dataesr/scientific-paragraphs-categorization huggingface dataset:
The Rd rate was determined according to the Laisk  [55]    Changes in cauliflower leaf light (R d ), dark (R n ) respiration as well as total light (R T ) respiration and (PhR) photorespiration (all expressed in µmol•CO 2 •m -2 •s -1 ) at 200 (R T 200 and PhR200), 400 (R T 400 and PhR400) and 600 (R T 600 and PhR600) µmol•m -2 •s -1 illumination rate in control grown (K), heat-stressed (H), heat-recovered (HA), cold-stressed (C) and cold-recovered (CA) plants. All parameters were measured on 3-month-old plants with fully developed leaves with the application of an infrared gas analyser. Data were recorded after at least 2 h of illumination. During the experiment, each of the analysed leaves were placed into a 6-cm 2 chamber of the analyser. Results were recorded after initial leaf acclimation to the desired light and CO 2 concentration, relative humidity and temperature.
Gas Exchange Measurements All analyses were carried out on at least three fully developed leaves from three 3-month-old plants. Leaves were taken from each plant representing all experimental variants (control versus stress-treated or control versus stress recovered plants). At least three biological replicates were analyzed. All parameters (the rate of total CO 2 assimilation [A g ], A n , total respiration rate [R T ], R d , R n , E, and g s ) were measured using an LI-6400 XT infrared gas analyzer (LI-COR, Lincoln, NE, USA) and adjusted to the enclosed leaf area determined by an LI-300 leaf meter (LI-COR, Lincoln, NE, USA). Data were recorded after at least 2 h-long illumination. During the experiment, each of the analyzed leaves were placed into a 6-cm 2 chamber of the analyzer. Results were recorded after initial leaf acclimation to the desired light and CO 2 concentration, relative humidity and temperature.
25% [w/v] DTT) and for the same time with solution B (solution A supplemented with 4. 5% (w/v) iodoacetamide without DTT) and subjected for the second dimension run (SDS-PAGE). For SDS-PAGE precast Ettan DALT 12. 5% (w/v) polyacrylamide gels (GE Healthcare) and an Ettan Dalt Six electrophoretical chamber (for six gels) were used. Conditions for the run were as follows: 45 min at 80 V and 15 h at 120 V. After electrophoresis, proteins on gel triplicates were either silver stained  [148]  for protein variation analysis or stained with colloidal CBB, according to Neuhoff et al. [149]  for MS analyses. 2D gels were scanned, analysed using 2D Image Master 7 Platinum software (GE Healthcare) and the normalized quantitative volume of protein spots was determined.
Peptide mixture was applied to an RP-18 precolumn (nanoACQUITY Symmetry ® C18-Waters 186003514, Waters, Warsaw, Poland) using water containing 0. 1% (v/v) trifluoroacetic acid as mobile phase and then transferred to a nano-HPLC RP-18 column (nanoACQUITY BEH C18-Waters 186003545) using an acetonitrile gradient (0 to 60% (v/v) acetonitrile for 120 min) in the presence of 0. 05% (v/v) formic acid with a flow rate of 150 nL•min -1. The column outlet was directly coupled to the ion source of the spectrometer working in the regime of data dependent MS to MS/MS switch. A blank run ensuring lack of cross contamination from previous samples preceded each analysis. Acquired raw data were processed by Mascot Distiller followed by Mascot search (Matrix Science, London, UK, 8-processor on-site license) against NCBInr (version 20100203) with taxonomy restricted to Viridiplantae.
Antibodies against NAD9 and CCMA were produced by  [158]  and  [159] , respectively. CcmF N1 and CcmF N2 antisera were generated by  [160]. Bound sera were detected using an anti-rabbit immunoglobulin G horseradish peroxidase or alkaline phosphatase conjugate diluted to 1/10,000 (BioRad Polska, Warsaw, Poland) and visualized with enhanced chemiluminescent reagents (GE Healthcare, Warsaw, Poland) or with Lumi-Phos WB Chemiluminescent Substrate (Life Technologies Poland, Warsaw, Poland). Immunoblotting images in triplicates were analyzed by Multi Gauge (v2. 2, Fujifilm, Tokio, Japan) software and the representative pattern was presented. Band intensities were calibrated to the protein loading in the linear relationship (the control denoted as 1. 00); the other bands were calculated relative to this value.
