dataesr/scientific-paragraphs-categorization huggingface dataset:
Notes Acknowledgments. We acknowledge the assistance of Lena McCormack and Magdalene Lynch (Northern Territory Rural Clinical School) for determining the primary languages for patients recruited to this study; the staff at the Pathology service (Alice Springs Hospital) for preparing the clinical material; and Cathy Magann for ensuring that this material was safely shipped to Paris, France. Disclaimer. No funding source was involved in any aspect of study design, data collection, data analyses, or manuscript preparation.
Study design Herds and animals investigated. From March 2011 to August 2012, a total of 516 ruminants (245 cattle, 137 sheep and 134 goats) belonging to 71 farms and localized in different ecosystems of Reunion Island were randomly selected for this study. The sample size was considered at a 95% level of confidence, 5% of desired absolute precision and expected prevalence of 10% for cattle, sheep and goats  [15]. Only female animals were sampled. At least five cows were chosen from each cattle herd (46) and 10 goats and ewes were chosen from each small ruminant herd  (25). Data collection. The study was based on data taken from interviews with the farmers. Data concerning farm characteristics, type of production, number of animals, proximity to another farm or sugar cane fields, presence of organic and other waste within the farm, wind exposure, proximity to a permanent water source, stability type, presence of ticks on animals, use of treatment against ectoparasites and insects, contact of animals with other animals or humans, grazing practice, manure spread on pastures, presence of tenrecs, rodent control, occurrence of pregnancy terminations within the herd during the last 12 months, purchasing behavior, quarantine of newly purchased animals and other biosecurity related factors such as hygienic precautions taken by the staff or any other people entering the farm (truck driver, veterinary and other visitors) were collected using a questionnaire.
Amplifications were performed in a Gene Amp 9600 thermal cycler (Perkin Elmer, Courtabeuf, France). Initial denaturation at 94uC for 5 min was followed by 60 cycles of 94uC for 30 sec, 60uC for 30 sec, 70uC for 1 min. The final extension step was 5 min at 72uC. Five microliters of amplification product was loaded on a 2% standard agarose gel (Eurobio, Courtabeuf, France). Gels were stained with SYBR Safe DNA gel stain (Invitrogen, Cergy Pontoise, France). The size marker used was a 100 bp low ladder (Sigma-Aldrich, Saint Quentin Fallavier, France). Gel was photographed under UV light and images were managed using the Photocapt Software package (Vilber-Lourmat, Torcy, France).
Statistical analyses The animals were considered positive when at least one sample (blood, swab or milk sample) tested positive by either serology or PCR. The serological and PCR data were analyzed using a generalized linear mixed model (glmmML library, R software), where the individual health status was the binomial response, and the variables from the questionnaire were the explicative factors. All of the explicative variables were categorical. The number of categories per variable was limited, such that frequencies of categories were only. 10%. These variables were selected from a preliminary step aimed at lowering the chance of obtaining results affected by multicollinearity in the dataset  [18]. All bilateral relationships between these variables were evaluated (x2). A two-stage procedure was used to assess the relationship between explanatory variables and the health status of the animals.
75 mm i. d. ; Supelco, Bellefonte, PA, USA). Samples were also analyzed with a Perkin-Elmer Turbo mass detector (quadrupole), coupled to a Perkin--Elmer Autosystem XL, equipped with fused silica capillary columns Rtx-1 and Rtx-Wax. Ion source temperature was 150 °C, energy ionization was 70 eV, electron impact mass spectra were acquired over the mass range of 35-350 Da (scan time: 1 s). Other GC conditions were the same as described above except for the use of a split ratio of 1/80. For HS-SPME-GC-mass spectrometry (MS) analysis, only the Rtx-1 column was used and volatile components were desorbed in a GC injector with an SPME Intel liner (0. 75 mm i. d. ; Supelco). The identifi cation of individual volatiles was based on comparison of calculated retention indices (apolar and polar columns) and mass spectra with those of our own library of authentic compounds or literature data (I l )  (21).
The so ware used for data acquisition and data analysis was Analyst v. 1. 5. 1 (AB Sciex). For each reference compound, a relevant transition of the pseudomolecular ion was selected and the mass parameters were optimized in direct infusion (fl ow rate: 10 µL/min) using the automated component optimization function of the Analyst so ware. Multiple EPI spectra were recorded in our MS spectral library for each compound. Data acquisition was performed in the multiple reaction monitoring (MRM) mode, followed by an EPI scan (MRM-EPI). EPI mass spectra were recorded in the range of m/z=50-1000 at 4000 Da/s. Compound identifi cation was allowed by comparison of retention time, MRM transition and the EPI mass spectrum of reference compounds. An external standard method was used for quantifi cation of fl avonoid compounds.
