dataesr/scientific-paragraphs-categorization huggingface dataset:
Case studies We use both simulation studies and an empirical dataset (on European carnivores) to investigate the measurement of functional originality. For each case (simulation or empirical dataset), we computed all the indices introduced in Table  1  as specified in Fig. 2. We calculated functional dissimilarities among species from raw data using the Euclidean distance metric with quantitative traits in the first case study; and Gower distance  (Gower, 1971)  with a mix of quantitative and nominal traits in the second case study. We obtained functional trees from functional distances using UPGMA and Ward methods (R function hclust, parameter "average" and "ward. D2", respectively; R Core Team 2016). Insert Fig. 2. Single-column fitting image.
For tree-based metrics, correlations with Rb were analyzed with centred Principal Component Analysis using the number of traits, the model of trait evolution and the method for tree construction as supplementary variables (using package 'ade4' in R;  Dray and Dufour, 2007). Then we analyzed the Spearman correlations between phylogenetic originality measures and functional originality measures for each originality index and simulation case. We used Spearman correlations in all cases as the high number of simulations restricted checking the shape of the relationships between phylogenetic and functional originality measures for each scenario, each originality index and between originality indices.
Functional and phylogenetic originalities of carnivore species in Europe We investigated the phylogenetic and the functional originalities of European carnivores. We based our study on  Temple and Terry (2007)  who identified 38 European Carnivora species. Among these species, four were introduced into Europe after 1500 A. D. (Herpestes javanicus, Neovison vison, Nyctereutes procyonoides and Procyon lotor), and seven were defined as marginal in Europe (Cystophora cristata, Erignathus barbatus, Martes zibellina, Odobenus rosmarus, Pagophilus groenlandicus, Felis chaus and Mustela sibirica). The qualification of marginal occurrence was attributed to these latter species as less than 1% of their population or of their range lies in Europe  (Temple and Terry, 2007). We took phylogenetic data from the Carnivora phylogeny established by  Nyakatura and Bininda-Edmonds (2012).
Trait data were obtained from the PanTHERIA database  (Jones et al. , 2009). Among the 53 traits present in the database, we eliminated those for which values were missing for more than a quarter of the species. To avoid circularity in our reasoning, we also discarded geographic traits. Indeed, we made a difference in originality between marginal and non-marginal species, marginality being defined by the geographic distribution of species. Among remaining variables, we removed missing values by using alternative data  (MacDonald, 2009; Myers et al. , 2015). As the trait database was still incomplete (due to missing values) we could not analyze all traits individually. We thus combined traits for this illustration, in order to measure the global functional originality of each species. We provide however in Appendix B a guide on how to deal with individual traits, particularly when some species have identical values for those traits.
Indeed, the model was capable to predict, within uncertainties (2σ), the f ROS-SOA measured in the PAM chamber for low organic aerosol concentrations (average 21 µg m -3 ), but considerably (factor of three on average) overestimated f ROS-SOA at higher concentrations (average 68 µg m -3 ). This is because such a range of concentrations at high OH exposures 440 and high f 44-SOA was not included in the training dataset, and as a result the model slightly underestimated the effect of OA concentration on f ROS-SOA (e. g. , a three-fold increase in OA concentration in the PAM chamber results in a decrease of f ROS-SOA by 45 %, while the model suggests that the same increase would only result in a 10 % decrease). Despite this, for similar conditions f ROS-SOA measured in the PAM chamber and the SC were similar within our uncertainties.
Acknowledgements This study was financially supported by the  Swiss National Science Foundation  ( NRP 70  " Energy Turnaround "), the  European Union 's  Horizon 2020 research and innovation programme  through the  EUROCHAMP-2020 Infrastructure Activity  under grant agreement No  730997 , the  Swiss National Science Foundation  starting grant  BSSGI0_155846 , and the  China Scholarship Council (CSC). 510.
