dataesr/scientific-paragraphs-categorization huggingface dataset:
Most food items were compiled from other food composition tables. The limitation of this methodology is obvious for mixed dishes in which we had to use similar recipes to calculate the BCAA content, except for Greek dishes in which the recipes were described. For other specific country dishes (such as Turkish, Moroccan, Romanian) BCAA was calculated solely from the recipes. One of the other study limitations was the BCAA content in cheese. CIQUAL contains a large variety of cheeses not found in other tables. In these cases, a similar type of cheese was substituted. The contribution of food groups to BCAA intake was calculated for the SPI collection to have representation in the French collection, and indeed our results were similar to others reported in the literature. At this stage of the development, this study has several limitations, particularly related to the validation of the BCAA database and potential correlation between the dietary intake and plasma levels of amino acids.
Indeed, the database should be validated based on guidelines of FAO/INFOODS  [60]  including tagnames for food items, criteria for establishing recipes and mixed dishes. In next steps, several tools might be used such as compilation tool FAO/INFOODS 1. 2. 1. Since most food items are coming from international databases and publications data at this stage there are no reasons to doubt about the accuracy of data. However, a special action of checking will be performed in the future. Another important issue is that the coefficient of variation for amino acids in food groups are approximately homogenous, which ideally should be kept between 10 and 20%. Along this line, database quality will be assessed in the future using several progressive grades and scoring. Another aspect that should be considered in perspective is the potential correlation with plasma levels of BCAA at various intake levels.
Finally, there are several future improvements expected for the program itself. One major feature is obviously the advice component, which depends on the algorithm to be used. In collaboration with the Bioinformatics Department of the University of Montpellier, preliminary work was initiated for constraint programming. Such an algorithm will not solve the difficult problem of menu planning but can be useful in determine BCAA content in food repertoires in rare cases of inborn errors of metabolism due to genetic defects in BCAA catabolism specific for each of the three BCAA  [24]. Other features to be considered in the near future include the possibility of the administrator calculating recipes similar to the former SIDI program, use of more languages such as Arabic, which would be useful in North Africa, and adaptation of the program for smartphones.
Conclusions In conclusion, MEDIPAD and its associated BCAA database provide a useful integrated software system that help to handle acquisition, evaluation, and compilation of food composition data and is applicable in the Mediterranean area. Besides BCAA plasma measurements in research studies, the program is an obligatory step for the accurate estimation of BCAA intake for further nutrigenomic investigations. Accessible from iPAD or laptop computer and already written in four languages, the program uses a friendly interface, which is useful for practitioners since is web-linked and secure, thus facilitating storage of data in France on a server with secure archiving (everyday) system and backup (each week) at the university site. MEDIPAD offers numerous possibilities for data extraction for statistical analysis and may be completed with new databases for food items.
Supplementary Materials: The following are available online at http://www. mdpi. com/2072-6643/10/10/1392/ s1, Figure  S1 : Screenshot of the MEDIPAD software illustrating the registration of 24HDR for the breakfast; Figure  S2 : Screenshot of the MEDIPAD software illustrating the registration of 24HDR for breakfast in the first day and possible corrections to assess quantity of foods; Figure  S3 : Distribution of BCAA content by centiles in CIQUAL French database and food items from SPI surveys; Table  S1 : Mean BCAA content (g/100 g) by food groups in 1331 compiled food items of CIQUAL; Table  S2 : Clinical features of patients from SPI collection stratified by BMI. Table  S3 : Contribution of food groups to total and individual BCAA intake in age category 9-13 years old in SPI surveys stratified by gender and nutritional status; Table  S4 : Contribution of food groups to total and individual BCAA intake in age category 14-18 years old in SPI surveys stratified by gender and nutritional status.
G. , D. C. , C. B. , D. Y. , C. L. , M. J. , J. Š. , S. M. , M. P. , F. H. , R. G. , J. M. M. , S. L. , E. K. , C. P. , D. L. , G. S. , V. T. , S. A. , A. Z. and I. S. ; Writing-original draft, S. H. , Y. C. , C. L. and F. G. ; Writing-review & editing, F. G. Funding: MEDIGENE research project was funded by European Commission grant FP7-279171 under the coordination of F. G. at University of Montpellier, France (https://cordis. europa. eu/project/rcn/101810_en. html).
3. Turkish food items and dishes (n = 72) were included from Turkish Food Composition Database (TürKomp) (http://turkomp. gov. tr/database?type=foods), and recipes calculated from Turkish cuisine had been developed by the Ministry of Health (General Directorate of Primary Health Care & Primary Healthcare Department of Nutrition and Physical Activity) [50]. 4. Romanian (n = 22) and Moroccan (n = 32) dishes (mixed-dishes) were also added and calculated in SIDI program using the National Composition Table of foods available for Romanian foods (http://hunkbody. ro/tabel-cu-continutul-nutritiv-al-alimentelor/).