Vaccines Three AI vaccines were used: a classical inactivated and two recombinant FP vectored vaccines. The whole virus beta-propiolactone (BPL)-inactivated vaccine (inH5N9) contained the Eurasian isolate A/chicken/Italy/22A/98 [H5N9] (Genbank HA gene: ABR37720), propagated on embryonated SPF eggs (experimental vaccine prepared by Merial Italia S. p. A. ). The inactivated antigen (H5N9-It) was formulated in a water-in-oil adjuvant similar to those used in classical avian inactivated vaccines. Two different experimental formulations of H5N9-It inactivated vaccine (inH5N9) were used. For studies 1 and 2, the vaccine was formulated at 0. 5 mL (350 HA units) per dose and for studies 3 and 4, it was formulated at 0. 3 mL (122 HA units) per dose. The first vectored vaccine contained an experimental FP recombinant (vFP2211) expressing a synthetic hemagglutinin (HA) gene derived from the amino acid sequence of the HA from A/chicken/Indonesia/7/2003 clade 2.
1. 1 H5N1 HPAI isolate (GenBank: ABO30346) that was modified at the cleavage site (RERRRKKRGLF mutated into RETRGLF)  [7]. The other FP vectored vaccine was the TROVAC®-AIV H5 (batches TAH5RF064 (study 2), RD021 (study 3), and RD030 (study 4) produced by Merial Select, Inc. , Gainesville, Georgia, USA) vaccine licensed in the USA and other countries. This vaccine contains the FP recombinant vFP89, which expresses the HA gene (Genbank: HMIVT8) of a HPAI H5N8 virus isolated in Ireland (A/turkey/Ireland/1378/83 [H5N8]). The FP vector (TROVAC® vector), insertion site and promoter were the same for the two FP vectored vaccines. It was derived from the seed of the commercial FP vaccine DIFTOSEC CT® (batch 5DCC3511 (breeders of study 1 and 2) and batch 7DCC3801-A (breeders of study 3 and 4) produced by Merial S.
3 mL of inH5N9. Chicks with anti-H5N9 MDA were either non-vaccinated, vaccinated with vFP89 at D0, vaccinated with 0. 3 mL of inH5N9 at D14, or vaccinated with   [17]  (Accession number EPI533441) was used for sequence analysis. This isolate was previously used in a published vaccination-challenge study  [18]  and is one of the antigenic variants that emerged in Indonesia as early as 2005  [16]. Morbidity and mortality were recorded during 2 weeks after challenge and oropharyngeal swabs were collected 2 and 4 days post-challenge to evaluate viral load by quantitative real time RT-PCR. Blood was taken 2 weeks after the first vaccination (D14) and 2 weeks after the second administration before challenge (D28). The level of MDA was evaluated from the serum of 5 additional chicks euthanized after hatch.
Sequence and laboratory analysis The identity and similarity between the HA1 amino acid sequence of the vaccine strains, the challenge isolate and the viruses used as antigens in the HI test (Table  2 ) were obtained using the Blastp software of the National Center for Biotechnology Information  [19]. The serological analyses were performed using the hemagglutination inhibition (HI) tests. Tests were conducted according to standard procedures, using 4 HA units/well. Different antigens were tested to check for cross-reactivity of the serums towards different recent H5N1 strains. The BPL-inactivated A/chicken/Italy/22A/ 98 [H5N9] (homologous to the inactivated vaccine strain) was tested on serums from all studies. The BPLinactivated NIBRG14 H5N1 antigen was used on serums from studies 1 and 2; the NIBRG14 is a 6/8 PR8-based reverse genetics mutant containing the HA (Genbank: ACR48874) and NA of the A/Vietnam/1194/2004 clade 1 H5N1 isolate.
