dataesr/scientific-paragraphs-categorization huggingface dataset:
The minimum δ 18 O v increases the lower the altitudes are to the near surface; for instance, minimum δ 18 O v values of -23 ‰ and -36 ‰ are seen at 1-2 and 2-3 km a. s. l. respectively, while values lower than -47 ‰ occur at altitudes above 3 km a. s. l. The hourly evolution of average δ 18 O v in the TY region shows the propagation of the surface front and upper-level trough at altitudes of 1-7 km a. s. l. and the associated subsidence of dry and cold air. It is worth noting that the arrival timing of cold and dry air subsidence in TY, 19:00-20:00 UTC (Fig. 5a ), corresponds to the onset of precipitation in SI at 19:00 UTC (vertical bars, Fig. 2 ). Overall the synoptic evolution simulated by COSMOiso is similar to the one analysed using an observational dataset by  Lee et al. (2016).
Conclusion On 15 to 16 October 2012, SI experiences a HPE (total precipitation of 62. 4 mm) with two phases of precipitation. The first one (P1) is induced by moist convection, while the second one (P2) is mainly associated with large-scale uplift along a front. The moisture transport and processes responsible for the HPEs that occurred over the SI area during IOP 13 have been analysed here using SWI data obtained from a numerical simulation with COSMO iso at 7 km horizontal resolution. The main findings are summarized in two schematic illustrations (Fig. 14 ). The 3 d backward trajectory analysis shows that the air parcels arriving in SI during P1 originate from the North Atlantic and descend within the upper-level trough over the north-western Mediterranean Sea. The SWI-depleted air mass within the descending air parcels rapidly takes up a large amount of water vapour from ocean evaporation (green encapsulated area in Fig.
Acknowledgements. We thank  Jean-Pierre Pinty  ( Laboratoire d'Aerologie ) for insightful suggestions and three anonymous reviewers for their interesting comments and suggestions. This work was supported by the  French Agence Nationale de la Recherche (ANR)  via the  IODA-MED  grant  ANR-11-BS56-0005 , the  MU-SIC  grant  ANR-14-CE01-014 , and the  MISTRALS/HyMeX programme. Financial support. This research has been supported by the  French Agence Nationale de la Recherche (ANR)  (the  IODA-MED  grant no. ANR-11-BS56-0005  and the  MUSIC  grant no. ANR-14-CE01-014 ) and the  MISTRALS/HyMeX programme. Review statement. This paper was edited by  Christian Barthlott  and reviewed by three anonymous referees.
, forthcoming) , which ought to have been transported in locally made containers. Furthermore, Chalcis was recently shown to be the origin of an important production of tablewares contemporary with the Günsenin III amphorae, the main "Middle Byzantine Production"  (Waksman et al. , 2014 ; see also  Waksman et al. , in this volume). Samples were taken from excavations in different sites in central Greece (Chalcis and other sites in the Euboea, Thebes), the majority of the samples coming from rescue excavations in Chalcis. Amphorae samples were studied for both their typology and their archaeometric features, in order to define the corresponding productions from both viewpoints, combining archaeological and archaeometric information (see e. g. Waksman, 2016). Among the array of available archaeometric approaches to ceramics  (Hunt, 2016) , chemical analysis was chosen because it enabled us to make use of a large body of comparative data, including chemical reference groups we had previously defined in the database of Lyon laboratory.
Acknowledgements This study was funded by the  French National Research Agency (ANR)  through the  POMEDOR  project, and we acknowledge the support of the  ANR  under reference  ANR-12-CULT-0008. We would like to thank the  Ephorates of Byzantine Antiquities of Chalkida and Thebes , the Directors of the American excavations in Thebes and  Dr. F. Kondyli ,  J. Burlot  ( Lyon University UMR 5138 ) for the pictures of fabrics,  S. Shabo  ( Lyon University UMR 5133 ) for the 3D model and  PALSE-IPEm  for funding its acquisition through the CERAM. 3Dproject, and the staff of the analytical facilities of  Lyon laboratory  ( CNRS UMR 5138 ).
The aim of this study is to explore the genetic profile of a sample of the Corsican population in order to retrace the genetic signatures back to the first migrations to the island during prehistoric times. This study explores the paternal side of the population, including 321 male samples throughout Corsica which were genealogically characterized. Genetic analyses of the Ychromosome were carried out, part of which has already been published  [21, 22]. In order to place our samples in a Mediterranean context, samples from Provence (France)  [22]  and Tuscany (Italy) were added to the cohort. Finally, Y-chromosome results were compared to databases from published literature on Mediterranean populations.