T. , P. G. , D. C. , C. B. , D. Y. , C. L. , M. J. , J. Š. , S. M. , M. P. , F. H. , R. G. , J. M. M. , S. L. , E. K. , C. P. , D. L. , G. S. , V. T. , S. A. , A. Z. and I. S. ; Writing-original draft, S. H. , Y. C. , C. L. and F. G. ; Writing-review & editing, F. G. Funding: MEDIGENE research project was funded by European Commission grant FP7-279171 under the coordination of F. G. at University of Montpellier, France (https://cordis. europa. eu/project/rcn/101810_en. html).
The case definitions of HAIs aim to accommodate differences, across Europe, in diagnostic practices such as taking microbiological samples for the diagnosis of HAIs. The minimal requirement for participation in surveillance of HAIs in ICUs is surveillance of bloodstream infections (BSIs) and pneumonia (PN). Reporting of urinary tract infections (UTIs) and catheter-related infections (CRIs) is optional. The data are collected by the national surveillance systems and submitted annually to ECDC. The results are published on the ECDC website  [2]. A software application, HelicsWin. Net, is available free-of-charge for entry of HAI surveillance data (https ://ecdc. europ a. eu/en/publi catio ns-data/ helic swinn et-hwn). The latest update of the ECDC protocol was triggered by the unexplained, large variation in the prevalence of HAIs among European countries reported by the ECDC point prevalence survey of HAIs and antimicrobial use in European acute care hospitals 2011-2012.
Acknowledgements Anne Savey ,  Coordination Center for Healthcare-associated Infection Prevention and Control in South-Eastern France, Lyon, France ;  Mercedes Palomar ,  Institut Recerca Biomedica Lleida (IRBLL) ,  Lleida, Spain ;  Antonella Agodi ,  University of Catania, Italy; Michael Hismayr, Medical University Vienna, Austria ;  Karl Mertens ,  Scientific Institute of Public Health (WIV-ISP ),  Brussels ,.
4). In the present study we choose U 0 , U 1 to be a perfect coherent structure (i. e. kink or breather) propagating in the required direction. The pseudo-code for the discrete time evolution U k , k 2 is given in Algorithm 1. We first advance the bulk of the edges and then update the graph vertices where several edges begin or end. The update is done using condition  (3. 5). A vertex is associated to U k (1, j) if branch j is out-going from it and U k (n, j) if branch j is entering it. The source code, implemented in the Matlab environment is freely available to consult and download at the following URL: https://github. com/dutykh/sineGordonGraph/ Algorithm 1 Algorithm to simulate a Hamiltonian equation, like the sine-Gordon (sG) equation on a network. Here n d is the degree of each vertex in the graph G.
Conclusions and perspectives We considered a discrete formulation of a scalar Hamiltonian equation on domains which are not manifolds and applied it to the sG equation. More precisely, the 1D lattices are assembled into arbitrary graphs (networks) and the coupled dynamics can be efficiently simulated using our methodology based on a simple symplectic numerical scheme. The edges of the graph deserve a special treatment based on local conservation laws. The performance of this formulation is illustrated on a connected graph involving four cycles. Our computational methodology can easily be generalized to the case where edges or vertices are active as for many engineering applications like fluid or traffic networks. The Matlab source code, which implements the algorithms described in this study can be freely accessed at the following URL address:   The numerical results revealed a sequence of topological changes during the collisions of elementary sG kinks at the graph vertices.
Spermatophores were identified as glossy white pellets in spermatheca under a stereo microscope and transferred separately to DNA purification wells. To minimize between-species DNA contamination risk, each batch of dissections, DNA purifications and amplifications of spermatophore DNA was performed on females of the same species. Each DNA sample was assigned to species A or B using a single diagnostic PCR of the Internal Transcribed Spacer 2 (ITS2) gene, which yields an amplicon of a specific size for a given species  (Peccoud et al. 2013). Individuals showing two bandsputative hybrids -were reprocessed through DNA extraction (re-using their carcasses after washing in water) and PCR in order to minimize the risk of DNA contamination being interpreted as hybridization. To identify the maternal species of each confirmed hybrid, we Sanger-sequenced a mitochondrial region encompassing the COI gene (sequences are available under Genbank under accession numbers xxx).
1995). Site-group activation indicators, κ, were sampled using Reversible Jump MCMC  (Green 1995). The model and MCMC algorithm were written and executed in NIMBLE 6. 10 (de Valpine et al. 2017) within R 3. 4. 1 (R Development Core Team 2017). One hundred MCMC chains of 600,000 iterations were run, the first 100,000 iterations were removed as burn-in and samples were saved each 50 iterations. Concatenated output (10 6 samples in total) was analyzed using R package CODA. Source code and data are available at https://bitbucket. org/DRJP/reproductive_isolation_mcmc/.