The BPL-inactivated NIBRG23 H5N1 antigen was used on serums from study 3; the NIBRG23 is a 6/8 PR8-based reverse genetics mutant containing the HA (Genbank: ABQ58921) and NA of the A/turkey/ Turkey/1/2005 clade 2. 2 H5N1 HPAI isolate. The H5N8 A/turkey/Ireland/1378/83 antigen, homologous to the HA used in the vFP89 vaccine was also used in studies 2, 3 and 4 and the BPL-inactivated A/chicken/West Java-Subang/29/2007 was used in study 4. The serums of breeders were also tested with the H5N9 antigen as well as with the NIBRG14 (studies 1 and 2) or NIBRG23 (studies 3 and 4) H5N1 antigen. The HI tests on serums from breeder hens were performed at Merial; those from their progeny of studies 1 to 3 and from study 4 were performed at Merial and SEPRL, respectively. The first tested serum dilution was 1 log2 (studies 1 to 3) and 3 log2 (study 4).
Altogether, these data confirm that MDA transferred from the vaccinated breeders to their progeny interfere with the immunogenicity and efficacy of inactivated vaccine given at least in the first 2 weeks of age, especially when multiple administrations of the vaccine are used in breeders and the same vaccine is used in the progeny. The interference is detected even with low MDA titers and is lower when heterologous inactivated vaccines are used in the progeny. It is therefore important to take into account this interference when designing the vaccination program of breeders and their progeny. The anti-FP and anti-AI MDA interference on vFP89 immunogenicity could be evaluated only before the boost (D14) in studies 3 and 4. Anti-FP MDA had only a slight negative effect on vFP89-induced H5N8 HI titers in study 3, but in study 4, the negative effect of anti-FP MDA was higher.
Acknowledgements This work was supported by the  French Ministry of Industry via LyonBioPole (Lyon, France). We thank  Sandrine Chanavat-Bizzini ,  Michelle Duboeuf ,  J. -F. Piriou ,  J. -L. Dumas ,  F. Vermorel ,  J. Beck  for technical assistance and  V. Cozette  for statistical analysis of study 3. The  NIBRG14  and  NIBRG23 H5N1  viruses were kindly provided by  NIBSC. We thank the  Indonesian Ministry of Agriculture  for cooperation and providing viruses and sequence data to the veterinary health research and diagnostics organization and laboratories. We gratefully acknowledge the authors, originating ( Dr. Teguh Y. Prajitno ) and submitting (Koel, B. F. ; van der Vliet, S. ;  Burke ,  D. F. ; Bestebroer , T. M. ; Bharoto, E. E. ; Herliana, I. ; Laksono, B. M. ; Xu, K. ; Skepner, E. ; Russell, C.
A. ; Rimmelzwaan, G. F. ; Perez, D. R. ; Smith, D. J. ; Prajitno, T. Y. ; Yasa, I. W. W. ; Osterhaus, A. D. M. E. ; Fouchier, R. A. M. ) laboratories of the Indonesian H5N1 challenge HA sequence from GISAID's EpiFlu™ Database, on which this research is based; all submitters of data may be contacted directly via the GISAID website [17]. TROVAC and DIFTOSEC are registered trademarks of Merial in the  United States of America  and in France, respectively, and elsewhere. BLAST is a registered trademark of the  National Library of Medicine.
The minimum was computed using golden section search and parabolic interpolation, by calling the ''fminbnd'' Matlab's function. The rotation angle minimizing the difference was divided by 2, and the corresponding rotation transform was applied to the original polygon, resulting in a polygon pointing upwards. The vertex located on top of each polygon was chosen as initial vertex (i. e. with index equal to 1). The vertex number of each contour polygon was reduced to the same number by sub-sampling, starting from the top vertex. The number n v of vertices of resampled polygons was chosen equal to 200. The position of each vertex was defined by the two x and y coordinates expressed in relation to the centre of gravity. Each contour was therefore described by the n c = 26n v = 400 coordinates of the vertices of its polygon.
All the resulting polygons started from the upper vertex, had the same number of vertices, and were oriented counter-clockwise. The vertices of all polygons were assumed to be in direct correspondence. A data table XY(i, j) was built with the rows i corresponding to the individual slabs and the columns j corresponding to the 400 x and y coordinates of the polygon vertices. Statistical analysis of stem contours. Statistical analysis of the contour was done in two steps. First, a principal components analysis was applied to help identifying the slab populations with similar or different contours. Then an analysis of variance was applied on the first principal components to identify which factors were relevant for modelling. Principal components analysis was applied on the XY data table formed by the coordinates of slab contours.
