dataesr/scientific-paragraphs-categorization huggingface dataset:
A AAB 62 03 qA731606 ); SÉPAQ;  Ministry of Agriculture and Forestry of Finland; Science Foundation Ireland  ( EEB0061 );  University of Toronto (Faculty of Forestry) ;  National Science and Engineering Research Council of Canada ;  Haliburton Forest  and  Wildlife Reserve ;  NKU College of Arts and Sciences Grant ;  Österreichische Forschungsförderungsgesellschaft  ( 837393  and  837426 );  Mountain Agriculture Research Unit of the University of Innsbruck ;  Higher Education Commission of Pakistan ;  Kerala Forest Research Institute, Peechi, Kerala ;  UNEP/GEF/TSBF-CIAT  Project  on Conservation and Sustainable Management of Belowground Biodiversity ;  Ministry of Agriculture and Forestry of Finland; Complutense University of Madrid/European Union   FP7  project  BioBio  ( FPU UCM 613520 ); GRDC; AWI; LWRRDC; DRDC;  CONICET (National Scientific and Technical Research Council)  and  FONCyT (National Agency of Scientific and Technological Promotion) (PICT, PAE, PIP) ,  Universidad Nacional de Luján y FONCyT  [ PICT 2293 (2006 )],  Fonds de recherche sur la nature et les technologies du Québec  ( 131894 ),  Deutsche Forschungsgemeinschaft  [ SCHR1000/3-1 ,  SCHR1000/6-1 ,  6-2 (FOR 1598 ),  WO 670/7-1 ,  WO 670/7-2 , and  SCHA 1719/1-2 ],  CONACYT  ( FONDOS MIXTOS TABASCO/ PROYECTO11316 );  NSF  ( DGE-0549245 ,  DGE-0549245 ,  DEB-BE-0909452 ,  NSF1241932 );  Institute for Environmental Science and Policy  at the  University of Illinois at Chicago ;  Dean's Scholar Program  at  UIC ;  Garden Club of America Zone   VI Fellowship in Urban Forestry  from the  Casey Tree Endowment Fund ; J.
Its common name is Geberber, and its fruits are edible  [4]. To the best of the authors' knowledge, at present no data on its chemical composition and/or biological activity have been reported in the literature. As part of a project aiming to valorize Ecuadorian spontaneous flora  [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] , the chemical composition and sensory profile of Myrcianthes myrsinoides (Kunth) Grifo and Myrcia mollis (Kunth) DC essential oils (EOs) are here reported for the first time. Gas chromatography mass spectrometry (GC-MS) and enantioselective GC-MS were used for the quali-quantitative analysis, and GC-olfactometry (GC-O) to evaluate the odor active compounds. Furthermore, both essential oils were tested to evaluate their inhibitory activity on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), two enzymes important as pharmacological targets in the design of drugs active against neurodegenerative diseases such as Alzheimer's disease  [26].
The sensory description of each odorant was determined by two trained panelists and resulting descriptors were consistent with the data reported in the literature. These results derived from the evaluation of two panelists are indeed not exhaustive, from a statistical point of view, to describe correctly the aromatic EO profile. However, they can be considered a contribution useful to justify the similar aroma for two chemically different products. A distinctive woody note was described for α-pinene and β-pinene  [16] , an herbal note for γ-terpinene, a plastic predominant odor for terpinolene, and a floral note for linalool. With M. myrsinoides EO, limonene was perceived with a flavor dilution factor (FD) of 16, while in the M. mollis EO, β-pinene and 1,8-cineole presented a FD of 8. FD were determined by aroma extract dilution analysis (AEDA), which allows a reliable qualitative and quantitative odor analysis of each analyte eluting from the chromatographic column to be obtained  [15].
4 and used at 25 mU/mL. After 10 minutes of preincubation, the substrate acetylthiocholine iodide (1. 5 mM) was added to start the reaction. Multiple 96-well microliter sites were read in the detection system during 30 min of incubation at 30 • C. All measurements were carried out in triplicate. When possible, the IC 50 values were calculated using the GNUPLOT package online (www. ic50. tk, www. gnuplot. info). Donepezil was used as reference ChE inhibitor and showed an IC 50 = 100 nM for AChE and 8500 nM for BChE. With this assay, the possibility of false positive inhibition results previously described for high concentration (> 100 µg/mL) of amine or aldehyde compounds cannot be excluded  [25].