Acknowledgments: The work was supported by the  Ministry of Science and Higher Education, Poland , grant number:  N N303 338835. We gratefully thank  Mikołaj Knaflewski ,  Alina Kału żewicz , and  Anna Zaworska  ( Poznan University of Life Sciences ) for the valuable help during cauliflower plant cultivation and the gas exchange measurements. We would like to thank  Michał Dadlez ,  Janusz Dębski  and the staff from  Mass Spectrometry Laboratory  ( Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw ) for MS analyses. We thank  Ludmiła Bladocha  ( Institute of Dendrology, Polish Academy of Sciences, Kórnik ) as well as  Grzegorz Pietkiewicz  ( Adam Mickiewicz University, Pozna ń ) for valuable technical assistance.
Sample collection Images of bony fishes from the North Sea were collected in January 2017 from nine online image databases (Appendix S1). Four criteria were used to only retain comparable images: (1) lateral views of (2) male individuals (to cope with any sexual dimorphism) (3) with all their fins well represented (i. e. , spread and not eaten), and (4) no eel-shaped species (discarded because of their recurrent serpentine representation). We considered images of all species recorded regularly during bottom trawl survey in the North Sea and fitting the four criteria previously cited. When available, several images of the same species were included to evaluate the robustness of the approach. A total of 218 images (48 photographs and 170 drawings) from 85 bony fish species of the North Sea were included in this study (Appendix S1).
Morphological diversity in the North Sea Abundance data of the North Sea fish community has been collected by the North Sea International Bottom Trawl Survey  (ICES 2015) , an international effort to monitor demersal fish populations. The sampling procedure monitored the North Sea on a regular grid of 1°longitude 9 0. 5°latitude, known as the ICES rectangles. Each contributing research vessel applies a standard otter trawl net which is hauled over the seabed for 30 min. The data for the first quarter of the period 2006-2015 were downloaded from http://datras. ices. dk/. To avoid any bias that may arise due to different sampling efforts (i. e. , different number of hauls per ICES rectangles), 10 hauls per ICES rectangles were randomly selected, and we assessed their species and morphological richness.
We repeated the random selection 100 times to estimate the variability of species occurrence (i. e. , the presence or absence of species). ICES rectangles with <10 hauls in the 10-yr period were removed from the analysis. In total, 172 ICES rectangles were included in the analysis. Two indicators of morphological diversity were calculated for each ICES rectangle from occurrence data and the mean scores of species on the three PCs defining the morphospace  (Vill eger et al. 2008 ). Morphological richness is the volume of the morphospace occupied by the convex hull of the community. Morphological dispersion is the mean distance to the barycenter of each community (Lalibert e and Legendre 2010). The morphological diversity was then compared to species (i. e. , taxonomic) richness obtained from the occurrence data.
Software and tutorial All statistical analyses were conducted in the programming environment R 3. 3 (R Core team 2017). Morphometric analyses were done with the package Momocs 1. 2. 3  (Bonhomme et al. 2014) , while morphological diversity indicators were calculated with the FD package. The geographic distribution of species and morphological richness was visualized with the mapdata and rgdal packages. A tutorial explaining the EFT on fish communities is available on GitHub: https://rfrelat. github. io/FishMorpho. html (https:// doi. org/10. 5281/zenodo. 1108518).
ACKNOWLEDGMENTS We thank the two anonymous referees for their useful comments that helped improve this manuscript. RF has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie Grant  Agreement No. 675997  ( ITN MARmaED ). The results of this publication reflect only the author's view, and the Commission is not responsible for any use that may be made of the information it contains. The study is a contribution to the  University of Hamburg Center of Excellence on  " Integrated Climate System Analysis and Prediction" (Cli-SAP ) funded by the  German Science Foundation.
Introduction Oceanic circulation and the carbon cycle play a major role in the regulation of the past and present climate. Heat and carbon dioxide in the atmosphere tend to equilibrate with the ocean surface and are transported down into the deep ocean through the Meridional Overturning Circulation (MOC). Biogeochemical cycling also generates organic carbon that transfers into the deep ocean through particle sinking. Because of this, the strength of the MOC and particle removal participate actively in the regulation of the climate on the Earth. Trace elements are also affected by these mechanisms and represent useful tools to provide constraints on these processes. The GEOTRACES programme has generated a large unique dataset that can now be used to better understand biogeochemical oceanic processes.