Restriction site-associated DNA sequencing Twelve RAD libraries were prepared according to the protocol described in  [19] , with small modifications (see the electronic supplementary material, methods). Libraries were sequenced on an Illumina HiSeq2000 using 100 bp single-end reads, at the Biology Institute of Lille (IBL, UMR 8199 CNRS) and at the MGX sequencing platform in Montpellier (France). The Stacks pipeline  [20, 21]  was used for the loci de novo assembly and genotyping. We applied several filters to the resulting dataset in order to filter for poor-quality single nucleotide polymorphisms (SNPs) and artefacts due paralogous sequences (electronic supplementary material, table S2 and methods).
Identification of sex-linked loci The presence of sex-linked loci, i. e. loci common to the two sex chromosomes but presenting differences in allele frequencies between sex (figure  1a ), was explored by performing a principal component analysis (PCA) using the package adegenet in R  [22, 23]. This analysis was performed on the total dataset (12 populations). The dataset was centred and missing data were replaced by the mean allele frequency for each locus.
Identification of sex-linked loci While the first four principal components of the PCA highlighted neutral population genetic differences  [24] , the fifth axis (1. 58% of explained variance) separated individuals from all populations in two clear groups that matched the male/female repartition of morphologically sexed individuals (figure  2 ). Only three individuals that were morphologically female appeared among males in the PCA. From this PCA, we identified potential females and males among individuals for which sex determination was not performed on the basis of the visible separation in two groups. Considering this separation, we postulate that the dataset comprised 169 females and 185 males, corresponding to a balanced sex ratio (p = 0. 40, electronic supplementary material, table  S5 ).
The sex ratio was balanced also inside each population, except in ELV12, where it was significantly biased towards male individuals (70% of males; p = 0. 03, electronic supplementary material, table  S5 ). There were 472 SNPs with a contribution to the fifth axis of the PCA higher than 1% (electronic supplementary material, figure  S2 ); these loci displayed the same allele fixed in almost all morphological females, and were at the heterozygous state in almost all morphological males. This observation was confirmed with PCA-identified males and females (figure  1b, c ). The genotypes of these 472 SNPs enabled the sexing of 95% of individuals for the whole dataset. Among these SNPs, when considering only morphologically sexed individuals, 379 SNPs were fixed in all females, 59 were at the heterozygous state in all males (the remaining SNPs were at the heterozygous state in almost all males).
The absence of Colours correspond to the (a) population of individuals (light blue: BANN20, dark blue: BANN40, dark orange: BANS20, yellow: BANS40, brown: ELV12, grey: MEJ40, dark green: FIG8, light green: MOR40, red: GAL20, light orange: GAL40, dark purple: POR20, light purple: POR40; see electronic supplementary material, figure  S1  and table  S1 ) and (b) sex of individuals determined morphologically (red: females, blue: males). markers diagnostic of sex in the overall dataset may indicate that these loci were submitted to a low but non-null recombination rate, as is the case when sexual chromosomes have recently diverged, or near the boundary of pseudoautosomal regions, where recombination is more frequent than in fully sexlinked regions  [25, 26]. It could also be the result of polymorphism within the restriction sites on the Y chromosome (i.
e. allele dropout) making it impossible to observe the Y allele with RAD-Seq in some populations  [27]. A low rate of mutation, recombination or allele dropout could suffice to make a marker go from diagnostic (heterozygous in 100% of males) to sex-linked but not diagnostic (heterozygous in less than 100% of males). For these different reasons, it may be difficult to identify strictly diagnostic loci common to all populations for such species with a strong genetic structure. Nevertheless, even if diagnostic markers of sex were not found at the scale of the overall dataset, the multilocus analysis enabled us to identify clearly males and females. Sex-linked polymorphisms identified by RAD-Seq have been found in the pistachio (Pistacia vera) and the salmon louse (Lepeophtheirus salmonis), where authors identified markers being heterozygous in females and homozygous in males, and suggested a ZW/ZZ system  [28, 29].
