dataesr/scientific-paragraphs-categorization huggingface dataset:
Component Amount Crude fibre (%) 1 was computed from data that were recorded in previous experiments on the same line with animals raised in the same season. Actual feed restriction was on average 75 and 74. 1% of the ad libitum intake in BS and SS kits, respectively. Individual BW and total FI of kits in the same cage were weekly recorded after weaning (32 days). Average daily gain for a specific week was calculated as the difference in BW at the beginning and end of the week divided by the number of days elapsed (i. e. , 7 ± 1 day). On control days, food was supplied after the kits were weighed. Information on sick animals was recorded. For each week, groups with animals that presented symptoms of an infectious disease, which was not caused a priori by antagonist behaviour (e. g. epizootic rabbit enteropathy, ERE, or respiratory problems), were discarded from the analyses, so that group size was always equal to 8.
The average number of weeks with records per cage was 3. 45 for animals on F and 3. 41 for animals on R. The distribution of the data for each FR, BW class and week, after data filtering, is in Table  2. The final set of data for analysis included information on 6264 individuals born from 1303 litters housed in 783 cages. The pedigree included information on 7701 individuals, tracing back 5 generations from that corresponding to the animals of the experiment. The average relatedness coefficient within a cage was equal to 0. 16.
Models and statistical analyses Preliminary analyses of the data were performed using mixed linear models that were implemented with "lme4" and "lsmeans" packages of the R software  [11]. Weekly records of BW, ADG and their coefficient of variation (CV ) within a cage were analysed. Analysis of BW and ADG included the random effects of animal, cage and litter and the systematic effects of FR (two levels: F and R), week of fattening (four levels), body weight at weaning (two levels: BS and SS), batch (14 levels), parity order (four levels: 1, 2, 3, >3), number of kits born alive in the litter (seven levels: <6, 6, 7, 8, 9, 10, >10) and the interaction between week and all other systematic effects in the final model. Triple interactions between all systematic effects were initially included but finally discarded because they were not significant.
I is the identity matrix. N l , N g and N p are the number of litters, groups and animals with records, respectively. The residual variance matrix was defined as R = σ 2 eF 0 0 σ 2 eR , where σ 2 eF and σ 2 eR are the residual variances for animals on F and R, respectively. Flat priors were used for systematic effects and variance components of the animal mixed models. The marginal posterior distributions of all the unknowns were approximated by Gibbs sampling  [13]  using the gibbs2f90 software  [14]. Two sampling processes of 1,500,000 iterations each were run. The first 100,000 iterations were discarded as burn-in. One sample of the parameters of interest was saved every 100 iterations. The sampling variance of the G 1 = σ 2 dF σ dF ,dR σ dR,dF σ 2 dR. G 2 =     σ 2 dF σ dF ,dR σ dF ,sF σ dF ,sR σ dR,dF σ 2 dR σ dR,sF σ dR,sR σ sF ,dF σ sF ,dR σ 2 sF σ sF ,sR σ sR,dF σ sR,dR σ sR,sF σ 2 sR     , chains was obtained by computing Monte Carlo standard errors  [15].
Rotavirus gastroenteritis Hospitalisations for RVGE were obtained from the Echantillon Généraliste des Bénéficiaires (EGB), a representative sample (1/97th) from the national database in which both healthcare claims and hospitalisations are recorded  [26]. We selected all children under 5 years of age, hospitalised with a diagnosis of rotavirus enteritis (A080 code in the 10th revision of the International Classification of Diseases (ICD10)) occurring between January 2009 and December 2014. The most recent mortality rate in French children under 5 years of age due to RVGE was found in the WHO 2013 report on child rotavirus deaths by country  [14]. Vaccine efficacy against RVGE hospitalisations and its decrease with time (waning effect) was modelled using Vezikari's estimates  [27] [28] [29].
