dataesr/scientific-paragraphs-categorization huggingface dataset:
We thank the  LIA BEEG-B (Laboratoire International Associé -Bioinformatics, Ecology, Evolution, Genomics and Behaviour) (CNRS)  and the PESSOA programme for facilitating travel and collaboration between EDB,  IMT  and  INSA in Toulouse  and the  IGC , in Portugal. This work was partly performed using HPC storage and computing resources from Genotoul and  CALMIP (Calcul Midi Pyrénées , Grant 2012 -projects 43,  44 , and Grant  2016 , project  P16011 ) bioinformatics platforms from Toulouse,  Midi-Pyrénées , France. We also used the Haystack and Elephant IGC computing resources. This study was partly funded by the  ERA-NET Biodiversa framework and Fundação para a Ciência e Tecnologia (INFRAGECO (Inference, Fragmentation, Genomics , and Conservation) Project ref. Biodiversa /0003/2015 ), the NOS-Alive Fellowship programme (ref.
The structure was solved by molecular replacement using the known m  7  GpppG-CBC complex structures (PDB:1H2T) as search model. There are eight complexes in the asymmetric unit with variable occupancy of the ARS2 peptide, probably due to the relatively low affinity. Data collection and refinement statistics are given in Table  2. Electron density for one example of the peptide is shown in Supplementary Fig. 4A. The overall structure of CBC is only perturbed locally by ARS2 binding (see below) and the binding of the cap analogue m 7 GTP to CBP20 is unchanged from described previously  2. The C-terminus of ARS2, which is only visible beyond residue 851, forms an extended chain that wraps around the CBP80-CBP20 interface, interacting with both subunits (Fig. 5a ). The total buried surface area upon ARS2 peptide binding to CBC is 2257 Å 2 (PISA server, www.
However, this is sterically incompatible with the presence of the side chains Asp852 and Arg854 of ARS2 with the result that CBP20 Tyr50 is stabilised in an alternative rotamer that allows it to stack with ARS2 Ile856 (Fig. 5b , left). Tyr859 is inserted between the subunits making contacts with CBP20 Met71 and Leu73 and CBP80 Ser558 and His561 (Fig. 5b , middle). Its hydroxyl points toward the mainchain amino group of CBP20 Glu53, whose side chain makes CBC inter-subunit interactions. To assess potential global changes in CBC structure we superposed, by means of CBP80, the m 7 GpppG-CBC complex (PDB:1H2T or 1H2U) on the complex with ARS2 (RMSD 0. 35 Å for 1H2T and 0. 38 Å for 1H2U). The superposition shows that the CBP20 β2-β3 loop (residues 71-81) and C-terminal extension to the RRM domain (residues 126-150, that are only ordered upon m 7 GTP binding) are slightly shifted toward CBP80, closing the groove in which the ARS2 peptide binds (maximum backbone displacement of 2.
7 ). Without structures of the lowaffinity CBC-peptide complexes, we can only speculate about the precise mechanism of synergistic binding. It is well established that cap-binding stabilises the fold of the otherwise flexible Nterminal (1-32) and C-terminal (125-150) regions of CBP20 2. Nevertheless, most of the CBP20 residues that interact with ARS2 or NELF-E are actually already structured in the absence of cap. However, superposition by means of CBP80 of the apo (PDB:1H2V), cap-bound (PDB:1H2T), and the ARS2 (or NELF-E)-CBC-m  7  GTP complexes shows that, due to the slight relative rotation of CBP20 upon ligand binding, the peptide binding groove is closer to optimally configured when the cap is bound rather than unbound (Supplementary Fig. 5 ). Second, the most highly conserved motif in the ARS2 C-terminal peptide is 861-DLDAP (Fig.
1d ), yet these residues lack electron density and appear not to interact with CBC. This suggests that this motif could have another functional role perhaps in a context when ARS2 is not bound to CBC. Third, the phosphosite database  43  contains strong evidence that ARS2 Tyr859 (Tyr864 in human ARS2 isoform 1) can be phosphorylated (http://www. phosphosite. org/siteAction. action?id=11169746). There is also evidence that the equivalent tyrosine in NELF-E, Tyr367, and possible also Tyr372 can be phosphorylated (http://www. phosphosite. org/proteinAction. action?id=5808). The structures suggest that these post-translational modifications would likely impede ARS2 or NELF-E binding to CBC, since the tyrosine side chains are buried, suggesting that complex formation could be regulated by phosphorylation.
