dataesr/scientific-paragraphs-categorization huggingface dataset:
The dataset was prepared by extracting all transversion SNPs and choosing alleles with minor allele frequency 3 10% in Yorubans to avoid the effect of Eurasian admixture into Yorubans, as described in (Gu ¨nther et al. , 2015; Kılıncet al. , 2016). 20, 135 This dataset was used for outgroup f 3 and D-statistics, F ST estimation, ROH analysis and also for kinship estimation analysis. For qpAdm analyses, we merged DS2 with SGDP v4  153  (Simons Genome Diversity Project, downloaded from https://reichdata. hms. harvard. edu/pub/datasets/sgdp/) by overlapping 1,479,034 SNPs. DS3: X chromosome SNPs from the 1000 Genomes whole genome sequencing dataset version (phase 3) 126 that were genotyped in West African Yorubans were extracted and those with minor allele frequency 3 10% were chosen (across n = 56 female and n = 52 male Yoruba individuals).
We also removed pseudoautosomal regions from X chromosomes as described in the human reference genome (hs37d5). We included only transversion SNPs in this dataset. The resulting 73,799 SNP list was used for X chromosome-based kinship estimation. Genotyping For each of the described SNP datasets, we genotyped ancient individuals at each SNP using reads with minimum base quality and mapping quality of 30. We pseudohaploidized our data, such that when multiple reads overlapped with the same SNP we randomly selected one read and this position was assumed to be homozygous in the ancient individuals. 20, 154 We removed the non-biallelic sites, transitions and indels including the sites that were found in an ancient individual but not in the reference data. To avoid the influence of postmortem damage, whenever we encountered a T or an A when the reference genome carried a C or a G, respectively, we coded that position as missing in the ancient genotype, following.
Principal components analysis We carried out principal component analysis (PCA) as a first assessment of the genetic affinities of the newly generated genomes from As xıklı and C ¸atalho ¨yu ¨k following. 20 First, we conducted PCA using a total of 49 modern-day West Eurasian populations from the Human Origins SNP Array dataset  25, 139  and projected the 136 ancient individuals (114 previously published and 22 reported in this study) onto the first two principal components inferred from modern individuals. The list of modern-day populations is presented in Figure  S3B. For this, the smartpca program in the EIGENSOFT package  155  was used with the parameters ''numoutlieriter:0'' and ''lsqproject:YES''. We used dataset DS1 for Figure  1B. We further repeated the PCA also using transversion SNPs only (Figure  S3C ).
f 3 -and D-statistics To investigate pairwise genetic affinity between populations or between individuals, we computed outgroup f 3 -statistics using DS2 (autosomal data) with the qp3Pop program in the ADMIXTOOLS package. 25 This quantifies shared drift between individuals/populations as their divergence from an outgroup population. 25 The calculation was performed at both the individual and the population levels. The Yoruba (YRI) population from 1000 Genomes Project phase 3  152  was used as an outgroup. To study population-level similarities, we converted f 3 -statistics into a pairwise distance matrix by subtracting all values from 1; we then summarized this distance matrix on two dimensions using multidimensional scaling (MDS) with the 'cmdscale' function in the R 'stats' package (http://www.
For D-tests we used the program qpDstat in the ADMIXTOOLS package, and used the Yoruba population as outgroup. Statistical significance and the confidence intervals were estimated using the block-jackknife procedure by ADMIXTOOLS. Confidence intervals shown in plots display ± 2 standard errors from the mean. We used a cutoff of |Z|  3  3 for nominal statistical significance but did not apply multiple testing correction, due to the descriptive nature of the analyses. We conducted additional individual-level D-statistics (a) only using shotgun data for Boncuklu to avoid the influence of technical biases that may arise due to use of capture and shotgun data, (b) comparing only Boncuklu and As xıklı Ho ¨yu ¨k data to directly test possible structure within Aceramic Central Anatolia (Figures  S3E  and S3F ).
Technical influence on f 3 -statistics Because our dataset includes genomic data produced by different laboratory procedures, including shotgun sequencing and 1240K SNP capture, we explored the possible influence of technical effects on outgroup f 3 -statistic estimates, taking advantage of the fact that our dataset contained both types of data for individuals from Boncuklu,  20, 21  and that Boncuklu Ho ¨yu ¨k shows high genetic homogeneity within the settlement (see below). We found that f 3 -statistics that include pairs of individuals with genomic data produced using alternative procedures are only slightly lower than f 3 -statistics that include pairs of individuals produced using the same procedure, when autosomal data is included (Figure  S1D ). On the other hand, calculating the same statistics with X chromosomal data, we observed a conspicuous technical effect (Figure  S1D ).
