dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank the  ESRF   BM05  beamline to have provided access to beamtime, as well as  Thierry Brochard  for his help with the dosimetry experiments. The computational work was performed on the computational resource bwGRiD  Cluster Tübingen  funded by the  Ministry of Science, Research and the Arts Baden-Württemberg  and the  Universities of the State of Baden-Württemberg, Germany , within the framework program bwHPC. We want to thank  Marek Dynowski  for providing access to the computational resource bwGRiD  Cluster Tübingen  and his technical support. We are grateful to  Smiths Heimann GmbH ,  Andreas Frank ,  Arno Folkerts  and  Christian Rauth  ( Wiesbaden, Germany ) for sharing information about inspection devices in airports, as well as to  Anne Bonnin  ( Paul Scherrer Institut, Switzerland ).
The expert system combines the benefits of the two first approaches and enables high level semantic description such as the reading order, the semantic of the balloon shapes, the relations between the speech balloons and their speakers, and the interaction between the comic characters. Apart from that, in this thesis we have provided the first public comic book image dataset and ground truth to the community *  [1]  along with an overall experimental comparison of all the proposed methods and some of the state-of-the-art methods †  [2, 3].
POPULATION DEMOGRAPHY The main strength of ancient DNA is to open access to genetic variation in past populations, thereby providing maps of allelic frequencies through space and time. This information can significantly improve the statistical power to detect past population processes, for example, demographic expansions and declines  (Ramakrishnan and Hadly 2009; Mourier et al. 2012) , population splits  (Skoglund et al. 2014b) , etc. This is particularly relevant in cases where some historical events, for example, demographic collapses, have erased most of the genetic variation existing in the past and where our ability to resolve past population dynamics from modern DNA data alone is limited  (Heled and Drummond 2008 , see also Fig. 2b ). However, the additional power gained by including ancient DNA depends on the summary statistics used, the effective population size (N e ), the   S1  available as Supplementary material in Dryad as http://dx.
doi. org/10. 5061/dryad. tt78r), calibrated by adding the donkey  (Orlando et al. 2013)  as outgroup, considering a split time of 2. 75 Myrs ±650 kyr BP based on the most credible range estimate for the date when caballine (horse) and non-caballine (donkeys, asses, and zebras) equine lineages became genetically isolated  (Jónsson et al. 2014 ). Bayesian phylogenetic inference was performed with BEAST 1. 8. 2  (Drummond et al. 2012) , considering 5 site categories treated as unlinked partitions, following  (Achilli et al. 2012). Divergence was estimated using a loguncorrelated molecular clock model, including dating of ancient samples as calibration tips. The phylogenetic inference was run for 200 million generations, sampling the chain every 30,000, with 10% burn-in. Convergence was checked with Tracer v1.
Since there is a relatively simple relationship between effective population size and the probability of coalescence (i. e. , the larger the population size, the lower the probability that two sampled alleles are inherited from the same ancestor), this step only depends on the timing of the coalescent events and not on the exact genealogical relationships among the sequences (Fig. 2a )  (Pybus et al. 2000 ). Yet, unaccounted-for population structure  (Heller et al. 2013) , sequencing errors  (Heled and Drummond 2008 ) and, more specifically, postmortem DNA damage can lead to spurious variations in the effective population size  (Axelsson et al. 2008). The software most commonly used within this framework is BEAST  (Drummond et al. 2012) , and since it allows serial sampling over different time periods, it has been used in a variety of ancientmainly mitochondrial-DNA studies  (Ramakrishnan and Hadly 2009).
BEAST implements a Bayesian framework to jointly infer any parameter of the associated coalescent, including the tree topology, the dates of the internal nodes, the rate of evolution, and substitution models  (Drummond et al. 2002). The latest version of the software, BEAST 2  (Bouckaert et al. 2014 ) contains an add-on  (Gavryushkina et al. 2014 ) allowing implementation of the above-mentioned FBD model (see section on Calibration and Divergence estimates)  (Stadler et al. 2013). The first and perhaps most iconic study so far analyzed more than four hundred ancient bison mtDNA sequences from northern and eastern Asia and northern America. Bayesian skyline-plot reconstructions show that the bison genetic diversity started decreasing between 45 and 30 kyr ago, concomitant with the onset of the last glacial cycle, and increased again after 10 kyr ago  (Shapiro et al.
