dataesr/scientific-paragraphs-categorization huggingface dataset:
One interesting deviation from the previous picture is that the new H i detections have their HI kinematics well aligned with their stellar kinematics. Earlier detections of relaxed H i discs in slow rotators were in roughly polar configurations, with the H i kinematic axis 90 • out from the stellar kinematic axis. S14 commented that it was difficult for their simulations to produce so many polar gas discs. The new detections alleviate that difficulty to some extent, though they do not eliminate it. In these senses the new H i data broaden the known diversity of H i properties in slow rotators, and it would be useful to re-examine the H i properties of simulated slow rotators. NGC 1222, one of the two slow rotators that we discuss in some detail, is a starbursting merger remnant. Its stellar body shows prolate-like rotation and the H i occurs in a moderate-inclination disc, with its kinematic axis roughly aligned with the stars and the ionized gas.
(2015). This object may be one of the "darkest" of the dark (optically faint) galaxies. The H i emission in AGC 249460 is not well resolved, so dynamical mass estimates have a large uncertainty, but they do help constrain the nature of the object. A Gaussian fit to the integrated line profile gives a velocity dispersion of 11. 0 ± 1. 3 km s -1. A 2D Gaussian fit to the column density gives an estimated deconvolved size of (43 ± 9 ) by (33 ± 11 ) FWHM, so a radius of 20 = 2. 4 kpc may be reasonable. These values give a virial mass estimate of 2. 7×10 8 M , which is only modestly larger than the known atomic gas mass of 1. 7×10 8 M. Thus, the data suggest that AGC 249460 is gravitationally bound, but it's not clear whether it requires a large dark matter component. AGC 249460 could be a tidal dwarf galaxy with very little dark matter.
It certainly does not have a dominant stellar component, and it's not entirely clear why there hasn't been much star formation. The peak column density in these data is 2. 1×10 20 cm -2 , which suggests that at higher resolution the H i may be thick enough to form H 2. We note also that the estimated virial/gas mass ratio would be larger if the object's actual distance is substantially less than the 24. 5 Mpc we have assumed, and in that case the evidence for dark matter would be stronger; but at the moment there is no other evidence against the association with the NGC 5574-5576-5577 group. Cappellari et al. (2011a) , though those marked with '?' are estimated by association or from a Hubble flow calculation. The primary target in column 3 indicates the nearest Atlas 3D galaxy and the dataset in which the object is found.
ACKNOWLEDGMENTS Thanks to  L. Coccato  for providing the [O iii] data from their paper, and to  Alison Crocker  and  Gareth C. Jones  for helpful discussions. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the  Jet Propulsion Laboratory, California Institute of Technology , under contract with the  National Aeronautics and Space Administration. We acknowledge the usage of the HyperLeda database (http://leda. univ-lyon1. fr).
Data were treated as previously reported (  12 ). In brief, the 95,906 reads obtained were cleaned, using CLC Genomics Workbench software v11. 0. 1, according to quality score (limit, 0. 01) and length (reads shorter than 100 bp were removed). De novo assembly (requirements included the following: map reads back to contigs, mismatch cost, 2 occurrences; insertion cost, 3 occurrences; deletion cost, 3 occurrences; length fraction, 50%; similarity fraction, 80%; and minimum contig length, 350 bp) was realized, and a 7,532-nucleotide (nt)-long PSV consensus sequence, including the complete open reading frame (ORF) (7,014 nt, determined from the CLC Genomics Workbench v11. 0. 1 software pipeline: start codon ATG, and standard genetic code), was identified from 49,761 reads. Partial 5= and 3= noncoding region sequences were obtained (423/480 and 95/106 nt long, respectively, with reference to previously published PSV sequences (GenBank accession no.