Circulation The circulation was obtained by forcing NEMO in the ORCA2 configuration with climatological air-sea boundary conditions consisting of heat, freshwater and momentum fluxes that were derived from bulk formulae. They are functions of wind, sea surface temperature, air temperature, air humidity and evaporation minus precipitation. For the tropics, daily wind stress was used, which was based on Euro-pean Remote Sensing (ERS) satellite data, and for the polar regions NCEP/NCAR reanalysis data were used  (Kalnay et al. , 1996; Kistler et al. , 2001). Surface salinity was restored with a timescale of 60 days towards the seasonal Polar Science Center Hydrographic Climatology (PHC) dataset to avoid model drift  (Timmermann et al. , 2005). The last year of this 200-year simulation is used as our 1-year climatology with a resolution of 5 days of the dynamics.
Observations In this study, we will focus on the GEOTRACES GA03 transect in the North Atlantic Ocean. Recently, a large number of measurements on both radionuclides and their carrier particles have been collected on this transect. This unique combination makes it especially useful to evaluate a radionuclide scavenging model. We will also compare our global ocean model with several observational datasets throughout the ocean (Table  3 ). Observations obtained from the GEO-TRACES programme are denoted with the respective GEO-TRACES transect number  (Mawji et al. , 2015; Schlitzer et al. , 2018). For the carrier particles most of our data come from  Lam et al. (2015) , which is a recent GEOTRACES dataset at the GA03 transect in the North Atlantic Ocean. An older compi- lation of particles is taken from  Lam et al.
4b ). Contrarily, total observed [CaCO 3 ], which is only provided along section GA03 where small particulate CaCO 3 measurements are available, is higher than the prediction of our modelled (only big) CaCO 3 particle concentration. The model produces a reasonable spatial distribution of biogenic silica: there are more elevated values in the high latitudes, but concentrations are underestimated at the surface at low latitudes (Fig. 4c ). The recent large dataset obtained from the full-ocean depth GEOTRACES GA03 transect  (Lam et al. , 2015)  provides an opportunity to analyse the performance of PISCES in more detail. PISCES generally produces the right order of magnitude for all four biogenic particles (small and big POC, calcium carbonate, and biogenic silica), but there still remain some shortcomings in their distributions (Fig.
S2, GA03 ). Secondly, in the western boundary currents, very low dissolved 230 Th concentrations are observed due to strong nepheloids and/or possibly strong deep ventilation from the north. Neither of these processes is represented in the model. The lack of nepheloids has an especially large impact on the GA02 transect, which has a relatively large number of measured profiles near the western boundary. Finally, between 32 and 20 • W, the model tends to underestimate 230 Th. The value of the correlation index is not that important because the goal of this study is not to give a perfect model-data comparison. The provided dust flux does not distinguish between different dust particle sizes or types. Furthermore, dust deposition is uncertain; therefore, we chose a dust flux that was available to the ORCA2 configuration of NEMO, and its biogeochemistry has been tested with that dust flux.
Whereas this is somewhat restricting, it is computationally efficient, and it restricts the number of degrees of freedom (which is usually a good thing in complex models). NEMO-ProThorP can also be used to set up a non-instant equilibration model (with a k + and k -) that may yield better concentrations in the upper ocean. The underlying model, NEMO 3. 6 (svn revision 5283), can be downloaded from http://www. nemo-ocean. eu/ (Madec and the NEMO team, 2016) after creating a login. NEMO includes the biogeochemical PISCES model  (Aumont et al. , 2015). For reproducibility purposes, version 0. 1. 0 of the radionuclide and lithogenic particles model code can be obtained at https://dx. doi. org/10. 5281/ zenodo. 1009065 (van Hulten et al. , 2017a). However, we plan to make this code available as part of the NEMO model.
The NEMO model is available under the CeCILL (http:// www. cecill. info/, last access: 27 August 2018) free software licence, modelled after the GNU GPL. The lithogenic particles and 230 Th/ 231 Pa-specific code is licenced under the same terms or under the GNU General Public License (https://www. gnu. org/ copyleft/gpl. html, last access: 27 August 2018) version 3 or higher. The authors would appreciate it if, in addition to the legal adherence to copyleft and attribution, they are informed about the use of the code. Finally, the most important raw model output files are available at PANGAEA (https://doi. org/10. 1594/PANGAEA. 887261) (van  Hulten et al. , 2018). The Julia scripts used for the statistics are included in the Supplement. This may be useful to reproduce the results or further inspect the model output.