These polymorphisms have also been found in the Atlantic halibut (Hippoglossus hippoglossus), the Nile tilapia (Oreochromis niloticus) and the date palm (Phoenix dactylifera), where an XX/XY system was suggested  [30] [31] [32]. Here, we highlighted a strong signal of sex-linked markers in our population genomic dataset. Considering the pattern of allele frequencies of these loci, they may be detected as being under balanced selection, which can easily lead to a misinterpretation of the signal when these loci are not expected (especially in species whose sex-determining system is unknown).
Acknowledgements. We thank  Nicolas Fernandez  and  Béatrice Loriod  from the Marseille TGML platform for their invaluable help and advice with the preparation of the RAD libraries;  Véronique Dhennin  from the  Biology Institute of Lille ; and the team of the MGX platform for the sequencing of the RAD libraries. We thank the molecular biology service of the IMBE and  Frédéric Zuberer  of the  Pytheas Institute  for their support in sampling. We thank the  Scandola Natural Reserve , especially  Jean-Marie Dominici , and also thank  Alexander Ereskovsky  for his advice in red coral sexing.
ACKNOWLEDGMENTS. We thank  David Heslop  and  Lie-Liang Yang  for insightful discussions and assistance. We are greatly indebted to the scientists and supporting staff of  Ocean Drilling Program (ODP) Leg 208. We used samples provided by  ODP , sponsored by the  US National Science Foundation  and participating countries under the management of the Joint Oceanographic Institutions. This research was made possible by  European Research Council Grants 215458 (GTS-NEXT , to F. J. H. ) and 617462 (EARTHSEQUENCING, to H. P. );  Nederlandse organisatie voor Wetenschappelijk Onderzoek (NWO)  Grants  864. 02. 007  (to L. J. L. ),  865. 10. 001 (to L. J. L. ), and  821. 01. 012  (to G. R. );  Natural Environment Research Council (NERC)  Grant  NE/K014137/1  (to P. A. W. ); and a  Royal Society Wolfson  award (to P.
2007 ). Our analysis is based on a series of meteorological variables (temperature, wind and radiation) observed at three observatories from ROSEA (Réseau d'Observatoires pour la Surveillance de l'Eau Atmosphérique) national network. It is also based on reanalyses (NCEP and ECMWF). The manuscript is organized as follows. In section 2, the three ROSEA observatories, the corresponding datasets, the large-scale diagnostic and the methodological approach are presented. Section 3 presents the analysis of large-scale conditions versus local processes using flow analogues. Conclusions appear in section 4.
b. Data used In order to base our analysis on a common period with a uniform data format, data from the Meteo-France standard weather station hosted by CRA-P2OA were used for this study. We employed hourly values concerning temperature and incoming shortwave radiation at 2 m, wind speed and direction at 10 m and rainfall between 2003 and 2013. In the framework of the current study, a similar quality control, homogenization and a combination of variables from various sources as seen in the SIRTA-ReOBS were performed for the meteorological variables collected in the Cézeaux-COPDD and CRA-P2OA observatories. To characterize the influence of large-scale circulations, we based our study mainly on daily temperature anomalies at 2 m above the surface at the three observatories. To ensure that our anomaly was not affected by seasonal variability in temperatures, it was defined by comparison to the average of the current month.
2017). Notably, few studies have examined the concomitant effects of both native and invasive host communities on infectious disease risks in invaded ecosystems. In this paper, we examined ecological interactions between native and invasive host rodents and their bacterial communities in the context of well-studied ongoing invasions in Senegal (West Africa). They concern two major invasive species (Global Invasive Species Database -http://www. issg. org/database/): the house mouse Mus musculus domesticus  (Dalecky, et al. 2015) Lippens et al. unpublished data)  and the black rat Rattus rattus  (Konecny, et al. 2013). Historical records and molecular analyses have shown that these rodents were first brought to Senegalese coasts by Europeans at colonial times, and remained in coastal villages and towns until the beginning of the 20 th century.