When the number of clusters is unknown, it can be inferred as the smallest number of K (the simplest model) within a credible range, giving the best fit to the data. Such a cross-validation procedure is provided within the program ADMIXTURE  (Alexander et al. 2009). Clustering approaches can be directly applied to genotype calls, pseudo-homozygous genotype calls (see Multivariate PCA Approaches), and genotype likelihoods. The latter is particularly convenient when low-coverage (ancient) genomes are examined and is implemented in the NGSAdmix software from the ANGSD suite  (Skotte et al. 2013). Clustering approaches have been extensively used in studies of ancient specimens, including horses (Der  Sarkissian et al. 2015b; Librado et al. 2015) , maize (da Fonseca et al. 2015), and cattle  (Park et al.
Tools allowing a range of analyses on low-coverage genomes in the genotype-likelihood framework are available in the open-source software Analysis of Next Generation Sequencing Data (ANGSD)  (Korneliussen et al. 2014). Analyses that can be performed in ANGSD range from estimation of population and individual statistics (SFS, Watterson's w , Tajima's D, inbreeding coefficients, etc. ), to population tests (ABBA-BABA, PCA, etc. -see above). This software has, therefore, been used in a number of ancient DNA studies, including for calculating the genome-wide distribution of heterozygosity and Tajima's D within user-defined genomic regions  (Orlando et al. 2013; Jónsson et al. 2014; Schubert et al. 2014b) , allele frequencies, inbreeding and F ST coefficients in modern and museum specimens of honey bees  (Mikheyev et al.
Analytical Tools for Ancient Metabarcoding A plethora of programs have been developed to perform metagenomic analyses of both metabarcoding and shotgun sequencing data sets (reviewed in e. g. ,  Sharpton 2014; Hoffman and Matsen 2015). A family of taxonomic assignment methods is e19 based on DNA sequence similarity between the query and taxonomically annotated sequences from comprehensive reference databases. One such method, the Basic Local Alignment Search Tool (BLAST;  Altschul et al. 1990 Altschul et al. , 1997) )  has been widely applied in ancient metagenomic studies, with subsequent analyses of taxonomic profiles sometimes carried out using MEGAN  (Huson et al. 2007). BLAST-based taxonomic assignment, however, suffers from a number of limitations  (Munch et al. 2008b ), including species mis-identification, and mapping scores based on local alignments that do not directly measure the statistical significance of the assignment.
Assignment methods based on phylogenetic criteria, and in particular the Statistical Assignment Package (SAP), were developed to address the latter limitation. SAP uses an automated method based on Bayesian phylogenetics for clustering sequences within supported taxonomic clades  (Munch et al. 2008a (Munch et al. , 2008b)). Other classification methods based on similarities in base composition or k-mer frequencies have been applied to modern data sets, (see e. g. ,  Sharpton 2014; Hoffman and Matsen 2015)  but their potential for analyzing ancient metagenomic data sets is currently unknown. Ancient metagenomic analyses have been carried out using computational pipelines, such as OBITools (https://git. metabarcoding. org/obitools/ obitools/wikis/home) and QIIME for microbes  (Caporaso et al.
2010) , which perform all analytical steps from post-sequencing DNA read processing, sequence comparison to reference databases and clustering, to taxonomic assignment, visualization, and statistical analyses. In addition, the program SourceTracker, which is part of the QIIME package, allows prediction of the source of microbial taxa representing distinct microbial communities within a microbiome  (Knights et al. 2011). It uses 16S rRNA data from different environments tested as sources, and directly estimates the proportions of contaminants from each source in the sink microbiome using Bayesian modeling. Applied to ancient coprolites from three sites  (Tito et al. 2012) , SourceTracker revealed variable preservation levels for the original gut microbiomes. While one sample was found to be representative of gut microbiomes typical of rural individuals, extensive microbial contamination from compost-like or unknown sources was identified in the other two samples.