Each collagen type presented three specific bands that were considered and quantified as a single band under Image Quant software (GE Health Care life Science, Grenoble, France). One volume of total protein extract of each of 15 fetuses was mixed and 50 µg of this mixed were deposited on all the gels for normalization. Each collagen type presented two or three specific bands which were considered and quantified as a single band under Image Quant software. The value obtained for the three bands of each sample was divided by the value obtained for the three bands of the mix of samples loaded on each gel. Each sample was measured in triplicate and results were expressed in arbitrary units. The other molecules were not analyzed by Western blot for technical reasons.
Image Acquisition and Analysis Histological sections were visualized under an Olympus fluorescence microscope BX 51 using a 10×, 20× or 40× objective and for fluorescence an adequate band pass filter (Alexa 488: excitation filter 460-495, emission filter 510-550, dichromatic mirror 505LP). High-resolution grayscale images were acquired with an Olympus cooled digital camera DP-72 with cell-F software (Olympus Soft Imaging Solutions, Münster, Germany). Azorubine died-sections were analyzed with a VISILOG 6. 7 professional software (Noesis, Gif sur Yvette, France) to calculate the mean cross-section area of fibers according to Meunier, et al. [29].
Statistical Analysis To evaluate changes before and after the initiation of liraglutide therapy in T2D patients, the non-parametric Wilcoxon test was used for anthropometric data, treatment modifications, and biological parameters. Correlations between quantitative parameters were calculated by the non-parametric Pearson test. Analyses were conducted using R software 2. 14. 0, with the level of statistical significance set at α = 0. 05. The statistical analyses for tests evaluating food behaviour and preferences were done with SAS 9. 4 software. Differences were considered significant when p ≤ 0. 05. For each food product from PrefQuest tests, a comparison of the expected normal distribution of the pleasure ratings and the observed distribution for all participants was assessed with a kappa coefficient.
So, hospital environment was the same that for M3, when they came back. So we do not think that hospital admission could influence the results at M0. We cannot exclude Hawthorne effect and social desirability of our patients; however, our results concerning fatty foods are similar to those recently described by Blundell et al  10. We included non-smokers or mild smokers patients (less than 5 cigarettes per day) who had not smoked since the day before tests. Heavy smokers were not included. As shown in previous data, only heavy smoking (20+ cig/day) alters gustatory pathways  34. Concerning smell impairment, it is shown a dose response with increasing number of daily smoked cigarettes  34  , others studies do not find impact of smoking habits (data collected in Thomas -Danguin et al, 2003  35  ).
Acknowledgements We gratefully acknowledge the help of  Emmanuelle Nedelec  for measuring plasma ghrelin and leptin levels. We also gratefully acknowledge  Suzanne Rankin  from the  Research Department of the Dijon University Hospital  for revising the English. This work was supported by a grant from the  Region of Burgundy, France  ( PARI 2014 ) awarded to  Laurent Brondel  and  Luc Pénicaud.
05), followed by the Nemenyi's post-hoc test when significant difference was found. The relationships between M. hyopneumoniae, M. hyorhinis, and M. flocculare species and the IL-8, IL-10, IL-12, and TNF-α cytokine production level were analyzed for significance using a Kruskall-Wallis unpaired test following by a Kolmogorov-Smirnov test to compare the groups in pairs when a difference was found. For IL-6, since data followed a normal distribution with homogeneity of variance, they were tested for significance using ANOVA following Tukey's post-hoc test when a significant difference was found. A p-value < 0. 05 was considered for significance and a p-value < 0. 1 was considered for a trend. Statistical tests were performed using R software (R development Core Team 2008) and SYSTAT software.
Acknowledgments: We would like to thank  Jean-Philippe Auger  and  Sonia Lacouture  for their assistance in the collection of femurs and in laboratory analysis. We are also grateful to the  Brittany Regional Council , the  Saint-Brieuc Metropolitan Area government , the  European University of Brittany-Loire (France) , and the  "Research Group on Infectious Diseases in Production Animals" of University of Montreal  for their administrative or financial contributions.