2013)  to amplify a 251bp portion of the 16S rRNA V4 region (V4F: GTGCCAGCMGCCGCGGTAA; V4R: GGACTACHVGGGTWTCTAATCC). This hyper variable region of the 16S rRNA gene allows an accurate taxonomic assignation of bacteria to the genus level  (Claesson, et al. 2010 ) for a wide range of bacteria. The technical procedures and bioinformatics analyses employed to get data considered in this work are presented in detail elsewhere  (Galan, et al. 2016). Briefly, the MiSeq data was processed with the program MOTHUR v1. 34, and taxonomic assignation was performed using the SILVA SSU Ref database v119 as a reference and refine using phylogenetic analyses and blast in GenBank. The reads generated by the Illumina MiSeq sequencing were clustered into Operational Taxonomic Units (OTUs) with a 3% divergence threshold.
Finally, the data were filtered to eliminate false positive and false negative results for each bacterial OTU. The presence of a given OTU within a given rodent was next validated using systematic technical replicates. Results were then summarized in a presence/absence dataset with only bacterial OTUs known or suspected to be pathogenic for human or wildlife kept for further investigation. Data analyses. Each invasion route was investigated separately. In order to avoid any confounding effects in the data analyses, we considered the factor 'invasion status' that combines the host species and site category on the invasion route. It included four categories: A) invasive species alone in sites of long-established invasion; B) invasive species at the invasion front; C) native species at the invasion front and D) native species at non-invaded sites.
We used individual species richness (number of OTUs recorded in a single individual host) and OTUs prevalence (infection by a specific OTU for which prevalence in the dataset reached at least 5%) as response variables. When an OTU was found exclusively or mainly (more than 95% of infected hosts) in only one host species, variations in specific prevalence were tested using a dataset restricted to individuals of this host species only. We assumed a binomial distribution (quasibinomial if overdispersion) for incidence data and a Poisson distribution (negative binomial if overdispersion) for species richness data. The full model included individual host factors (gender and body mass), invasion status (A, B, C and D) and pairwise interactions between host factors and specific invasion status. Sampling site was considered as a random factor.
Trapping campaigns inside villages and private lands were conducted with permission given by the adequate institutional and familial authorities. None of the rodent species investigated in the present study has protected status (see list of the International Union for Conservation of Nature). All procedures were designed to minimize animal suffering and were approved by the official guidelines of the American Society of Mammalogists  (Sikes, et al. 2011). The spleen samples were sent in dry ice to Montpellier (France) to be conserved in experimental animal room from CBGP (34-169-003). All transfer and conservation procedures were carried out paying attention to comply with current international legislations. Variations in specific prevalence were tested using a dataset restricted to a single host species when at least 95% of infected hosts by an OTU were from one species.
Acknowledgments. We thank  Ambroise Dalecky ,  Khalilou Bâ ,  Mamadou Kane ,  Aliou Sow ,  Philippe Gauthier ,  Youssou Niang  and  Mamoudou Diallo  for their participation to the field sampling in Senegal,  Hélène Vignes  for the MiSeq sequencing and  Alexandre Dehne-Garcia  for his help in the use of the CBGP HPC computational platform. We also thank  Laurent Granjon ,  Sylvain Piry  and  Jean-Marc Duplantier  for their precious help and advice during this work. This work was supported by the  ANR   ENEMI  project ( ANR-11-JSV7-0006 ). We are particularly indebted to all the people in Senegal who allowed us to carry out rodent trapping in their homes.
Introduction Cultural heritage (CH) digitization and preservation are two complex processes that involve several underlying techniques and algorithms to make CH mockups available for current and future generations. Digital content preservation is inspired from the manufacturing industry where companies use adapted archival platforms and PLM frameworks to store critical data and knowledge about important facts at each stage of product lifecycle. This data can be very important in the future for several reasons such as avoiding previous mistakes or for iterative purposes. In this paper, we consider cultural heritage assets as products, their history as a lifecycle, and study their lifecycle preservation from a product viewpoint. In order to express the need behind the long term-preservation of cultural heritage several concepts need to be introduced.