METHODS Clinical Assessment Clinical data from patients with mutations in the RP1L1 gene were collected. Examinations were carried out after written informed consent and in accordance with the tenets of the Declaration of Helsinki. The study was approved by the ethics committee of the Medical Faculty of University of Tübingen. For follow-up observations, data were partly collected in a retrospective fashion. Patients underwent complete ophthalmologic examination including psychophysical (decimal best corrected visual acuity [BCVA] and perimetry) as well as electrophysiologic tests (fullfield and multifocal ERG). Semi-automated kinetic perimetry using Goldmann stimulus III4e within the 908 visual field and automated static perimetry within the 308 visual field were performed using a perimeter (Octopus 900; Haag-Streit International, Wedel, Germany).
PCR products were purified by ExoSAP-IT treatment (GE Healthcare, Freiburg, Germany) and sequenced with dye termination chemistry (BigDye Terminator ver. 1. 1; Applied Biosystems [ABI], Darmstadt, Germany). Sequences were run on a capillary sequencer (ABI 3100; ABI) and analyzed with sequence analysis software (version 5. 1; ABI) and sequence trace alignment software (SeqMan; DNASTAR, Madison, WI, USA). In a subsequent screen, exons 1, 2 (forward primer 5 0 -GAG GTG TTA TGG GGA GTG GA-3 0 , reverse primer 5 0 -GAG GCA AGA GAG ATC CCA AA-3 0 ) and exon 3 (forward primer 5 0 -ATT TTG GAG GCA GTG GTG ATG CTG AG-3 0 , reverse primer 5 0 -CGC AGA GCT CTC TGA CAC TTC TGG ACT TA-3 0 ) of RP1L1 were analyzed in selected cases via Sanger sequencing as described above. The repetitive region covering amino acids 1,312-2,160, were not analyzed.
In addition, one patient (OCMD40) was homozygous for this very same mutation. Another patient with OCMD was heterozygous for the variant c. 3599G>A;p. G1200D (OCMD41) and one patient for c. 2849G>A;p. R950H (OCMD42). Both variants are already published as pathogenic variants, but the latter may be rather considered a variant of uncertain significance with respect to its frequency in the Genome Aggregation Database (gnomAD; available in the public domain, http://gnomad. broadinstitute. org/; minor allele frequency [MAF] 0. 02685%; including four homozygous cases listed in 275,576 alleles), and especially c o m p a r e d t o t h e f a r m o r e c o m m o n m u t a t i o n c. 133C>T;p. R45W with a 310 lower allele frequency in the normal population (MAF 0. 0018%; three heterozygous in 274,220 alleles).
SD-OCT images revealed intact retinal layers in the fovea and thinning of the photoreceptor layer toward the periphery. The patient displayed the novel homozygous nonsense mutation c. 3022C > T;p. Q1008*, which had never been observed in any database and is predicted to be disease-causing. The second patient (arRP2, female, 45 years) noticed night blindness at the age of 25 years and a slow progression of visual problems (i. e. , concentric narrowing of the visual field, slight decrease of central vision) over the years. At examination, BCVA was 0. 8 and 0. 63 on the right and left eye, respectively, visual fields for the target III4e were narrowed to approximately 158 without remaining peripheral islands. Dark adaptation thresholds were slightly elevated, full-field ERGs still showed remaining cone responses and mfERG recordings detected well-preserved macular function, similar to patient arRP1.
32  In human, mutations in RP1 are associated with both dominant and recessive forms of RP  [38] [39] [40]  accounting for approximately 5. 5% and 1% of dominant and recessive RP, respectively (Human Gene Mutation Database or HGMD). 41, 42  In 2010, Akahori et al. 1  successfully linked the disorder OCMD to chromosome 8 and the RP1L1 gene. Since the discovery of causative RP1L1 mutations in patients with OCMD, a number of cases have been reported. 1, 4, [14] [15] [16] [17] 43, 44  It seems that RP1L1 is the sole gene associated with autosomal dominant OCMD. The most common mutation is c. 133C > T;p. R45W in exon 2,  1, 14, 16  but very recently, a second hotspot located between amino acid numbers 1196 and 1201-which is downstream of the doublecortin domain (DCX)-has been identified. 14  According to the recommendation of Fujinami et al.