Y-STR based phylogenetic networks Samples derived for haplogroups DYS445 = 6, L497, L91, M12, M241, M267, M406, M410, M527, M530, M67, M92, M96, P15, P16, P287, P303, Page55, Page8, V13 and V22, i. e. 298 samples, were typed for short tandem repeats of 17 Y-STR markers using the AmpFlSTR Yfiler Kit (Applied Biosystems) according to manufacturer recommendations. Three additional markers, DYS388, DYS445 and DYS461, were typed separately (S3 Table)  [27, 28]. Phylogenetic networks were constructed for haplogroups represented by more than 10 individuals using the program Network 4. 6. 1. 1 (Fluxus-Engineering) and applying the median joining algorithm with the following STR loci: DYS19, DYS388, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS439  [29]. Networks were constructed both at a Corsican level and at a broader level with data from Provence (this study and  [22] ), Tuscany and continental Italy  [30].
Mediterranean genetic relationships Y chromosome haplogroup frequencies from 83 Mediterranean populations in published data (North Africa, Iberia, Italian Peninsula, Adriatic Balkans and Western Mediterranean islands) totalizing 7588 men were harmonized to a common set of 12 lineages: E-M96 (xM35), E-M35 (xM78), E-M78, G-M201, I-M170, J1-M267, J2-M172, R2-M479, R1-M173, K-LT-NOP-M9 (xM207), CF-M130-M89 (xM201, xM170, xM304, xM9 ), and Y(xM174, xM130, xM89)  [6, 14, [33] [34] [35] [36] [37] [38] [39] [40] [41] [42]. Genetic relationships within the Liguria and Tyrrhenian Seas were analyzed in a subset of 31 populations out of 83 refined for 23 haplogroups: E-M96 (xM78), E-M78, E-M81, G-M201, J1-M267, J2-M172 Ã , J2-M12, J2-M410 (xM67, xDYS445 = 6), J2-DYS445 = 6, J2-M67 Ã , J2-M92, R2-M124, R1a-M173 Ã , R1a1-M17, R1b-M269, I (xM438), I2-M438 (xM26, xM423), I2-M26, I2-M423, I2-M223, Q-M242, Y (xM96, xM522, xM201 ), and K-M9 (xM74).
Y-Chromosome genetic diversity based on haplogroup frequencies was calculated with the ARLEQUIN v3. 5. 1. 2 package  [43]. Finally, our Y-STR data was merged with those from Sardinia, Sicily and continental Italy  [30]. Variance and Rst genetic distances were respectively plotted through a Principal Component analysis (PCA) and Multidimensional Scaling (MDS) using the XLSTAT tool (Data Analysis and Statistical Solution for Microsoft Excel. Addinsoft, Paris, France, 2017). Haplogroup R represented approximately half of the lineages in both Corsican and Tuscan samples (respectively 51. 8% and 45. 3%) whereas it reached 90% in Provence. Sub-clade R1b1a1a2a1a2b-U152 predominated in North Corsica whereas R1b1a1a2a1a1-U106 was present in South Corsica. Both SNPs display clinal distributions of frequency variation in Europe, the U152 branch being most frequent in Switzerland, Italy, France and Western Poland.
Discussion The genetic profile of Corsican Y-chromosomes was explored in order to retrace the genetic signatures back to the first migrations to the island during prehistoric times. A total of 842 individuals including 321 from Corsica, 259 from Provence (France) and 261 from Tuscany (Italy) were analyzed for Y-chromosome haplogroups. Their results were compared to databases from published literature on Mediterranean populations. Our results showed a highly heterogeneous distribution of Y-chromosome haplogroups in the 183km long and 83km-wide island, with a mosaic of numerous small-scale, micro-regional population groups. The most ancient Corsican genetic signatures might be represented by haplogroup I2 derived individuals, as this haplogroup was reported to be associated to human expansion phase of Sardinia during pre-Neolithic period  [14].
Interestingly, very few studies on the chemical composition of felt-tip pen have been carried out to date. Sodo et al. 3  used Raman spectroscopy to analyze historical drawings, but found limitations such as low sensitivity, uorescence interference of constituent articial dyes and paper matrices, and inability to conclusively identify individual dyes in ink mixtures. Izzo et al. 4  and Germinario et al. 5  performed comprehensive analyses of felt-tip pen brands and colors. However, both studies employed multi-analytical approaches based on the use of high-cost instrumentation; moreover, these approaches were generally destructive and required relatively large amounts of sample. These approaches are invaluable for constituting reference articial dye databases equivalent to the already established databases for organic colorants.
