dataesr/scientific-paragraphs-categorization huggingface dataset:
B Side-by-side comparison of oak unigene sets (OCV1: assembly from Ueno et al. [8] , OCV2: assembly from Tarkka et al. [22] , and OCV3: this paper). N50 length is defined as the length for which the collection of all contigs of that length or longer contains at least half of the total of the lengths of the contigs. C Comparison between OCV3-91k (Unigenes with BlastX hit) and OCV3-101k (Unigenes without BlastX hit) subsets: assembled sequences (in bp), mean and median contig sizes, N50. The remaining 101,311 contigs without BlastX hits in SwissProt or the selected plant gene models (referred to hereafter as the OCV3-101 k subset) were then aligned (using BlastX: e-value 1e -5 -E 2 -W 5) with the nr protein database and the genome sequence of Prunus persica (using BLAT and EST2 genome software,  [29] ).
Only 2. 4% of these contigs could be aligned with sequences in the nr protein database. These contigs also diverged much more than the OCV3-91 k subset (Table  3A ) from the Prunus persica genome. Matches to the Prunus persica genome sequence were obtained for 59% of the OCV3-91 k contigs but only 6. 2% of the OCV3-101 k contigs. Moreover, we successfully mapped 64,001 OCV3-91 k and only 8,380 OCV3-101 k contigs onto 17,038 and 5,265 Prunus persica gene models, respectively (Table  3B ). The number of exons per gene model was three times higher for OCV3-91 k than for OCV3-101 k. All together, these results indicate that OCV3-101 k consisted mostly of non-coding RNA. Besides, OCV3-91 k contained 46,415 (51%) contigs supported by short reads only, whereas OCV3-101 k contained 86,575 (85%) such contigs.
Functional annotation and GO classification of oak transcripts We assigned functions to the OCV3-91 k contigs with the Gene Ontology (GO) classification, which provides a standardized set of terms to describe the genes and gene products of different species. First, we designated functions for each contigs on the basis of matches with the Pfam database. A total of 1,112 GO terms to 24,999 contigs (i. e. 27. 54%) were identified. A second series of GO annotation was based on the GOA database. For the 77,784 OCV3-91 k contigs giving significant matches to A. thaliana proteins, 65,198 (i. e. 71. 82%) were annotated with at least one GO term. We retrieved the functional categories associated with their best Blast hits in Swis-sProt, and this yielded 13,355 GO terms for 61,139 contigs. Based on best Blast hit results, we were able to associate 76,457 contigs with GO terms in this second round.
Overall, at least one GO term was assigned to 77,277 contigs (i. e. 85. 12% of OCV3-91 k) (Additional file 5); 24,180 of these contigs (31. 29%) were associated with GO terms from both series, 819 contigs (1. 06%) were associated with GO terms from the first series, and 52,278 contigs (67. 65%) were associated with GO terms from the second series. For the 77,277 contigs associated with at least one GO term, 72,558 were associated with 1,820 GO terms (70%) for Biological Processes (BP) , 72,235 were associated with 267 GO terms (10%) for Cellular Components (CC) and 71,458 were associated with 515 GO terms (20%) for Molecular Functions (MF) , accounting for a total of 2,602 GO terms (Additional file 6). These proportions are similar to those in the GOA database: 25,725 (66%), 3,474 (9%) and 9,685 (25%) GO terms for BP, CC and MF, respectively.
Finally, it would be tempting to highlight the differences in functional classes between the OCV3-91 K sequences associated with GO terms and At GO annotations. However, we believe that such an analysis would be misleading, given the complex nature of any transcript catalog. We will wait until the generation of an oak gene model before carrying out such analyses, to avoid making erroneous predictions  [30]. Comparative genomics and the detection of conserved orthologous sequences common to peach The rosids comprise two major clades of orders  [31] : the fabids (i. e. eurosids I) and the malvids (i. e. eurosids II). Quercus species are fabids and are relatively closely related to Prunus (Figure  3A ). BlastX alignment of the OCV3-91 k contigs with the malvid (Arabidopsis, Eucalyptus), fabid (peach, poplar) and basal rosid (grape) gene models (Table  2 ) demonstrated that evolutionary relationships (based on the Ks metric, see the Methods section) between oak and fabid representatives (red distribution in Figure  3B ) were stronger than those between oak and malvid representatives (blue distribution in Figure  3B ).