Acknowledgments Supported by  BMBF  Grant  01GM1108A  (SK),  T ÜFF-Grant 2247-0-0  (DZ), and a grant of the  Kerstan Foundation  (GZ, DZ). Disclosure:  D. Zobor , None;  G. Zobor , None;  S. Hipp , None;  B. Baumann , None;  N. Weisschuh , None;  S. Biskup , None;  I. Sliesoraityte , None;  E. Zrenner , None;  S. Kohl , None.
Introduction Geochronological datasets in external parts of mountain belts are primordial to date metamorphism, deformation and fluid activity, to model exhumation rates, and to appreciate the role of tectonic activity, topography and climate influence on orogenic evolution. Geochronological data can either be interpreted as apparent cooling ages or crystallisation ages. Apparent cooling ages are assumed to record the time at which a rock cooled below the closure temperature of the 5 thermochronometer. Exhumation rates can thus be derived by correlating the apparent cooling ages with the closure depth for a given geothermal gradient  (Brandon et al. , 1998; Willet and Brandon, 2013). For geochronometers with closure temperatures above the rock/mineral (re)-crystallization temperature, geochronological data record the age of crystallisation.
, 2015). On the other hand, this is 30 contradictory with the short-duration and episodic growth of cleft monazite  (Janots et al. , 2012)  suggesting that it precipitates due to tectonic/hydrothermal activity rather than by progressive cooling during exhumation  (Bergmann et al. , 2017; Gasquet et al. , 2010; Grand'Homme et al. , 2016). In this paper, LA-ICP-MS and microthermometric data on fluid inclusions were successfully combined with geochronological data on monazite crystals to reveal local advective heating due to hydrothermal circulation in vein systems during exhumation of the Lauzière Granite (Belledonne massif, Western Alps). The impact of advective heating on the thermal regime of the host-rock was then evaluated from ZFT data in host rock granite samples collected at the direct contact, 30 meters and 100 meters away from the cleft.
, 2003; Rossi et al. , 2005)  and the Oisans massif to the south (270-360°C, 2-5 kbar; review in  Bellanger et al. , 2015). A complex geochronological dataset exists for the metamorphism recorded in shear zones and veins in the ECM, with three age-groups at ca. [24] [25] [26] [27] [28] [29] [30] attributed to 15  the different deformation stages  (Gasquet et al. , 2010; Leloup et al. , 2005; Rolland and Rossi, 2016). Underthrusting of the ECM is generally estimated to have occurred around 30 Ma  (Bellanger et al. , 2015; Cenki-Tok et al. , 2011; Nziengui, 1993; Rolland and Rossi, 2016). The Ar-Ar and ZFT datasets suggest that cooling and exhumation started at ca. 18 Ma  (Boutoux et al. , 2016; Seward and Mancktelow, 1994) , in a compressive tectonic regime until 12 Ma (dating in horizontal veins;  Bergemann et al.
3 to 314. 9°C; N = 4) compared to the main second group (QzP2; 178. give lower T h (120. 6 to 147. 7°C; N = 8). Eutectic temperature were determined between -21. 2 and -23°C, which is in good agreement with T e for H 2 O-NaCl and H 2 O-NaCl-KCl systems, respectively at -21. 2 and -22. 9°C  (Bodnar, 2003; Hall et al. , 1988). For the entire dataset, T m ice obtained in quartz and monazite crystals overlap within uncertainty: they range from -6. 0 to -9. 6°C (Fig. 4 ), which converts to salinities between 9. 2 and 13. 5 wt. %NaCl equivalent. There is no significant difference in salinities between the 5 fluid inclusion populations, although fluid inclusions trapped at lower temperature have generally 5 lower salinities. Based on similar T m ice and T h values (Fig. 4 ), the first population of quartz inclusion (QzP1) is considered equivalent to primary inclusions in monazite (MnzP), whereas the secondary fluid inclusion population in monazite (MnzS) overlap with the main group of primary inclusions in quartz (QzP2).
