dataesr/scientific-paragraphs-categorization huggingface dataset:
One intriguing interpretation is that these stars belonged to the massive building block(s) of the proto-Milky Way that formed the backbone of the Milky Way disc. Alternatively, they might have formed in the early disc and have been dynamically heated, or have been brought into the Milky Way by one or more accretion events whose orbit was dragged into the plane by dynamical friction before disruption. The combination of the exquisite Gaia DR2 data and surveys of the very metal-poor sky opens an exciting era in which we can trace the very early formation of the Milky Way.
Lastrom(Θ |M) Gaia DR2 provides us with a parallax and its uncertainty δ , which is instrumental in breaking the dwarf/giant distance degeneracy for most stars. The astrometric likelihood is trivially defined as Lastrom( |δ , r) = 1 √ 2πδ exp - 1 2 -0 -r -1 δ 2. (8) Here, 0 = -0. 029 mas is the parallax zero-point offset measured by  Lindegren et al. (2018). Even in cases for which the parallax is small and the associated uncertainties are large, the Gaia data are often informative enough to rule out a nearby (dwarf) solution.
Orbital inference Gaia DR2 provides proper motions in right ascension and declination with their associated uncertainties and covariance. Combining this with the distance inferred through our analysis, we can calculate the velocity vector PDF P (v) = P (vr, vα, v δ ) for all 42 stars in our UMPs sample. This PDF, in turn, allows us to determine the properties of the orbit of the stars for a given choice of Galactic potential. We rely on the galpy 4  package  (Bovy 2015 ) and choose their MWPotential14, which is a MW gravitational potential composed of a power-law, exponentially cut-off bulge, a Miyamoto Nagai Potential disc, and a Navarro, Frenk & White (1997) dark matter halo. A more massive halo is chosen for this analysis, with a mass of 1. 2 • 10 12 M compatible with the value from Bland-Hawthorn & Gerhard (2016) (vs.
We foresee a statistical improvement of this first study with the arrival of homogeneous and large datasets of EMP stars, such as observed within the Pristine or SkyMapper surveys  (Starkenburg et al. 2017a; Wolf et al. 2018). With these surveys, the window function and the selection criteria of the objects for which distances and orbits are derived will be much better known. Table  1. Physical parameters of the analysed UMPs found in literature. [Fe/H], [C/Fe], vr, T lit , log(g) lit are from the articles listed in the column References. vr and the binarity flag denoted with a are from  Arentsen et al. (2018) , the vr values for binary systems denoted with a are the systemic radial velocities corrected for the binary orbital motion. vr values for stars that are not known to be in a binary system and from the compilation of  Arentsen et al.
ACKNOWLEDGEMENTS We would like to thank  Benoit Famaey ,  Misha Haywood  and  Paola Di Matteo  for the insightful discussions and comments. FS, NFM, NL, and RI gratefully acknowledge funding from  CNRS/INSU  through the  Programme National Galaxies et Cosmologie  and through the  CNRS grant   PICS07708. FS thanks the  Initiative dExcellence IdEx  from the  University of Strasbourg  and the  Programme Doctoral International PDI  for funding his PhD. This work has been published under the framework of the IdEx Unistra and benefits from a funding from the state managed by the  French National Research Agency  as part of the investments for the future program. ES and AA gratefully acknowledge funding by the  Emmy Noether program  from the  Deutsche Forschungsgemeinschaft (DFG). JIGH acknowledges financial support from the  Spanish Ministry  project  MINECO AYA2017-86389-P , and from the  Spanish MINECO  under the  2013 Ramón y Cajal program  MINECO  RYC-2013-14875.
KAV thanks  NSERC  for research funding through the  Discovery Grants program. This research has made use of use of the SIMBAD database, operated at  CDS, Strasbourg, France  (Wenger et al. 2000). This work has made use of data from the  European Space Agency (ESA) mission Gaia  (https://www. cosmos. esa. int/gaia),processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www. cosmos. esa. int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.
Statistical analyses The normal distribution of the data was checked with a Shapiro-Wilk's test. Therefore, statistically significant differences were assessed by non-parametric Kruskal-Wallis' test ran with the Dunn's multiple pairwise comparisons at a significance level p = 0. 05. Analysis were performed using XLSTAT (Addinsoft, Paris, France). Spearman's rank correlation coefficient between analysed parameters were calculated and presented in a table of correlation. A first level of significance was set at p < 0. 05, additionally, a Bonferroni correction was applied to correct the inflation of alpha on data distributions, setting an additional significance level p < 0. 006 for Table  2  and p < 0. 003 for Supplementary Material 3. Principal components analysis (PCA) was performed to visualize the distribution of environmental conditions in relation to study sites and to confirm correlations between variables found using non-parametric Spearman's rank correlation with the software CANOCO 4.