ADMIXTURE analysis We performed unsupervised genetic clustering using ADMIXTURE 24 software to estimate ancestry components in ancient genomes produced in this study. We used present-day Eurasian, African, Asian, and American groups' genotype data from the Human Origins dataset (n = 231)  25, 139  and merged this with the ancient individuals' genotypes. We filtered the dataset by pruning for linkage disequilibrium using PLINK  156  with the parameters ''-indep-pairwise 200 25 0. 4'' and for missing genotype with ''-geno 0. 99'', leaving 518,401 SNPs to be analyzed. We conducted ADMIXTURE analysis for each value of K ranging from 2 to 15 and determined the clusters of each ancient individual using the ''projection'' function of ADMIXTURE. We visualized the results using PONG software. 157.
F ST estimation We computed pairwise F ST to evaluate genetic differentiation among early Holocene populations from Anatolia, Levant and Iran. Population-level F ST were calculated for ancient population samples that included at least two ancient individuals -the same criterion as used for f 3 -statistics-based population comparisons. The smartpca program in the EIGENSOFT package  155  was used with default parameters ''inbreed:YES'' and ''fstonly:YES'', and with DS2 (autosomal data). We visualized the results on two dimensions using multidimensional scaling (MDS) with the 'cmdscale' function in the R 'stats' package (http://www. r-project. org/) (Figure  S2B ; Table  Z6 ). qpWave/qpAdm admixture analysis We modeled target Anatolian Ceramic period populations (C ¸atalho ¨yu ¨k and Barcın) as admixture between two or three source populations using the qpWave (v1200) and qpAdm (v1201)  158  programs in ADMIXTOOLS (v7.
Estimating genetic relatedness and pedigree relationships Overview of kinship analyses We first inferred relatedness coefficients for pairs of As xıklı and C ¸atalho ¨yu ¨k individuals and previously published Anatolian Neolithic individuals. For this we used three different software, NgsRelate,  35  lcMLkin,  36  and READ,  37  as described below. NgsRelate and lcMLkin infer the genetic kinship coefficient (q) between a pair of individuals, i. e. , the probability that a pair of randomly chosen alleles from two individuals each are identical-by-descent (IBD). For this they first estimate k 0 , k 1 , k 2 (Cotterman coefficients), which are the probabilities of sharing 0, 1 and 2 alleles IBD between a pair of individuals, such that k 0 + k 1 + k 2 = 1. The kinship coefficient q is then calculated as q = k 1 / 4 + k 2 / 2.
ACKNOWLEDGMENTS We thank all colleagues at the  METU CompEvo and Hacettepe Human_G groups , and  O ¨zlen Konu  for helpful discussion, the  Konya Museum  and the  Ministry of Culture of Turkey  for permissions, and three anonymous reviewers for suggestions. Funding: The work was supported by  ERC  ( Consolidator Grant  no. 772390  to M. S. ),  EMBO  ( Short-Term Fellowship  grant no. STF 7909  to R. Y. ),  TU ¨BITAK of Turkey  (grant no. 117Z229  to M. S. ),  AHRC/NSF  ( AH/M008908/1  to A. B. and I. H. ),  NCN of Poland  (grants no. 2012/06/M/ HS3/00286  to A. M. ,  2017/24/T/HS3/00511 , and  2014/15/N/HS3/01272  to  M. Ch. ), National Science Foundation of the USA (Senior Biological Anthropology, NSF   BCS-1827338  to M. P. ), the  French State via the 'Investments for the Future' framework program ,  Initiative d'Excellence de l'Universit e de Bordeaux (IdEx)  ( Award  No.