The parameters of these distributions were selected to correspond to published estimates for central values and confidence intervals. The calculations of B, R and BR ratio were iterated 20,000 times, allowing estimation of median and empirical 95% intervals, further referred to as 2. 5th and 97. 5th percentiles (2. 5th-97. 5th), for the estimators. To mimic the French context where the two vaccines are used, each iteration was performed as follows: once the baseline numbers of RVGE and intussusception were drawn, the benefit and the risk were calculated from a mixture of vaccinated cases (Rotarix and RotaTeq). The SAS 9. 4 software (SAS Institute Inc. Cary, North Carolina, US) was used to implement the model and perform all simulations.
Discussion We show that the BR ratio of rotavirus vaccination in France is 214 RVGE hospitalisations prevented for every additional intussusception hospitalisation, thereby suggesting that vaccine-prevented hospitalisations for RVGE far outweigh vaccine-induced hospitalisations for intussusceptions. Should the national vaccine coverage reach 92%, either with Rotarix or RotaTeq or a mixture of both, our model suggests that ca 10,400 hospitalisations for RVGE would be prevented and ca 50 cases of intussusception would be induced annually. Some assumptions were made to derive these estimates. Although the annual incidence of RVGE hospitalisations varies over time, we assumed it was constant and used a single average value. The incidence of hospitalisations for RVGE was estimated from the French hospital discharge part of the EGB database, where vaccinated and unvaccinated cases cannot be distinguished.
Regarding hospitalisations for RVGE, they were defined by the ICD10 code A080 only because there are no microbiological results available in the EGB database. Moreover, duplicates are possible but unlikely because in France, young children should be admitted to paediatric and not to general hospitals. Finally, the chosen vaccine-induced intussusception risk values were those of Carlin's work  [9]. For Rotarix, they are higher than the pooled values calculated by Stowe in a meta-analysis of six studies  [35] : 6. 76 vs 6. 03 in the first week after dose one and 2. 11 vs 1. 83 in the first week after dose two. Choosing smaller values would have increased the BR ratio estimate. The present model could be complicated in several ways. In each iteration, parameters were drawn from independent distributions although some correlation could have been present, for instance, that in a given child, the vaccine-induced RR of intussusception after the second or third dose would be positively correlated with the RR after the first dose.
(1. 77), σ = 0. 39 IS: intussusception; RR: relative risk; RVGE, rotavirus gastroenteritis; SD: standard deviation. a EGB (Echantillon Généraliste des Bénéficiaires): extraction of acute gastroenteritis admissions in infant before 5 years of age from the French hospital stays database. b The waning effects between first-and second-year efficacies were considered similar to Rotarix (i. e. a 5. 3% decrease after first and second dose, and a 7. 8% decrease after third dose [28] ) c Efficacy after second dose and its confidence interval were taken as average values between post-dose one and post-dose three results. noted as A(w), on the proportion of the population vaccinated by dose d at age w, v d (w), and on the RR of the adverse event in the t th week after dose d of vaccination, noted as RR d (t).
Based on observed data from the French hospital administrative database (EGB), 2009-2014 B. Based on observed data from the Epistudy registry, 2008-2012 0. 04 Hospitalisations for RVGE (1/week) 0. 000 0. 002 0. 004 0. 006 0. 008 0. 010 0. 012 0 50 100 150 200 250 Hospitalisations for intussusception (1/week) 0. 00 0. 01 0. 02 0. 03 0 10 20 30 40 50 EGB: Echantillon Généraliste des Bénéficiaires; RVGE: rotavirus gastroenteritis. The solid line in both figures depicts the fitted Gamma distribution.
Flight initiation distance and local population abundance The analyses reported here are based on extensive data on FIDs and abundance of each species in urban and rural habitat. These estimates were collected during the breeding seasons 2009-2010 in the 3 study areas  (D ıaz et al. 2013; Møller et al. 2012) , before measuring distances to human habitation. Hence, we assume that FIDs and abundances will have changed little, or similarly for all species, between 2010 and 2012-2015. In brief, when an individual bird had been located with a pair of binoculars, the observer moved at a normal walking speed toward the individual, while recording the number of steps. The distance at which the individual took flight was recorded as the FID after multiplying the number of steps by step length. If the individual was positioned in the vegetation, the height above ground was recorded to the nearest meter.