We also found a correlation between the δ 13 C ORG and salinity as well as between δ 13 C ORG values of stems and leaves (Table  2 ). In Table  2  we also presented the values of correlation coefficients between δ 13 C of DIC and leaves and stems of organic matter in relation to C/N ratio and percentage coverage of S. pectinata, which were in many cases high and statistically significant. The δ 13 C values of extracted lignin phenols were presented as the sum of V, S and C phenols group for each replicate (Supplementary Material 1). Due to low amount of sample collected, we could not acquire data of δ 13 C monophenols for Maardu lake, the sampling point with the lowest salinity. The most 13 C-depleted values were recorded for a sample from Tallinn Bay in both cases for leaves and stems (Supplementary Material 1).
The sampling area in the case of Tallinn Bay was open without any trees, rushes and that was different compared to Maardu Lake where the shoreline was covered by a wide belt of Phragmites australis (Cav. ) Trin. ex Steud. Those differences might have influence to the photosynthesis intensity due to different shadow effect. According to  Cloern et al. (2002) , the values of δ 13 C ORG of submerged vascular plants recorded in the trophy gradient varied from -16‰ to -31‰. In our study, we registered higher values of S. pectinata δ 13 C ORG ranging from -7. 8‰ to -17. 1‰. Our results are similar to the largest recorded database of δ 13 C ORG for submerged macrophytes: a study by  Herzschuh et al. (2010a)  regarding lakes located in the Tibetan plateau and Central Yakutia (values from -23. 3‰ to +0.
A bulk of charcoal or plant macroremains (Table  2 ) was preferred to a single remain in order to reduce the dating risk of older material reworked by blowing to the dune. The 14 C measurements were calibrated with CALIB 7. 0. 4 (Stuiver and Reimer 1993)  using the IntCal13 dataset  (Reimer and others 2013). The CALIB tool sum probabilities were used with all the 14 C measurements to compute cumulative probability distribution per site with two sigma ranges. After calibration, the radiocarbon dates were used to establish age-depth models by exponential smoothing, one per dune profile (cf. in  Carcaillet and others 2006). The age-depth models were then used to simulate the ages of undated burned paleosoils. One measurement in each radiocarbon series appeared to be too old compared with the other data: 3316 ± 85 BP (UQ-2117) at 175 cm at Villemontel and 1870 ± 80 BP (UL-1268) at 49 cm at Lunette.
Aphelidea, NCLC1, and Cryptomycota* (also named Rozellomycota  [28] , Rozellida  [29] , Rozellosporidia  [30] , and/or short-branch microsporidia  [31] ) are represented by green, blue, and purple rectangles, respectively. The six representative sequences recovered from the Oslo coastal station  [4]  are colored in red. Numbers on branches are shown in the order of bootstrap support values (percentages; computed from 100 non-paramteric ML bootstrap replicates) and then posterior probabilities (inferred from two converged PhyloBayes chains). Code numbers in front of species names are NCBI -GenBank identifiers. Each collapsed branch is detailed in Table  S4. The branch leading to M. vibrans was truncated for display purpose. SSU sequences of classically defined microsporidia are excluded from this analysis because they form excessively long branches in SSU rRNA gene trees.
These data demonstrate that the detection of NCLC1 was geographically restricted to the North-East Atlantic and the North Sea (Figure  4C ). This constitutes an incomplete and biased sampling profile, but it suggests that NCLC1 is resident in these environments but is absent and/or undetected from water samples on the western side of the Atlantic on the date of sampling. This analysis identifies a relatively low abundance for NCLC1, except for one sample (OSD-148), which demonstrated an $4% relative abundance of an NCLC1 SSU rRNA gene sequence (Figure  4C  and Table  S3 ). We identified three significant NCLC1 co-occurrences within the Ocean Sampling Day data; one association was between an NCLC1 ASV and a rhizarian ASV, although we note that sampling of this ASV within the Ocean Sampling Day dataset had limited reads and so may be an artifact, even though a significant pseudo p value was recovered (Table  S3 ).
STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: tested in silico using both ARB software (v. 6. 0. 4) and TESTPROBES available on the Silva website (https://www. arb-silva. de) [48]. d KEY RESOURCES The six oligonucleotide probes were purchased from biomers. net (Germany) and were labeled at 5 0 end with horseradish peroxidase (HRP).
This analysis was conducted in the R programming language (RCore2013) using the 'tidyverse' (https://www. tidyverse. org/) set of tools. The code used to perform these calculations (plotting_and_testing_association. r) can be found in the supplemental data, see Zenodo repository: DOI 10. 5281/zenodo. 2788876. SSU sequence alignment and phylogenetic tree reconstruction SSU sequences from 200 taxa were retrieved from previous publications  [4, 6] ; additional sequence homologs were identified through BLASTN similarity searches (http://blast. ncbi. nlm. nih. gov//blast. ncbi. nlm. nih. gov/). Sequences were then aligned using MAFFT v7. 2 iterative refinement method Q-INS-i (https://mafft. cbrc. jp/alignment/server/, [50] ). The alignment was subsequently edited with trimAL v4  [51]  using the 'gappyout' parameter (''distribution0based algorithm'') and manually masked with seaview v4  [52] , resulting in a final alignment of 1542 nucleotide sites (of which 1221 were parsimony informative).
ACKNOWLEDGMENTS The authors are grateful to  Vladyslava Hostyeva  for phytoplankton counting and  Valentin Foulon  for his help with the epifluorescence microscope and the  Cytometry core facilities of LEMAR, Brest. We thank  Prof. Keith Gull  for use of TAT1 antibody. A. C. was supported by the  ANR  project  ACHN 2016   PARASED  ( ANR-16_ACHN_0003 ). F. M. is supported by  Genome Canada  via a  Genome Atlantic Postdoctoral Fellowship  and a  Donald Hill Family Fellowship. A. M. and T. A. R. are funded by the  Royal Society through University Research Fellowships. Parts of this project were supported by the  BiodivERsA ERA-Net project BioMarKs  and a  Gordon and Betty Moore Foundation   MMI Grant  ( GBMF3307 ).
We therefore decided to use two different probes with a single shift in the nucleotide sequence position (i. e. , CHY-445-01 and CHY-445-02). For negative controls for the specific and general probe we used the reverse complement of each probe named CHY-445-01-RC, CHY-445-02-RC and CHY-NCLC-01-RC (see Key Resources (with 4 discrete categories). Two independent Markov chain Monte Carlo chains (MCMC) were run for 20k generations and sampled every 10 generations with the first 3k discarded as the burnin. Resulting posterior probabilities were mapped onto the ML phylogeny presented. Ocean Sampling Day 2014 and sequence co-occurrence analysis SSU rDNA amplicon sequence and contextual data from the Ocean Sampling Day 2014 initiative  [41]  were retrieved from the Micro B3 project repository (https://github.
com/MicroB3-IS/osd-analysis/wiki/Guide-to-OSD-2014-data); microbial community filtering, DNA extraction and Illumina MiSeq sequencing protocols are described in the OSD handbook (http://mb3is. megx. net/osd-files? path=/2014/protocols; see also  [46]  for an overview of the sampling and sequencing protocol). OSD amplicon sequences were retrieved as pre-processed sequences (technical sequences removed; non-merged paired end reads) and only SSU-V4 sequences obtained following the NPL022 protocol (according to the OSD nomenclature) were analyzed as part of this study. To allow comparison between depth samples, only samples collected from surface waters were kept for analysis. All OSD amplicon were then processed with DADA2  [56] ; SSU-V4 sequences were first error corrected and dereplicated, and paired end reads were merged to produce an amplicon sequence variant (ASV) dataset.
ASV sequences were then checked for potential chimeras. ASVs were taxonomically classified using the PR 2 v4. 10 reference database (  [59] ; https://github. com/pr2database/pr2database) and the RDP naive Bayesian classifier  [65]  using a minimum bootstrap confidence of 50, as implemented in DADA2. To produce an SSU-V4 dataset representing only protists sampled during OSD-2014, ASVs classified as multicellular eukaryotes were discarded from the study. Furthermore, to detect spurious SSU-V4 sequences, ASVs were aligned to PR2 representatives using MAFFT v7  [66]  and ASVs with poor sequence overlap thresholds, identified with trimAl v1. 4 ([51]; '-seqoverlap' lower than 0. 8), were discarded. The final SSU-V4 sequence dataset was comprised of 7,766 ASVs totalling 2,552,000 sequences across 145 samples.
