dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We thank  Professor Haig Kazazian ,  Professor Bert Vogelstein ,  Dr. Bruno Amati , and  Dr. Alister Funnell  for helpful discussion. We thank  Professor Daniel Azoulay ,  Professor Denis Castaing ,  Professor Rene  ´Adam and  Dr. Eric Vibert  ( Centre Hepatobiliaire, Villejuif ), and the  Tissue Biobank Group (AP-HP and UniversiteParis-Sud)  for providing HCC specimens. We thank  Dr. Christine Beck  and  Professor John Moran  for providing the genomic coordinates of a recently published full-length L1 insertion cohort (Beck et al. , 2010). Research performed in the laboratories of D. S. , G. N. , P. C. , F. D. C. , J. F. , and G. J. F. was funded by the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement No. 259743 underpinning the MODHEP consortium.
J. K. B. and P. M. B. were supported by  Wellcome Trust Clinical Fellowships  ( 090385/Z/09/Z  and  090386/Z/09/Z , respectively) through the  Edinburgh Clinical Academic Track (ECAT). J. L. G. P was supported by  FP7-PEOPLE-2007-4-3-IRG ,  CICE-FEDER-P09-CTS-4980 ,  PeS-FEDER-PI-002 ,  FIS-FEDER-PI11/01489 , and the  Howard Hughes Medical Institute  ( IECS-55007420 ). J. F. acknowledges the support of the  Institut National de la Santeet de la Recherche Medicale (INSERM) , the  Association pour la Recherche contre le Cancer  ( ARC 4866 ), and the  Institut National du Cancer  ( INCa 2009-PAIR-CHC ). G. J. F. acknowledges the support of a New Investigator Award from the  British BBSRC  ( BB/H005935/1 ) and a  C. J. Martin Overseas Based Biomedical Fellowship  from the  Australian NHMRC  ( 575585 ).
Data Analysis Distribution of mites (number, strain, sex) in the ball and on the leaf Because data obtained during our observations were normally distributed, we used only parametric tests. For both experiments (I and II), t-tests were used to determine whether the distribution of mites (A 1 , silk-ball formation: number of mites in balls and leaf discs) was equal. For experiment I, t-tests were also used to determine whether green and red mites were homogeneously distributed. Tests were performed using GraphPad Prism version 5. 01 for Windows (GraphPad Software, San Diego, California, USA, http:// www. graphpad. com).
Population differentiation obtained by the isofemale lines approach (Experiment II) Alleles were assigned using the software Genemapper 4. 0 (Applied Biosystems). Pairwise F ST values were calculated for each population comparison (N = 3) and for the isofemale lines (IF1, IF2). An exact test for genetic structure (pairwise differentiation test for population differentiation using allelic distribution in the various populations) was used as implemented in GENEPOP  [37, 38].
Acknowledgments We thank  Thomas Van Leeuwen ,  Lebdi Grissa Kaouthar , and  Marc Migon , who provided the mite strains used in the experiments, and  Prof. Stanley Lutts , who allowed us to use his culture chamber. We thank  Michel Pirnay  for building the cages and lighting system. We are very grateful for the help provided by  Jean-Francois Martin  in genotyping the mites and by  Jean-Marie Cornuet  in data analysis (kin association tests). We also thank  Dries Bonte  ( Ghent University ),  Jean-Louis Deneubourg  and  Claire Detrain  ( Université Libre de Bruxelles ) for their comments on the manuscript and  Angelica Lim  for the English proofreading. This paper is publication no. BRC224  of the  Biodiversity Research Centre (Université catholique de Louvain ). Data used in this work were (partly) produced through molecular genetic analysis technical facilities of the  Centre Méditerranéen Environnement Biodiversité.
It also carried a red LED (Light Emitting Diode) to permit an easy and reliable tracking in conditions of changing background brightness. A NiMH rechargeable battery provided energy for about 3. 5 hours in our experimental conditions. The robots had a microcontroller PIC16LF877 with 8K Flash EPROM memory, 368 bytes RAM and no built-in float operations. Programming was done with the IDE of the CCS-C compiler, and the compiled programs were downloaded in the Alice memory with the PICdownloader software (EHL elektronika).
