dataesr/scientific-paragraphs-categorization huggingface dataset:
Robustness Tests Two types of robustness of the QR smoothing method were tested. The first was a test of robustness to diet changes using data from cows that change between indoor TMR feeding and grazing, assuming that a diet change to or from grass would cause quite a big gut-fill change, but that EBW would not change unless one of the diets lacked energy. The second was a test of the robustness to variation in data noisiness using data from different farms. Diet Change Effect. Data from the SRUC Crichton Royal Farm (Dumfries, UK) with 2 genetic lines and 2 feed types were used; this data set is referred to as SRUC data. Genetic line S was selected for high milk merit; genetic line C was standard merit. Cow diet type was either high forage, that is, grazing from mid spring to early autumn and fed on TMR when housed the rest of the year (seasonally grazing, SG), or low forage, meaning permanently housed (PH), and was previously been described by  Randall et al.
(2015). This design allowed us to use the PH cows as a control group in comparison with the SG cows that experienced a gradual diet change from TMR to grass in the spring and vice versa in the autumn. For SG cows, the TMR that was fed when they were housed had a NDF content of 437 g/kg of DM and a ME content of 10. 8 MJ/kg of DM. Cows were milked 3 times daily and weighed after each milking. The BCS was assessed once per week. Cows calved continuously throughout the year. Data from January 1, 2009, to November 30, 2010, were obtained. During this period there were 2 gradual grass turn-out and 2 grass turn-in events. From these data, we excluded 5 d, because mean BW across cows for either lactation 1, 2, or 3+ was more than 50 kg from a smoothed mean [using the LOESS function in R (R Development Core  Team, 2015) ].
These aberrant days occurred during winter and were likely due to cold weather causing malfunction of the weighing scale. Only weight observations between 1 and 305 DIM were used. Within a lactation, outliers more than ±50 kg from the mean of the previous 2 observations were removed. This cleaning rule did not remove any observations 10 d after diet change. After this cleaning, data contained 237 lactations with a varying number of weight observations. Periods from 30 d before to 30 d after each grass event that had at least 60 weight observations and at least 60 d (out of 61 d in a period) were selected. The cleaning procedures left 192 periods originating from 157 lactations by 140 cows in the data set (i. e. , each cow contributed from 1 to 4 periods) containing a total of 31,622 observations.
e. , the PH cows gave the baseline trend against which the SG cows that changed between housed and grazed periods were evaluated). The random part of the model accounted for the fact that the nondiet design elements (merit and parity) would affect overall weight, which may have affected size of change in BW because gut-fill and energy requirements are proportional to BW. In this model, the dependent Y = diet + sub-period + sub-period × diet + cow × parity, [M1] where diet = (PH; SG), sub-period = (30 d before diet change; 30 d after diet change), and cow × parity was a random effect. Nonsignificant interactions were removed, leaving only significant interactions and main effects in the model. Farm Effect. The effect of farm on BW variation was tested using a data set of 1,592 lactations from 9 Danish commercial farms with Lely milking robots in which cows were weighed at each milking.
Calculating EB body Step by Step The description of going from live weight to EB body has different pathways depending on the data available, and on the purpose of the calculation. To calculate EB body , one needs to know the following: are BW measured before or after milking? If BCS is available, is it assessed frequently (i. e. , from an automated source of technology) or not? Further, one needs to know the purpose of calculating EB body because the smoothing approach will depend on the purpose (i. e. , if short-term or long-term trends is the focus, as mentioned above in the Meal-Related Gut-Fill Variation section). A flowchart and accompanying list of equations for doing this are given in Appendices A and B.
Sensitivity Analysis Residual Gut-Fill Variation. The fits of Equation  [1]  for the INRA and the Friggens data set are shown in Figure  1. For the INRA data, a = 0. 43, b = 0. 05, and c = 0. 54, and for the Friggens data, a = 0. 37, b = 0. 05, and c = 0. 63. The SD of the residuals was 18. 0 × 10 -3 and 9. 51 × 10 -3 for the INRA and Friggens data, respectively. Despite large differences in ration type (and location, and so on), there is a very strong similarity between the 2 time-trends in relative intake suggesting that a correction for RGF according to DIM would have a general applicability. Our previous RGF was a constant of 0. 26 kg/kg of LFEB, which we consider as representing the RGF once intake has stabilized in mid-lactation (i. e. , the asymptote). The difference between the exponential (dynamic) RGF method and the constant RGF method on EBW is shown by breed and parity on the DCRC data set in Figure  2.