Manual separation and cleaning was per- formed by visual inspection and correlation of the original BSE image with the corresponding segmentation. Where necessary, the segmentation was corrected and cleaned with the pencil tool in Photoshop®. Clean phase maps contain segmented pyroxene and amphibole phases, and each pyroxene grain is in contact only with its own amphibole corona. The x-y coordinates of the clast (pyroxene) and the aggregate (pyroxene + corona) outlines are measured and exported using Fiji and a modified version of the Jazy XY export macro (by Rüdiger Kilian, available at https://github. com/kilir/Jazy_macros; last access: September 2016). Using a MATLAB script (available from the author upon request), the x-y coordinates of clast and aggregate outlines are converted to polar coordinates (r-θ ), and the corona thickness, thc(θ ), is determined at each point along the pyroxene clast as the shortest distance between the clast to the aggregate outline (Fig.
Albite crystallographic preferred orientation Three EBSD maps are collected along one shear band in the Ab+En sample 518. Orientation data of plagioclase from three distinct sites (Fig. 12 ) are used to test for the presence of a crystallographic preferred orientation (CPO). Grains are calculated with a threshold angle of 10 • and merged across boundaries consistent with the albite twin law. Porphyroclasts and their adjacent fragments as well as grains with < 2 µm equivalent diameter and < 3 points are excluded (Fig. 12b ). The pole figures (Fig. 12c ), which combine the data of all three sites, show a weak but distinct CPO for which especially [010] and (010) show systematic arrangements of a maximum ∼ 35 • off the periphery and with a high angle to the trace of the shear band. [100] axes and poles to (110) form local maxima along the trace of the shear band plane.
A4 Strain and flow descriptors The ISA and the finite stretching direction can be derived because the initial thickness of the shear zone is known (with an error of ±0. 03 mm) and the end thickness can be measured after the experiment from the thin section. This uncertainty associated with the initial thickness leads to some uncertainty concerning the amount of thinning and therefore also to a range of values for the ISA, the finite stretching direction, and Wk. A5 Microstructure analysis A5. 1 Data acquisition SEM analyses are performed either with the Zeiss Merlin SEM at Tromsø University or with a Philips XL30 ESEM at the nano-imaging lab of the Swiss Nanoscience Institute (SNI) at Basel University. Chemical analyses are performed using standardless energy-dispersive X-ray spectrometry (EDS) at 15 keV of acceleration voltage with a ZAF matrix correction for spectra quantification.
A5. 2 EBSD analysis For electron backscatter diffraction (EBSD) measurements, thin sections were polished with colloidal silica suspension and subsequently coated with a thin layer of carbon. Samples were analyzed in the Zeiss Merlin SEM at the University of Tromsø with a Nordlys nano-camera in high vacuum at 15 keV of acceleration voltage and probe currents of ∼ 15 nA. Data are acquired with the Oxford AZtec software and processed with Channel 5 and the MATLAB toolbox MTEX (available at https://mtex-toolbox. github. io, last access: January 2018;  Bachmann et al. , 2010). Orientation data are analyzed and plotted using MTEX. The de la Vallée Poussin kernel with a half-width of 10 • was used for pole figure contouring, whereas a kernel half-width of 12 • was used for contouring of inverse pole figures (IPFs).
A5. 3 Image analysis Phase segmentation is performed on BSE-SEM images, whereby individual minerals are identified by their Z contrast. Using the software Fiji (link at: http://fiji. sc/Fiji; last access: August 2017) and the plugin Statistical Region Merger, automatic pre-segmentation was achieved. The automatic segmentation was then manually inspected and corrected where necessary. Grain maps were produced by manually tracing (supervised segmentation) grains from SEM or TEM images. Grains were analyzed for their 2-D area using Fiji, and for each grain the diameter of the area equivalent circle, d equ , is calculated. d equ = 2 • (A/π ) (A4) A is the area of the digitized shape. Grain size distributions are presented as histograms of the 2-D number-weighted distribution of equivalent diameters.
Shear bands are traced and digitized on BSE-SEM images. The x-y coordinates of the outlines of the digitized structures are smoothed to remove pixel artifacts and exported using Fiji. The smoothed x-y coordinates are used as input for the SURFOR program  (Panozzo Heilbronner, 1984; Heilbronner and Barrett, 2014) , which determines the orientation distribution function (ODF) of the boundary segments. The ODFs are presented as rose diagrams.
