at various geographic scales and over centuries. Although our simu-lations are based on a real pedigree, they do not contain identifying information and we can freely share this genome-wide dataset along with spatiotemporal metadata for over 1. 4M individuals. Of course, these simulations are far from perfect. They do not account for natural selection beyond what is captured in the pedigree  (36).
The pedigree itself contains some amount of recording errors. Mismatches between genealogical ancestry and biological ancestry are not uncommon, and these will be difficult to overcome  (22, 40). However, we believe that the genetic model, the simulation tools, and the publicly available simulated data we described provide a lens to investigate population genetics at an unprecedented resolution. For a given ancestor, we generate a heat map using the location of towns weighed by the average contribution of that ancestor to the probands of each town. The marriage location of each of the major contributors is indicated by a blue dot.
Acknowledgements We acknowledge the contributions of Ivan Krukov who we consider eligible for authorship, but were unable to contact for approval. We are grateful to all of the participants who enabled this study by contributing their DNA, and to the participants who provided family information enabling the reconstruction of their genealogy. For data from Quebec, we thank the BALSAC team for their management and curation of the genealogy database, the  CARTaGENE team and the Genome Quebec  for their management and curation of genotype data. For data from France, we thank the EREN team for their management and curation of SU. VI. MAX genotype data. We thank  Wilder Wohns ,  Yan Wong , and  Gil McVean  for enlightening conversations at early stages of the project, and  Aaron Ragsdale  for his comments on early drafts of this manuscript.
Data and materials availability R code for analyses and visualizations are available (https://github. com/LukeAndersonTrocme/ genes_in_space/). Tree sequences of simulated genomes are freely available on Zenodo (https://doi. org/10. 5281/zenodo. 6839683). Quebec genotype data are available upon request to (www. cartagene. qc. ca) and (https://www. mcgillgenomecentre. ca/) for CARTaGENE and Genizon cohorts respectively. Genealogical data are available on the Scholars Portal Dataverse platform from the University of Québec in Chicoutimi (https: //doi. org/10. 5683/SP3/BW7DIG. ).
1989 Destombe et al. , 1992 Destombe et al. , 1993;; Hughes and Otto 1999 ; mating system and sexual selection,  Richerd et al. 1993; Engel et al. 1999). The availability of genomic and genetic resources for these four Gracilaria species should aid in our understanding of the evolutionary ecology of red algae in their dynamic environment, during invasions of new habitats, under cultivation practices, and in response to climate change. Moreover, these new resources will add to the existing genomic data and illuminate key processes in eukaryotic evolution. The Rhodoexplorer Red Algal Genome Database currently includes the Gracilaria species discussed here but will include all the high-quality genomic resources available for the Rhodophyta (e. g. , genomes and transcriptomes), thereby providing a unique resource for comparative analyses.
Genome Assembly Genome assembly sizes were 72 and 76 Mb for G. gracilis and G. chilensis, respectively. In addition, we created a draft genome assembly based on the Illumina sequencing only for G. caudata (30 Mb) and reassembled the genome of G. vermiculophylla  (Flanagan et al. 2021 ) to a final 45 Mb after bacterial contamination removal. The above genome assemblies were comparable with the genomes of Gracilaria domingensis  (78 Mb; Nakamura-Gouvea et al. 2022)  and Gracilaria changii  (36 Mb; Ho et al. 2018). PacBio assemblies of G. chilensis and G. gracilis produced here (138 and 279 contigs, respectively; N50 of 1. 56 and 0. 56 Mb, respectively) are the most contiguous red macroalgal genomes presently available in public databases, apart from G. vermiculophylla and Pyropia yezoensis where the addition of a HiC library enabled scaffolding nearly at the chromosome level  (Wang et al.
2020; Flanagan et al. 2021). In G. vermiculophylla, however, regardless of the high N50 of 2. 56 Mb, the total number of contigs/scaffolds was also high  (7,753/4,240). The G. caudata assembly was fragmented with a low N50 of 21 kb and 55,767/5,535 contigs/scaffolds. Despite the differences in assembly size, BUSCO scores were similar across the long-readsequenced G. gracilis and G. chilensis (83. 6% and 81. 6% of conserved proteins present) and the more fragmented G. caudata genome (81. 6%, Eukaryota_odb10;  Manni et al. 2021 , Simão et al. 2015 ; table  1 ). The reassembled genome of G. vermiculophylla contained 71. 8% of the conserved proteins. Given the diversity of Rhodophyta and the lack of lineage-specific databases, these results are in the expected range. A recent study estimated the presence of conserved eukaryotic genes (Eukaryota_odb10) in red algal genomes at a median level of 69%  (Hanschen et al.
Gene Prediction and Annotation Gene prediction yielded a total of 7,943, 8,737, and 9,460 protein-coding sequences for G. chilensis, G. caudata, and G. gracilis (table  1 ), which was comparable with other red macroalgal genomes, C. crispus (9,815 genes;  Collén et al. 2013)  and G. changii genome (10,912 genes;  Ho et al. 2018). In addition, we annotated the reassembled genome of G. vermiculophylla, which yielded fewer genes (6,807). Among these genes, 70. 6-76. 6% did not contain any introns, as typical for the compact genomes of red algae  (Qiu et al. 2015). Most Gracilaria genes had homologous sequences in the Uniprot database (84. 2-89. 7%) and were annotated with at least one INTERPRO hit (91. 7-93. 6%). Between 47. 9% and 54. 4% of genes were associated with gene ontology (GO) annotations.
Rhodoexplorer Red Algal Genome Database In addition to depositing the raw reads and sequenced genome in a public repository, we integrated the data into the newly created Rhodoexplorer Red Algal Genome Database (https://rhodoexplorer. sb-roscoff. fr), which will include more red algal genomes in the future. The services provided include the following: • Information about the sequenced strains, with links to external databases (NCBI, WoRMS, and Algaebase). • Assembly and annotation metrics. • Data downloads: genomic, genes and proteomic data sets, structural and functional annotations, orthology clusters, etc. • A Blast interface with a selection of red algal genomes, predicted and de novo assembled transcriptomes and proteomes. • Visualization tools: a genome browser to visualize the predicted genes and the RNA-sequence (RNAseq) data mapped on the genome and a web interface to visualize functional annotations and retrieve individual protein sequences.