dataesr/scientific-paragraphs-categorization huggingface dataset:
6 (±0. 11) days (±) and 11 (±15) days in the Mauritian and Hawaiian FAD arrays, respectively, while no CAT diff were recorded in the Maldivian array. These values are larger than those expected for straight line movements between FADs. Previous studies of Girard et al. [18]  found that tuna movements between FADs consist of two components: (i) oriented movements towards FADs at short distances and (ii) a random-walk dynamics at large distances. Adding an additional directed movement to FADs within a given radius to the random-walk behaviour will not change the trends in CAT diff and CAT return found for the simple random walk model. However, fitting a model that accounts for both this directed movement component and for the actual geometries of the FAD arrays (including the presence of the islands) on the field data is key for testing the hypothesis of a random-walk component in tuna movements more quantitatively.
Conclusion and perspectives The trends observed from tagging data for the absence times (travel time between two associations) appear to be consistent with the existence of a random search component in the behavior of tuna within a FAD array, in addition to the oriented component of the movements observed when tunas are a few kilometres from the FADs  [18]. Conversely, the observed trends in FAD residence times appear to be driven by more complex processes involving, for instance, inter-individual interactions at the FADs, such as those suggested by the meeting point hypothesis, or due to prey availability. As our study is the first to focus on the role of FAD densities (inter-FAD distances) on tuna behavior for a particular species and size class, further studies on different FAD arrays would be necessary to strengthen our conclusions.
For a dataset of 493 test groups in Nile tilapia O. niloticus, small standard errors of the estimate of the variance of IGE for body weight were obtained  [6]. A larger number of groups (250-500) and a large group size (60) are required for accurate estimation of genetic parameters for IGE when the heritability of social effects is low  [16, 17]. The number of half-sib families may also affect the precision of the genetic parameters. Variances of DGE and IGE could not be estimated in  [6]  when the number of half-sib families was small, because the common environmental effect was confounded with DGE. Rearing density may also affect the standard errors of estimates of genetic parameters of IGE. When the rearing density is low, social interactions among shrimp are rare and difficult to detect.
Characterization Techniques X-ray diffraction (XRD) patterns of the synthesized powders and the bulk samples were obtained using an INEL EQUINOX 1000 diffractometer (INEL, Artenay, France) operating with CuKα radiation (λ = 1. 5406 Å). The existing phases were determined using the International Centre for Diffraction Data-Powder Diffraction Files 2 (ICDD PDF2) database. The lattice parameters and the average crystallite sizes were calculated with the FullProf program (Version 2006)  [10]  using the Rietveld method  [11]. The particle size, the morphology, and the microstructure of the consolidated samples were studied using a JEOL-2011 transmission electron microscope (TEM, JEOL, Tokyo, Japan) operating at 200 kV. Microstructure examination of fracture surfaces was carried out using Field Emission Gun Scanning Electron Microscopy (FEG-SEM; Ziess, Oberkochen, Deutschland).
The grain size of Nickel and Ni 3 P was determined by a statistical study of 200 particles using the Image Tool program (Free software, Version 2, University of Texas Health Science Center, San Antonio, TX, USA). The phosphorus content in the samples was determined by inductively coupled plasma (ICP) measurements. The SPS process of the powders was accomplished with an SPS-515S SYNTEX apparatus (Fuji Electric Industrial Co. , Osaka, Japan). The densities of the consolidated samples were measured by the Archimedes method using 2-propanol as a measuring liquid (0. 786 density at 25 • C). Compressive tests of specimens with dimensions of 1. 5 mm × 1. 5 mm × 2. 4 mm were conducted at room temperature (RT) using a homemade micro-sample testing machine with a load cell of 5 kN maximum capacities and a strain rate of about 3.
The XRD patterns of densified samples obtained by the R-SPS process showed, besides intense peaks of Ni, the presence of low-intensity peaks (Figure  2 ). According to the X-ray diffraction database, these peaks can be attributed to Ni3P phase (PDF Card No. 34-0501). This phase was formed during the SPS process and derived from the use of sodium hypophosphite in the synthesis process  [6]. Actually, SPS acted as a reactive process and transformed the metastable alloys into bulk submicrometer grain-sized MMCs, where the matrix was composed of nickel and Ni3P was the reinforcement phase formed during sintering. The mechanism of this phase apparition assumed the diffusion of phosphorus from the inside of the initial nanoparticles to the grain boundaries, where nucleation and growth of Ni3P nanoparticles occurred.
