dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2018). We merged individuals into groups (Supp. Mat. 1F,G). For ancient samples, these groups were chosen manually, trying to strike a balance between reducing overlap in the PCA and keeping culturally distinct populations separate. We used geographic location to first broadly group samples into geographic areas (such as Iberia, Central Europe and Balkans), and then further annotated each of these groups by different time periods. Contemporary DNA datasets from Western Eurasia. We downloaded and processed the Human Origins dataset to characterize a subset of Eurasian human genetic diversity at 594,924 autosomal SNPs  (Lazaridis et al. , 2014). To be consistent with previous studies  (Lazaridis et al. , 2014; Mathieson et al. , 2015) , we focused on a subset of 777 individuals from Western Eurasia.
Estimation of F ST -coefficients To measure pairwise genetic differentiation between two populations, we estimated average pairwise F ST and standard error via block-jackknife over 1000 markers, using average_patterson_fst from the package scikit-allel. When analyzing ancient individuals that were represented as pseudo-haploid genotypes, we analyzed only one allele to avoid artificial genetic drift. For this analysis, we removed first degree relatives within each population. Another estimator, average_hudson_fst gave highly correlated results (r 2 " 0. 89), differing mostly for populations with very low sample size (n ď 5) and did not change any qualitative conclusions.
Inference of Y haplogroups To determine the haplotype branch of the Y chromosome of male ancient individuals, we analyzed informative SNPs on the Y-haplotype tree. For reference, we used markers from https:// isogg. org/tree/ (Version: 13. 238, 2018). We merged this data-set with our set of calls and identified markers available in both to create groups of equivalent markers for sub-haplogroups. Our targeted sequencing approach yielded calls for up to 32,681 such Y-linked markers per individual. As the conventions for naming of haplogroups are subject to change, we annotate them in terms of carrying the derived state at a defining SNP. We analyzed the number of derived and ancestral calls for each informative marker for all ancient Sardinian individuals, and additionally reanalyzed male ancient West Eurasians in our reference data set.
Results from fitting models of admixture with qpAdm. A) Two-way models of admixture for ancient Sardinia using Western Hunter-Gatherer (WHG) and Neolithic Anatolia (Anatolia-N) individuals as proxy sources. B) Three-way models of admixture for ancient Sardinia using Western Hunter-Gatherer (WHG), Neolithic Anatolia (Anatolia-N), and Early Middle Bronze Age Steppe (Steppe-EMBA, abbreviated Steppe in table), individuals as proxy sources. C) Single-source models to assess continuity of each Sardinian period with the previous one (see main text for guide to abbreviations). E) Results of three-way models showing multiple eastern Mediterranean populations that can produce viable models (Results shown with individuals from Lombardy [Bergamo in the HOA dataset] as one of several possible proxies for north Mediterranean ancestry, see part F).
Acknowledgements We thank  Maanasa Rhagavan  for in-depth feedback on drafts,  Anna Di Rienzo  and  Goncalo Abecasis  for helpful discussions, and  Magdalena Zoledziewska  for useful comments and early assistance. We would like to thank  Antje Wissgott ,  Cäcilia Freund  and other members of the wet laboratory and computationally teams at MPI-SHH in Jena. We thank  Nadin Rohland ,  Éadaoin Harney ,  Shop Mallick , and  Alan Cooper  for contributing to generating the data for the four samples processed at the  Australian Centre for Ancient DNA  and in D. R. 's ancient DNA laboratory. We also thank  Dan Rice ,  Chi-chun Liu , and members of the  Novembre lab  for helpful discussion and feedback. This study was supported in part by the  National Science Foundation  fellowship  DGE-1746045  and the  National Institute of General Medical Sciences  under training grant award number  T32GM007197  to J.
Data Availability The raw reads and aligned sequences of the data generated from this study will available through the European Nucleotide Archive (ENA) before publication under accession number [TBD prior to publication]. Processed genotype calls will be posted to the Novembre Lab website and on Data Dryad. The contemporary Sardinia data used to support this study have allele frequency summary data deposited to EGA under accession number EGAS00001002212. The disaggregated individual-level sequence data for 1,577 used in this study is a subset of 2,105 samples (adult volunteers of the SardiNIA cohort longitudinal study) from  Sidore et al (2015)  and are available from dbGAP under project identifier phs000313 (v4. p2). The remaining individual-level sequence data are from a case-control study of autoimmunity from across Sardinia, and per the obtained consent and local IRB, these data are only available for collaboration by request from the project leader (Francesco Cucca, Consiglio Nazionale delle Ricerche, Italy).