Identification of transcripts differentially expressed across a panel of tissues An inventory of the numbers of contigs present in several oak tissues or specific to a given tissue revealed that RO (roots harvested from six-month-old seedlings after exposure to cold, heat, high CO 2 concentration, water stress and hypoxia) made the greatest contribution to the OCV3-91 k contigs, with 78,502 (86. 47%) matching contigs (Additional file 9). Adding a second tissue (endodB) to the RO dataset further increased the number of contigs by 6. 7% (6,084 new contigs). Successive additional inclusions of LE, CA, swB and XY increased the number of contigs by 2. 43% (2,202 contigs), 1. 01% (919 contigs), 0. 57% (521 contigs) and 0. 31% (283 contigs), respectively. We found that 56,672 contigs (62. 42%) contained reads from all six tissues.
43%) and 1,632 (0. 85%) differentially expressed contigs, respectively (FDR 5%). Only 23 contigs were identified by all three methods (Additional file 14) and 862 contigs were identified by at least two statistical methods (Figure  5  and Additional file 15). In total, 663 of these 862 contigs belonged to OCV3-91 k. GO term enrichment analysis was performed for these 663 differentially expressed contigs, with Pathway Studio software. Both the Gene and Plant Ontology databases were used. Among the 663 contigs, 340 were found to be upregulated in ecodormant buds (146 "specifically" at this  The most differentially expressed GO terms identified in the enrichment analysis are indicated in the first column for each dormancy stage. The localization of the genes in the functional network is indicated in the last column when available.
phenological stage and 194 were more strongly expressed in ecodB than in swB, Additional file 16). For this first set of genes, enrichment analysis for pathways and groups (EAPG, p-value < 0. 05) yielded 202, 71 and 137 hits for the biological process (BP), cellular component (CC) and molecular function (MF) categories of the Gene Ontology database, respectively (Additional file 16). The five BP terms displaying the highest level of enrichment corresponded to "ribosome biogenesis", "translation", "response to cold", "response to water deprivation" and "response to cadmium ion". Similar results were reported by Ueno et al. in 2013  [32]  for 454 sequencing on eco-dormant buds. In this previous investigation, a forcing test was used to determine the dormancy status of the buds. No such test was carried out in our study.
The similarity in BP terms between the two studies suggests that the buds analyzed here were also in the ecodormancy phase. The first five MF groups related to "structural constituent of ribosome", "transmembrane receptor activity", "calmodulin binding", "translation factor activity", "nucleic acid binding" and "nucleoside-triphosphate activity". Finally, 86 significant hits (EAPG, p < 0. 05) were obtained against the Plant Ontology database, with the ontologies displaying the highest levels of differential expression corresponding to "guard cell", "stamen", "LP. 08 eight leaves visible", "LP. 06 six leaves visible" and "male gametophyte". A total of 323 contigs were upregulated in swelling buds, 44 being "specific" to this phenological stage and 279 being more strongly expressed in swB than in ecodB (Additional file 16).
For this second set of genes, 192, 45 and 148 EAPG hits (p value < 0. 05) were obtained with the BP, CC and MF terms of the Gene Ontology database, respectively. The five BP categories displaying the highest level of enrichment were "DNAdependent DNA replication initiation", "regulation of cell cycle", "DNA unwinding involved in replication", "cell cycle and microtubule-based movement activity". The MF categories displaying the highest level of enrichment were "carboxylesterase activity", "lipid binding", "microtubule motor activity", "DNA-dependent ATPase activity" and "cyclin-dependent protein kinase regulator activity". Finally, 102 significant hits (EAPG; p < 0. 05) were obtained against the Plant Ontology database, the BP categories displaying the highest level of enrichment being "IL.
De novo transcript assembly A schematic diagram of data processing for this study is shown in Figure  1. Short reads and long reads were subjected to different bioinformatic treatments, as described below. Assembly of Illumina reads from putative full-length cDNAs (set #3) A total of 17,196,106 Illumina paired-end reads bearing no similarity to vector sequences were assembled with Velvet V1. 1. 03 [74]  and kmers 37, 41, 45, 49, 53, 57 and 61. A meta-assembly of the resulting contigs of more than 100 bp in length was then generated with TGICL V2. 1  [75]. In total, 4,359 contigs were generated from the 6,571 cDNA clones initially amplified, and these contigs were subsequently cleaned up, with the removal of the remaining vector sequences with crossmatch (-minmatch 10 -minscore 15). Pre-assembly of long reads (sets #1, #2A and #4) We used MIRA V3.