Acknowledgements This work was funded by the  European Union   H2020  project  Nanorestart  ( 646063 ) and the  Irish Research Council (IRC)  project  GOIPD/2015/716. The authors would like to thank the director of the studio  Fellini in Cinecittà, Rome (Italy) ,  Roberto Mannoni , close friend and assistant of  Federico Fellini , for authorizing the use of historical felt-tip pens.
We combined our data with previously published ancient DNA data  2Ð4,20Ð37  to form a genome-wide dataset of 476 ancient individuals (Supplementary Table  1 ). The combined dataset included Beaker-associated individuals from Iberia (n=20), southern France (n=4), northern Italy (n=1), central Europe (n=56), The Netherlands (n=9) and Britain (n=19). We further merged these data with 2,572 present-day individuals genotyped on the Affymetrix Human Origins array  22, 31  and 300 high coverage genomes sequenced as part of the Simons Genome Diversity Project  38.
Genomic insights into the spread of the Beaker Complex Principal component analysis (PCA) revealed striking heterogeneity among individuals assigned to the Beaker Complex (Fig. 1c , Extended Data Fig. 1a ). Genetic differentiation in our dataset was mainly driven by variable amounts of Steppe-related ancestry, with Beaker Complex individuals falling along the axis of variation defined by Yamnaya steppe pastoralists and Middle Neolithic/Copper Age European populations. We obtained qualitatively consistent inferences using ADMIXTURE model-based clustering  41  (Extended Data Fig. 1b ). We grouped Beaker Complex individuals based on geographic proximity and genetic similarity (Supplementary Information, section 4), and used qpAdm 2 to model their ancestry as a mixture of western European hunter-gatherers (WHG), northwestern Anatolian farmers, and Yamnaya steppe pastoralists (the first two of which contributed to earlier European farmers; Supplementary Information, section 6).
More data from southern Britain (where our sampling is sparse) and nearby regions in continental Europe will be needed to fully understand the complex interactions between Britain and the continent in the Neolithic  43. The distinctive genetic signatures of pre-Beaker Complex populations in Iberia compared to central Europe allow us to test formally for the origin of the Neolithic farmer-related ancestry in Beaker Complex individuals in our dataset (Supplementary Information, section 6). We grouped individuals from Iberia (n=19) and from outside Iberia (n=84) to increase power, and evaluated the fit of different Neolithic/Copper Age groups with qpAdm under the model: Yamnaya + Neolithic/Copper Age. For Beaker Complex individuals from Iberia, the best fit was obtained when Middle Neolithic and Copper Age populations from the same region were used as a source for their Neolithic farmer-related ancestry, and we could exclude central and northern European populations (P < 4.
Among the different continental Beaker Complex groups analysed in our dataset, individuals from Oostwoud (Province of Noord-Holland, The Netherlands) are the most closely related to the great majority of the Beaker Complex individuals from southern Britain (n=14). They had almost identical Steppe ancestry proportions (Fig. 2a ), the highest shared genetic drift (Extended Data Fig. 4b ) and were symmetrically related to other ancient populations using f 4statistics (Extended Data Fig. 4a ), showing that they are consistent with being derived from the same ancestral population without additional mixture into either group. We next investigated the magnitude of population replacement in Britain with qpAdm 2 by modelling Beaker Complex and Bronze Age individuals as a mixture of continental Beaker Complex (using the Oostwoud individuals as a surrogate) and the British Neolithic population (Supplementary Information, section 6).
6. 1)  62 , and removed duplicated sequences. We evaluated DNA authenticity by estimating the rate of mismatching to the consensus mitochondrial sequence  63  , and also requiring that the rate of damage at the terminal nucleotide was at least 3% for UDG-treated libraries  63  and 10% for non-UDG-treated libraries  64. For libraries that were promising after screening, we enriched in two consecutive rounds for sequences overlapping 1,233,013 SNPs (Ô1240k SNP captureÕ)  2, 19  and sequenced 2x76 cycles and 2x7cycles on an Illumina NextSeq500 instrument. We processed the data bioinformatically as for the mitochondrial capture data, this time mapping only to the human reference genome hg19 and merging the data from different libraries of the same individual. We further evaluated authenticity by studying the ratio of X-to-Y chromosome reads and estimating X-chromosome contamination in males based on the rate of heterozygosity  65.