Acknowledgements. We would like to thank  Marion Gehlen  and  Olivier Aumont  for the discussions on the calcite parameterisation in PISCES, among other things. The first author is grateful to  Jörg Lippold  for both the discussion and encouragement that also helped this work. This study was supported by a  Swedish Research Council  grant ( 349-2012-6287 ) in the framework of the French-Swedish cooperation in the common research training programme in the climate, environment and energy agreement between VR and LSCE for the project "Particle transport derived from isotope tracers and its impact on ocean biogeochemistry: a  GEOTRACES project in the Arctic Ocean ". This study was partly supported by the project " Overturning circulation and its implications for the global carbon cycle in coupled models " (ORGANIC; the  Research Council of Norway , grant no.
The libraries were sequenced (2 × 75 bp) on Illumina HiSeq2500 and HiSeq4000 platforms, according to our modified experimental and software protocols for generation of high-quality data for low-diversity samples  16. Primary i-BLESS data analysis. Data analysis and interpretation were performed using our iSeq software for multi-scale analysis and high-level interpretation of DSB sequencing data, and are described in detail elsewhere (http://breakome. utmb. edu/software. html). Briefly, we used iSeq to ensure sequencing data quality before mapping. Next, iSeq was used to remove proximal and distal i-BLESS barcodes (TCGAGGTAGTA and TCGAGACGACG, respectively). Reads labeled with the proximal barcode, which are directly adjacent to DSBs, were selected and mapped to the yeast genome S288C with bowtie v0.
12. 2 using alignment parameters '-m1 -v1' to exclude multiple mapping and low-quality reads. The tail base pairs were trimmed using bowtie '-3' option, the parameter choice was based on the iSeq quality report. Hygestat_BLESS v1. 2. 3 (part of iSeq software suite, available from http://breakome. eu/software. html) was used to implement mappability correction and identify DSB-rich regions (or "fragile regions") with a significant increase of read numbers (hypergeometric test with Bonferroni correction, P value < 0. 001) in treatment versus control samples within windows of selected size. Analysis of BamHI, NotI, SrfI, AsiSI and I-SceI data. To analyze samples in which DSBs were induced by a restriction enzyme (BamHI, NotI, SrfI, AsiSI or I-SceI), we used hygestat_bed (part of iSeq software suite) to identify reads within a given vicinity of the cutting sites and estimate P values of enrichment (hypergeometric test with Bonferroni correction).
Absolute DSB frequencies for noncanonical I-SceI sites were estimated using qDSB-seq method  22  using I-SceI spikein. Autocorrelation and cross-correlation analysis. To identify potential periodic patterns in mapped i-BLESS reads, we performed autocorrelation analysis of the i-BLESS data, using 1 nt bin size and 800 nt range. To further study localization of i-BLESS reads, we computed cross-correlation of the i-BLESS data with the MNaseseq  18  data on nucleosome positioning. The cross-correlation was calculated for every integer shift value n by determining Pearson correlation coefficients between i-BLESS read depth at all genomic positions and MNase read depth, shifted by n nucleotides. To compute autocorrelation for i-BLESS data, we cross-correlated it with itself. Break-seq data analysis.
We mapped Break-seq reads (HU 1 h, GSM1419918) to the budding yeast genome sequence and obtained read depth of DSBs using the same parameters as for analysis of the i-BLESS data, described above. G-quadruplex analysis. We used AllQuads  29  to identify G4 structures. Both canonical intra-strand and non-canonical inter-strand G4 structures were predicted, and then annotated according to Saccharomyces Genome Database 41. To test whether the significantly fragile intervals (see Primary i-BLESS data analysis) were enriched in G4 sequences, enrichment analysis was performed as described below (Enrichment analysis) using intervals of mappable length of 20 nucleotides. To compare G4s and other regions, we defined inside and flanking regions of G4s. The flank of a given G4 region was defined as flanking regions with the same total length as the G4 sequence on both sides.