F) Results of three-way models showing multiple north Mediterranean populations that can produce viable models (Results shown with Jewish individuals from Turkey ['Turkish-Jew' in the HOA dataset] used as one of several possible proxies for east Mediterranean ancestry, see part E). As a visual aid, p-values greater than 0. 01 are bolded. Full results are reported in Supp. Info. 6. Proxy Source Populations Admixture Fractions Standard Error Target a b c p-value a b c a b c A Sar-NECA WHG Anatolia-N - 0. 677 0. 173 0. 827 - 0. 014 0. 014 - Sar-EMBA WHG Anatolia-N - 0. 062 0. 163 0. 837 - 0. 007 0. 007 - Sar-Nur WHG Anatolia-N - 0. 182 0. 166 0. 834 - 0. 009 0. 009 - B Sar-NECA WHG Anatolia-N Steppe 0. 588 0. 172 0. 824 0. 003 0. 016 0. 023 0. 026 Sar-EMBA WHG Anatolia-N Steppe 0. 041 0. 163 0.
We present information on primary type specimens for 13,282 species and subspecies of reptiles compiled in the Reptile Database, that is, holotypes, neotypes, lectotypes, and syntypes. These represent 99. 4% of all 13,361 currently recognized taxa (11,050 species and 2311 subspecies). Type specimens of 653 taxa (4. 9%) are either lost or not located, were never designated, or we did not find any information about them. 51 species are based on iconotypes. To map all types to physical.
org), and many others. Another important goal of our project is to standardize collection acronyms, a problem that has inhibited comparisons between collections and datasets for many years. For some collections, more than half a dozen acronyms have been used across multiple publications, which makes it extremely difficult to keep track of their specimens. This becomes an even bigger problem when specimens are cross-referenced, for example in DNA sequence databases. For example, publications have referred to the Raffles Museum of Biodiversity Research of the National Museum of Singapore as either LKCNHM, NMS, NUS, RM, RMBR, ZRCS, or USDZ as the collection acronym. We have consolidated such acronyms into a single acronym (here: ZRC, for Zoological Reference Collection for the Raffles Museum following  Sabaj (2016)  and replaced ambiguous acronyms with unique ones whenever necessary (see Methods).
Materials and methods Primary type information was collected from numerous sources including published type catalogs, books, taxonomic monographs, species descriptions, unpublished museum collection catalogues and databases such as online type catalogs (see references and Supplementary Table  S1 ). Not all literature sources can be cited here, or in the table, given that the type information for thousands of species was extracted from their original descriptions, taxonomic revisions, or from collection catalogues. These references can be found in the Reptile Database and in  Uetz & Stylianou (2018). Note that we focus on primary types: holo-, lecto-, neo-and syntypes. Secondary type specimens (e. g. , allotypes, paratypes) were beyond the feasible scope of this compilation. However, the Reptile Database lists paratypes for more than 2000 species.
While we could have opted to delete paratypes to make this compilation more consistent, we decided to include as much information as was available to us. The type catalog in the Reptile Database is an ongoing project, so we will try to include all secondary types in the future. For a more detailed definition of primary type specimens see  ICZN (1999: Chapter 13, Article 61, and chapter 16, Articles 71-75). Importantly, we only consider types of currently accepted species and subspecies. The primary types of some junior synonyms can be found in the species accounts within the Reptile Database, although this list is not complete. Taxon names, type information, and literature data, were stored internally in a Filemaker database and processed using custom scripts written in Filemaker Pro 16, Python 3, and R 3.