False positives can result from contamination, nucleotide mis-incorporations at damaged nucleotides, and more generally from sequence errors, but can be detected through multiple replications and controls  (Ficetola et al. 2015). Second, the evolutionary relationships among metabarcodes do not necessarily reflect the true evolutionary relationships among species, for instance due to gene flow, incomplete lineage sorting, or horizontal gene transfer. Third, as so far restricted to taxonomic assignment, ancient metabarcoding analyses do not provide any information about the functional content of an environmental sample. Finally, the accuracy of taxonomic assignment requires high-quality comparative databases, and databases skewed toward specific taxonomic groups can mislead species-level assignment.
Efficient and Accurate Microbial Profiling from Ancient Samples Considering the limitations of ancient metabarcoding  (Ziesemer et al. 2015) , it is expected that microbial profiling of ancient specimens will mainly rely on HTS in the near future. However, HTS data sets are rapidly increasing in size, causing growing computational challenges. Moreover, the assignment accuracy can be limited by the short read length of ancient DNA templates. These problems are particularly acute for characterizing ancient microbial diversity from shotgun HTS data using BLAST-based approaches  (Warinner et al. 2014 ), but can be overcome with the program MetaPhlAn  (Segata et al. 2012; Truong et al. 2015). The MetaPhlAn database consists of a collection of specific taxonomically informative markers identified from pairwise genome comparisons of characterized microbial genomes.
It is, however, not immune to representation bias, as the vast majority of environmental microbes is still largely unknown, although likely to improve in the shorter term due to decreasing sequencing costs and the multiplication of microbial genome sequencing projects. MetaPhlAn was first applied to ancient shotgun HTS data to characterize the microbial diversity present in the DNA extracts from 7 horse remains dated back between 13 kyrs and 200 years ago (Der  Sarkissian et al. 2014) , representing a recent colonisation from the depositional soil. MetaPhlAn and the series of statistical analyses used VOL. 66 to compare microbial profiles in Der  Sarkissian et al. (2014)  have been implemented in two pipelines: as a module of the PALEOMIX package, dedicated to wholegenome resequencing analyses  (Schubert et al.
75 Myrs ±650 kyr BP based on the most credible range estimate for the date when caballine (horse) and non-caballine (donkeys, asses, and zebras) equine lineages became genetically isolated (Jónsson et al. 2014). Bayesian phylogenetic inference was performed with BEAST 1. 8. 2 (Drummond et al. 2012) , considering 5 site categories treated as unlinked partitions, following (Achilli et al. 2012). Divergence was estimated using a loguncorrelated molecular clock model, including dating of ancient samples as calibration tips. The phylogenetic inference was run for 200 million generations, sampling the chain every 30,000, with 10% burn-in. Convergence was checked with Tracer v1. 6. 0 (Rambaut et al. 2014) , also used for reconstructing the Bayesian skyline demographic profile, plotted with ggplot2 package (Wickham 2009 (Wickham  ), R (R et al.
Small artefacts such as microliths or beads were easily removed and repositioned along with the bones; one exception to this rule was a lignite bead found on the neck of individual Rein 1. Remarkably, there was a distinct lack of ceramic vessels in megalithic tombs, at least during the earlier period of their use. Researchers assume that this was due to ritual reasons  [5]. The archaeological material suggested a date for the megalithic tomb at Alto de Reinoso in the Late Neolithic. Overall the finds exhibited strong chronological coherence and were all Radiocarbon dates were obtained from three human bone samples recovered from different layers in the ossuary, giving a maximum chronological range of between 3770 and 3539 (2 sigma cal BC) (S2 Table ). The OxCal v4. 2. 4 software [28] allowed us to narrow down the actual time span represented by the radiocarbon dates to a period of 60 to 80 years, or roughly three generations (S2  Table  and S5 Fig).
However, the unusually high caries intensity in deciduous teeth (17. 8%) suggests that nearly all subadults suffered from tooth decay (exclusively molars) in their primary dentition. With 13. 4% affected deciduous teeth similar values exist at San Juan ante Portam Latinam  [62]  while the collective grave of Benzingerode, Germany, did not contain a single carious deciduous tooth  [25]. Several datasets on caries intensity in deciduous teeth in earlier Linearbandkeramik communities in Germany exist: 5. 4% at Aiterhofen  [64]  and 2. 7% at Wandersleben  [65]. The reasons for the rather high percentages of caries in deciduous teeth seem to be associated less with the socioeconomic status of the population but rather with specific dietary habits, especially the consumption of carbohydrate-rich sticky food such as porridge but also due to prolonged breastfeeding  [66, 67].