Species-specific life-history traits We extracted the mean species-specific values for the western Palearctic of several relevant population and life-history traits from the literature, as it was logistically impossible to obtain local data for most species. We used data reported in  Cramp and Perrins (1977-1994)  that are widely used in comparative analyses. Estimates of these traits are reported in Supplementary Material. Migration distance was estimated as the difference in latitude between the mean values of the northernmost and the southernmost breeding distribution and the mean values of the northernmost and the southernmost winter distribution, relying on information in  Cramp and Perrins (1977-1994)  and del  Hoyo et al. (1992 Hoyo et al. ( -2008)). Migration distance was subsequently estimated as the mean latitude during breeding minus the mean latitude during winter.
Body mass was recorded as the mean mass of males and females from the breeding season, as reported by  Cramp and Perrins (1977-1994). If more than one estimate was reported by that source, we used that with the largest sample size. We estimated breeding distributions of the species in the Western Palearctic from the electronic version of  Cramp and Perrins (1977-1994)  by importing these maps into Adobe Photoshop, separating summer, resident, and winter distributions. Next, we imported files containing single distribution patches into the program Image from NIH, and estimated the number of pixels occupied by summer and resident distributions reflecting breeding ranges. Finally, we converted the number of pixels to km 2 by estimating the area of 5 islands and peninsulas of known size: British Isles, Iceland, Svalbard, Novaya Zemlya, and the Iberian Peninsula, using the same map as a reference.
Thus, this approach controls for known confounding variables that have evolved after divergence between pairs of closely related species, but also for unknown confounding variables simply because pairs of closely related species by definition are similar in most respects. This pairwise comparison is particularly powerful when analyzing large datasets, because it relies on the assumption that interspecific competition should be the strongest between closely related species due to the largest share of phenotypic traits determining their ecological niches  (Godoy et al. 2014). We further considered the strength of interspecific competition by weighting paired data by the inverse of the phylogenetic distance among species within pairs. The duration of divergence was estimated from the consensus tree based on date in  Jetz et al.
Gene Expression Analyses Total RNA was extracted from pools of whole body specimens (50 to 3 individuals per sample at 6, 10, 21, and 41 dph depending on fish size) using TRIzol reagent (Invitrogen R , San Diego, CA, USA) following manufacturer's protocol. RNA was quantified using a Gene-Quant spectrophotometer (Amersham Biosciences) and purity established by the absorbance ratio 260/280 nm. The integrity of the RNA was examined by gel electrophoresis. Total RNA (1 µg) was retrotranscribed using the QuantiTect Reverse Transcription Kit (Qiagen R ); electrophoresis using a 1. 2% agarose gel was run to assess the specificity of RT-PCR product. Real-time qPCR was performed using an ABI PRISM 7300 (Applied Biosystems). For each gene, a species-specific Taqman assay was designed (Applied Biosystems) using the sequences acquired from the GenBank database (Supplementary Table  1 ).
Statistical Analyses Results are given as mean and standard deviation. Data expressed as percentage (survival, incidence of skeletal deformities, eye migration success, and mineralization degree) were previously arcsin(x 1/2 )-transformed. All data were checked for normality (Kolmogorov-Smirnov test) and homoscedasticity of variance (Bartlett's test) and then compared by means of One Way ANOVA for multiple comparisons. When significant differences were detected, Tukey multiple-comparison test was used to detect differences among experimental groups. The level of significant difference was set at P < 0. 05. All the statistical analyses were conducted using GraphPad Prism 5. 0 (GraphPad Software, Inc. ).
The interests of establishing such coordination on this scale therefore seemed just as important, if not more so, than the acquisition of data on a particular species  (Dutartre et al. 2012a ). Furthermore, knowledge transfer between those engaged in research, policy and management is recognised as a key issue for IAS management in Europe  (Caffrey et al. 2014)  and at the international level  (Lucy et al. 2016). In this context and in order to meet those needs, a French national working group on biological invasions in aquatic environments (IBMA) was created in 2009, with the aim to develop a general approach to aquatic IAS management in metropolitan France.