DATA AND CODE AVAILABILITY All data and code are available with DOI's given in the methods section. Specifically, physical and chemical parameters of the water column obtained using CTD ocean water sampling are available at http://biomarks. eu/ctd007 (and replicated here at figshare DOI: 10. 6084/m9. figshare. 9821936). The phylogenetic tree file, masked and unmasked SSU rDNA alignments are available at Zenodo repository: DOI 10. 5281/zenodo. 2788876. All sequence data used were derived from the NCBI 'GenBank' database and accession numbers are provided in Figure. 1B. The R code used to test statistical association in the FISH data are available at Zenodo repository: DOI 10. 5281/zenodo. 2788876.
Chemicals, Peptides, and Recombinant Proteins SUPPLEMENTAL INFORMATION Calcofluor White Sigma-Aldrich, USA https://www. sigmaaldrich. com/catalog/ Supplemental Information can be found online at https://doi. org/10. 1016/j. product/sial/18909?lang=en&region=GB Deposited Data cub. 2019. 09. 074. All physical and chemical parameters of the samples This paper are available at http://biomarks. eu/ctd007 water column obtained using a CTD (and replicated at FigShare https://doi. org/10. 6084/ m9. figshare. 9821936) tree file, masked and unmasked SSU rDNA alignments This paper Zenodo repository: https://doi. org/10. 5281/ zenodo. 2788876. Ocean Sampling Day 2014 Data [41, 46] https://github. com/MicroB3-IS/osd-analysis/ wiki/Guide-to-OSD-2014-data see also http://mb3is. megx. net/osd-files?path=/2014/ protocols Oligonucleotides FISH Probe (5 0 -3 0 ) GTCCTAGATTCACTGCTC This paper, ordered from CHY-NCLC-01 biomers.
net (Germany) FISH Probe (5 0 -3 0 ) GATTCTAATGCCCCCCAA This paper, ordered from CHY-445-01 biomers. net (Germany) FISH Probe (5 0 -3 0 ) CGATTCTAATGCCCCCCA This paper, ordered from CHY-445-02 biomers. net (Germany) FISH Probe (5 0 -3 0 ) [reverse complement negative control] This paper, ordered from CHY-NCLC-01_RC GAGCTGTGAATCTAGGAC biomers. net (Germany) FISH Probe (5 0 -3 0 ) [reverse complement negative control] This paper, ordered from 445_01_RC TTGGGGGGCATTAGAATC biomers. net (Germany) FISH Probe (5 0 -3 0 ) [reverse complement negative control] This paper, ordered from 445_02_RC GTTGGGGGGCATTAGAAT biomers. net (Germany) Software and Algorithms The R code used to test statistical association between This paper Zenodo repository: https://doi. org/10. 5281/ NCLC1 and Diatoms in the FISH data zenodo.
2788876. mathFISH for FISH probe design [47] http://mathfish. cee. wisc. edu ARB software (v. 6. 0. 4) for SSU rRNA probe design [48] ( https://www. arb-silva. de) TESTPROBES for FISH probe optimization [48] ( https://www. arb-silva. de) R programming language (RCore2013) 'tidyverse' set N/A (https://www. tidyverse. org/) of tools for statisitical analysis BLASTN similarity search for sequences with shared [49] https://blast. ncbi. nlm. nih. gov sequence identify from NCBI nt database MAFFT v7. 2 sequence alignment for automated [50] https://mafft. cbrc. jp/alignment/server/ sequence alignment trimAL v4 for automated sequence alignment [51] http://trimal. cgenomics. org refinement and sampling (Continued on next page).
Courtship behavior analysis. All courtship behaviors including, singing, tapping, wing extension, licking, chasing and attempts at copulation were manually scored for ten min after the first courtship event. The Courtship Vigor Index (CVI) is the fraction of a ten min observation period spent by the male in courtship behavior after the onset of courtship behavior. The difference in time between when flies first interacted and started courting was defined as the latency to court and the difference between the first encounter and the onset of copulation was defined as the copulation latency. Statistical Analysis. All statistical analyses were performed using R statistical program (Version 1. 14. 4, Vienna, Austria) software and Prism7 (GraphPad Software, La Jolla, CA) for graphs. Behavioral data were analyzed with nonparametric tests.