Impact of advective heating on zircon fission track age resetting Novel ZFT obtained in the Lauzière massif (samples R2 and R3) confirm that metamorphic temperatures were high enough to anneal the pre-Alpine ZFT signature  (Yamada et al. , 1995). The ZFT dataset indicate that the Lauzière granite cooled down below 240-280°C at around 14-16 Ma (Figs. 7  and 8 ), in good agreement with previous ZFT data in the in the Belledonne massif  (8-15 Ma; Fügenschuh and Schmid, 2003; Seward and Mancktelow, 1994; Figg. 1b ). In the cleft 10 hanging-wall, the rejuvenation of the ZFT age at 10. 3 ± 1. 0 Ma indicates a resetting of the ZFT geochronological system by advective heating due to the hot hydrothermal fluid penetrating the cleft. It is difficult to quantify the spatial impact of advective heating linked to fluid circulation at the outcrop scale.
In the present study, the two samples taken at quite some distance from the cleft (30 m and 100 m) have ZFT ages older than monazite growth in cleft, indicating no significant resetting by related cleft fluid circulation. However, along the eastern 15 margin of the Lauzière granite, fluid circulation is not restricted to clefts but is evidenced in outcrop by retrogression and growth of mica-like phyllosilicates, as evidenced in the Mont Blanc massif by  Rolland and Rossi (2016) , and the formation of centimetric scale veins. It is thus not possible to rule out that the ZFT dataset of the deformed Lauzière granite was not affected by fluid circulation during the deformation phase responsible of the cleft formation or even during an earlier, ductile deformation stage. 20.
, 2016). Combined with the new microthermometric data, the monazite age is interpreted to date the first stage of hydrothermal growth following the fracturation and infiltration of a hot fluid at T of 410-520°C into the host-rock that had already cooled 30 below 240-280°C (Fig. 8 ). In other words, there is a 150-250°C temperature difference between the fluid from which monazite precipitates and the fracturing host-rock, in which fluid infiltrates. Assuming an undisturbed crustal geothermal Solid Earth Discuss. , https://doi. org/10. 5194/se-2018-84 Manuscript under review for journal Solid Earth Discussion started: 10 September 2018 c Author(s) 2018. CC BY 4. 0 License. gradient, it implies that the source of the fluid was at least 6-10 km deeper than the host-rock. Based on the structural data of the subvertical cleft (Fig.
Despite this research, to date, no systematic effort has been done for the shape of the unsteady flow event hydrograph over a fixed rough bed and their flow variables. Following the above consideration, the object of this research is to investigate the hydrograms and characteristics of flow variables over a fixed rough bed. The present research conducts an experiment in a tilting laboratory flume with a fixed bed with unsteady flow condition at National Institute of Technology, Rourkela, India. The mean flow velocity and bed shear stress over a rigid grass bed were measured to study the effect of unsteadiness on the flow characteristics and finally compared with experimental data of steady flow case for respective flow depths.
Acknowledgements. XXL is an international project based around an XMM Very Large Programme surveying two 25 deg 2 extragalactic fields at a depth of 5. 8 × 10 -15 erg s -1 cm -2 in (0. 5-2 keV) at the 90% completeness level (see XXL paper I). The XXL website is http://irfu. cea. fr/xxl. Multiband information and spectroscopic follow-up of the X-ray sources are obtained through a number of survey programmes, summarised at http://xxlmultiwave. pbworks. com/. We would like to thank  A. Mantz  and  B. Poggianti  for comments on the manuscript. The Saclay group acknowledges long-term support from the  Centre National d'Etudes Spatiales (CNES). EK thanks  CNES  and  CNRS  for support of postdoctoral research. SF acknowledges financial support from the  Swiss National Science Foundation. This work was supported by the  Programme National Cosmology et Galaxies (PNCG)  of  CNRS/INSU  with  INP  and  IN2P3 , cofunded by  CEA  and  CNES.