Displacement pull down. CBC-NELF-E  or CBC-PHAX  were immobilised on m 7 GTP-sepharose and incubated for 1 h at 4 °C with different amounts of ARS2 147-871 or NELF-E 1-380 in 20 mM HEPES, pH 7. 8, 120 mM NaCl, 2 mM tris (2-carboxyethyl)phosphine, respectively. The flow through, as well as the elution from the beads after extensive washing, was analysed by SDS-PAGE followed by Coomassie staining. Cross-link mass spectrometry. Purified CBC-PHAX complexes were crosslinked with H12/D12 disuccinimidyl suberate (DSS, Creative Molecules Inc. ) at 35 °C for 30 min. The reaction was quenched, digested with LysC (Wako) and trypsin followed by peptide separation using SEC as described previously  47. MS data acquisition and analysis using the xQuest/xProphet software was performed according to ref. 47.
Data were integrated using the XDS suite  49  and analysed using the CCP4i suite  50. Structures were solved by molecular replacement with PHASER 51 using the known structure of CBC bound to m 7 GpppG (PDB:1H2T). Crystals of m 7 GTP-CBC-ARS2 were of space group P1 with eight complexes in the asymmetric unit. Two of the unit cell angles are 90°( the other being 90. 3°) and although the data integrate only marginally better in P1 than P2 1 (R meas 0. 126 and 0. 145, respectively) refinement is only possible in P1. Depending on the quality of the electron density, 11-14 residues from the ARS2 Cterminal peptide were placed in each of the eight CBC complexes and only Bfactors were refined, not occupancies, which were set to 1. Crystals of m 7 GTP-CBC-NELF-E were of space group P2 1 with four complexes in the asymmetric unit.
Acknowledgements We thank the staff of the  ESRF-EMBL Joint Structural Biology Group , in particular  Matthew Bowler , for access to and help on ESRF beamlines. We thank the  EMBL Grenoble Eukaryotic Expression Facility  and high-throughput crystallisation facility (HTX), and the  EMBL Heidelberg Proteomics Core Facility. We also thank  Thomas Bock  and  Martin Beck  ( EMBL Heidelberg ) for sharing their cross-linking protocols and  Edouard Bertrand  ( CNRS, Montpellier ) and colleagues for enlightening discussions. This work used the platforms of the Grenoble Instruct Center (ISBG:  UMS 3518 CNRS-CEA-UJF-EMBL ) within the  Grenoble Partnership for Structural Biology (PSB) , with support from  FRISBI  ( ANR-10-INSB-05-02 ),  GRAL  ( ANR-10-LABX-49-01 ).
It has a broad physics programme ranging from studying the Standard Model (namely Higgs boson) to searching for extra dimensions, and particles that could make dark matter. The Detector Control System (DCS) is responsible for monitoring of the slow control data of the experiments such as information from gas and cooling systems, environmental sensors (humidity, pressure and temperature) and radiation detectors  [2]. Furthermore, the DCS controls all Low Voltage (LV) and High Voltage (HV) power supply channels, which are required to drive on-detectors electronics. The DCS front-end panel also shows the current status of each chamber like ON, OFF or Trip condition. All important parameters are recorded and archived in the condition database. The configuration information, such as nominal channel voltages and current limits can be stored in a configuration database, from where they can be applied to the running system on demand.
During data taking mode, when any parameter changes its value, DCS stores and updates each selected parameter in the condition database. The DCS system issues early warnings about abnormal conditions and subsequently triggers the safety switches in order to protect the detector and its electronics from severe damages. The CMS DCS is based on commercial WinCC Open Architecture (WinCC-OA) Supervisory Control and Data Acquisition (SCADA)  [3]  and toolkit from the Joint Control Project (JCOP). -1 -.
The dosimeters operate by positive charge build-up on the gate oxide (SiO 2 ) layer of the transistor. The positive charge trapped for long time at room temperature leads to a shift of the transistor gate voltage that is proportional to the radiation dose and is measured by the RADMON sensor. In GE 1/1, RADMON is installed on the GEM cooling plate as shown in figure  3  to monitor the radiation dose at high η region. The readout system uses a master-slave message based protocol. The main controller addresses one of several connected RADMON sensors at a time. The address of each sensor controller is set -4 - by onboard micro-switches  [8]  as shown in figure  4. The main controller connects to the PC over a CANBUS or RS-485 interface and sends the data to the device that converts the serial data into the TCP/IP port.