Merging newly generated data with published data We assembled two datasets for population genetics analyses: -HO includes 2,572 present-day individuals from worldwide populations genotyped on the Human Origins Array  22, 31, 69  and 470 ancient individuals. The ancient set includes 103 Beaker Complex individuals (87 newly reported, 5 with shotgun data  3  for which we generated 1240k capture data and 11 previously published  3, 4  ), 68 newly reported individuals from relevant ancient populations and 298 previously published 2Ð4,20Ð37 individuals (Supplementary Table  1 ). We kept 591,642 autosomal SNPs after intersecting autosomal SNPs in the 1240k capture with the analysis set of 594,924 SNPs from Lazaridis et al. 22. -HOIll includes the same set of ancient samples and 300 present-day individuals from 142 populations sequenced to high coverage as part of the Simons Genome Diversity Project  38.
ADMIXTURE analysis We performed model-based clustering analysis using ADMIXTURE  41  on the HO reference dataset, including 2,572 present-day individuals from worldwide populations and the ancient individuals. First, we carried out LD-pruning on the dataset using PLINK  71  with the flag -indep-pairwise 200 25 0. 4, keeping 306,393 SNPs. We ran ADMIXTURE with the cross validation (--cv) flag specifying from K=2 to K=20 clusters, with 20 replicates for each value of K and keeping for each value of K the replicate with highest log likelihood. In Extended Data Fig. 1b  we show the cluster assignments at K=8 of newly reported individuals and other relevant ancient samples for comparison. This value of K was the lowest for which components of Caucasus hunter-gatherers (CHG) and European hunter-gatherers were maximized.
Inference of mixture proportions We estimated ancestry proportions on the HOIll dataset using qpAdm 2 and a basic set of 9 Outgroups: Mota, Ust_Ishim, MA1, Villabruna, Mbuti, Papuan, Onge, Han, Karitiana. For some analyses (Supplementary Information, section 6) we added additional outgroups to this basic set.
The arrival of the Beaker Complex precipitated a profound demographic transformation in Britain, exemplified by the absence of individuals in our dataset without large amounts of Steppe-related ancestry after 2400 BCE. It is possible that the uneven geographic distribution of our samples, coupled with different burial practises between local and incoming populations (cremation versus burial) during the early stages of interaction could result in a sampling bias against local individuals. However, the signal observed during the Beaker period persisted through the later Bronze Age, without any evidence of genetically Neolithic-like individuals among the 27.
Acknowledgements We thank  D. Anthony ,  J. Koch ,  I. Mathieson  and  C. Renfrew  for comments and critiques. We thank  A. C. Sousa  for providing geographical information on a Portuguese sample and A. Mart'n and  L. Loe  for help in contacting archaeologists. We thank  M. Giesen  for assisting with samples selection. We thank the  Museo Arqueol-gico Regional de la Comunidad de Madrid  for kindly allowing access to samples from  Camino de las Yeseras. We thank the  Hunterian Museum, University of Glasgow , for allowing access to samples from sites in Scotland, and particularly to  Dr. S. -A. Coupar  for help in accessing material. We thank the  Museu Municipal de Torres Vedras  for allowing the study and sampling of  Cova da Moura collection. We are grateful to the  Orkney Museum  for allowing access to samples from Orkney, and particularly to  G.
ACKNOWLEDGEMENTS I would like to thank  Christian Rose  ( Société belge d'Études celtiques, Bruxelles ) and  Guillaume Oudaer  ( EPHE, Paris ) for their comments on the text, and  Arthur Laisis  ( EPHE, Paris ) for his translation of the Lithuanian texts, and  Natalya Krasnova ,  Henni Ouerdane  ( Skoltech, Moscow ) and  Audrey Ferlut  ( UMR 5189 Hisoma, France ) for their help with the English translation.
Introduction: There is a lack of data on health care consumption of patients suffering from schizophrenia, as well as on the related health care costs. Factors associated with health care costs have not been widely studied, whereas knowledge on this topic would allow identifying risk factors and delineating strategies to improve patients' health and follow-up, likely to also decrease health care costs. The aim of this study was to estimate the average direct health care cost of patients with schizophrenia in France and to identify the factors associated with this cost. Methods. The study population included patients with schizophrenia enrolled in the FondaMental Advanced Centers of Expertise for Schizophrenia cohort. We accounted for the costs directly related to the treatment of schizophrenia.