Mortality trajectories in the wild We obtained 24 long-term individual-based data sets from wild vertebrate populations (mammals, birds, reptiles and amphibians) that covered a range of positions along the slowfast life history continuum (Table  S1 )  (Gaillard et al. 1989 (Gaillard et al. , 2016)). The data sets were either census data with almost complete detection or typical capture-mark-recapture/-recovery (CMRR) data. We combined data for males and females since sex information was unavailable for several data sets. For inference on age-specific mortality we used the R package BaSTA  (Colchero & Clark 2012; Colchero et al. 2012). We tested 10 different functional forms of age-specific mortality, including two and three parameter Weibull, Gompertz and Gompertz-Makeham, Logistic, and combinations of these with an initial declining juvenile mortality and, finally, a model with a single adult stage (i.
ACKNOWLEDGEMENTS We thank  Jeanne Altmann  for access to the baboon data and  Josephine Pemberton ,  Tim Clutton-Brock  and  Loeske Kruuk  for access to the red deer data, and  D. H. Nussey  for comments. We acknowledge funding from the  Max Planck Society ,  Marie Curie Fellowship  ( PIEF-GA-2008-220322 ),  ERC  grant number  249872 , the  German Research Foundation  ( Be 916/3  to 9), the  Swiss National Science Foundation  ( SNF PP00P3-133641 ), the  National Science Foundation  ( BCS-1232349 ,  BCS-1219368 ,  BCS-0621020 ,  IOS 0919200 ),  National Institute of Aging  ( P30 AG-012836 ,  P01 AG031719  and  R01 AG034513 ),  Ramon y Cajal Research Grant   RYC-2016-21114 ,  Wenner-Gren Foundation ,  Leakey Foundation ,  National Geographic Society, Zoological Society of San Diego, University of Pennsylvania and Argentinean National Council of Research.
The ecology and distribution of green phytoplankton (Chlorophyta) in the ocean is poorly known because most studies have focused on groups with large cell size such as diatoms or dinoflagellates that are easily recognized by traditional techniques such as microscopy. The Ocean Sampling Day (OSD) project sampled surface waters quasi-simultaneously at 141 marine locations, mostly in coastal waters. The analysis of the 18S V4 region OSD metabarcoding dataset reveals that Chlorophyta are ubiquitous and can be locally dominant in coastal waters. Chlorophyta represented 29% of the global photosynthetic reads (Dinoflagellates excluded) and their contribution was especially high at oligotrophic stations (up to 94%) and along the European Atlantic coast. Mamiellophyceae dominated most coastal stations.
prasinophytes clade IX  11  dominate oceanic waters. However, no global analysis of the relative importance and distribution of the different green algal groups in the ocean has yet been performed. High Throughput Sequencing (HTS) methods provide large metabarcoding datasets which enable the exploration of the diversity and distribution of protist groups in the ocean  12. The Ocean Sampling Day (OSD) project  13  sampled in 2014 the global ocean, mostly at coastal stations, at the boreal summer solstice (June 21). At each station, the V4 region of the 18S rRNA gene was sequenced. In this paper, we analyze the OSD V4 metabarcoding datasets with the aim to describe the distribution of the major classes of Chlorophyta in the global coastal ocean.