Related Work Digital preservation for cultural heritage is widely studied. Several research projects are funded all over the world to establish, not only standards and good practices, but also some novel ideas in order to adapt existing approaches from other fields to the field of cultural heritage. Data about cultural heritage is stored in several file formats. Digital preservation is about the standards and best practices that guide the acquisition and the conservation steps. In this section, we discuss the impact of 3D technologies on cultural heritage, and present a survey of current innovations related to long-term digital heritage acquisition, enrichment, content management and digital preservation.
3D digital heritage acquisition and modeling The massive advances in 3D imaging had a positive impact on digital heritage. Some researchers are comparing this impact to the one of photography in the 19 th century  [8]. 3D acquisition for cultural heritage assets is very critical, since assets are very fragile and their handling requires special care. The scanning of cultural heritage assets is very complicated compared to normal objects. In fact, CH assets often require restricted access and cannot be easily manipulated (touching, moving, rotating, etc. ), which further complicates their scanning process  [9]. Nowadays, with the advances in imaging capture and processing technologies, high quality captures can be performed using handheld devices. Software like: SELVA3D  [10] , Smoothie 3D  [11]  or AutoDesk 123D  [12]  can transform a 2D still image to a digital 3D model.
Data Enrichment Data enrichment is the practice of enhancing, refining, valuing and linking the raw data. Semantic enrichment for cultural data has been an active and fruitful field of research in previous years. In 3D cultural heritage context, linking the collected data is a critical mission for many reasons. This process is tedious and requires a lot of analysis. 3D annotations are used to semantically enrich shapes, adding more knowledge to the 3D model. These annotations are associations between selected portions of the 3D shape and some data describing it. The metadata schemes for cultural data are defined by several standards like the CIDOC-CRM or the CRMdig ontologies  [28]. These standards aim at sharing cultural heritage information by a common and stretchable semantic scheme. Several approaches tackled the semantic enrichment challenge of 3D models like AIM@SHAPE  [29] , 3D-COFORM  [30] , Focus K3D  [31] , CULTURA  [32] , V-MusT  [33] , and  [34].
Content Management Museums around the world use special software applications to manage their CH inventory e. g. Software like MuseumSoftware  [37] , Adlib  [38]  and Museumplus  [34]. These tools are data management systems used for cataloguing purposes. They list some data about assets illustrated by 2D images. Some novel approaches were introduced too. 3D-COFORM, for example, used a secured repository infrastructure to store and manage 3D cultural data. We can also cite other frameworks like  [39]  where the authors presented a centralized content management system (CMS) adapted to cultural heritage with advanced functionality like semantic queries and distributed storage. However, since new digital technologies emergence and the progress in 3D imaging, the application of 3D visualisation technologies has become very reliable and cost-effective, especially in the content consuming market with technologies like 3D television, Virtual Reality (VR) and Augmented Reality (AR).
Nowadays, virtual museum software products like Versoteq  [40]  or 3DStellwerk  [41]  are used to create virtual museum tours adapted to variety of content consuming platforms (VR Headset, 3D TV, Smartphones and tablets, Etc. ). 3D cultural heritage content is very attractive for consumers and considered as very lucrative. Several other software like SketchFab  [42] , which is a web-based 3D visualisation framework, focus on the 3D presentation of cultural heritage models. The Fedora based 3D repository presented in  [43]  is a good example of a complete 3D digital heritage CMS. It has two core parts. The first part is a digital objects repository storing, aggregating, managing and extracting digital objects in a wide range of formats and data types. The second core component is a semantic resource index which establishes an indexing data structure for a complex information mapping for relations between an object and its components.
Digital Preservation Due to the wide use of digital technologies to capture and store cultural heritage, the need to preserve this data for the future is becoming very important, especially because of the high value of the assets. Digital preservation is becoming more reliable than physical preservation, thanks to the increasing performance of processing systems and the dropping costs of archival media. Digital Obsolescence is an alarming threat to every knowledge management organisation. These organisations fear the loss and the non-usability of their critical data in the future, especially that new technologies are being widely adopted  [44]. Digital preservation is currently studied as a solution for digital obsolescence. The initial approach to digital preservation was the OAIS system (Open Archival Information System) in the mid 90's.