The images were then converted to binary images by applying a min-max threshold to isolate the red portion of the H channel. The resulting blobs of pixels were fitted with an ellipse function whose center position provided the position of each robot. Positions were corrected with respect to camera lens distortion, position and angle using the Matlab Camera Calibration Toolbox (Computer Vision Research Group, California Institute of Technology). Robot positions were used to produce an image (8006600 pixels) where uniform light discs of fixed blue intensity (Red = 0, Green = 0, Blue = 7) marked trail pheromone spots. Each disc was centered on the trajectory traced by a robot and did not overlap with the previous disc drawn along the same trajectory. Discs pertaining to different trajectories or that were not directly following each other on the same trajectory could overlap.
Misalignment between the camera and the beamer was corrected using the Matlab Camera Calibration Toolbox. The projected image covered a surface of approximately 1406105 cm. The size of the blue disc after projection was fixed to 6 cm. This allowed the formation of light trails large enough for two robots to cross without being pushed outside the trail. These parameter values that produce consistent trail laying and trail following behaviors with these robots were established in a previous study  [28].
Data collection and analysis All data processing and statistical analysis were performed with R version 2. 7. 0  [38]. Individual behavior. In order to quantify the impact of the bifurcation structure on the individual displacement of the robots, we first analyzed their individual behavior when crossing an asymmetrical bifurcation. We tested whether their choice to follow the most direct branch resembled the choice observed in ant experiments  [16]. During the first 2 minutes of each experimental replicate with network configuration A, we measured the proportion of robots crossing an asymmetric bifurcation and choosing to enter the most direct branch, i. e. the branch deviating by an angle of 30u from the original direction of the robot. Choices influenced by the contact with another robot at the bifurcation were excluded from this measure to be comparable to the individual choice data in  [16]  that had been obtained from isolated ants without direct interaction with a conspecific.
Deviation from a random choice was tested using a x 2 test for given probabilities. Comparisons with actual ant behavior at asymmetrical bifurcations (data taken from  [16] ) were performed with a Fisher's exact test for count data. Significant differences between robot and ant behaviors would suggest that the ants' choice is not simply dictated by the inertia of their movement. Collective behavior. In order to quantify path selection efficiency in the different network configurations we had to assess (a) whether robots created a pheromone trail between source and target area and at what speed, (b) the length of this path and (c) the persistence of this trail. Efficient robots should find short paths quickly, short paths should persist longer than long paths, and there should be less changes in path selections.
We divided the network into segments, each of them corresponding to a corridor between two bifurcations. For each type of network, we computed the total pheromone intensity every second on each segment of the maze using data coming directly from the pheromone deposit device. This total intensity was obtained as the sum of all pixel values in one segment. A segment was considered as used when the total intensity was above a threshold of 50,000. This threshold roughly corresponds to the amount of light pheromone that 2 robots would deposit in a segment of the maze if they were following each other closely. Distributed over the entire segment, it also corresponds approximately to the minimum amount of light necessary to activate the trail-following behavior of a robot. We determined the path selected by robots as follows.
Acknowledgments We thank  Roland Siegwart ,  Fabien Tache ,  Peter Siegrist ,  Celine Ramoni  and all the members of the  Autonomous Systems Lab  for their help with the development of the robotics setup. We also thank  Vincent Fourcassie,  Jacques Gautrais  and the members of the  DYNACTOM group  for useful discussions and comments. We also thank two anonymous reviewers for their critical and constructive comments.
Three flowering variables were observed on the first stem which exhibited a panicle on each plant: & The date of panicle emergence (PE), which was defined as the date the panicle was visible one centimeter above the top of the stem; & The date of onset of flowering (OF), which was defined as the date the first stamen became visible; and & The interval between the PE and the OF. These three flowering variables were expressed in degree days (dd), using the same base temperature of 10 °C as Jensen et al. [22]. Five variables related to panicle architecture were observed on two panicles per pot on average: Analyses of variance (ANOVA) were all performed with the SAS Software System  [31]  using the GLM procedure. ANOVA was performed to investigate the effects of clones, and clone × environmental conditions interactions on all of the observed variables.