This would allow delineating strategies to improve patients' health and quality of life and to diminish health care costs. However, the estimation of the health care cost of schizophrenia and the identification of factors associated with higher costs require to precisely define the target population based on relevant and homogeneous diagnostic information that are still lacking in French national databases. Nonetheless, the national network of 9 expert centers for schizophrenic patients created under the auspices of the FondaMental foundation constitutes an opportunity Factors associated with direct health care costs in schizophrenia to conduct studies on the health care cost of schizophrenia and its associated factors (www. fondation-fondamental. org)  (Schürhoff et al. , 2015). Indeed, this network provides standardized diagnostic assessment for patients suffering from schizophrenia.
In addition, it has built databases, which encompass data related to patient clinical characteristics (e. g. , disease severity and somatic comorbidities) additionally to diagnostic information, patient demographic and socioeconomic characteristics (e. g. , age, gender, employment and marital status) as well as data related to health care provided for each patient (e. g. , number and duration of psychiatric full-time hospitalizations and drug consumption). The main objective of this study was to estimate the average direct health care cost of patients with schizophrenia and to identify the factors associated with this cost.
Potentially associated factors with direct health care costs We studied three categories of factors potentially associated with direct health care costs: demographic, socioeconomic and clinical characteristics. For each category, the choice of the variables included in the analysis was based on the findings of the literature and on the availability of data in the FACE-SZ database. A literature review was conducted to identify factors associated with direct health care costs in patients with schizophrenia. However, only a few studies were found  (Sarlon et al. , 2012)   (Desai et al. , 2013). Indeed, the vast majority of studies related to direct health care costs of schizophrenia did not report information on factors associated with those costs  (Wu et al. , 2005; Chang et al. , 2008; Frey, 2014; Garattini et al.
, 2012). This result may be linked to a geographic variability in the mental and non-mental health care supply as well as to variability in the general characteristics of the area (e. g. level of urbanization) that may be related to mental health care consumption  (Toulopoulou et al. , 2017; Newbury et al. , 2016). As our data came from a multicenter survey, we included the expert center of inclusion as a proxy to assess a potential variability in direct health care costs that would be linked to the specificities of the geographical areas.
Description of direct health care costs We described the overall direct health care cost by its mean, standard deviation, median, first and third quartiles, minimum and Nine centers identified with an anonymized number maximum. We tested the normality assumption of the direct health care cost distribution using a Kolmogorov normality test. To account for uncertainty attached to the study sample, we used a bootstrapping method, which is a resampling procedure, to estimate 95% confident intervals (CI) of the mean, median, first and third quartiles of the overall direct health care cost. Through this method, we randomly created 1000 samples of the same size as the original dataset by selecting patients from the FACE-SZ database  (Bland et al. 2015; Statistics Notes). Uncertainty was also associated with unit costs.
In fact, the daily costs of full-time and part-time hospitalization and the cost of a psychiatric ambulatory consultation were based on a survey including a sample of public mental health care hospitals in which variability was observed. To account for this variability, we performed a sensitivity analysis using the first and third quartiles of the unit costs for each resource taken into account. In addition, as the number of psychiatric ambulatory consultations was not specifically recorded in the database, we hypothesized, based on a French national survey  (Coldefy, 2011)  and following expert opinions, that on average 12 consultations per year were provided for each patient with schizophrenia, either with a psychiatrist or with another mental health professional (e. g. psychologist, nurse, social worker).
Discussion We conducted a cross sectional study to estimate the direct health care cost of schizophrenia based on a multicenter The average direct health care cost estimated in our survey is in the same order of magnitude than those of previous studies. In France, the General Scheme estimated the cost of psychotic disorders from the public payer perspective at €10,350 per patient in 2014  (Assurance Maladie, 2015). In Germany,  Frey et al. (2014)  estimated that the average direct health care cost attributable to schizophrenia amounted to €12,251 per year and per patient; and in Australia (Access Economics (Firm) and SANE  Australia, 2002)  this cost was estimated at $15,611. However, these studies were based on administrative databases with no standardized clinical evaluation. Therefore potential variations in the diagnoses made by clinicians are likely to lead to a heterogeneous study population including a very broad spectrum of patients with psychotic symptoms.