Such platforms are available at different geographical scales: for example, the Global Invasive Species Database (GISD) (http://www. iucngisd. org), developed and managed by the Invasive Species Specialist Group (ISSG) of the IUCN, the Invasive Species Compendium (ISC), managed by CAB International (http://www. cabi. org/isc/), the Delivering Alien Invasive Species Inventories for Europe database (DAISIE) (http:// www. europe-aliens. org) funded by the sixth framework programme of the European Commission, or, at a national scale, the Great-Britain Non-native Species Secretariat information portal (GB NNSS) (http:// www. nonnativespecies. org) and the Belgian Forum on Invasive Species (BFIS) (http://ias. biodiversity. be/). However, most information available on those platforms are delivered in English and this constitutes a real obstacle for French natural area managers.
In France, the IUCN French committee's initiative on IAS in the French overseas territories has developed an information database (http://www. especes-envahi ssantes-outremer. fr/) but information on IAS in aquatic environments in continental France remained scattered in many documents and websites. In view of this context, to meet those needs and to improve managers' access to scientific information, in 2012 the IBMA working group created an online resource centre on IAS (http://www. gt-ibma. eu). The working group gathered all available and relevant tools and resources and made them available online: feedbacks from management efforts, information databases, management guides and best practices, dynamic mapping, international, European, national, local strategies and legislation, species alerts, and current events.
Since its creation, the platform has been improved and expanded upon, offering new webpages, resources and features. Its visitor rate is continuously rising, with a number of unique visitors multiplied by eight in three years, and the number of downloaded documents has been multiplied by four during the 2014-2016 period (from 4,231 in 2014 to 17,884 in 2016) (Figure  2 ). These growing visitation rates highlight the usefulness of the platform and its importance at the national level. In order to centralise, structure, and make available information on differing IAS management options, in 2016 the working group created an online information database on more than 450 introduced species in aquatic environments. Inspired by the existing international and national databases on IAS (GISD, DAISIE, ISC, GB NNSS, etc.
) and drawing on the experience of the database system developed for the French overseas territories by the IUCN French committee, the IBMA database provides for each species access to documented management techniques, introduction pathways, assessed impacts and links to distribution maps. Resources such as feedbacks from management efforts, photo galleries, fact sheets, bibliography and legislation are openly accessible. The database provides access to other national or regional platforms on biodiversity (for instance, to the National Inventory of the Natural Heritage (INPN) (https://inpn. mnhn. fr), the Information System on Flora (SI FLORE) (http://siflore. fcbn. fr/) and to international and European databases on IAS such as ISSG-GISD, ISC-CABI, DAISIE, the Belgian Wallonia Biodiversity platform (http://biodiversite.
wallonie. be/fr/invasives. html) or the GB NSSS. The database is updated as often as possible, for instance when new information on management is available or when new species are mentioned in continental France. Newsletters are an important tool to disseminate research results  (Matzek et al. 2014; Bayliss et al. 2013). It is a way to engage managers, and due to the summarised format of the information being disseminated managers can more easily allocate time to read a newsletter and hence keep up with latest research and news  (Martin et al. 2012 ). Since 2014, as requested by the members of the IBMA working group, a newsletter is edited every two months and sent to more than 850 subscribers. The newsletter summarises current activities on IAS at different geographical scales. Particular research subjects such as biological control, biosecurity, species alerts, and innovative management techniques are regularly explored in technical dossiers.
France has not been well represented among the international community of IAS management. For example, no French network or initiative on IAS was identified as a potential contributor to the INVASIVESNET initiative, a new international association for knowledge and open data on IAS, launched in 2016  (Lucy et al. 2016). Until now, this was due to a lack of a national coordination, mostly exclusive French-written papers on local management actions and no identified national internet platform. The IBMA working group is now trying to catch up with those initiatives and has developed a functional internet platform and information database. It has also translated its main productions into English to facilitate their transfer to other countries. With a view to exchanging information on a wider scale, the IBMA working group wishes to participate in different networks and initiatives at a European scale, to trigger regional cooperation and share best practices, information and knowledge.