The interpretation was focused on the effect of the clone and the interaction between the environmental condition and the clone effect: the environmental condition effect was not interpreted as there was no replication for each environmental condition tested. Three t tests were performed on all of the observed variables with the SAS Software System  [31]  using the T TEST procedure. These t tests were performed for each clone studied separately to identify which of the two environmental factors (temperature or day length) was responsible for the differential sensitivity of the clones: the first t test compared the two temperatures, cool vs. warm (environmental conditions 1 and 3 vs. environmental conditions 2 and 4, respectively) while the second t test compared the two day lengths, short days vs.
Acknowledgments The authors would like to acknowledge the support of the  Picardie Regional Council  via the  PEL  project. Our special thanks go to  Marie-Chantal Mansard  and the staff working in the INRA greenhouses in Estrées-Mons for their practical advice and technical assistance, which enabled the success of the experiments. We also thank  Alexandra Hocdé  and  Ghislaine Lauwerier  for their assistance with the experiments during their professional training. We thank  Professor André Gallais  and all the reviewers for their valuable comments. We particularly thank  Danièle Roques , from  CIRAD in Guadeloupe , and  Nils Berding , from  BSES Meringa in Australia , for their input on sugarcane. Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Samples Stool samples were collected from dogs admitted to four participating veterinary clinics in geographically distinct areas across the UK. With owner consent, dogs were recruited to the study if they passed stools whilst hospitalized. Stools were collected by veterinary personnel, then stored at 220uC until and during transportation to the laboratory, whereafter they were stored at 280uC prior to nucleic acid extraction. Stool samples were also collected from healthy dogs owned by veterinary staff at each clinic, as well as from dogs at participating boarding kennels. Basic case data was recorded for each dog from which a stool sample was collected, including age, breed, sex, reason for admission, and any recent history of enteric disease. Serum samples were obtained from two separate dog populations.
All 6 CNV sequences listed in Genbank in August 2012 (table  1 ) were used to design a CNV specific primer-probe (PrimerDesign Ltd, table  2 ). The target sequence is the highly conserved region of the RdRp (NS7). A positive control amplicon was used to generate a standard curve. As few as 100 copies of the CNV amplicon were reliably detected in a reaction volume of 20 ml. In addition to CNV, samples were also screened for two other canine enteric viruses known to be circulating in the UK. Primer-probes used for canine parvovirus (CPV) and canine enteric coronavirus (CECoV) are listed in table 2, as well as the primer-probe sequence used to detect the internal extraction control. A 1-step qRT-PCR protocol was used to improve ease and efficiency of sample handling. 2 ml of extracted RNA was added to 26 Precision OneStep qRT-PCR MasterMix (PrimerDesign Ltd), 6 pMol/ml primers, and 3 pMol/ml probe.
Virus-like Particle (VLP) Production Three different CNV strains with maximum sequence difference were selected for VLP production. The sequences of the three CNV-VP1 genes were obtained from GenBank (table  1 ) and restriction enzymes sites designed (59 NotI for all strains, 39 BbsI for CNV strains 170, C33 and 39 BsaI for CNV HK) to enable later ligation into the baculovirus transfer vector pTriex1. 1. Sequences were synthesized by BioBasic Inc. in the vector pUC57. CNV-VP1 sequences were digested from pUC57 and re-ligated into pTriex1. 1 that had been digested with NcoI and NotI (NEB). The correct sequence for all three CNV-VP1 inserts was confirmed by sequencing. Recombinant baculoviruses were generated using the flash BAC baculovirus expression system as per the manufacturers instructions (Oxford Expression Technologies).
Samples Collected Stool samples and clinical data were collected from 111 dogs admitted to veterinary clinics distributed across the UK between August 2012 and March 2013. The mean age of the dogs was 5. 2 years (standard deviation 4. 2 years), with 42 different breeds represented. Diarrhoea and/or vomiting lasting more than 24 hrs prior to admission, was reported in 52% of these cases. The gastrointestinal clinical signs in a proportion of these cases were unlikely to be attributable to primary gastroenteritis (e. g. pyometra, foreign body ingestion), thus overall it was found that 43% of dogs enrolled in the study were suffering from gastroenteritis, infectious or otherwise. Control samples were collected from 117 healthy dogs (mean age 5. 6 years, standard deviation 3. 6 years) from boarding kennels or belonging to veterinary staff.