Grain growth during heat treatment by SPS was accompanied by narrowing peaks observed on XRD patterns. The weight percentages and the crystallite size of both phases were determined using the Fullprof program based on the Rietveld method (Table  1 ). The weight percentages of Ni3P phases varied from 5% to 10%. The XRD patterns of densified samples obtained by the R-SPS process showed, besides intense peaks of Ni, the presence of low-intensity peaks (Figure  2 ). According to the X-ray diffraction database, these peaks can be attributed to Ni 3 P phase (PDF Card No. 34-0501). This phase was formed during the SPS process and derived from the use of sodium hypophosphite in the synthesis process  [6]. Actually, SPS acted as a reactive process and transformed the metastable alloys into bulk submicrometer grain-sized MMCs, where the matrix was composed of nickel and Ni 3 P was the reinforcement phase formed during sintering.
This result was confirmed in a previous work by electron energy loss spectroscopy (EELS) analysis  [7]. The weight percentages and the crystallite size of both phases were determined using the Fullprof program based on the Rietveld method (Table  1 ). The weight percentages of Ni 3 P phases varied from 5% to 10%. TEM investigations of the microstructure of the bulk samples and the grain size distributions determined by TEM are presented in Figure  3. It was found that the mean grain size values for nickel depended on the size of the starting Ni-P alloy nanoparticles. The larger the size of the initial particles of Ni-P alloys, the larger the grain size of Ni present in the MMC materials-about 3-5 times larger than the mean particle sizes in the initial powders (see Table  1 ). However, the grain growth was more important when the starting nanoparticle size was lower, indicating that the high-temperature consolidation (600 • C) resulted in grain coarsening, in agreement with previous reports  [13, 14].
To better understand the mechanism of acclimation to uctuated salinity, transcriptional regulation of related pathways still need to be explored. In this work, digital gene expression (DGE) of 27 samples were performed in order to investigate the gene expression and regulation in response to hyposaline stress and recovery from stress in U. compressa. By comparing the RNA-seq data of hyposaline stress and recovery, we identi ed some key genes and pathways involved in responses to salinity stress in U. compressa. The ndings of the present study will lay the foundation for elucidating the molecular mechanisms of salinity reduction and provide useful information for further study of U. compressa.
De novo transcriptome assembly was performed using Trinity (v2. 5. 1) with all parameters set default  (25). Then transcript abundance was estimated by RSEM(26) and transcripts with low expression level (TPM<5) were removed. Transcriptome annotation was performed with a Blastx search against the NCBI-nr and the Swissprot database with an E-value cut-off of 10 -5. The interproscan and GO annotation were performed on the Blast2GO  (27). And KEGG pathways were assigned to the transcripts using the online KEGG Automatic Annotation Server, (http://www. genome. jp/kegg/kaas/). The singledirectional best hit (SBH) method was used for KEGG Orthology (KO) assignment.
Metabolic network reconstruction Using the annotation from Blast2GO, especially the EC number, a genbank le was created with in-house Python scripts. This le was given as an input to Pathway Tools version 22. 0(28). Using the gene annotations, Pahtway Tools predicted biochemical reaction and metabolic pathways. This information was stored in a Pathway Genome DataBase (PGDB). Using the PADMet toolbox version 2. 6(29), the PGDB was converted into a le compatible with the so-called "PADMet format", which was used to create a wiki website (https://gemaureme. genouest. org/ucomgem/index. php/Main_Page). The website integrates both the prediction of Pathway Tools (genes, metabolites, reactions, pathways) and gene expression data.
Differentially expressed genes identi cation and functional enrichment analysis Single-end reads were mapped to the reference transcriptome using Bowtie2 and expression of transcripts were calculated by RSEM  (30). Then DESeq2 was used for the differential expression analysis by comparing control and treatment samples  (31). A corrected P-value of 0. 05 and |log2fold-change| > 1 were set as the threshold for signi cant differential expression. GO and KEGG enrichment analysis of differentially expressed genes was performed using the TBtools software  (32). GO terms and KEGG pathways with corrected P-values below 0. 05 were considered signi cantly enriched by differentially expressed genes. 2. 6 Prediction of long non-coding RNAs and their targetgenes As described by Li et al  (33) , three criteria were used to identify long non-coding RNAs: 1) the transcripts that have no hits with known protein-coding genes on the same strand; 2) the transcripts have no coding potential according to the result of Coding Potential Calculator (CPC)  (34) , and Coding-Non-Coding Index (CNCI)  (35) ; 3) the transcripts have no hits with known protein domains in Pfam database(36).