Results and discussion We assembled data for primary type specimens (or at least the collections that house them) for 13,282 of the 13,361 (99. 4%) currently recognized reptile species and subspecies listed in the Reptile Database. That is, for 13,282 reptile taxa we found some information about their primary types, including those considered lost or unknown, but only 12,658 taxa appear to have known existing types. These numbers only include currently accepted names but omit synonyms. A common problem was to associate specimens with collections and institutions. Many species descriptions do not give explicit collection information or do so only indirectly, especially in the older literature. For instance, if an author is affiliated with a certain museum, it is often tacitly assumed that all described specimens are maintained in that collection.
Digitization of type collections. Several projects around the world have started to digitize and unite museum collection data into more comprehensive digital catalogues of specimens (not just types). In the US, the National Science Foundation (NSF) has supported efforts such as VertNet  (Guralnick et al. 2016)  and iDigBio (https://www. idigbio. org) for many years. Internationally, GBIF (https://www. gbif. org) has worked on similar projects with a focus on geo-referencing specimen localities  (Constable et al. 2010). However, we do not know what fraction of vertebrate collections and their types have so far been included within these larger scale projects. Those efforts should not be confused with other projects that digitize the actual specimens, e. g. by photographing or CT-scanning  (Broeckhoven et al.
Often it is not indicated in published type information whether tissue samples are available and where they are stored. In theory, it should be easy to distribute available DNA extracts from type specimens to multiple collections, but this is rarely done. For numerous applications, genomic DNA would be a much better resource, especially since mtDNA is of limited use beyond bar-coding and phylogenetic studies. For instance, genomic DNA allows us to investigate the genetic basis of many biological traits such as venom (Junqueira-de-Azevedo et al. 2016), coloration  (Saenko et al. 2015) , ecological adaptations  (Li et al. 2018)  or morphology such as limb loss  (Thompson et al. 2018). The National Center for Biotechnology Information (NCBI), which maintains both GenBank and the NCBI taxonomy database  (Federhen 2012) , has recently started to include specimen information, including type data, into their database  (Federhen 2015).
This allows researchers to refer a specific DNA sequence to a voucher specimen, if the latter exists. Given that specimens in collections may be misidentified and species names may change due to taxonomic revision, this is a welcome improvement that will help map sequences to specimens. For example, accession MF154856 in GenBank contains the RAG1 sequence from the holotype of the gecko Goggia matzikamaensis  (Heinicke et al. 2017) , with specimen voucher and the type material qualifiers: specimen_voucher="MCZ: R-192186" and type_material="holotype of Goggia matzikamaensis". Outlook. While type specimens remain critical to taxonomy, an ever-improving digital infrastructure makes it increasingly easy to gain virtual access to type specimens. Access is facilitated both by databases such as the Reptile Database, but also by access to DNA databases and 3D scans of specimens.
In the near future, researchers will be able to remotely investigate a specimen using computerized 3D visualizations of external (e. g. http://digitallife3d. org) as well as internal (https://www. morphosource. org) anatomy. We are still a long way from predicting phenotypes from genome sequences, and thus type specimens will continue to be required for a long time as the standard for taxonomic reference. We therefore expect this catalog will facilitate future research on the taxonomy and systematics of reptiles by increasing the visibility and utility of the primary types and the collections that house them. Availability and updates to this catalog. The type catalogue described in this paper is available as a downloadable spreadsheet in Supplementary Table  S3. The data will be continuously updated in the Reptile Database (http://www.
Acknowledgments Open access fees were defrayed by authors. Digitization of the ZISP collection was supported by the  Russian Foundation for Basic Research  ( RFBR 17-54-61015  and  18-04-00040 ) and the  Zoological Institute, Russian Academy of Sciences  State (Project  AAAA-A17-117030310017-8 ). Jacqueline Ellis helped at an earlier stage with URL mapping,  Jakob Hallermann  provided details on certain types.
The VBS-GECKO parameterization for secondary organic aerosol (SOA) formation was integrated in the chemistry-transport model CHIMERE. Concentrations of organic aerosol (OA) and SOA were simulated over Europe for the July-August 2013 period. Simulated concentrations with the VBS-GECKO were compared to results obtained with the former H 2 O parameterization implemented in CHIMERE and to observations from EMEP, ACTRIS and other observations available in the EBAS database. The model configuration using the VBS-GECKO parameterization slightly improves the performances compared to the model configuration using the former H 2 O parameterisation. The VBS-GECKO model configuration performs well for stations showing a large SOA concentration from biogenic sources, especially in northern Europe but underestimate OA concentrations over stations close to urban areas.