In winter 2016-2017, Highly Pathogenic Avian Influenza (HPAI) H5N8 virus spread across Europe, causing unprecedented epizootics. France was massively affected, resulting in the culling of over 6 million poultry. Boosted regression tree (BRT) models were used to quantify the association between spatial risk factors and HPAI H5N8 infection in poultry holdings and to generate predictive maps for HPAI infection. Three datasets were combined to build the model: a dataset of the reported outbreaks in poultry, a dataset of the poultry holdings where the virus has not been reported and a set of relevant spatial risk factors, including poultry production and trade, and water bird habitat. Results identified key associations between the 'foie gras' production systems and HPAI H5N8 risk of occurrence and indicate that strengthening surveillance of fattening duck production systems and making the transportation of fattening ducks more secure would be key priority options for HPAI prevention and control.
Methods Data collection. H5N8 poultry outbreaks. Data regarding all confirmed HPAI H5N8 outbreaks (n = 478) in commercial poultry holdings in France were obtained through the French Ministry of Agriculture (DGAl). A confirmed outbreak was defined as the detection of at least one laboratory-confirmed HPAI H5N8/Nx infected animal (by virus isolation or PCR) in a commercial poultry flock. Outbreak data were grouped at commune (smallest administrative unit in France, with a median surface of 10 km2) level over the period of November 2016 to March 2017, and geo-referenced using the commune centroid coordinates obtained from GEOFLA ® (http://professionnels. ign. fr/geofla). While communes with one or more HPAI H5N8 outbreaks were considered as positive cases, pseudo-negative cases were generated based on two conditions: (i) having a number of poultry holdings >1 to exclude communes without commercial poultry production, and (ii) no HPAI H5N8 outbreaks had been reported (Fig.
Spatial predictor variables. Twelve variables, mainly related to poultry production and water bird habitat were considered for their potential influence on the spatial distribution of HPAI H5N8 outbreaks (Table  1 ). Set 1 included the three following variables containing general information on hosts: the densities of human population, of chicken holdings and of duck holdings per commune. The density of chicken and duck commercial holdings per commune was computed from the DGAl and the organisation of fattening duck producers (CIFOG) databases, which registers all producers of the poultry and the fattening duck sector, respectively. In addition, the human population density per commune generated from GEOFLA ® (http://professionnels. ign. fr/geofla) was included as a proxy variable for surveillance bias and to account for any anthropogenic transmission mechanisms.
Set 2 included the nine following variables containing detailed characteristics of the duck production systems: the densities of holdings raised for meat, of fattening duck holdings, of fattening duck holdings with outdoor access, of incoming and of outgoing fattening duck movements, of force-feeding units, of poultry slaughter houses, of waterways per commune, and the distance between the commune centroids and the closest water bodies. The density of holdings with ducks raised for meat, of fattening duck holdings and of duck holdings with outdoor access per commune were computed by commune from the DGAl and CIFOG databases. The density of outgoing (from the breeding stage) and the density of incoming (to the force-feeding stage) fattening duck movements per commune was computed from the CIFOG database over the period of October 2016 to February 2017.
The list of force-feeding units and of poultry slaughter houses per commune were obtained through the DGAl, from which densities were also computed for each commune. Data on the spatial distribution of wild bird species is generally difficult to obtain at high resolution, with surveillance efforts varying strongly according to the season and to the geographical areas. Therefore, indicators of water presence were used as proxy variables to quantify the possible association between wild birds' habitats and the distribution of HPAI H5N8 outbreaks. The density of waterways (i. e. , rivers, streams, canals, etc. with length >20 m per ha) and the distance between the commune centroids and the closest water bodies (i. e. , lakes, swamps, reservoirs, floods, etc. with area >25 ha) were thus generated from BD CARTO ® (http://professionnels.
In such case, spatially correlated observations could be split over the test or training set during the CV procedure and violate the independence assumption of the test/training set. In case the test set is non-independent of the training set, the procedure to determine the optimal number of trees will fail and the optimal number of trees selected to adjust a BRT will be overestimated. Therefore, spatial CV was implemented to decrease the probability that two observations aggregated in space were split between the test and training set and to measure the generalization performance of the models. The spatial CV uses the 'block' method to partition the dataset into four spatial folds based on the lines of latitude and longitude that divide occurrence localities as equally as possible  9, 24.