G4 sequences were clustered based on the loop length into: 3 subcategories (G4 L 1-4 : all loops ≤ 4 nt; G4 L 5-7 : all loops ≤ 7 nt, but at least one loop > 4 nt; G4 L 8-16 : all loops ≤ 16 nt, but at least one loop > 7 nt) or 16 groups G4 L k , each group consisting of G4 with all loops of length ≤ k, but at least one loop of length = k. The number of i-BLESS reads was counted using inhouse PERL script. Kolmogorov-Smirnov test was used to evaluate the significance of the differences between them. Absolute DSB frequencies near G4 structures were estimated using qDSB-seq method  22  with NotI spike-in. Enrichment analysis. To determine whether a given genomic feature is enriched in DSB-rich regions, we used hygestat_annotations v. 2. 0 (part of iSeq software suite). Specifically, hygestat_annotations computed the proportion of mappable nucleotides belonging to both the DSB-rich regions and the given feature (observed overlap), and the proportion of mappable nucleotides belonging to both genomic regions and the given feature (expected overlap).
Acknowledgements This work was supported by  Polish National Science Centre  ( 2011/02/A/NZ2/00014  to K. G. and  2015/17/D/NZ2/03711  to M. S. ) and  Foundation for Polish Science  (TEAM to K. G. ). Funding to M. R. , Y. Z. , A. M. , J. N. and A. K. was provided by the  NIH  grant ( 5 R01 GM 112131  to M. R. ). Funding to P. P. was provided by  ANR ,  INCa ,  MSD Avenir Fund and Ligue contre le Cancer. N. C. is supported by the  Karolinska Institutet , the  Swedish Research Council , the  Swedish Cancer Research Foundation , the  Ragnar Söderberg Foundation , and the  Swedish Foundation for Strategic Research.
Occurrence data Geographic coordinates, when not available on the specimen labels, were obtained using Google Earth. The map was built using SimpleMappr  (Shorthouse 2010). This map includes a layer with the Biodiversity Hotspots (sensu Conservation International;  Mittermeier et al. 2004 ). Additionally, a spreadsheet containing occurrence data extracted from specimen labels was made available at Zenodo; the spreadsheet is organized by specimens and their unique identifiers, when available. Diagnosis. Body dark brown to blackish; cephalic spines long and thin; anterior edge of paranota not reaching the eyes; discoidal area biseriate and subcostal area irregularly quadriseriate.
Data resources SimpleMappr http://www. simplemappr. net/map/8595 KML http://www. simplemappr. net/map/8595. kml Zoobank Zetekella henryi sp. n. : 9480B3E7-E726-4718-8EBF-69C58A867887 Figshare Photographs of the dorsal habitus and labels of all holotypes (except M. minusculus), two paratypes of M. minusculus and of the new records vouchers Zenodo Spreadsheet containing label information of all studied specimens and their respective unique identifiers.
Materials and methods Type specimens are deposited in College of Life Science, China West Normal University, Nanchong, Sichuan Province, China. The abdomen of specimen was separated from the body, and then boiled in a 10% NaOH solution for 5 minutes until muscles were completely dissolved leaving tegumentary structures. After rinsing in distilled water for several times, the abdomen was subsequently transferred to glycerine for final dissection and observation. Terminalia were conserved under the specimen in genital vials. Photographs for external morphology and terminalia characters were taken using Leica DFC495 camera attached to Leica M205C stereomicroscope and further refined with LAS V3. 8 and Helicon Focus v3. 10 software. Morphological interpretations and subsequent terminologies for male genitalia follow  Bourgoin (1987) , for female genitalia  Bourgoin (1993)  and for wing venation  Bourgoin et al.
(2015). The total genomic DNA was extracted from leg of holotype specimen (♂) using the TransGen EasyPure Genomic DNA Kit. COI gene was amplified using the same primers and amplification procedure as  Wang et al. (2016). The DNA sequencing was conducted at Sangon Company (Shanghai, China). Software Seqman from package DNAstar v5. 01 (www. dnastar. com) was used for checking sequence chromatograms and assembling contigs. Mega v7. 0  (Kumar et al. 2016)  was used for performing alignments. IQtree v1. 4. 1  (Nguyen et al. 2015)  was used for maximum likelihood phylogenetic analysis using 10000 ultrafast bootstrap  (Minh et al. 2013 ) with substitution model automatic selected. Figtree v1. 1. 2 (Rambaut 2016 ) was used to visual the tree. The COI sequence of Sinonissus brunetus sp. n. was registered in GenBank with accession number MG921598, the other COI sequences used in this study were obtained from  Wang et al.
7: 32. 7: 14. 5: 20. 0. It differs by 124 and 126 nucleotidic bases with Issus coleoptratus (Fabricius, 1781) (GenBank accession number: KX702932) and Latissus dilatatus (Fourcroy, 1785) (GenBank accession number: KX702947) respectively, along the complete length of 681 bp.