Molecular genetics The HVR I and coding region single nucleotide polymorphisms (SNPs) of the mitochondrial genome (GenoCoRe22;  [32] ) were successfully reproduced for 26 out of the 27 individuals analysed (www. ncbi. nlm. nih. gov/genbank; accession numbers KT868907-KT868932), resulting in an extremely high amplification success for ancient DNA analyses especially in relation to studies from south-western Europe (S1 and S7 Tables). Furthermore, H -plex analyses  [70]  defined the specific subhaplogroup of an individual belonging to haplogroup H (S8 Table ). The individuals buried in the megalithic tomb at Alto de Reinoso belonged to mtDNA (sub-) haplogroups H3 (n = 1; 3. 7%), J (n = 1; 3. 7%), K (n = 8; 29. 6%), T2 (n = 4; 14. 8%), U4 (n = 1; 3. 7%), U5b (n = 7; 25. 9%), V (n = 2; 7. 4%), and X (n = 3; 11.
00031), Rein 30 (Δ 87 Sr/ 86 Sr M1-M2 = 0. 00026), and Rein 5 (Δ 87 Sr/ 86 Sr M1-M2 = 0. 00019) were larger than those of all individuals with both measurements within the local range. As these differences are larger than the analytical error they may point to a shift in diet catchment areas during childhood, even though it would have involved localities with very similar geological conditions to those at Alto de Reinoso. The site is surrounded by calcarenites and conglomerates of the Lower Neogene  [90] , which were also used in the construction of the tomb itself and are widely distributed around the site (S6 Fig). Only a few studies on bioavailable 87 Sr/ 86 Sr isotope ratios from archaeological sites on the Iberian Peninsula have been published so far  [91] [92] [93]. A rich comparative dataset from the area, which includes human enamel, bone, dentine, and faunal samples was gathered at the early medieval cemetery of San Martín de Dulantzi (Algría-Dulantzi, Álava) some 90 km north-east of Reinoso, where Cretaceous limestone and marls prevail  [92].
In examining the dataset as a whole, one of the striking features is that three of four individuals with a slightly divergent Sr isotope pattern compared to the remainder of the population (Rein 3, 23 and 30), had genetic profiles that did not have any parallels in the collective burial (Fig  5 ), despite the fact that numerous haplotypes were represented at the site. The lack of evidence regarding to biological relations between these three individuals and the other members of the community supports the assumption that they had come from elsewhere. The isotope ratios in the late mineralising tooth crowns of Rein 3 and Rein 30 were equivalent to the local baseline, which means that if there had been a change of location it would have occurred during their childhood. The individuals with identical haplotypes, on the other hand, largely yielded Sr isotope ratios typical of the locality and very slight differences between the 87 Sr/ 86 Sr ratios in the earlier and later mineralised teeth, which both argues against residential changes.
This further confirms the notion of a closely related community, several generations of which sourced their food from geologically uniform economic areas. One possible exception was the 16-20 yearold male individual Rein 5 (hg T2b) with 87 Sr/ 86 Sr ratios typical of the locality in the first permanent molar, whilst the second permanent molar yielded the lowest Sr isotope ratio of the entire dataset. Whilst it is quite possible that the individual was born locally, he may have lived with a different community for some of his childhood. However, due to the only slight difference in the 87 Sr/ 86 Sr ratios of both teeth and the small number of comparable samples it must be emphasised that this is only one possible interpretation. The Sr isotope ratios overall paint a picture of the funerary site at Alto de Reinoso as a largely closed community within which (long-distance) mobility probably played a rather insignificant role.
by means of a principle component analysis (PCA) and Ward type hierarchical clustering (Fig 4a and 4b). The first and second principal components (PCs) account for approximately 38% of the overall variability of the dataset on the PCA. The closest groups to Alto de Reinoso are the Early/Middle Neolithic Bernburg (BEC) populations in Central Europe, the Late Neolithic south French Treilles group (TRE) and the Chalcolithic El Mirador community (Fig 4b). The north Spanish and the central Portugal Neolithic groups together with the south-western European hunter-gatherers (HGSW) are separated from the main cluster along the N, U, and H haplogroups. The Central European hunter-gatherer metapopulation (HGC) is clearly separated from the Iberian groups and Central European Neolithic too, indicating population discontinuity during Neolithisation of Central Europe [16,86,89].