Slice test and LS2 system requirements A first test system is implemented in the GEM assembly and in quality assurance laboratory for cosmic ray chamber characterisation. In the laboratory, it is needed to control scintillators (cosmic test stand), GEM chambers HV/LV and finally store information in the GEM database. The HV -5 - scanning of the GEM chambers is one of the main procedures controlled through the DCS system. As mentioned in section 1. 3, during the slice test two different HV powering schemes will be used, the first one using a resistor divider and a second one using seven independent voltage channels using multi-channel power supplies. In slice test, 4 super-chambers will be equipped with the resistor divider and these will get power from a CAEN A1527 HV mainframe power supply.
Acknowledgments We gratefully acknowledge support from  FRS-FNRS (Belgium) ,  FWO-Flanders (Belgium) ,  BSF-MES (Bulgaria) ,  BMBF (Germany) ,  DAE (India) ,  DST (India) ,  INFN (Italy) ,  NRF (Korea) ,  QNRF (Qatar) , and  DOE (U. S. A. )  and specially my colleague  Oliver Holme.
Our prediction was that benthic diversity, number of taxa, total biomass of infauna and total density of epifauna and infauna, would be higher in areas with colonies present. Photos of the seafloor (data on epifauna) and grab samples (data on infauna) were taken at three control areas and at five areas near seabird colonies, within a depth range of 122 to 442 m. A database of 26 environmental parameters was built to study the environment-benthos relationships. Infauna, which was relatively uniform across the LSR, was numerically dominated by Annelida. Epifauna was much patchier, with each study area having unique epibenthic assemblages. Brittle stars were highly abundant in epifaunal communities, reaching 600 individuals per square meter. The presence of seabird colonies was not a major driver of benthic community structure in the LSR at the depths studied.
In some cases however, even this level of identification could not be ascertained and some taxa were left at the phylum level (e. g. , Porifera). Infauna data from each grab sample were divided by the sediment volume associated with that specific grab sample, to obtain density (ind. l -1 ) and biomass (g l -1 ) data. Prior to statistical analyses, infaunal taxa which were only found in one area were removed to better detect similarities between communities (26 taxa removed)  (Clarke and Warwick, 2001).
2  for examples of the photos analyzed). This number of replicates per area (n = 15) was sufficient because each area was relatively homogenous and Species Accumulation Curves showed that the addition of new species had slowed and the curves were approaching a plateau after 15 photos analyzed. At the center of each selected and then scaled photo, a surface of 0. 692 m 2 (0. 675 × 1. 025 m) was delimited based on average area covered by the photos. This delimited surface was scanned to identify and count the epibenthic megafaunal organisms, using the software PhotoQuad  (Trygonis and Sini, 2012). Our definition of epibenthic megafauna included all organisms that were on or near the bottom and visible on photos. Fishes, crustaceans and all other mobile or sessile organisms were counted. Each colony of large distinct organisms, such as sponges and soft corals, was counted instead of being only recorded as present or absent as for encrusting species.
Environmental variables A SBE 39 temperature and pressure recorder was attached to the 4KCam system to provide water depth and temperature associated with each photo. Salinity data closest to the seafloor were extracted from CTD casts done in each area. To quantify organic matter deposited on the bottom, the three subsamples of surface sediments from each grab sample were dried for 48 h and burned at 450 °C for 6 h  (Byers et al. , 1978). The pigment concentrations (chl a μg g -1 dry weight and phaeo μg g -1 dry weight) in sediments for each of the three subsamples were determined following the method of Riaux-Gobin and Klein (1993), which is based on a 24 hour acetone extraction and fluorescence readings. Grain size of surface sediment was estimated for each of the analyzed photos (method similar to  Hardy et al.
, 2002)  for 2008 to 2012. Daily satellite-derived sea ice concentration data (%, 25 km-resolution pixels) from Special Sensor Microwave Imager SSMI/Sounder sensors were obtained from the National Snow and Ice Data Center (NSIDC, http://nsidc. org;  Maslanik and Stroeve, 1999). For the whole time-series of five years preceding our oceanographic mission in 2012, we extracted yearly mean values of chlorophyll a concentrations, primary production (derived from an Arctic-adapted model; see  Bélanger et al. , 2013 and its validation in Lee et al. , 2015)  and duration of open water. The latter was defined as the number of days during one year where sea ice concentration represented b10% of the studied surface  (Ardyna et al. , 2014). Yearly maxima and mean velocities data of modelled currents were obtained for the year 2010 using a regional Arctic-North Atlantic iceocean system.