ACKNOWLEDGMENTS We thank  Nicolaj I. Nielsen  ( SEGES Cattle, Denmark ) for useful discussions and for allowing us to use the AMS data and  Søren Højsgaard  ( Department of Mathematical Sciences, Aalborg University, Denmark ) for making the R-code for data smoothing available. We also thank  Maelkeafgiftsfonden  (the  Danish Milk Levy Foundation ) for funding this study, which was part of the  Danish  project " Vaegt på bedre fodereffektivitet " (More weight on increased feed efficiency). The SRUC receives financial support from the  Scottish government. Author contributions are as follows:  NCF  and VMT conceived the analysis; AF, NCF, MGGC, and MRW contributed with data; VMT performed the analysis; and VMT, MGGC, AF, MRW, and  NCF  wrote the paper.
Vector competence tests for chikungunya, dengue and zika viruses ARwP-M vector competence for CHIKV, DENV and ZIKV viruses was evaluated in comparison with ARwP Ae. albopictus to ascertain whether the introduction of the wMel Wolbachia infection may affect this biological trait. Viruses. CHIKV (CHIKV 06. 21; accession number AM258992) was isolated in 2005 from a newborn male from La Reunion presenting meningo-encephalitis symptoms  [63]. This strain belongs to the East-Central-South African (ECSA) lineage known to be better adapted to Ae. albopictus due to the E1-A226V mutation  [19, 20]  and this genotype was involved in the 2007 outbreak in Emilia-Romagna Region (Italy)  [64]. We assumed that the widespread of this CHIKV strain was a valid argument to chose it over others as more suitable to be involved in severe epidemics.
DENV (DENV-1 1806; accession number EU482591) was obtained in 2010 from an autochthonous case in Nice, France  [14]. ZIKV (ZIKV PE243; accession number KX197192) was isolated from a patient in Recife (Brazil) in 2015  [65]. Viral stocks were prepared after several passages of the isolate onto Ae. albopictus C6/36 cells for CHIKV and DENV, and Vero cells for ZIKV. Experimental infections and viral titrations. One-week-old mosquitoes were isolated in boxes (60 females/box) and starved for 24 h before infection. The blood meal was composed of two parts of washed rabbit erythrocytes, one part of the viral suspension and a phagostimulant (ATP) at 5 mM. The infectious blood-meal at a viral titer of 10 7 FFU/mL for CHIKV and DENV-1 and, 10 7 PFU/mL for ZIKV was placed in capsules (Hemotek, Lancashire, UK) wrapped with a piece of pork intestine maintained at 37˚C.
Data analysis Survival curves of the three different lines (ARwP, S ANG , and ARwP-M) were compared using Kaplan-Meier method and log-rank (Mantel-Cox) test. One-way repeated-measures ANOVA and Bonferroni mean separation were used to compare fecundity and egg hatch data between lines. Percent data was transformed to arcsin square root of proportions before the analysis. Normality of the experimental data was determined by the Shapiro-Wilk test. ANOVA was also used to compare the mean level of observed and expected CI in the male competitiveness trials. Difference between lines in infection rate (IR) dissemination efficiency (DE) and transmission efficiency (TE) were analyzed by the Fisher's exact test while Kruskal-Wallis test was used to compare the mean number of viral particles detected in bodies and saliva.
Transinfection results and vertical transmission More than 900 Ae. albopictus embryos were microinjected in total and 12 eggs were viable after the treatment and gave first instar larvae. Among obtained larvae, 8 emerged as adults, 4 of which were found infected with wMel Wolbachia. Two infected females were used to establish transinfected isofemale lines and one out of them transmitted the wMel infection to the progeny. All of the tested G 1 individuals were confirmed as positive for wMel Wolbachia and vertical transmission accuracy always approached 100% over the following generations with few exceptions only among male progeny (98. 89±1. 01% in mean) (Table  1 ). The obtained line was named ARwP-M. The confirmation of the transinfected Wolbachia strain was achieved by sequencing the wsp gene  [61]  to perform a comparison with published wMel wsp sequence (Accession Number: AF020064.
Acknowledgments We thank  Luis Teixeira  ( Instituto Gulbenkian de Ciência, Oeiras, Portugal ) for gently furnishing the D. melanogaster strain used as wMel Wolbachia donor during the microinjections. We thank  Marta Piscitelli  ( ENEA-Casaccia Research Centre, Division for Health Protection Technologies ) as responsible of the facility for the housing and care of the mice used for blood feeding. We also thank  Giuseppe Marzo  ( ENEA-Casaccia Research Centre, Division for Technologies and Facilities for Nuclear Fission and Nuclear Material Management ) for statistical advice and  Jason Cardone  for his help with language editing.