026. 2500 EDTA disodium salt dihydrate Sigma Aldrich Cat#E5134 Critical Commercial Assays High Sensitivity DNA Kit (Bioanalyser 2100) Agilent Technologies Cat#5067-4626 MYbaits Human Whole Genome Capture Arbor Biosciences (Ann Arbor, MI) Cat# 302508. v5 Kit (African baits) High Sensitivity D1000 Screen Tape Agilent Technologies Cat# 5067-5584 (Tapestation 2200) MinElute PCR Purification Kit QIAGEN Cat#28004 Deposited Data Ash002 BAM file European Nucleotide Archive (ENA) ENA: ERS4811035 Ash033 BAM file European Nucleotide Archive (ENA) ENA: ERS4811084 Ash040 BAM file European Nucleotide Archive (ENA) ENA: ERS4811085 d RESOURCE AVAILABILITY B Lead Contact B Materials Availability d EXPERIMENTAL MODEL AND SUBJECT DETAILS B Archaeological background B Description of archaeological sites B Description of archaeological material d METHOD DETAILS B Radiocarbon dating B Molecular biology laboratory methods d QUANTIFICATION AND STATISTICAL ANALYSIS B Sequence read processing B Authentication of data, contamination estimates and molecular sex determination B Mitochondrial DNA and Y chromosome analyses B Dataset processing B Population genetic analyses B Estimating genetic relatedness and pedigree relationships B Inferring phenotypic traits and inbreeding for As xıklı-128 B Estimating the expected ranges for kinship coefficients using simulations B Spatial distances versus genetic distances among burials SUPPLEMENTAL INFORMATION Supplemental information can be found online at https://doi.
-55 Continued REAGENT or RESOURCE SOURCE IDENTIFIER ADMIXTOOLS 20 https://github. com/DReichLab/AdmixTools ADMIXTURE 19 https://dalexander. github. io/admixture/download. html PLINK 60 https://www. cog-genomics. org/plink2 PONG 61 https://github. com/ramachandran-lab/pong NgsRelate 34 https://github. com/ANGSD/NgsRelate lcMLkin 35 https://github. com/COMBINE-lab/maximum- likelihood-relatedness-estimation READ 36 https://bitbucket. org/tguenther/read/src/master/ HIrisPlex 62-64 http://hirisplex. erasmusmc. nl/ Other Agencourt AMPure XP beads (60 mL) Beckman Coulter Cat#A63881 T4 Polynucleotide Kinase (T4 PNK) Thermo Fisher Scientific Cat#EK0032 T4 DNA Ligase Thermo Fisher Scientific Cat#EL0011, EL0014 Adenine Triphosphate (ATP) Thermo Fisher Scientific Cat#R0441 T4 DNA Polymerase Thermo Fisher Scientific Cat#EP0062 dNTP Set Thermo Fisher Scientific Cat#R0182, R0181 dNTP Mix Thermo Fisher Scientific Cat#R1121, R1122 Bst polymerase, large fragment New England Biolabs Cat#M0275S 10X ThermoPol reaction buffer New England Biolabs Cat#B9004S Amplitaq Gold 360 DNA Polymerase Thermo Fisher Scientific Cat#4398833 (with AmpliTaq Gold Buffer) KAPA HiFi HotStart Uracil+ Kit Kapa Biosystems Cat#KK2801 Herculase II Fusion DNA Polymerase Agilent Technologies Cat#600675 10X Tango Buffer Thermo Fisher Scientific Cat#BY5.
However, this research is not informative in the case of sudden lethal infectious mortality crises (e. g. plague, cholera) because these acute diseases do not have time to develop bone lesions. Another point of discussion in palaeopathology is to try to define the health state of the population (growth stress markers, indices of nutritional deficiencies) that might indicate a favourable and aggravating context during an epidemic crisis. In addition to investigation on any pathological lesions detected on the skeletons, it can sometimes be demonstrated that the individuals were grouped  4 It is a research line of the project ANR-19-CE27-0012, Pestilences and human societies: emergence, evolution and bio-cultural transformations, led by D. Castex. One of the aims is to draw up a historical corpus of antique epidemic crises supported by different textual evidences 5 Castex 2008.
Randomisation Randomisation will be carried out centrally by Interactive Web Response Service (IWRS, ENNOV Clinical solution) using a random list generated by the permuted-block method, and stratified on the case manager to produce balanced 1:1 groups. The allocation sequence will be generated by the statistician in charge of the study, blinded to the coordinating centre and investigators. The randomisation will be performed by the case manager who will connect to the eCRF (ENNOV Clinical randomisation module). The randomisation will allow transmission of individual login connection codes to the application for patients allocated to the intervention group, thus ensuring that patients in the control group cannot download and use the application. There is no blinding for the patient or the case manager.