A range of titres were identified (figure  2 ), varying from 1:1600 (1 dog) to 1:100. The most prevalent titre in this preliminary screen was 1:400. All 189 serum samples identified as positive by the initial ELISA screen against pooled CNV VLPs, were then tested against individual CNV VLPs. The results show significant variation between the seroprevalence of different strains (figure  3 ). CNV strain HK predominated in both cohorts of dogs, whereas strain C33 showed the lowest seroprevalence in both groups. These data also indicated that a proportion of dogs have seroconverted to more than one of the CNV strains used in this study. In the 1999-2001 cohort 30. 6% dogs were seropositive to 2 or 3 strains, a percentage that increased to 40. 4% in the 2012-2013 cohort.
The HK sequence differences are such that the primerprobe used in the qPCR survey would not detect strain HK. In light of the results of the serosurvey, this issue was addressed retrospectively to the first viral RNA survey. A new primer set was designed to detect the most conserved region of the HK VP1 protein. A SYBR-based qPCR assay was used to screen all 228 stool samples for the presence of any norovirus strain using primer pair p289/290 and also specifically for CNV strain HK using a newly designed primer pair. No positive samples were identified using either primer pair (data not shown). Seroprevalence to the CNV strains surveyed in this study has been shown to have significantly increased over the past decade in the populations studied. In the 1999-2001 cohort of dogs 38. 1% were seropositive, whereas in the 2012-2013 cohort this proportion has almost doubled.
Not only does this data provide the first proof that CNV has been present in dogs for at least 8 years prior to its initial discovery  [7] , it also implies that the number of dogs exposed to these strains of CNV has significantly increased during this period. This conclusion does come with certain caveats however, as the study populations of dogs used are not directly comparable. The 1999-2001 samples were collected from dogs that had been at a rehoming kennels for 3 weeks whereas the 2012-2013 dogs were all privately owned pets. Seroprevalence and overall viral prevalence to many viruses is known to be higher in facilities where dogs are kept in close contact  [21][25]. This does suggest that the apparent increase in seroprevalence to the CNV strains studied is real, as typically owned pets will be exposed less frequently to viruses than dogs in kennels.
It would be valuable to assess the current CNV seroprevalence in kenneled dogs, which is predicted to be greater than 60%. VLPs of three different CNV strains were pooled together to establish the overall seroprevalence to the virus. CNV strains included were identified in 2007 from Italy (170), Portugal (C33) and Hong Kong (HK). Following the initial serosurvey with the pooled VLPs, positive samples were entered into ELISAs with VLPs from each of the individual strains separately. Our data would indicate reactivity to all three strains in the UK dog population. Blocking assays demonstrated no significant crossreactivity between the three CNV strains in the samples tested, proving that antibodies generated in response to infection were likely to be strain specific. The human immune response against human norovirus is of short duration (up to 14 weeks) and is homotypic, i.
Acknowledgments The authors would like to thank veterinary surgeons  Devi Nair ,  Jennifer Stallwood  and  Sophie Martin  who were invaluable for assisting in canine stool sample collection, in addition to the rest of the veterinary teams at  VetsNow Hospitals in Gillingham, Lincoln and Northolt and Swayne and Partners, Bury St Edmunds. We would also like to thank  Abington Boarding Kennels  and  Greenlow Kennels in Cambridgeshire  for assisting with stool sample collection. Finally, we are grateful to  Pet Blood Bank UK  for providing us with valuable canine blood samples.
Statistical analysis Linear mixed-effects models [LMMs  (Gałecki and Burzykowski, 2013) ] were used to examine the relationship between the response variables (pulp acidity and composition) and the explanatory variables (fruit age, cultivar), and their interactions. We used quadratic and cubic terms of fruit age when the curve passed through a maximum and had an asymmetrical shape. We used the lme function in the 'nlme' library  (Pinheiro et al. , 2013)  in the statistical program R 2. 14. 0. "Banana plant" was treated as a random effect because banana plants were assumed to contain unobserved heterogeneity that cannot be modeled. A temporal correlation structure was used to account for temporal pseudoreplication. Model selection was made using the top-down strategy  (Zuur et al. , 2009) : starting with a model where the fixed component contains all explanatory variables and interactions, we found the optimal structure of the random component.