These were performed under the same statistical model described above, to test the effect of Bird and Area nested in Bird factors on epifaunal community composition. Square-root transformation was chosen to down-weight the dominant taxa which were prominent in our data set. Pairwise comparisons were carried out to identify where differences within levels of different factors were detected. Multidimensional scaling (MDS) was used to obtain a graphical ordination of the samples, based on the Bray-Curtis similarity matrix. The multivariate dispersion of data was analyzed with a PERMDISP routine. Similarity Percentages Test (SIMPER) was done on the Bray-Curtis similarity matrix of square-root transformed density data to determine the epifaunal taxa that contributed the most to dissimilarities between Areas.
Similarly to the approach used for the multiple linear regressions, Area B1 was excluded due to missing data and the spatial resolution of environmental variables was standardized. The DISTLM was performed on 19 variables Birds, [PHO], [NIT], [Chl a] BW , D, T, OM, Sed Chl a, Sed Phaeo, FS, FG, MG, CG, VCG, VSB, SB, MB, LB, DOW, based on the justifications listed above to avoid collinearity. The best selection procedure was run with 9999 permutations and with different selection criteria: AICc, BIC and adjusted R 2. The best compromise between these three criteria was chosen following the same method used for multiple linear regressions detailed above  (Anderson et al. , 2008). SIMPER, PERMANOVA, MDS, PERMDISP, DISTLM and dbRDA were carried out using the software PRIMER-E version 6 with PERMANOVA+  (Anderson et al.
Acknowledgements We thank officers, crew members, scientists and technicians for their work with us aboard CFAV Quest and  CCGS Henry Larsen. Special thanks go to  R. Benjamin ,  K. Chalut ,  A. Cogswell ,  J. Gagnon ,  C. Grant ,  B. MacDonald  and  A. Robertson  for their participation in the field sampling. We also would like to thank  M. Blais ,  J. -A. Dorval ,  C. Grant ,  L. de Montety ,  V. Roy ,  L. Tréau de Coeli ,  L. Tremblay  and  F. Vermandele  for their help in the laboratory and/or with the statistical analyses. Thanks to  M. Casey ,  S. Higginson  and  Y. Lu  for producing and sharing bottom current velocity data. This project was funded by the  Natural Sciences and Engineering Research Council of Canada (NSERC ;  Discovery grant   RGPIN 262860-2013 ),  Fisheries and Oceans Canada (DFO)  at the  Bedford Institute of Oceanography, Natural Resources Canada (NRCan ) at the  Bedford Institute of Oceanography, Defence Research and Development Canada (DRDC) Halifax , the  Network of Centres of Excellence of Canada ArcticNet, Québec-Océan (FRQNT , Regroupement stratégique 2015-2021  Québec-Océan no 186795 ) and the  Institut des sciences de la mer de Rimouski (ISMER)  from  Université du Québec à Rimouski (UQAR).
Results Mitochondrial gene diversity and differentiation among Camelus. We analyzed 27 complete mitogenomes of Old World camels (Table  S1 ), including three sequences from GenBank (C. dromedarius: NC_009849. 1, C. bactrianus: NC_009628. 2, C. ferus: NC_009629. 2) to investigate signals of selection in Camelus possibly due to adaptation to different environmental regimes. With a mean read coverage of 20X [10-26X]  after correcting for a maximal read coverage of 30, the alignment of all mitogenomes displayed a total length of 16,390 bp excluding repetitive regions and contained 1,347 variable sites (1,262 parsimony-informative, 85 singletons). We calculated the mitogenome diversity within each of the three Old World camel species and found higher haplotype (H d ) and nucleotide diversity (π) in dromedaries (H d = 1.
97, P = 0. 0083) (Tables  S9  and 10 ). The excess of replacement polymorphism was not significant in the wild Bactrian camel lineage (Tables  S11  and 12 ). The significant results of the MK test (global and extended) indicating signals of purifying selection in the mitogenomes of the genus Camelus are summarized in Table  2. Evolution of mitochondrial protein-coding genes focusing on the lineage-specific evolutionary changes. To test for selective pressure acting on a particular Camelus lineage, we used a maximum likelihood (ML) approach and examined variation in the ratio of dN/dS (ω) on the codon-based alignments of ten different mammalian species including Old World camels (C. dromedarius, C. bactrianus, C. ferus), New World camels (Lama glama, L. guanicoe, Vicugna pacos, V. vicugna), Bos taurus, Pantholops hodgsonii and Homo sapiens (see Table  S1  for accession numbers).