4. 0  [76, 77]  to assemble 75,957 Sanger sequences, 2,790,004 Roche 454 reads and the de novo Illumina pre-assembly of 4,359 contigs. Contigs of less than 100 bp in length were filtered out. The CD-hit-EST V4. 5. 4 clustering algorithm  [78, 79]  was used to reduce redundancy within this long-read pre-assembly (sequence identity threshold 0. 95; word length 8). BLAT V34 was then used to validate this assembly, by mapping the initial Sanger and Roche-454 reads onto the long-read contigs. The minimum identity threshold was set to 98%. Pre-assembly of short reads (sets #2B and #5) The de novo assembly of the whole dataset was timeconsuming due to memory issues, so we used Diginorm (Digital normalization with khmer,  [80] ) to normalize the raw data digitally. This process greatly decreases the size of shotgun data sets and the memory and time requirements for de novo sequence assembly, with no significant impact on the contigs generated.
Diginorm was used to eliminate redundant reads. The coverage of each read was estimated (kmer-based approach) and reads with a coverage of less than 20 x were retained. Reads were assembled with Velvet V1. 2. 07 and Oases V0. 2. 8, using kmer 51. Potential fungal sequence contamination was identified by aligning the contigs with the sequences in the NCBI GenBank non-redundant protein sequence database (release 21/11/2012) with Blastx V2. 2. 15 (e-value cutoff 1e -04 ). Redundancy was reduced with CD-hit-EST (sequence identify threshold 0. 95; word length 8).
Functional annotation and categorization of the oak proteome by comparative genomics We compared the 192,097 oak contigs (referred to as OCV3-192 k) with six protein datasets, including Swissprot (release 02-2013)  [81]  and five plant proteomes: Prunus persica V1. 0 (27,864 proteins,  [82] ), Populus trichocarpa V2. 0 (40,668 proteins,  [83] ), Vitis vinifera V1. 0 (26,346 proteins,  [84] ), Eucalyptus grandis V1. 1  (36, 376  proteins,  [85] ), Arabidopsis thaliana V9. 0 (27,416 proteins,  [86] ). We used the BlastX program implemented in the blast + tool  [87]. For each database, alignments with a score greater than 300 (BLOSUM62, gapo = 10, gape = 1, e-value = 1e10 -5 ) were retained and the best alignment was used to identify the probable open reading frame to be considered for subsequent analysis.
On the basis of these criteria, 90,786 oak transcripts (OCV3-91 k) were retained. We established a first set of Gene Ontology (GO) terms  [88]  based on the best hit with Swissprot and the At proteome. We retrieved the GO terms associated with Swissprot and TAIR best hits from the Gene Ontology Annotation (GOA) project  [89]. A second set of GO terms was associated with OCV3-91 K contigs by comparison of the 90,786 sequences with the Pfam V27. 0 protein family database, using InterProScan V4. 8  [90, 91]. The GO terms were mapped onto plant GOslim terms with Blast2GO software  [92]. The ontology level was set to 2. Due to the computational limitations of Blast2GO software, we retained only GO terms associated with at least 100 contigs. Identification of orthologous gene pairs between Quercus and malvids/fabids: inference of the timing of speciation OCV3-91 k was aligned (BlastX, best match, e-value = 1e -10 ) with gene models for Prunus persica, Populus trichocarpa, Vitis vinifera, Eucalyptus grandis and Arabidopsis thaliana.
Acknowledgments We thank  J. Descat  for assistance with the herbivory treatment and  I. Van Halder  for providing the caterpillars, ML  Desprez-Loustau ,  C Robin  and  T Decourcelle  for carrying out the interaction experiment with gypsy moth, powdery mildew and Phytophtora,  C. Hubert  for sequencing the putative full-length cDNA clones at the  Genome & Transcriptome Facility of Bordeaux. This work was supported by the  ANR   GENOAK  project ( 2011 BSV6 009 01 , " Sequencing of the oak genome and identification of genes that matter for forest tree adaptation ") and the  European Commission  under the  FP6 program  ( FP6-2004-GLOBAL-3 ,  Network of Excellence EVOLTREE "Evolution of Trees as drivers of Terrestrial Biodiversity ",  N°016322 ). The Data provided by FB, MT, HS and LF were generated in the TrophinOak Project (http://www.