(2006). First, border values of each of the eight input factors of the models were estimated as the extremes values of the dataset corresponding to the fruit stage considered for the sensitivity analysis. Then, for each input factor, their range of values was divided into five equal levels and a 5 8 factorial simulation design was created. Next, an analysis of variance (ANOVA) was performed on the model responses to study the contribution of each input factor to pH and TA variability. A sensitivity index (SI) of each input factor was calculated by dividing its sum of squares by the total sum of squares  (Monod et al. , 2006).
Cocoa Analytics Intact and visually perfect beans of non-fermented and fermented (without roasting) samples were carefully manually shelled and coarsely ground in a Limprimita cocoa breaker (Capco, Ipswich, UK) and then ground further in a knife grinder in liquid nitrogen to avoid heating transformations, until obtaining a maximum 0. 5 mm particle size. The resulting cocoa powder was sieved (0. 5 mm) and kept at 280uC until analysis in a FOSS 6500 near infrared spectrometer (Welltech, Capitol Heights, ML, USA). Of 3-g cocoa powder samples delivered in 50-mm diameter ring cups, reflectance was scanned at 2-nm intervals, from 400 to 2500 nm. The data (average of 32 scans per wave length interval) was stored as log(1/R) with R being the reflectance and 1 referring to the reflectance of a standard ceramic reference.
The spectrum acquisitions were at random. Each sample was measured twice. Statistical analyses were made using Win-ISI II (Infrasoft International, Port Matilda, PA, U. S. A. ) and XLStat (Addinsoft, Paris, France) software. The spectra were mathematically corrected for light scattering using the standard normal variate and Barnes detrend correction  [14]. Second derivatives were calculated on five datapoints and smoothed using Savitzky and Golay polynomial smoothing  [15]  on five data points. The relative contents (in percent of total dry matter) of total fat and dry matter, the methylxanthines caffeine and theobromine, the flavan-3-ol epicatechin and the procyanidins B2, B5, C1 were assessed based on calibration curves developed at CIRAD (Table  4 , note that the values reported may therefore divert from values determined following the newly developed AOAC guidelines  [16] ).
Statistical Analyses Normal-distribution of the traits scored was tested in the univariate procedure in SAS  [20]  and Pearson's correlations were run in the corr procedure. The significance of factors for the performance of individual traits was determined in analyses of variance of the models Trait = Factor+Replication (Tree was the factor and harvest 1 and 2 were the replication term) or Trait = Factor 1+ Factor 2+ (Factor 16Factor 2)+Replication (factors were individual tree, genotype, harvest, or farm, replications were either trees belonging to the individual genotypes or trees within each farm. For these analyses, the SAS glm procedure with the SS3 option in the model statement was used. Multiple comparisons of least-squares means were carried out with the multiple t-test (tdiff) option in the lsmeans statement, to account for unequal replication numbers.
Acknowledgments Wilberth Phillips  and  Carlos Astorga ,  CATIE ,  Costa Rica , provided information on parental accessions and leaf samples. We based our selection of farms on a survey of cacao-producing households in Waslala conducted in 2007 by the  CATIE-led Proyecto Cacao Centroamerica. The collaborator visible in Figure 4 has given written informed consent, as outlined in the PloS consent form, to publication of his photograph. Eva Ho ¨hne, Martin Luther University Halle-Wittenberg , and  Martina Trognitz ,  University of Heidelberg , provided valuable editorial support and graphics. Hans Grebe , PMH, provided logistical support to field work.
Metagenomic library construction Two different gut microbiota were sampled as previously described  [44, 71] , in the frame of a study registered as a clinical trial (http://clinicaltrials. gov/, Calibrated Diets and Human Intestinal Microflora NCT00639561) and carried out at the Center for Clinical Investigation (CCI) of Grenoble University Hospital (France). The first one was a fecal sample of a healthy 30 years old male, who followed a vegetarian and fish-eating diet for twelve years before sampling. The distal ileum sample was obtained from a 51 years old male patient undergoing colonoscopy and surgery for lower colon cancer suspicion, after he has been submitted to a cleansing preparation. A segment of 2 cm 2 was obtained, immediately frozen and kept at 280uC until processing. Both individuals showed an average body mass index.