Materials and Methods Sampling and sequencing. 157 water samples from 145 marine locations were filtered on 0. 22 µm pore size Sterivex without prefiltration and frozen at -80 °C. Metadata (Temperature, Salinity, Nutrients and Chlorophyll a) were obtained from https://github. com/MicroB3-IS/osd-analysis/wiki/Guide-to-OSD-2014-data. Temperature and salinity were measured in situ during the sampling. Nutrients concentration were estimated from historical data uploaded from the World Ocean Database 2013  14  (https://www. nodc. noaa. gov/OC5/WOD13/) and Chlorophyll a was estimated from remote sensing ocean color from the MODIS AQUA database (Moderate Resolution Imaging Spectroradiometer, http://oceancolor. gsfc. nasa. gov/cgi/l3). In this paper, we only considered 141 samples obtained from the surface layer (Table  S1 ).
All molecular processing steps were performed by the OSD team. DNA was extracted using the Power Water isolation kit (MoBio, Carlsbad, CA, USA) following the manufacturer instructions. V4 was amplified using TAReuk454FWD1 (5′-CCA GCA SCY GCG GTA ATT CC-3′) as forward primer and the modified TAReukREV3_modified (5′-ACT TTC GTT CTT GAT YRA TGA-3′) as reverse primer  15, 16. The Illumina libraries were prepared using the Ovation Rapid DR Multiplex System 1-96 (NuGEN, link to protocol:https://owncloud. mpi-bremen. de/index. php/s/RDB4Jo0PAayg3qx?path=/2014/protocols). Sequencing (2 × 250 paired end) was done with Illumina technology MiSeq using V3 chemistry by the LGC genomics GmbH (Germany, http:// www. lgcgroup. com/). Data processing. R1 and R2 were filtered based on quality and length and assembled by the OSD consortium which provided the so-called "workable" fasta files (http://mb3is.
megx. net/osd-files?path=/2014/datasets/ workable). This dataset provided around 5 million workable V4 region of the 18S rRNA gene metabarcodes. The raw files have been deposited at EBI (http://www. ebi. ac. uk/ena/data/view/ERX947554). All subsequent sequence processing was done with Mothur v 1. 35. 1  17. Reads were filtered to remove those shorter than 300 bp or containing ambiguities (N). Then, reads were aligned to SILVA seed release 123 alignment  18  corrected manually with the Geneious software v 7. 1. 7  19 : gaps at the beginning and the end of sequences were deleted. The aligned datasets were filtered by removing columns containing only insertions. Chimeras were checked using Uchime v 4. 2. 40  20  as implemented in Mothur. The datasets were pre-clustered using Mothur. After distance matrix calculation, the sequences were clustered using the Nearest Neighbor method and Operational Taxonomic Units (OTUs) were built at 99% similarity.
OTUs represented by only one sequence (singletons) were deleted. OTUs were finally assigned using the Wang approach  21  and the PR² database  22  , available at https://doi. org/10. 6084/m9. figshare. 5913181, for which the Chlorophyta sequences had been checked against the most recent taxonomy  23. OTUs for which assignation bootstrap value was lower than 80% were not taken into account. Each OTU was linked to a reference sequence and an OTU was considered to be assigned when the lowest taxonomic level ("Species" level in PR 2 ) differed from "unclassified". In order to validate OTU assignation, all OTU reference sequences were further BLASTed against the GenBank nr database using megablast.
Statistical analyses. For all analyses of the relative abundance of specific classes, we only considered samples for which more than 100 Chlorophyta reads were obtained (122 samples). Graphics and ecological analyses were performed using the R v. 3. 0. 2 software (http://www. R-project. org/). We used the package Treemap to draw treemaps (Fig. 1 ), ggplot2  24  to draw maps and bar graphs, ComplexHeatmaps  25  for heatmaps, Gplots for all other plots. Distance to the coast was calculated for each station using Rgdal and Rgeos packages and the coastline file available (http://www. naturalearthdata. com/downloads/10m-physical-vectors/10m-coastline/). The Vegan package  26  was used to compute slopes of rarefaction curves (function rareslope) and Bray-Curtis dissimilarity matrices (function vegdist).