Sequence processing Sequences from the putative "full-length" cDNA-enriched library (set #3) After base-calling with Phred [71], we eliminated vector and adapter sequences with cross_match (http://www. phrap. org/phredphrap/general. html), with the following parameters: -minmatch 10 -minscore 15. The vector database contained five vector sequences: pBluescriptSK (-) (X52324. 1), a phagemid excised from lambda ZAP, pCR4-TOPO (Invitrogen, Carlsbad, CA, USA), pDNR- LIB, PDONR222. T, pGM-T_Easy. Low-complexity re- gions (mononucleotide repeats, PolyA) were then masked with RepeatMasker [72]. Using cross_match (-minmatch 10 -minscore 25), we then eliminated con- taminants by comparison with several sequence data- bases, including Univec, and databases for the budding yeast and E. coli genomes. Valid sequences, with a PHRED-score of more than 20 over at least 100 bp lengths (to exclude potentially uninformative sequences) were retained for further analysis.
Sanger and 454 sequences (sets #1, #2A and #4) All available Sanger ESTs were retrieved from the SURF database (http://genotoul-contigbrowser. tou- louse. inra. fr:9092/Quercus_robur) and trimmed with Seqtrim 0. 110 [73] to remove the library-specific clon- ing vector, It was then chemically fragmented and converted into single-stranded cDNA by random hexamer priming. The second strand was then generated to create double-stranded cDNAs. Paired-end libraries were prepared according to the Illumina protocol (TruSeq Illumina DNA sample prep kit, Illumina, San Diego, CA, USA). Briefly, fragments were end-repaired, 3'-adenylated, and ligated to Illumina.
Center of concrete core (m = M 2 ) Finally, for the concrete core central region, the next expressions are used: 2 2 2 4 8 2 2 2 M c M c M V           (12)         j M j M j M c j M c w w j M T T k k V 2 2 2 2 2 1 1 2            (13) This thermal analysis procedure was implemented in Matlab and it represents the first step of the fiber beam model developed by the authors for simulating the fire response of CFT columns. The description of the fiber beam model and its validation against experimental tests was presented in a previous publication  [12]. The model proved to give very accurate times of fire resistance and to reproduce precisely the whole fire response of CFT columns along time.
VALIDATION The model presented has been validated by contrasting its calculated crosssectional temperatures with experimental data. For this purpose, experimental results from tests carried out by the authors were used but also data from other experimental programs reported in the literature were employed. Ibañez C, Aguado JV, Romero ML, Espinos A, Hospitaler A. Fire design method for concrete filled tubular columns based on equivalent concrete core cross-section. Fire Safety Journal. 2015; 78:10-23. doi: 10. 1016/j. firesaf. 2015. 07. 009 14.
EXPERIMENTAL TESTS FOR VALIDATION In order to validate the thermal model, data from two experimental campaigns were used. On the one hand, results from tests carried out by the authors and reported in previous works  [13]   [14]  were employed. All the CFT columns were tested at AIDICO (Instituto Tecnológico de la Construcción) in Valencia, Spain. The analyzed specimens comprised columns filled with normal and high strength concrete of different type infill: plain, bar reinforced and steel fiber reinforced concrete, and, in all cases, the aggregates were calcareous. These specimens were heated following the standard ISO-834 curve  [10]   [11]. The main characteristics of these columns can be found in Table  1. On the other hand, data from tests performed by Lie and Chabot  [15]  were also used so that the validation process was not limited to comparison with own experimental results.
EQUATIONS FOR CROSS-SECTIONAL TEMPERATURE FIELD An extensive thermal parametric analysis, based on the one presented by the authors  [8]  in previous work, was carried out in order to generate data enough to obtain an accurate formulation by means of a nonlinear regression analysis. This parametric analysis covered section external diameters ranging from 139 to 508 mm combined with the minimum and maximum commercially available values of steel tube thicknesses for each case. The geometry of the analyzed composite sections can be found in Table  3. For each specimen, the analysis lasted 180 min so all the standard fire classes were covered (form R30 to R120) and data of the cross-sectional temperature distribution was registered every minute. The concrete core of the CFT columns included in the thermal parametric analysis was considered to be normal strength concrete with a moisture content of 3% for all the cases.
Numerical results generated through an extensive thermomechanical parametric analysis were used to carry out a multiple nonlinear regression analysis and, as a result, the expression for the buckling correction factor was built. The equations for temperature calculation as well as the one for obtaining the buckling fire resistance were assessed following the guidelines included in CEN-Horizontal Group Fire for checking the accuracy of simplified methods. The simple method predictions were compared to experimental data and they showed to be slightly conservative. In general, it can be said that the method produces satisfactory values of the fire resistance.