Acknowledgements The support of the  International Scientific Association for Probiotics and Prebiotics and CIFSRF/IDRC  Canada are appreciated. The discussion group also included  Serge Carrier ,  Nikhat Contractor ,  Eden Ephraim Gebreselassie ,  Annahita Ghessemi ,  Anu Kaukovirta-Norja ,  Tami Mackle , and  Jonas Faijerson Saljo.
Our biochemical in vitro data based on BLI measurements shows that the NFRe ectodomain does not bind chitopentaose, suggesting that NFRe might not be involved in chitin signalling. To test this hypothesis in planta we measured the induction of reactive oxygen species (ROS) in response to CO8 or CO4 in the nfre mutants and wild type. We found that wild type, nfre-1 and nfre-2 mutants produced comparable levels of ROS, indicating that NFRe is unlikely to be involved in chitin signalling (Figure  3 -figure  supplement 4 ). Together, these results show that NFRe represents an influential component of the epidermal Nod factor signalling in L. japonicus, promoting intracellular signalling that leads to optimal calcium spiking, activation of gene transcription and efficient nodule organogenesis on the expanding root system.
Phylogenetic tree and alignment Clustal Omega was used to prepare multiple sequence alignment for phylogenetic analysis. The region between 55 and 251 in this alignment was realignment to adjust the positions of CXC motif. This alignment was used for the phylogenetic analysis with Neighbor Joining. The distance was measured with Jukes-Cantor and the bootstrap was 1000 replicates. These alignment and phylogenetic analyses were performed in the CLC Main Workbench v7. 9. 1. The amino acid sequence of OsCERK1 (Os08g0538300-01) is available in The Rice Annotation Project Data Base (rap-db). The other sequences below are available in NCBI: AtCERK1 (NP_566689), NFR1 (CAE02590), NFRe (AB503681), LYS2 (AB503682), EPR3 (AB503683), LYS4 (AB503685), LYS5 (AB503686), LYS6 (AB503687), LYS7 (AB503688).
4, 500 mM NaCl, 0. 01% Tween20. Parallel background measurements using biosensors immobilized with free biotin were subtracted from R7A Nod factor and (GlcNAc)five curves to correct for unspecific binding. Sensorgrams were processed using Forte-Bio Data Analysis 7. 0 (Pall ForteBio). Equilibrium dissociation constants from steady-state analysis were calculated in GraphPad Prism 6 (GraphPad Software) by nonlinear regression using the response at equilibrium (Req) plotted against protein concentration.
Microscopic observations for promoter analysis using tYFPnls For promoter activity using tYFPnls, transformed roots were fixed with paraformaldehyde and cleared as described previously  (Warner et al. , 2014). The samples were analysed on a ZEISS confocal microscope LSM780. The whole root images were obtained using Z-stack and tail scan tools, the images of root surface were obtained using Z-stack tool. Final images were generated by Maximum Intensity Projection in ZEN software (ZEISS) or ImageJ.
Acknowledgements We would like to thank  Rebecca Fitchett  for proofreading the manuscript,  Terry Mun  for computational analysis support,  Mette Hofmann Asmussen  for technical assistance and  Finn Pedersen  for taking care of the plants. This work was supported by the  Danish National Research Foundation  grant no. DNRF79 , and by  The Bill and Melinda Gates Foundation , as part of Engineering the  Nitrogen Symbiosis for Africa.
Data analysis The non parametric Kruskal-Wallis test was used for analysis of entry rates. Proportional data (exophily, blood feeding, mortality) were analyzed using logistic regression. Each treatment was successively used as the reference class for multiple comparisons. One analysis has been run on the An. gambiae s. l. collected in the huts and another analysis has been run on all mosquitoes collected. Data of mortality and KD recorded with the bioassays were compared between treatment arms using a χ 2 test. Analysis were done using STATA 6 Software (Stata Corporation, College Station, TX, USA).
Measurement of Reactive Oxygen Intermediate Production Measurements of reactive oxygen species were performed on half 9-mm disks prepared with a cork-borer from leaves of 4-week-old plants using a method adapted from  Smith and Heese (2014). The day before the experiment, disks were placed in water in a 96 wells plate. The day of measurements, the water was replaced by 180 µL of 20 µg mL -1 horseradish peroxidase and 0. 2 µM luminol (Sigma-Aldrich). After 6 min, 20 µL of treatment solutions were added through injectors of a luminometer (TECAN Infinite R M1000, Männedorf, Switzerland). Luminescence was monitored for 2 h with relative light unit (RLU) measurements every 2 min. Data corresponded to a mean of four independent biological repetitions obtained from six foliar disks.