Face-toface or video interviews will be conducted by a psychologist trained in qualitative research, based on an interview grid design to explore: (1) The user experience, including acceptability, appropriation and use of the application, (2) The perceived benefits and shortcomings of the application, (3) The changes induced by the application in the patient-case manager relationship, and (4) The impact on recovery, care pathway and care adherence. All interviews will be audio-recorded and transcribed verbatim. Thematic content analysis will be performed using the NVivo software (NVivo QSR international). Triangulation will be conducted by combining the results Open access of patients and the case managers, and by combining the interviews and the quantitative results. The qualitative results will inform the interpretation of the quantitative results on the impact and use of the application.
Implementation process Evaluation will be performed at 12 months in the intervention group of the fidelity of use and effective use of the PLAN-e-PSY application by the case manager and the patients, which encompasses: fidelity of use of the defined procedures, use of the different parts of the application, proportion of case management consultations during which the application was not used at 12 months, proportion of patients who stopped using the application at 12 months and reasons given, effective time of use of the application-these elements will be collected from the internal monitoring data of the application. The acceptability and appropriation of the application by patients and the case manager will be assessed during the semistructured interviews.
General aspects A significance threshold of 5% will be considered in the analyses. The analyses will be carried out using SAS software, V. 9. 4 (SAS Institute, Cary, North Carolina, USA) and R software. 42 The analysis of the primary and secondary outcomes will be carried out on the intentionto-treat (ITT) population. Missing data will not be replaced. The primary analysis of the primary end point will be performed using a mixed model assuming that missing data are randomly missing; this will allow to consider all patients for the ITT analysis. A secondary analysis will be performed by replacing the missing score changes with the highest negative changes observed in the study.
Developing methodologies These studies show that considerable information can be elicited about the process and dating of grave disturbance, especially where recent excavations have sought explicitly to investigate the practice. Re-examination of legacy data can also be profitable. Even today, minimal recording and publishing standards limit understanding. Developing protocols for identifying, recording and categorising post-burial interventions is therefore a priority  (Klevnäs 2013: 131-34; Noterman 2016: 125-48; Aspöck et al. in press ; see also  Kinkopf & Beck 2016). Within the studies synthesised here, evidence for grave reopening was extracted from descriptions, drawings and photographs in publications and archives. Field observations taken to indicate reopening range from traces of surface digging to locate graves, to intrusive pits and displaced objects in the backfill, through to disarticulation or fragmentation of human remains and other finds within the grave itself (Figure  1 ;  Aspöck et al.
Within the furnished zone (Figure  5 ) the prevalence of grave reopening varies considerably. Some of the variation is regional, with higher average rates in Bavaria (at least 54 per cent of graves) than in northern France (30 per cent), the Low Countries (41 per cent) or Kent (15 per cent). In the large French dataset the reopening rate rarely exceeds 50 per cent at any site, whereas in southern Germany, Austria, Hungary and Romania, almost all graves are disturbed in some cemeteries (e. g. Bofinger & Przemyslaw 2008; Bóna & Horváth 2009: 58-77; Dobos 2014). Regional patterns in early medieval burial customs are traditionally interpreted as being linked to historically named ethnic groups. Thus, varying prevalence in grave reopening has been suggested to relate to differing attitudes towards the dead among populations  (Roth 1978).
11 Along similar lines, Thomai Dalpanagioti approaches the teaching and learning of metaphoric expressions by Greek learners of English at the B2 European reference level, using semantic-frame theory from cognitive linguistics. In frame semantics, lexical units evoke a frame, and the explicit analysis of the elements within this semantic frame can lead to better understanding and use of metaphoric expressions in a foreign language. Delpanagioti gives concrete examples of structured metalinguistic activities designed around output from the FrameNet 1 and MetaNet 2 online databases for semantic analysis. She also argues that this type of metalinguistic work fits coherently into task-based language classrooms, and gives an interesting set of suggestions for usage-based lexical activities. 12 Magdalena Zinkgraf and María Angélica Verdú analyze the acquisition of formulaic sequences by advanced learners of English in Argentina, as illustrated through their spontaneous use of a set of target expressions in written essays, over a four-month period (post-learning).
Splinters consists of small bone pieces, usually less than 2cm in length. They outnumber any other categories and sometime preserve small remains of cortical and/or medullar surfaces indicating their original position within the diaphyseal section. They are too small to allow their refitting to any other pieces. Epiphyses were not considered in the present study. Morphometric and qualitative data collection on the cleaned diaphyseal fragments, flakes, and splinters followed the procedure described for the archaeological samples. In addition, for flakes and splinters, we established their original position relative to the cortical thickness (cortical, medullar surface, or unknown), and recorded the presence of the percussion bulb. Statistical tests and data representation were performed in R-CRAN  [155].