We detected 4 sites (in ND2, ATP6), 10 sites (in ND1, ND2, COX3, ND3, ND4, ND5) and 12 sites (in ND2, ATP8, ND4, ND5, CYTB) under positive selection in dromedaries, Bactrian camels and wild camels, respectively (Table  S13 ). However, the significance of the detected sites could not be confirmed in the subsequent LRTs (Table  S13 ). Changes in the physicochemical properties of functional proteins by amino acid replacements. The analysis of functional divergence in amino acid changes was performed using TreeSAAP software  52  , which takes into account the magnitude of the impact of the amino acid replacement on local physicochemical properties of the protein. Changes with a magnitude ≥6 and P < 0. 001 were considered as indicating positive directional selection for a given physiochemical property  52.
Methods Sampling and sequencing of complete mtDNA. Genomic DNA was extract ed from whole blood of 24 specimens of Old World camelids (Table  S1  and Fig. 1 ), using Master Pure TM DNA purification kit for blood (Epicentre version III). This sampling was designed to span the known phylogenetic tree of Old World camelids, and to include mtDNA of species that are well adapted to hot, arid (nine dromedaries) and cold, dry (nine wild and six domestic Bactrian camels) environments. Blood samples were retrieved commensally either during routine veterinary treatment or during a radio-collaring project for Mongolian wild camels. All data sets were collected within the frames of the legal requirements of Austria and Mongolia. Capture and collaring of wild camels was conducted within a cooperation agreement between the International Takhi Group and the Mongolian Ministry of Nature, Environment and Tourism (signed on 15.
02. 2001 and renewed on 27. 01. 2011). The 500 bp paired-end Illumina library preparation and sequencing of each sample on a single lane of Illumina HiSeq 2000 platform was performed within the framework of a whole-genome re-sequencing study of Old World camelids (Fitak et al. in preparation). Three reference mitogenomes were retrieved from GenBank (Accession numbers NC_009849. 1, NC_009628. 2, NC_009629. 2). Read processing and alignments. The raw sequence reads for each individual were trimmed at the 3′ end to a minimum phred-scaled base quality of 20 and minimum length of 50 bp (base pairs) using POPOOLATION v1. 2. 2  85. For each species, the trimmed reads were mapped against the corresponding mitochondrial reference genome (C. dromedarius Genbank Accession no: NC_009849. 1, C. bactrianus: NC_009628.
2, and C. ferus: NC_009629. 2), using BWA v0. 7  86  with the following parameters (-l 200 -n 0. 01 -o 1 -e 12 -d 12 -t 6). Duplicate reads were removed using Picard-tools 'MarkDuplicates' v. 1. 89 (http://www. picard. sourceforge. net) and only the filtered reads, which were properly paired and unambiguously mapped with mapping quality score >20 were used for further analyses. The consensus sequence for each sample was generated using CLC Genomics Workbench 6. 5. 1 (http://www. clcbio. com). The consensus mitogenomes were aligned with CodonCode Aligner v. 3. 7. 1 (Codon Code Corporation, USA). The mitochondrial sequences of all 13 protein-coding genes, two rRNA subunits (12S, 16S) and control region of the three camel species were identified using the corresponding reference sequences of dromedary, domestic and wild Bactrian camel.
Mitochondrial gene diversity and differentiation among Camelus. Summary statistics of the 27 camel mitogenomes, within and between species were calculated with DnaSP v5. 10. 1  88. Within species diversity parameters included the number of polymorphic (segregating) sites (S), number of haplotypes (h), haplotype (H d ) and nucleotide (π) diversity, average number of nucleotide differences (k) and Watterson's theta (θ S ) based on the number of segregating sites (Table  1 ). The software was also used to carry out neutrality tests including Tajima's D  47  , Fu and Li's F 48 , Fu's Fs  89  , and Ramos-Onsins and Rozas R 2 statistic  49. Both D and F can detect historical population expansions and contractions, whereas Fs and R 2 explicitly test past population expansion and are more powerful  49.
In the extended MK test we calculated polymorphisms within one species and the divergence (fixed SNPs) at nonsynonymous and synonymous sites in pairwise comparison. In our second approach, we examined whether mitochondrial protein-coding genes in the Camelus lineage show any specific patterns of evolutionary rates. We assessed the variation in the ratio of dN to dS among the branches of a phylogenetic maximum likelihood (ML) tree using MEGA6  90  , with the best-fitting model HKY + G + I according to the Bayesian Information Criterion (BIC). Using the ML method implemented in the CODEML program of PAML v. 4. 8  51  , we applied the background and the branch-specific model on the 11,379 bp concatenated alignment (including gaps) of the mitochondrial protein-coding genes from ten different species (34 individuals).