(2012). Reference gene BnELF5 was chosen for its stability in our conditions among seven genes tested using the GeNorm software  (Vandesompele et al. , 2002). F (Forward) and R (Reverse) primer sequences in 5 to 3 orientation were: F GGACTCATCGTTTGGTTCTTCTTTT R CGTTTTGGTTACGCTATGAACAGTC for BnWRKY33, F GAGATGTGGTTCCTCCACCA R ACTTGAGCCCTCGAA GAAGC for BnMPK3 and F GCCAATGTGTTACACC GAGATC R CCGAAATCCCCAAGCTTTAGA for BnMPK4;  (Lloyd et al. , 2014)   (Wang et al. , 2009) ; F TGGACCACCACCTAT GATGA R GCTGCGGATTCTCTTCTGAC for EFL5  (Yang et al. , 2014) ; F CTTGGTTTCGATGAC GCAGAGC R CGACGTTGGTGCTGGAGATTTAC for BnMYC2  (Aliakbari and Razi, 2013) ; F CACCGCTCCGTGAAGTTAGATA R ACCCCAAAAGCTCCTCAAGGTA for BnERF1  (Babula-Skowrońska et al. , 2015)  and F GATTTGAGAGCCGTGAGTGC R CATTGCTGCATTGGTCCACA for BnPR4.
Stomatal Aperture Measurements Foliar disks (7 mm in diameter) from 3 to 4-week-old plants were prepared with a cork-borer and immersed in RL or control solutions. After 3 h, disks were placed on glass slides and observed under a scanning confocal microscope (Carl Zeiss, Oberkochen, Germany). Auto-fluorescence of chlorophyll was observed using laser emissions at 638 and 488 nm. The images were optimized by scanning in XY mode while adjusting laser transmissivity and voltage of photomultiplier tubes. Then, in XYZ mode, Z-scans were performed. Three-dimensional reconstructions of images were done using ZEN 2. 3 SP1 software (Carl Zeiss). The width of the stomatal aperture was measured using ImageJ software 1. Aperture corresponded to the minor axis of an ellipse fitted on each stoma. A total of at least 140 stomata from 10 disks of 10 different plants per condition were used for average and standard error determinations.
Callose Deposition Colorations Ten-day-old to fifteen-day-old B. napus plants (two leaves stage) were sprayed with treatment solutions (1 mL for each plant). Leaves were harvested after 24 h and submerged into a 1/3 acetic acid/ethanol (v/v) solution for 12 h. Leaves were rinsed 30 min in 150 mM K 2 HPO 4 before being transferred for 12 h in a 0. 01% methyl blue (w/v) solution in the same buffer. Tainted leaves were embedded in 50% glycerol and observed with an epifluorescence microscope Leica DMI 6000B (Leica, Wetzlar, Germany) with a DAPI filter. Callose was quantified from photographs using ImageJ software as the number of callose corresponding pixels relative to the total number of pixels covering plant material. Contrast settings of the photographs were adjusted to obtain an optimal separation of the callose signal from the background signal.
Seedling Growth and Chlorophyll Content Measurements For in vitro growth inhibition tests, 2-day-old seedlings were transferred to petri dishes containing agar growth medium supplemented with RL or control solutions. Length measurements and studies of fresh weight were done on day 7. Values corresponded to the average of measurements from three independent experiments (24 plants per condition). For quantifying spray effect, 3-day-old in vitro grown seedlings were transferred to a hydroponic culture system (Araponics, Liege, Belgium) containing liquid growth medium. On day 4, the aerial part of seedlings was sprayed until flow with RL solution. Pictures were taken on day 10 to allow root length measurement with ImageJ software. Aerial part and roots were weighted separately as fresh material and lyophilised over night before being weighted as dry material.
ACKNOWLEDGMENTS We sincerely thank  Caroline Boulnois  ( Service d'Analyse Physicochimique, UTC, Compiègne ) for technical assistance in confocal microscopy. We gratefully acknowledge  Laurent Gutierrez  ( Centre de Ressources Régionales en Biologie Moléculaire, UPJV, Amiens ) for his welcoming access to molecular biology equipment and greenhouses. We finally thank  Stacy Johnson  and  Adrian Troncoso-Ponce  for their careful reading of the manuscript.