MELCHIOR2 is a reduced version of the MELCHIOR1 mechanism, obtained by the Carter's surrogate molecule method  (Carter, 1990). In CHIMERE, the aerosol evolution is described by a sectional aerosol module (e. g. Bessagnet et al. , 2004 Bessagnet et al. , , 2009;; Schmidt et al. , 2001). The size distribution of aerosol particles is here represented using 9 bins, ranging from 10 nm to 10 μm. Aerosol formation is represented in the model by nucleation for sulfuric acid  (Kulmala et al. , 1998) , coagulation between particles (e. g. Debry et al. , 2007; Jacobson et al. , 1994)  and condensation/evaporation via absorption according to the "bulk equilibrium" approach (e. g. Pandis et al. , 1993). For inorganic species, the gas/particle equilibrium concentrations are calculated using the ISORROPIA v2.
1  (Fountoukis and Nenes, 2007)  thermodynamic module. For organic species, the equilibrium concentrations are calculated using the SOAP (Secondary Organic Aerosol Processor) thermodynamic module  (Couvidat and Sartelet, 2015). The gaseous formation of secondary organic species able to partition between the gas and the condensed phases (so leading to SOA formation) are represented in the CHIMERE β version using the H 2 O mechanism. Here, the VBS-GECKO parameterization has also been implemented. The H 2 O and VBS-GECKO organic aerosol modules are described hereafter. The chemical speciation of emitted non-methane volatile organic compounds (NMVOC) is taken from  Passant (2002)  as described in  Menut et al. (2013). Primary organic aerosol (POA) from emission inventories are considered as SVOC.
0  (Emmons et al. , 2010) ). Wildfire emissions were not considered. The VBS-GECKO mechanism was evaluated comparing the simulated results to the H 2 O mechanism and particulate phase measurements available in the EBAS database (http://ebas. nilu. no/). EBAS is a database hosting observation data of atmospheric chemical composition and physical properties in support of a number of national and international programs ranging from monitoring activities to research projects. EBAS is developed and operated by the Norwegian Institute for Air Research (NILU). This database is populated for example by the EMEP measurements  (Tørseth et al. , 2012)  or the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS, http://www. actris. eu/) ones. 48 rural background stations provide measurements for fine particulate matter and were thus selected here for a statistical evaluation: 36 stations for PM 2.
The distribution of alkanes and alkenes was estimated based on (i) the EMEP guidebook (https://www. eea. europa. eu/publications/emep-eea-guidebook-2016), providing speciation data for emissions for various types of vehicles and (ii) the COPERT4 software  (Ntziachristos et al. , 2009)  providing data for a vehicle fleet. Data are only available for light compounds and are here extrapolated to the heavy ones for the needs of the study. Thus, 75 % of the S/IVOC species are here assumed to be alkanes and 25 % alkenes. The SVOC total emissions and distributions over volatility bins are unchanged between each simulation. The distribution of IVOC among volatility bins is also unchanged but the total IVOC emissions are modulated according to the assumptions on IVOC emissions. Table  5  gives the speciation of VBS-GECKO species for the various model configurations and the VBS-GECKO mechanism for S/IVOC is presented in Table  S3  of supplementary material.
Acknowledgments The authors gratefully acknowledge  Olivier Favez ,  Liine Heikkinen  and  Laurent Poulain  for providing ACSM data realized in the framework of ACTRIS. This work was financially supported by the  French Environment and Energy Management Agency (ADEME)  and  INERIS. We also thank  French Ministry of Ecology  for its financial support. Simulations were performed using the TGCC-CCRT super computers.
Stellar streams are regarded as crucial objects to test galaxy formation models, with their morphology tracing the underlying potentials and their occurrence tracking the assembly history of the galaxies. The existence of one of the most iconic stellar streams, the double loop around NGC 5907, has recently been questioned by new observations with the Dragonfly telescope. This new work only finds parts of the stream, even though they reach a 1σ surface brightness limit of 30. 3 mag arcsec -2 in the g-band. Using 7. 2 hours of Luminance L-band imaging with the Milanković 1. 4 meter telescope, we have re-observed the putative double loop part to confirm or reject this assessment. We do not find signs of the double loop, but see only a single, knee-shaped stellar stream. Comparing our to the data by the Dragonfly team, we find the same features.