Global transcriptome assembly and annotation In order to obtain as many transcripts as possible, A mixed library of different abiotic stress conditions was sequenced and assembled (Additional le 1). A total of 2. 17x10 8 ltered reads (without adaptor and low-quality bases) were obtained and the average GC content was 57%. After assembly, the global transcriptome contained 19,079 transcripts with the length ranging from 201 to 9,987bp. The mean length of transcripts was 1,409bp. The annotation of global transcriptome was performed using different database: NCBI non-redundant protein sequences (Nr), Swiss-prot, Kyoto Encyclopedia of Genes and Genomes database (KEGG), Protein family (PFAM), and Clusters of Orthologous Groups of proteins (COG). In total, 10,045 52. 65% unigenes were similar to proteins in at least one of these databases.
Analysis of differentially expressed gene To explore the gene expression pattern of U. compressa under hypo-salinity stress, a total of 27 RNA libraries generated from three replicates under the nine treatments were sequencing on a Nextseq500 platform. Raw data generated in each library ranged from 10. 0 to 13. 2 million reads. After removing low quality data, approximately 9. 8-12. 1 million clean reads remained, of which around 90% reads were mapped to the reference transcriptome. DESeq analysis were performed to identify the differentially expressed genes (DEGs) from read count data of various treatments. The thresholds of DEGs was set as the false discovery rate (FDR)≤0. 01 and |log 2 Ratio|≥1. The numbers and relationships of DEGs between different stress conditions were shown in Fig.
Acknowledgements We would like to thank  Anne Siegel  and  Jeanne Got  from  Dyliss team  for uploading and maintaining the metabolic network website page. This work has also bene ted from the computational resources of the bioinformatic platform in College of  Marine Life Sciences, Ocean University of China and ABiMS bioinformatics platform  ( FR 2424 ,  CNRS-Sorbonne Université, Roscoff ).
Sequencing and genome features of the C. novyi isolate The complete genome features of the C. novyi isolate are summarized in Table  2  and Figure  5. The genome consisted of a single circular chromosome with two circular plasmids. The sizes of the C. novyi isolate chromosome and plasmids 1 and 2 were 2,296,219 bp, 134,627 bp, 68,232 bp, respectively. The GC content of the chromosomal DNA was 27. 9%, and 33 rRNA genes, 84 tRNA genes, and 54 pseudogenes were identi ed. The GC content of plasmid 1 was 26. 3%, and 13 pseudogenes were identi ed. The GC content of plasmid 2 was 25. 5%, and 13 pseudogenes were identi ed. The assembled and annotated sequences of the C. novyi isolate chromosome and plasmids 1 and 2 were submitted to NCBI (accession numbers: CP029458. 1, CP029459. 1, and CP029460. 1).
16S rRNA gene sequencing analysis 16S rRNA gene sequencing was performed by a sequencing facility (Biofact Co. , Daejun, Korea) using a pure culture of the C. novyi isolate. The 16S rRNA gene sequence of the C. novyi isolate was identi ed by a BLAST search and compared with other Clostridium species sequences downloaded from the NCBI database. Multiple alignment of the 16S rRNA gene sequences was performed using MegAlign (DNASTAR, Madison, Wisconsin, USA), and a phylogenetic tree was constructed with the neighbor joining method using MEGA 6  (30). Cell culture assay of C. novyi isolate on Vero cells Vero 76 cells (ATCC CRL-1587) were maintained in high-glucose Dulbecco's modi ed Eagle's medium (DMEM; Welgene, Korea) supplemented with heat-inactivated 5% fetal bovine serum (FBS; Invitrogen, USA), 2 mM L-glutamine, and a 100× antibiotic-antimycotic solution [Anti-Anti, Invitrogen; 1× solution contains 100 IU/ml penicillin, 100 μg/ml streptomycin, and 0.
Meshes The meshes were created using the VISUAL-MESH TM software  [30]. Thanks to the symmetry (see the D-D line in Figure  4 ), only half of the geometry needs to be discretized. The three different meshes considered are presented in Figure  5. The first mesh (A) is intended for element type Q1P0, and the other two (B and C) for the stabilized P1P1 element  [24]  and the nodal approach; this is summarized in Table  2. Mesh A was generated manually, but both meshes B and C were obtained with an automatic mesh generator. Note that mesh C is more refined than the other two in the weld pass (colored green in Figure  5 ) and in the heat-affected zone.