FUNDING This research was supported by the  Hauts de France Council and European Regional Development Fund , and was realized in the context of the  MAELIA  project. Noadya Monnier Ph. D. thesis was co-funded by  HdF Council and ERDF. Abdellatif Dahi  post doctoral position was funded through a grant in partnership with the SAS PIVERT, within the frame of the  French Institute for the Energy Transition (Institut pour la Transition Energétique (ITE) PIVERT  (www. institut-pivert. com)as part of the  Investments for the Future ("Investissements d'Avenir "), by the  French Government  under the reference  ANR-001-01. Work done in RIBP was supported by the EliDeRham grant from the  French Region Grand Est.
g. Stevens 1989; Rohde 1996; Fortes & Absalão 2004; Weiser et al. 2007; Veter et al. 2013). Here, we test for the existence of a Rapoport effect among fossil representatives of a marine group of invertebrates: the ammonites (Cephalopoda). Our study focuses on a c. three million-year-long interval in the Early Jurassic (the early Pliensbachian), and covers what was a vast tropical epicontinental sea at that time (present-day Europe, the Middle East and North Africa; Fig. 1 ). Such a case study presents several advantages. First, it uses one of the most highly resolved fossil datasets available, because the taxonomy of early Pliensbachian ammonites has been thoroughly revised up to the species level by  Dommergues et al. (2009)  and species occurrences are documented at the scale of the chronozone (i.
Third, assuming the validity of the climatic variability hypothesis for extant organisms, the dataset seems appropriate to test for the applicability of this hypothesis and the existence of a Rapoport effect in deep time, because the environmental and supposedly climatic contrast that characterized the two provinces is known to have influenced both ammonite dispersal  (Zaca€ ı et al. 2016)  and phylogenetic conservatism of species range size  (Zaca€ ı et al. 2017). Fourth, it extends the study of the Rapoport effect to the marine realm and to the fossil record, both of which have been largely neglected in previous studies (Table  1 ). Our goal is thus to test for the existence of a Rapoport effect in ammonites and for the applicability of the climatic variability hypothesis in a fossil marine environment, and to estimate the influence of the singular geographical and environmental configuration of the early Pliensbachian western Tethys on the latitudinal distribution of species range size.
2018, table S1). We analysed the relationship between species range size and latitude using generalized estimating equations (GEE; see  Morin & Chuine 2006 and Morin & Lechowicz 2011). Paradis & Claude (2002) proposed using GEE in the context of comparative analyses, the relatedness among observations (i. e. species) being computed from the phylogeny. These authors also underlined the ability of GEE to deal with phylogenies containing polychotomies, which is the case in our dataset (see  Zaca€ ı et al. 2018, fig. S1, and Hardy et al. 2012). Here, we fit a GEE model to explain variation in species latitudinal range size (response variable) depending on variation of species latitudinal midpoints (explanatory variable), while removing phylogenetic autocorrelation. Considering the continuous nature of the response variable, we used a Gaussian error distribution for this variable, with an identity link function in the GEE model.
2004a; Dera et al. 2009a Dera et al. , b, 2011b;; Price et al. 2016) , a sea-level rise (Hallam 2001) and more humid climatic conditions  (Dera et al. 2009b). For analyses on chronozone/province subdatasets, interspecies phylogenetic distances were calculated on subtrees containing only species occurring in the chronozone/ area of interest (see Zaca€ ı et al. 2018). Analyses were conducted on 'complete' dataset and subdatasets, meaning that all species were conserved, even those showing only one occurrence and thus null latitudinal range sizes. We also conducted analyses on datasets containing only species showing more than one occurrence in order to evaluate the influence of null range sizes on the relationship between species range size and latitude.
RESULTS At the scale of the early Pliensbachian, latitudinal range sizes of western Tethys species increase significantly with latitude (Fig. 2A ; Table  2 ) and thus show a Rapoport effect. However, when species are separated according to their province of occurrence (i. e. MED, NWE and transprovince species), only NWE species exhibit such a pattern (see Fig. 2C   S2 ) for analyses of transprovince species). This positive relationship between NWE species range size and latitude could be driven by an outlier, that is, the species showing the largest range at the highest latitude (Beaniceras luridum Simpson, 1855). However, it remains significant even when this species is removed from the dataset analysed (Zaca€ ı et al. 2018, table  S2 ). The relationship observed at the scale of the western Tethys is therefore probably driven by NWE species.