Acknowledgments We thank  Willi Dindorf  and  Sabine Moeller-Rieker  ( University of Mainz ),  Sigrid Klaus ,  Michael Brauns  and  Bernd Höppner  ( Curt-Engelhorn-Centre Archaeometry gGmbH Mannheim ) as well as  Bernd Kromer ,  Susanne Lindauer ,  Robin van Gyseghem  and  Ute Blach  ( Klaus-Tschira Archaeometry Centre at the Curt-Engelhorn-Centre Archaeometry Mannheim ) for technical assistance for the preparation of samples and for conducting measurements,  Sandy Haemmerle  (prehistrans) for language editing, and  Sandra Pichler  ( Integrative Prehistory and Archaeological Science, Basel, Switzerland ) and the anonymous reviewers for comments that greatly improved the manuscript.
Materials and Methods Participants. Ten amusic participants and ten non-musician control participants matched for age, handedness, educational background (years of education), and musical training (years of musical instruction: teaching/ practice) participated in the study. The amusic group (age range: 62 to 72 years) and the control group (age range: 61 to 75 years) were right-handed francophone participants from Montreal and surrounding areas. Participants reported no history of neurological or psychiatric disease, and had audiometric thresholds below 30 dB HL for frequencies below or at 4 kHz. Data from the pre-tests are presented in Table  1  and Supplementary information Table  A. Participants gave their written informed consent and were paid for their participation. The research was carried out in accordance with approved guidelines of the Comité d'éthique de la recherche en arts et en sciences (CERAS) of the Université de Montréal.
Note that this pattern of results differs from that described in 4 and 1 , where amusics showed decreased performance in comparison to controls for the one-semitone interval. The amusic group participating in the present study thus exhibit better pitch change detection abilities than the group from these previous studies (see Supplementary information Table  A ). Tone pairs were created using eight piano tones differing in pitch height (Cubase software, Steinberg), but all belonging to the key of C Major (C3, D3, E3, F3, G3, A3, B3, C4, frequency range from 130. 81 Hz to 261. 63 Hz). This material was chosen to allow for comparisons between Task 1 and Task 2 (as Task 2 was a tonal melodic task, see below). Task 2: Short-term memory task with tone sequences. For each sequence length (three-tone sequences, four tone sequences) 128 different diatonic melodies (presented as the first sequence, S1) were created using the piano tones of Task 1.
Statistical analyses. Statistical analyses were conducted with Statistica (StatSoft, Inc, Tulsa, OK, USA). Performance in both tasks was evaluated as percentages of Hits (correct responses for different trials/ number of different trials) minus percentages of False Alarms (FAs, incorrect responses for same trials/number of same trials). Percentages of Hits-FAs were analyzed with a repeated measure ANOVA. To analyze significant interaction, post hoc tests were performed using Fischer LSD. For all the measures of interest we tested if the samples (controls and amusics) were derived from a population normally distributed using Kolmogorov-Smirnov tests. These analyses revealed that all data were normally distributed (P > 0. 20). Furthermore, we computed correlations over all participants and for the amusic and control group, separately.
Acknowledgements This work was supported by grants from the  Natural Sciences and Engineering Research Council of Canada , the  Canadian Institutes of Health Research , and the  Canada Research Chairs program  to IP and by a grant from " Agence Nationale de la Recherche" (ANR)  of the  French Ministry of Research   ANR-11-BSH2-001-01  to BT and AC. PA was funded by a  PhD fellowship  from the  Centre National de la Recherche Scientifique (CNRS)  and by exchange funding from the  ERASMUS MUNDUS Auditory Cognitive Neuroscience Network. This work was conducted within the framework of the  LabEx CeLyA ("Centre Lyonnais d' Acoustique ",  ANR-10-LABX-0060 ) and of the  LabEx Cortex ("Construction, Function and Cognitive Function and Rehabilitation of the Cortex ",  ANR-11-LABX-0042 ) of  Université de Lyon , within the program " Investissements d'avenir"  ( ANR-11-IDEX-0007 ) operated by the  French National Research Agency (ANR).