Finally, the procedure was repeated 50 times to account for sources of uncertainty in data splitting. The generalization performance of the BRT models was assessed by calculating the predictive deviance, i. e. , y -p f , where y is the dependant variable from testing dataset and p f the fitted probability. BRT profiles were generated to determine the relationship between the predictor variable and the proportion of infected holdings. To facilitate results interpretation, the predicted proportion of infected poultry holdings was converted into a probability of having at least one outbreak in the commune estimated with a Binomial distribution as following, P(X > 0) = 1 -(1-p) n , where n is the number of poultry holdings in the commune and p is the proportion of infected holdings predicted by the Poisson BRT model.
The mean predicted probability of having at least one infected poultry holding per commune was generated and mapped over the whole of France. To check the uncertainty of prediction, the standard deviation of the predictions was also mapped. Models were run in R software version 3. 4. 2  20 using dismo package  21. The data generated and analysed during the current study are available from the corresponding author on reasonable request. Variables selection. A comparison of the BRT models performance was used to reduce the total number of predictor variables in order to deal with multi-collinearity among predictor variables related to duck production (i. e. the coefficient correlations ranged from 0. 52 to 0. 78 between the density of duck holdings and the densities of holdings with ducks raised for meat, of fattening duck holdings, of fattening duck holdings with outdoor access, of force-feeding units, of incoming and outgoing fattening duck movements) and to limit the model overfitting.
Acknowledgements The authors gratefully acknowledge the  Direction Générale de l′Alimentation (DGAl, France)  of the  French Ministry of Agriculture  and the  Comité Interprofessionnel des Palmipèdes à Foie Gras (CIFOG, France)  for supplying the data, particularly  Marie-Cécile Moisson  and  Marie Laborde  for providing additional detailed information about the data. They are also very grateful to  Kim Stevens  ( RVC, UK ) and  Anne-Lise Tran  ( CIRAD, France ) for advice in relation to spatial maps and geocoding, to  Timothée Vergne  ( IRD, France ) for providing useful comments on this research study, to  Mattias Delpont  ( ENVT, France ) for providing detailed information on the French poultry industry, and to  Guillaume LeLoch  ( ENVT, France ),  Nicolas Gaidet  ( CIRAD, France ),  Matthieu Guillemain  ( ONCFS, France ) and  Olivier Dehorter  ( CRBPO, France ) for providing details on the suitable habitats and migrations of wild birds.
This work was carried out within the framework of the  Chaire de Biosécurité at the École Nationale Vétérinaire de Toulouse , which is funded by the  French Ministry of Agriculture. The research leading to these results received funding from the  People Programme  ( Marie Curie Actions ) of the European Union's  Seventh Framework Programme  ( FP7/2007-2013)  under  REA  grant agreement n. PCOFUND-GA-2013-609102, through the  PRESTIGE programme  coordinated by  Campus France.
, 2014; Harding et al. , 2016). It aims to reseed the Solent with oysters, and restore oyster bed habitat to support a self-sustaining population. Since 2017, broodstock oysters are suspended in novel restoration cages from marina pontoons across the Solent to increase reproduction and provide a source of larvae to populate the surrounding seabed. Monitoring of growth, health, survival, reproduction and recruitment is ongoing. In addition, seabed cages containing native oysters were deployed to test their physiological performance and ecosystem service provision at different elevations above the seabed. Effects of density on survival, growth, reproduction, benthic structure and biodiversity are assessed estuary-wide to provide data for future seabed deployment within designated European and UK marine sites.
Acknowledgements. We thank the funding institutions, ARK Natuurontwikkeling,  Blue Marine Foundation ,  European Maritime Fund, German Federal Program for Biological Diversity, FEAMP Aquaculture Innovation ,  Marine Conservation Society ,  Marine Directorate  of the  German Federal Agency for Nature Conservation and Natural Resources Wales , for the substantial support of oyster restoration projects. We also acknowledge our industry project partners  Cochet-Environnement, CRC Bretagne, ESITC-Caen, Glenmorangie, MDL Marinas, WindMW. Furthermore , we would like to thank the members of the  Native Oyster Restoration Alliance (NORA)  for their valuable contributions to the  Berlin Oyster Recommendation  and for sharing their knowledge and thoughts. Two anonymous reviewers helped to improve the manuscript; we thank them for their constructive criticism and helpful comments.