New connections and networks at the European scale are created by attending international conferences and presenting the working group. New projects, such as crossborders initiatives on feedbacks from management efforts, should be carried out and feed into existing European networks on IAS management. At a broader scale, the working group could also become a future member of INVASIVESNET. Information from the community of practitioners formed by the IBMA working group could feed this international "network of networks" and the working group could benefit from the open data publishing that will result from INVASIVESNET.
Acknowledgements We would like to thank all the members of the IBMA working group, who greatly contribute to its success and development, by submitting new and ambitious project ideas, sharing information and knowledge for all, providing articles for the newsletter, species alerts, contributions to the information database, and, last but not least, for the great enthusiasm, dynamism and support they have shown since the creation of the working group. We would also like to warmly thank the FINS II organisation team and committee who have allowed us to present our work during the FINS II conference in Croatia, Zagreb, July  11-14 2016. We thank the reviewers for their constructive and helpful suggestions that have greatly improved the manuscript. We also wish to thank the ONEMA and the  French Biodiversity Agency  for funding the coordination team of the IBMA working group and its activities.
23 rapes (Vitis vinifera L. ) are amongst the world's major fruit crops and are highly valued for fresh fruit consumption and winemaking. The grapevine genome  24  provides a strong foundation for elucidating the molecular genetics involved in grapevine physiology and response to environment. Specifically, seminal studies involving large-scale gene expression profiling have revealed important mechanisms and biomarkers critical for grapevine development across organs/tissues  25, 26  and berry phenotypic plasticity (e. g. genotype Â environment interactions). 27 The availability of the grapevine genome and the rapid accumulation of publicly available grapevine whole-genome microarray and RNA-seq datasets provide the raw material necessary for GCN and CRE analyses. To date, several studies have utilized GCN and CRE analyses in revealing biologically relevant target genes of grapevine TFs  [28] [29] [30]  and/or providing clues into the regulatory relationships of TFs in key metabolic and ripening pathways.
31, 32 However, to date no study has characterized grapevine promoter architecture and identified putative CRE regulatory modules at a genome-wide scale. In this study, the distribution and organization of promoter CREs and their properties were analysed for all currently predicted protein-coding genes in grapevine. Further insights into the biological role(s) of genes containing these CREs were achieved through analysis of enriched plant biological pathways. Meta-analysis of next-generation sequencing (RNA-seq) datasets and the grapevine tissue developmental atlas revealed the importance of many CREs in stress and developmental regulation. A bottom-up strategy was adopted to identify regulatory modules potentially driven by CREs in both stress-and development-specific GCNs. We apply a robust approach by integrating different layers of information-promoter architecture, gene expression, and GCNs-to identify the cisregulatory code during environment stress, growth, and/or development in grapevine.
Discovery of known plant CREs in grapevine promoters Candidate plant CREs, were compiled from two plant promoter databases, namely AGRIS  4  and PLACE,  3  and from protein-binding microarray inferred CREs of 25 Arabidopsis TF families. 5 A total of 559 non-redundant CREs were retained for subsequent analysis. The promoters of the grapevine genes were downloaded from EnsemblPlants using Biomart (http://plants. ensembl. org/index. html; 1 March 2016, date last accessed). Sequences between -1 to -1,000 bp upstream of each gene TSS containing < 10% N sequences were deemed as candidate promoter sequence of each gene. All 559 non-redundant CREs were scanned for exact pattern match (no mismatch) across 29,839 promoters on both þ and -strands, and indexed for the number of occurrence, strand, and position information.
Compilation of transcriptome datasets, differential expression (DE), and comparative gene expression analysis Two different compilations of databases were made: a stress-related compendia, which was mainly derived from next-generation sequencing (RNA-seq) datasets publicly available from NCBI Sequence Read Archive (http://www. ncbi. nlm. nih. gov/sra; last accessed 01/03/ 2016), and a grapevine tissue developmental series (atlas), based on the NimbleGen Grape Whole-genome microarray platform. For RNA-seq datasets, quality control of raw single-and pair-end FASTQ reads were performed with Trimmomatic v0. 36,  33  ensuring all reads maintained a minimum Q score of 20 and a length of 40. Bowtie2 v2. 2. 7  34  was used with default parameters for read alignments using the 12Â grapevine reference genome PN40024.