Software implementation. Image processing was performed within the Matlab environment (The MathWorks, Natick, MA, USA). Geometric operations on polygons and point sets were performed using software developed within the Matlab environment and integrated into ''MatGeom'', a freely available library for geometric computing within Matlab (http://matgeom. sourceforge. net/). Estimation of intensity maps was performed within the R Software using the spatstat package  [41]. Statistical analyses (principal component analyses, general linear models) were performed within the Matlab environment. In order to facilitate reproducibility of results and their adaptation to other data, the Matlab and R scripts used to process images and geometric data are provided in File S1 and S3. Some pre-.
Discussion The spatial organisation of vascular bundles in maize stems was investigated using tools from spatial statistics together with a spatial normalisation procedure. A statistical model of the internode contour was computed using the whole data set, therefore providing a reference space for comparing observations. Vascular bundle positions were projected onto this reference space, resulting in spatially normalised observations. The different acquisitions were analysed together, and an average bundle intensity map was obtained. The resulting distribution of bundles established within the stem is more representative than those obtained using a single image. The spatial normalisation procedure is generic and can be applied to other types of plants and other types of objects. In the present work, the projection onto a reference space used a rather simple polar transformation.
Analyses were performed under a 40× objective lens for perikarya, fibre varicosities, and nerve terminal distribution. Double staining. The double immunofluorescent staining was observed under a confocal microscope, Zeiss LSM 700 (Carl Zeiss, O Berkochen, Germany), fitted with four laser diodes (excitation wavelength 405 nm, 488 nm, 555 nm and 639 nm). Image analysis was performed under a 40× oil immersion objective (Plan-Apochromat, 40×/1. 3 oil DIC M27), using ZEN control software. The thickness of the optical sections was 0. 3 μm. Homogenously distributed kp-immunoreactive neurons in the ARC nucleus (17-45 per animal) were analysed in each lamb, and a fibre and a neuron were considered to be in contact or in close apposition when contact was observed on two successive focal plans and when the distance between the maximum staining intensity was less than 0.
Statistical analysis GAs are involved in multiple aspects of plant development  (Davière and Achard, 2013). Therefore, to avoid potentially confounding phenological differences between wild-type Ler and quad-della mutant plants, statistical differences (P ≤ 0. 05) were determined within each genotype by one-factor analysis of variance (ANOVA) using SPSS version 20 (SPSS Inc. ) followed by a Tukey HSD post-hoc test. The results from statistical analyses are shown in Supplementary Table  S2  at JXB online. Gene expression can be highly variable; therefore, either a statistically significant difference or a >5-fold increase over constitutive control levels was considered as an increase in transcript levels.
g. WorldClim database), a resolution that is still very coarse relative to the home ranges or body size of most species  [13, 18]. For instance,  [8]  showed that climate grid lengths used in SDMs are, on average, ,10,000-fold larger than studied animals, and ,1,000-fold larger than studied plants. Their meta-analysis showed that the WorldClim was the most widely used climatic dataset in global SDMs. As this commonly used coarse scale climatic data in SDMs overlook the spatiotemporal thermal heterogeneity experienced by organisms, there is an urgent need for a more sophisticated use of these datasets for making inferences about biological processes that are driven by hour to hour operative temperatures of organisms. An important yet poorly studied issue in climate change biology is to quantify to what extent climatic conditions differ between widely used 1 km 2 interpolated grid cells of global climatic database and real-world landscapes of similar areas.
Addressing these questions is not an easy task as the mosaic of climatic habitats relevant for small ectothermic species at a 1-km 2 scale in real-world landscapes may be outstandingly complex. In this study, we focused on highland agricultural landscapes of the tropical Andes as most prior similar data came from low elevation and temperate agroecosystems. In such systems, most crop pests experience, over their entire life cycle, climatic conditions in three well-defined environmental layers (air, air inside-canopy and soil) and these conditions are remarkably stable over the year  [19]. In this context, we firstly decided to map over replicated 1-km 2 climatic grid cells the ecologically relevant local temperatures for ectothermic crop pests in agricultural landscapes, and to compare these maps to interpolated temperature grid cells of the widely used WorldClim database.
Temperature data collection In each of the three-altitudinal belts, we measured temperature regimes in six habitats (five crops and natural grasslands) where insect pests can be found. In each habitat, we defined three layers: air, air inside-canopy (referred as ''air canopy'' in the text) and soil. These layers are all used by most insect pests over their life cycle: air layer by adults, air canopy layer by adults and leaf-eating larvae and pupae, soil layer by tuber feeding larvae and pupae. In each layer of each habitat, temperature was recorded with a 1 min time step using data loggers (Hobo U23-001-Pro-V2 internal temperature loggers, Onset Computer Corporation, Bourne, USA) with an accuracy of 60. 21uK over the 0-50uC range and a resolution of 0. 02uK at 25uC. According to  [4] , 1) air loggers were fixed on a wooden stake at 1 m high to overstep most crop canopies and sheltered by a 20 cm 2 white plastic roof to minimize solar radiation heating; the roof was itself placed 5 cm above the logger to avoid warming by greenhouse effect, 2) air canopy loggers were placed 0.