When both the proportions of faunal fragments in general, and those bearing flake scars in particular, are considered, our experimental data closely matches the pattern emerging from the CCS. Likewise, all the specimens with contiguous flake scars from the RCS fall within the range of variation of our experimental data, both in terms of number of flake scars per item and their breadth. The most important difference between the experimental and the archaeological samples refers to the co-occurrence of impact scars and flake scars. These two anthropogenic modifications were recorded on ~90% of the experimental sample but were seldom observed on archaeological specimens. Finally, we do not find in our experimental material the high prevalence of long bone fragments observed in the PBT sample with numerous contiguous and interspersed series of flake scars.
Acknowledgments We wish to express our gratitude to  F. C. Boucherie Chevaline  for kindly supplying the horse bones, and to  Anne Bruge Ansel  and  Matieu Dubroca  for providing the pebbles and the limestone anvil used in the experiments. We also thank  Marco Peresani ,  Camille Daujeard ,  Delphine Vettese  and an anonymous reviewer for their feedback on a previous version of the manuscript.
This research was supported by grants given to ZL by the  National Natural Science Foundation of China  (grant number: 41630102 and 41672020; http://www. nsfc. gov. cn/english/site_1/index. html),and by the  Shandong University 111 Project  (grant number:  111-2-09 ; https://en. sdu. edu. cn/). Funding was also provided to LD and FD by the  Sino-French PHC   Cai Yuanpei program  (grant number:  36707NF ; https://cn. ambafrance. org/-Le-programme-Cai-Yuanpei-1628-), the  Talents Program of the Initiative d'Excellence (IdEx) of the Bordeaux University  (https://idex. ubordeaux. fr/fr/), and the  Research Council of Norway through its Centre's of Excellence funding scheme, SFF Centre for Early Sapiens Behaviour (SapienCE) , project number  262618  (https://www. forskningsradet. no/en/). LD was granted financial support from the  China/Shandong University International Postdoctoral Exchange Program  (http://www.
chinapostdoctor. org. cn/) and the  Sino-French PHC Xu Guangqi program  (grant number:  41230RB ; https://cn. ambafrance. org/-Leprogramme-XU-Guangqi-). PACEA ( UMR5199   CNRS ) is a Partner team of the  Labex LaScArBx-ANR  n˚ANR-10-LABX-52 (https://lascarbx. labex. ubordeaux. fr/). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Materials and Methods In order to characterize the use of space, we applied intra-site geoarchaeological approach which uses soil micromorphology as the main tool  (Courty et al. , 1989; Cammas and Wattez, 2009). Samples were collected from floors of different rooms of Area Pi based on the questions raised during the excavations (fig. 2 ). Unfortunately, the person who was in charge for geoarchaeological study and sampling during the excavation (2008-2014), is not any more a member of the team and no document of sampling protocol or of samples' exact position is available. We only have data on the layers that have been sampled and the room they belong. Samples of undisturbed blocks were consolidated at the soil laboratory of the department of «Dynamique des Milieux et Organisation Spatiale» at Agroparistech in Paris and studied under a polarized microscope according to guidelines of  Bullock et al.
Discussion on the use of space in Room 16 Comparing archaeological data (especially the presence of a cooking jar in the room) and micromorphological observations, we assume that the pavement supported a movable hearth which could indicate the presence of a hole on the roof in order to evacuate the smoke. This chimney allowed humidity variations due to seasonal meteorological changes (humid weather, rain) to be recorded on the floor next to the hearth. At this stage of the research, clayey coatings are not considered as taphonomy effect due to the reason that their thickness varies from one microlayer to the other but also, they are not observed in all collected samples from the Area Pi. The presence of humidity in the floor favors biological activity during the occupation, which also can affect the good preservation of the floor.
Acknowledgement We would like to express acknowledgement to  Dr. Julia Wattez  and  Dr. Laurent Lespez  for their intellectual guidance. This work has received financial support from the  LabEx DynamiTe  ( ANR-11-LABX-0046 ), as part of the  "Investissements d'Avenir" program , and from the  Institute of Aegean Prehistory (INSTAP). We gratefully acknowledge the anonymous reviewers for their detailed and helpful comments that improve the quality of the text.