AgroParisTech-INRA Objectives: There are limited data available on true ileal nitrogen and amino acid digestibility of protein sources. The goal of this study was thus to determine for the first time in healthy volunteers the ileal digestibility of zein and whey proteins. Methods: Twenty-two volunteers (10 women and 12 men; aged 37 ± 12y) were equipped with a double lumen intestinal tube positioned at the ileal level. They received a single meal of protein-free biscuits and a drink containing zein (n = 8), whey protein isolate (WPI, n = 7) or no protein (protein-free, n = 7). 13C-inuline was added to the drink as a non-absorbable marker. Ileal effluents were collected over a 9-h period after meal ingestion. Total nitrogen content was measured in effluents and correction for endogenous losses evaluated with the protein-free group was used to determine true digestibility of zein and WPI proteins.
| Behavioural and background data For the individual training, we coded whether the birds successfully cooperated with the human partner (tray locked). For the dyadic and the delay tests, we recorded the number of successful cooperations (tray locked) and cooperation attempts (both birds held the string at the same time but did not lock the tray properly). For the triadic test, we recorded the number of successful cooperations (tray locked) with P1 and P2. We also recorded the behaviour of the initiator (middle subject) with regard to P2 (went to P2 after P1 or did not go) as well as when possible (the video was frequently obscured by the position of the subject) the behaviour of P2 with regard to the partner (no behaviour towards partner, pulled early but stopped, pulled early but stopped and looked to partner's side, first looked to partner's side) and with regard to the timing of the pulling (before partner arrived, when Plexiglas cover was released, when partner also pulled).
08. 2016 database (Supplementary Table  S1 ). αand β-diversity indexes were assessed at the taxonomic rank of OTUs (MOTHUR,  Schloss et al. , 2009). Sample richness estimated by observed richness, Chao 1 index, the Shannon index and Simpson's index were used to compare the soil fungal community α-diversity. To visually identify patterns of community structure among the samples (β-diversity), a Principal Coordinates Analysis (PCoA) analysis based on ThetayC dissimilarity matrix, was performed with MOTHUR  (Schloss et al. , 2009).
Statistical Analysis Differences between leptospermone treatments at days 0, 4 and 45 were assessed using a Kruskal-Wallis non parametric test (P < 0. 05) using "nparcomp" package of R software  (Konietschke et al. , 2015). Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) was performed to select discriminant OTUs between different treatments using the function "splsda" from R package mixOmics  (Lê Cao et al. , 2017).
Infections can spread among livestock notably because infected animals can be brought to uncontaminated holdings, therefore exposing a new group of susceptible animals to the disease. As a consequence, the structure and dynamics of animal trade networks is a major focus of interest to control zoonosis. We investigate the impact of the chronology of animal trades on the dynamics of the process. Precisely, in the context of a basic SI model spreading, we measure on the French database of bovine transfers to what extent a snapshotbased analysis of the cattle trade networks overestimates the epidemic risks. We bring into light that an analysis taking into account the chronology of interactions would give a much more accurate assessment of both the size and speed of the process. For this purpose, we model data as a temporal network that we analyze using the link stream formalism in order to mix structural and temporal aspects.
Introduction Production of dairy and meat products is a major economic field in Europe. Fighting disease spreading is thus a key issue for the protection of economic interests, as well as human health and animal welfare. Among the various routes to infect holdings, such as contamination by wildlife or contacts between herds in pastures, cattle trade movements spread pathogens at national and international levels, and are thus a major way of infection. People and decision makers in Europe have recently become more aware of the problem. In particular, since the Bovine Spongiform Encephalopathy crisis of 1996, each state of the European Union has to identify every bovine on its territory and to register cattle trade movements. The Base de Données Nationale d'Identification (BDNI) database, which is the focus of this work, is the French enforcement of this decision.