Observations and data reduction The galaxy NGC 5907 was observed on three consecutive nights (24 -26 October 2019) with the 1. 4 meter Milanković telescope mounted at the Astronomical Station Vidojevica (Serbia), using an Andor IKONL CCD camera. The observations were taken at an airmass between 1. 66 < X < 2. 97. The dark current is 0. 02 e-/sec. All images were taken in the luminance L-filter with 300 second exposures. The integrated exposure time reached was 7. 2 hrs. We had photometric nights with an average seeing of 1. 4. The galaxy was at an altitude of 40 degrees at the beginning and went down to 20 degrees at the end of observations each night. Utilizing the focal reducer delivers a square field-ofview with sides of 13. 3. We applied a large dithering pattern randomized within a maximum offset of 4 , which is crucial when digging deep into the low-surface brightness regime at the 28-29 mag arcsec -2 level  (Slater et al.
This stack will give a background model, which is free from astronomical sources due to the large dithering pattern we have applied. Because it is normalized, it can be scaled to the measured background values in the scientific exposures using the the global background value estimated by Source Extractor and ultimately removed, resulting in our final fully calibrated and background subtracted science frames. The final, fully calibrated and dithering image reached a field-of-view of 18. 8 × 20. 3. The python pipeline can be found on gitlab 1. The astrometry in the science frames was solved by astrometry. net (Lang et al. 2010 ). To create our final scientific image, we have stacked all science frames with IRAF's imcombine command, using a median stack and an average sigma clipping rejection algorithm.
Low surface brightness features In Figure  1  we present the fully stacked and calibrated image of the surroundings of NGC 5907, slightly enhanced with a Gaus-1 gitlab. com/VoltarCH/milankovic-telescope-reduction-pipeline sian blur. What low-surface brightness features does it reveal? We detect a narrow low-surface brightness feature stretching 10. 5 (≈ 43 kpc at 14 Mpc) from the disk of the galaxy towards the east and then bending 4. 2 (≈ 17 kpc at 14 Mpc) towards the north, where it gradually disappears. This morphology is reminiscent of stellar streams found in other galaxy group, e. g. around NGC 1052  (Müller et al. 2019). In Figure  2   2008 ). There are no hints of these structures in our image. We applied the same post-processing techniques as  Martínez-Delgado et al. (2008) , namely, a histogram equalization and a Gaussian blur.
Along these regions, we measure a 1σ surface brightness limit of 29. 7 mag arcsec -2 g-band (i. e. a 3σ limit of 28. 4 mag arcsec -2 ). However, we note that this is measured before the image is enhanced, giving a lower limit of what is detectable. In Figure  3  we also show the part of the image with a 100% coverage of exposures, corresponding to the deepest part of the full stack. The two putative streams are residing well within this area, so incompleteness of the data should play no role. In contrast, the part of the stream to the west (i. e. bottom right) of NGC 5907 is not detectable in our image, whereas it is A&A proofs: manuscript no. aanda visible in the Dragonfly images (see Figure  2 ). This part coincides with an incomplete area of the image, see also our weight map in Figure  3.
4 meter telescope, reaching a depth of 29. 7 mag arcsec -2 in the g-band, and find no signs of the iconic double loop around NGC 5907. Rather, we find a single knee-shaped stream as independently found by the Dragonfly team. These results emphasize the need for an independent confirmation of the reliability of the detected low-surface brightness features by the usage of different telescopes, carefully designed observing strategies, and consistent scientific processing techniques. This work used following scientific software: Astrometry. net  (Lang et al. 2010) , the DAOPHOT2 suite  (Stetson 1987) , and IRAF  (Tody 1993) ; as well as following python3 packages: Astropy  (Astropy Collaboration et al. 2013) , ccdproc  (Craig et al. 2015) , and sep  (Barbary 2016) , which is a python implementation of Source Extractor  (Bertin & Arnouts 1996).