Background: Estimations of survival rates are diverse and the choice of the appropriate method depends on the context. Given the increasing interest in multiple imputation methods, we explored the interest of a multiple imputation approach in the estimation of cause-specific survival, when a subset of causes of death was observed. Methods: By using European Randomized Study of Screening for Prostate Cancer (ERSPC), 20 multiply imputed datasets were created and analyzed with a Multivariate Imputation by Chained Equation (MICE) algorithm. Then, cause-specific survival was estimated on each dataset with two methods: Kaplan-Meier and competing risks. The two pooled cause-specific survival and confidence intervals were obtained using Rubin's rules after complementary log-log transformation. Net survival was estimated using Pohar-Perme's estimator and was compared to pooled cause-specific survival.
The use of multiple imputation in survival analysis is now widespread. However, Goetghebeur and Ryan  [7] , Andersen et al. [8] , Lu and Tsiatis  [9] , Gao and Tsiatis  [10] , Lu and Liang  [11] , Bakoyannis et al. [12]  and Sen et al. [13]  all proposed methods for estimating regression parameters, but not for estimating survival function. Only a few authors have proposed methods to estimate cumulative incidence, see for example Lee et al. [14, 15] , Nicolaie et al. [16]  or Moreno-Betancur and Latouche  [17]. Our aim was to compare three measures: • the results of Pohar-Perme's net survival based on the database without causes of death • the pooled cause-specific survival of Kaplan-Meier  [18]  after multiple imputation, when censoring other-cause deaths • the pooled cause-specific cumulative incidence estimator after multiple imputation, accounting for deaths due to other causes as competing risks.
ERSPC database This study included 2844 men, aged between 56 and 78 years old, presenting with a prostate cancer and included in the ERSPC  [19] [20] [21]  from 2003 to 2011, in the Hérault department, France. The clinical variables were completed from the Hérault cancer register, and the causes of death from the ERSPC. The following clinical variables were recorded: PSA level at diagnosis (ng/ml), clinical staging (cT,cN,cM) based on tumour size, regional lymph nodes and metastasis, type of first treatment, Gleason score, PSA level post treatment (ng/ml) and pathological staging (pT,pN,pM). Comorbidities and residual tumour after surgery were not taken into account as these data had not been collected for the whole study. Clinical tumour stages (cTstage) were categorized as 1a,1b,1c for a tumour present but not detectable clinically or with imaging, 2a,2b,2c for a circumscribed tumour in the prostate tissue and stages 3a, 3b and 4 when the tumour had invaded the capsule or other nearby structures.
Other patients with observed cause of death (106 patients) were considered dying of other causes. Consequently there are 161 patients (50 %) with cause of death missing. Follow-up was performed up to June 30, 2013 (end point date). The duration of follow-up was defined as the time elapsed between diagnosis and death if the patient had died, and the date of last news if the patient was lost from follow-up, and the censoring date otherwise. Fortysix patients were excluded because their dates of last news was the same as the date of diagnosis. The shortest follow-up time was 1 day, and the longest almost 10 years (3624 days). The mean follow-up time was 1822 days (almost 5 years) and the median 1853 days (slightly more than 5 years). Data used in this study are publicly available and approved by two ethical committees for studies using human subjects (National Data Processing Consultative Committee for Medical Research-CCTIRS-and by the Commission Nationale Informatique et Libertés-CNIL) which provided approval to access at population-based cancer, ERSPC and RNIPP data in Hérault and advocates that all medical information are confidential and anonymous (declaration n°900075).
MAR hypothesis Missing data mechanism, which is the process that governs the probability of being missing, can be classified into three categories  [23] : From these, the MAR assumption is a starting point in multiple imputation since MICE performs well when it holds. We examined all the variables to be imputed and explained the reason of missingness. As MAR hypothesis is essential, it is important to assess it, especially for the cause of death variable that has 50 % of missing values. • Even if they are not widely used and their practical value is unclear, Enders  [24]  proposed 2 tests to assess MCAR versus MAR. Note that it is impossible to test MNAR versus MAR because one would need missing information. The first method, proposed by Dixon  [25] , uses a series of independent t-tests to compare missing data subgroups, and the second one, by Little  [26] , uses a multivariate extension of the t-test approach.