Conclusions A nodal-integration-based finite element method was developed for the numerical solution of thermomechanical problems and implemented into the SYSWELD TM software  [27]. The approach uses linear triangular (in 2D) or tetrahadral (in 3D) meshes, thus permitting the use of standard present-day tools for automatic meshing. As a consequence of the placement of integration points at the nodes instead of the Gauss points of the elements, it avoids volumetric locking phenomena currently encountered with the standard finite element method, for elastoplastic or viscoplastic constitutive equations involving plastic incompressibility. Nodal subdomains, as required by Chen's et al. [19] [20] [21]  SCNI approach to nodal integration, were defined for both triangular and tetrahedral meshes, as a natural byproduct of the discretization of the domain of study into finite elements.
2011; Peksa and Skaloud 2011; Yahr et al. 2006). At the local scale (for instance along elevational gradients), this may translate into habitat-specific photobiont switches  (Vargas Castillo and Beck 2012). Above all, temperature has often been identified as a key factor of photobiont selection of lichens in Antarctica  (Green 2009; Kappen and Valladares 2007; Ruprecht et al. 2012a ). In warmer regions, myco-/photobiont interactions show increased specificity leading to one-to-one interactions in contrast to more generalist interactions in colder environments  (Singh et al. 2017 ). Thus, it appears that symbiotic interactions in lichens can react very sensitively to environmental change although this conclusion is based on a small database, and these responses have been investigated only in a few species  (Allen and Lendemer 2016; Colesie et al.
Discussion The McMurdo Dry Valleys at 78° S in Victoria Land, Antarctica are known as the largest continuous ice-free landscape on the continent and are mostly colonized by lithic and soil related microbial communities  (Bottos et al. 2014; Colesie et al. 2014a; De Los Rios et al. 2014; Lee et al. 2019; Pérez-Ortega et al. 2012; Yung et al. 2014). The only comprehensive evaluation to date for saxicolous lichens was that of Pérez-Ortega et al. (  2012 ) which showed a high number of mycobiont species (26) and, in contrast, a low number of photobiont species (four). Here we use a new and much larger dataset focused specifically on the lecideoid lichen group that includes some other species with similar morphologies in the same and adjacent areas and the respective data of  Perez-Ortega et al.
Acknowledgements We are grateful to  T. G. A Green  (Waikato, NZ; Madrid, E),  M. Affenzeller ,  A. Blaschka ,  G. Brunauer ,  A. M. Zimmermann  ( Salzburg, A ) for valuable advice and  R. Türk  ( Salzburg, A ) for collecting one third of the lichen samples in 2010 and providing the picture for Fig. 1d. The lichen collections were supported by grants to SCC from the  New Zealand Foundation for Research, Science and Technology  ( UOWX0710 ), the  New Zealand Ministry of Business, Innovation and Employment  ( UOWX1401 ) and the  University of Waikato. Antarctica New Zealand  is thanked for logistic support. This study and open access was financially supported by the  Austrian Science Fund (FWF) :  P26638_B16 , Diversity, ecology and specificity of Antarctic lichens.
Samples used in this study, with information on haplotypes, collecting localities and Genbank accession numbers of different markers. To avoid redundant data accumulation, for every haplotype only one reference sequence was uploaded to Genbank. Table of contents Online Resource 1a…………………………… 1 Online Resource 1b…………………………… 5 Online Resource 1c…………………………… 7 Online Resource 1d…………………………… 8 3 600 -78. 073 163. 717 Buellia sp. 3 T46710 3 600 -78. 073 163. 717 Rhizoplaca macleanii (Dodge) Castello T46713 4 350 -78. 028 163. 843 Lecidea polypycnidophora Ruprecht & Türk T46716 4 412 -78. 040 163. 802 Lecidea polypycnidophora Ruprecht & Türk T46717 4 442 -78. 040 163. 806 Lecidea polypycnidophora Ruprecht & Türk T46718 4 442 -78. 040 163. 807 Carbonea vorticosa (Flörke) Hertel T46719 4 425 -78. 038 163.