At each measurement site, LAI values were visually estimated (twice) measuring the ratio of leaf area within a 1-m 2 quadrant sub-divided into 0. 1 m 2 cells delimited by strings. This indirect method did not account for leaves that lie on each other however it relates to shaded areas that influence insidecanopy and soil microclimates  [23]. Each of the 162 measurement combinations (3 altitudinal belts 66 habitats 63 layers 6 3 LAI classes) was replicated 1-3 times depending on availability of habitats at a given elevation and phenology stage. In total 324 independent temperature time series were acquired over 15 days between September and December 2011 (data available in Appendices S9, S10 and S11). Importantly, under the climatic conditions of the study area, 15-days time series characteristics did not differ from those obtained over one year (see Appendix S4 for details).
Global solar radiations Infrared and visible radiations (expressed in Watt/m 2 ) were monitored in each altitudinal belts using a LI-1400 LI-COR datalogger equipped with a LI-200 pyranometer sensor (LI-COR, Lincoln, USA) placed perpendicular to gravity. Between 9:00 AM and 4:00 PM, mean global solar radiations ranged from 500 to 1000 watts/m 2 , with temporal variability mainly induced by shortterm changes in cloud cover. Times series analyses using Fourier transforms. Air and air canopy temperature time series showed extreme events during a few minutes that were certainly due to strong radiations experienced at the study sites 2 these affected loggers recording despite their plastic roofs. Therefore, we found relevant to fit our time series data with a discrete Fourier transform (DFT) at the daily frequency k d (Fig.
Data analyses We also ran DFT analyses on a four-year monitoring (2008-2012) of air temperatures (recorded at one meter high with half an hour time step with the same shelter process described above) to measure the seasonality. Analyses were performed for the threealtitudinal belts of the study area (2800, 3200, 3600 m) by reading the amplitude at the seasonal frequencies (91, 182 and 364 days, see Appendix S6). On average the Fourier transform amplitudes at 91, 182 and 364 days were 0. 14 (+/20. 01), 0. 44 (+/20. 04), 0. 97 (+/20. 03)uK indicating that the seasonality was negligible in the study area  [24]. All Fourier analyses were performed in MATLAB R2011a (Mathworks, Natick, USA). The effects of habitat, elevation, LAI classes and the interaction ''elevation 6 LAI classes'' on daytime and nigh-time DFT amplitudes and on DFT thermal time lag were assessed using a two-way ANOVA with Bonferroni corrections.
When habitat was found significant, we ran post-hoc 4. 2. Thermal landscape analyses. To compare local temperatures with global interpolated climate data employed in species distribution models, we considered one of the most widely used and readily available climate database, WorldClim  [25]. The WorldClim database is a set of global climate layers (interpolated averages of monthly minimum, maximum and mean 1. 5 m high air temperatures from weather stations spread out worldwide) with a spatial resolution of 30 arc seconds. Close to equator, this resolution is equivalent to squares of 0. 86 km. In each altitudinal belt, we selected one WorldClim grid cell with homogenous slope (between 5. 4u and 7. 9u), micro-topography and exposition (southwest). Based on a digitized municipal cadastre (from the town council of Salcedo, Cotopaxi province) and a 5-m resolution digital orthophoto (Ecuadorian Military Geographical Institute, www.
01-0. 5,. 0. 5) based on a survey of 85 sites in the region, in which we quantified landscape composition (% of each crop and LAI classes) in 100-m radius sampling circles (see Appendix S7). For each habitat, we assigned the corresponding air, air canopy and soil temperature values at each elevation. Finally, since we were particularly interested in minimal and maximal values, as they are the most biologically relevant for ectothermic crop pests  [4] , we focused on minimum and maximum temperatures obtained from the DFT analyses and the WorldClim database. Afterwards, we decomposed the variance of temperatures between global interpolated grids and local temperatures measured in agricultural landscapes by mapping the differences in minimum and maximum temperatures between the air local temperatures (Air L ) and the WorldClim interpolated temperatures (Air WC ) for the three studied grid cells.