Differences in latencies to attack, lunge or establish dominance were evaluated by nonparametric two-independent-sample Mann-Whitney U-tests. For comparisons in number of lunges, average number of lunges, head butts and wing threats in intraslope fights, the nonparametric two-independent (unpaired)-sample Mann-Whitney U-tests were used, while for comparisons in interslope fights, the nonparametric Wilcoxon matched-pairs signed-rank tests was used. All courtship data were evaluated by the nonparametric two-independent (unpaired)-sample Mann-Whitney U-tests. Chi-Square tests were used to evaluate the relationship between two populations. Differences were considered statistically significant when the p value was less than 0. 05. Outliers were tested with a Grubb's test and the significant outliers were excluded.
Acknowledgements We thank all the members of the  Kravitz Lab  for many helpful discussions and support on this project,  Edward A. Kravitz  for his critical evaluation and editing of the manuscript and  Jacqueline Palavicino  for figure design. These studies were supported by  NIH   R35-MIRA grant 1-R35-GM118137-01. Eviatar Nevo  thanks the  Ancell Teicher Research Foundation of Genetics and Molecular Evolution  for financial support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
1) Water sorption The sorption kinetics of water vapor into a material depends on numerous factors, such as the chemical composition, the physical and chemical properties, etc. A continuous gravimetric analysis was performed in order to understand possible interactions of water molecules and [C6Py][PF6] over the whole range of water activity. Fig. 2  shows that the experimental data of the water vapor sorption kinetics of [C6Py][PF6] depend directly on the water activity a. As one can see, the water uptake increases with time to the achievement of the sorption equilibrium after certain period of time. Besides, the maximal amount of sorbed water increases when the water activity a increases. Moreover, the sorption kinetics becomes longer starting from a = 0. 8. Before this value, the equilibrium state (i.
Motivation: Comparative plasmid genome analyses require complex tools, the manipulation of large numbers of sequences and constitute a daunting task for the wet bench experimentalist. Dedicated plasmid databases are sparse, only comprise bacterial plasmids and provide exclusively access to sequence similarity searches. Results: We have developed Web-Assisted Symbolic Plasmid Synteny (WASPS), a web service granting protein and DNA sequence similarity searches against a database comprising all completely sequenced natural plasmids from bacterial, archaeal and eukaryal origin. This database pre-calculates orthologous protein clustering and enables WASPS to generate fully resolved plasmid synteny maps in real time using internal and user-provided DNA sequences.
Introduction The Darwinian evolution of genomes from the three domains of life is fast-tracked by the acquisition of traits through horizontal gene transfer  (Cordaux and Batzer, 2009; Cossu et al. , 2017; Seth-Smith et al. , 2012). This process is mediated by plasmids and viruses defined as mobile genetic elements. In contact with their hosts, replicating plasmids in particular have been shown as remarkably plastic  (Cury et al. , 2018). The comparative analysis of plasmid genomes constitutes a daunting task due to the lack of dedicated, plasmid-centric resources. Similarity searches in public databases of the National Centre for Biotechnology Information (NCBI) cannot be restricted exclusively to plasmid DNA or protein. Recently, plasmid assets have been developed proposing either a comprehensive manually curated bacterial plasmid list  (Brooks et al.
, 2019)  or a bacterial plasmid database which can be interrogated using sequence similarity programs  (Galata et al. , 2019). The Easyfig synteny tool allows the efficient comparison of genomes and plasmids but requires user-installation  (Sullivan et al. , 2011). Bioinformatics web tools providing access to a database of bacterial, archaeal and eukaryal plasmids and their synteny are still missing at this time. In this work, we present the database-backed WASPS web service which in addition to similarity searches allows the real-time generation of fully resolved plasmid synteny maps. The evolutionary relationships between user-provided sequences and databases sequences can be inferred using these synteny maps. The WASPS database is updated at regular intervals, comprises all completely sequenced natural plasmids from the three domains of life and provides full precalculated orthologous gene clustering.
WASPS consists of three modules. The WASPS database is a relational database containing all entries from the NCBI RefSeq plasmid repository encompassing all completely sequenced bacterial, archaeal and eukaryal plasmids of natural origin. At database creation, each protein-encoding gene is hierarchically linked to its plasmid of origin using GenBank keys. All corresponding protein sequences undergo orthologous clustering using UCLUST  (Edgar, 2010)  and obtain a centroid identifier. At this date, the WASPS database contains 18 915 bacterial, 240 archaeal and 36 eukaryal plasmids. The WASPS Webtool provides a user interface for the remote interrogation of the database and proposes 5 distinct features: 1. Text-based search in plasmid and proteins definitions and accession numbers. 2. Protein and DNA-based similarity searches with user-provided sequences using BLAST  (Altschul et al.