UDP-Glc was measured as described above. (B). UGP + and UGP -cells were cultivated for 4 days in normal growth medium prior to incubating the cells, for the indicated times, with glucose-free medium to which 1 mM Glc and 5 mM Gal were added. In one experiment the cells were pretreated for 30 min with 10 µg/ml cycloheximide (CHX). UDP-Glc (U-Glc) and UDP-Gal (U-Gal) were measured as above. The quantities of these nucleotide sugars have been expressed as a percentage of the quantity found to occur at the 6 h time point in the absence of CHX. All data points represent a single determination. (C,D). UGP -cells were grown normal growth medium for 4 days, washed in glucose-free RPMI 1640 and then incubated for the indicated times in this medium containing 1 mM Glc + 5 mM Gal (Gal). Where indicated, the cells were then rinsed with glucose-free RPMI 1640 prior to being incubated for the indicated times in normal growth medium (chase).
Subsequent to these incubations, UDP-Glc was measured. The observed UDP-Glc levels have been expressed as a percentage of that occurring at 6 h of Gal treatment. All data points represent a single determination. In a parallel experiment, cells were radiolabeled with [2-3 H]mannose for 30 min and DLO were extracted and examined by thin-layer chromatography (D). The fluorograph shown in D was scanned densitometrically and the percentage of total DLO occurring as Glc 3 Man 9 GlcNAc 2 was computed. F. UGP -cells were incubated for up to 48 h in the indicated media. After harvesting, the galactosylation of cellular proteins was examined by RCA lectinoblot as described for Figure  4A. This is a representative experiment, and in another experiment, a control membrane, where the blot was incubated with RCA-I in the presence of 500 mM lactose, revealed that detection of bands was sugar dependent (as demonstrated in Figure  4A ).
In Vitro Activity Assay and Determination of Kinetic Parameters Analysis of enzymatic activity and determination of kinetic parameters in the forward direction of the UGP reaction (production of UDP-Glc and PP i ), including curve fitting and evaluation using GraphPad Prism 4 software, were performed as described before  [24] , with the following adaptations: UTP concentration was varied between 0. 01 and 0. 8 mM at a constant concentration of 2 mM of Glc1P or Gal1P; and concentrations of Glc1P, or Gal1P, were varied between 0. 01 and 1 mM, or 0. 01 and 2 mM, respectively, at a constant concentration of 1 mM UTP. Supplementary Materials: Supplementary materials can be found at http://www. mdpi. com/1422-0067/21/6/2028/ s1.
Where indicated, the cells were then rinsed with glucose-free RPMI 1640 prior to being incubated for the indicated times in normal growth medium (chase). Subsequent to these incubations, UDP-Glc was measured. The observed UDP-Glc levels have been expressed as a percentage of that occurring at 6 h of Gal treatment. All data points represent a single determination. In a parallel experiment, cells were radiolabeled with [2-3 H]mannose for 30 min and DLO were extracted and examined by thin-layer chromatography (D). The fluorograph shown in D was scanned densitometrically and the percentage of total DLO occurring as Glc 3 Man 9 GlcNAc 2 was computed. F. UGP -cells were incubated for up to 48 h in the indicated media. After harvesting, the galactosylation of cellular proteins was examined by RCA lectinoblot as described for Figure4A.
UGP -cells were grown normal growth medium for 4 days, washed in glucose-free RPMI 1640 and then incubated for the indicated times in this medium containing 1 mM Glc + 5 mM Gal (Gal). Where indicated, the cells were then rinsed with glucose-free RPMI 1640 prior to being incubated for the indicated times in normal growth medium (chase). Subsequent to these incubations, UDP-Glc was measured. The observed UDP-Glc levels have been expressed as a percentage of that occurring at 6 h of Gal treatment. All data points represent a single determination. In a parallel experiment, cells were radiolabeled with [2-3 H]mannose for 30 min and DLO were extracted and examined by thin-layer chromatography (D). The fluorograph shown in D was scanned densitometrically and the percentage of total DLO occurring as Glc 3 Man 9 GlcNAc 2 was computed.
The Belle detector surrounds the interaction point of KEKB. It is a large-solid-angle magnetic spectrometer that consists of a silicon vertex detector, a 50-layer central drift chamber (CDC), an array of aerogel threshold Cherenkov counters (ACC), a barrellike arrangement of time-of-flight scintillation counters (TOF), and an electromagnetic calorimeter (ECL) comprised of CsI(Tl) crystals located inside a superconducting solenoid coil that provides a 1. 5 T magnetic field. An iron flux-return located outside of the coil is instrumented to detect K 0 L mesons and identify muons. For the study of B → ppππ, samples simulated with the Monte Carlo technique (MC) are used to optimize the signal selection criteria and estimate the signal reconstruction efficiency. These samples are generated with EvtGen  [13] , and a Geant  [14] -based software package to model the detector response.