Acknowledgements. We thank the team of the center for nanoimaging (SNI) at the  University of Basel and Tom Eilertsen at Tromsø University  for help and assistance with the electron microscopy. Terry Tullis  is thanked for providing the Maryland diabase material, and the Cranberry Lake diopside was kindly provided by  Jacques Précigout. Willy Tschudin  is thanked for excellent thin section preparation. We gratefully acknowledge the funding provided by the  Swiss National Foundation  grant  NF 200020_144448  and financial support from the  Freiwillige Akademische Gesellschaft, Basel , during the last stages of finishing this paper. John Wheeler  and  Andrew Cross  are thanked for thorough reviews and their suggestions and comments to improve the paper. Edited by: Michael Heap Reviewed by:  John Wheeler  and  Andrew Cross.
Many if not all assays provide imperfect detection of plant pathogens and, as a result, generate false absences or false zeros in the data set. We estimated detection probabilities-and thereby distinguished true zeros from false ones-using the source plant observation and vector observation sub-models (Eq. 3 and 4). These equations model the processes that generate false zeros for detecting X. fastidiosa in source plant petioles and vectors (z i obs SP and z i obs V , respectively) and relate this to our measured X. fastidiosa populations (Xf i SP and Xf i V , respectively). The variables of primary interest here are the detection probabilities, p obs SP and p obs V , for source plant petioles and vectors, respectively. The structure of these observation sub-models is similar to N-mixture models for imperfect detection for estimating population abundances  (Royle 2004 (Royle , reviewed in D enes et al.
2015)). Finally, we model the test plant infection process (Eq. 5). Here, the variables of interest are the coefficients b 9 , b 10 , and b 11 that estimate the relationship between probability of transmission, p i trans , to source plant genotype (DSF or WT) and to X. fastidiosa populations in vectors, k i V. Because coefficients for each genotype are included in this sub-model, we can estimate overall probabilities of transmission for each genotype. We took a Bayesian approach to fitting the hierarchical transmission model. We fit the model using the Markov chain Monte Carlo (MCMC) engine provided with the NIMBLE package (version 0. 6-10) for R 3. 5. 0 (NIMBLE Development Team 2015, de Valpine et al. 2017, R Core Team 2017). We used vague priors for the coefficients and probabilities (Eq.
6), and three MCMC chains each with 110,000 iterations and a burn-in period of 10,000. We assessed MCMC chain convergence by calculating the Gelman-Rubin diagnostic and effective sample size  (Gelman and Rubin 1992, Brooks and Gelman 1998). R code for fitting models is available at https://doi. org/10. 5281/zenodo. 1445808.
ACKNOWLEDGMENTS We would like to thank  Dylan Beal ,  Alexandra Catesson ,  Thomas Dequipe ,  Emily Yao ,  Jeffery Ezennia , and  Tina Wistrom  for help with maintaining plants and insect colonies, culturing, and laboratory work. Renee Koustoukis  helped with collecting dormant grape cuttings. We received helpful comments on our results and manuscript from  Sandy Purcell ,  Matt Daugherty ,  Clelia Baccari , members of the  Almeida Lab , and two anonymous reviewers. This study was funded by the  PD/GWSS Program ,  California Department of Food and Agriculture  (agreement number  15-0217-SA ).
Results Genetic data. We analysed a combination of published and newly generated microsatellite data from 30 pinniped species, with a median of 253 individuals and 14 loci per species (see Methods and Supplementary Table  1  for details). Measures of genetic diversity, standardised across datasets as the average per ten individuals, varied considerably across the pinniped phylogeny, with observed heterozygosity (Ho) and allelic richness (Ar) varying by over two and almost five-fold respectively across species (Supplementary Table  2 ). Both of these measures were highly correlated (r = 0. 92) and tended to be higher in ice breeding seals, intermediate in fur seals and sea lions, and substantially lower in a handful of species including northern elephant seals and monk seals (Fig  1A ). Bottleneck inference.
Therefore, although studies of individual species are usually limited by uncertainty over the underlying mutation characteristics, our ABC analyses converged on similar estimates of mutation model and rate across species, allowing us to appropriately parameterise our bottleneck analyses. To explore whether our results could be affected by population structure, we used STRUCTURE  41  to infer the most likely number of genetic clusters (K) across all datasets. For all of the species for which the best supported value of K was more than one (n = 12), we recalculated genetic summary statistics and repeated the bottleneck analyses based on individuals comprising the largest cluster. Using the largest genetic clusters did not appreciably affect our results, with repeatabilities for the genetic summary statistics and bottleneck signatures all being greater than 0.
Methods Genetic data. Microsatellite data were obtained from a total of 30 pinniped species including three subspecies of ringed seal (summarised in Supplementary Table  1 ). We generated new data for five of these species as described in the Supplementary methods, while the remaining datasets were previously published. Sample sizes of individuals ranged between 16 for the Ladoga ringed seal to 2386 for the Hawaiian monk seal, with a median of 253 individuals. The number of loci genotyped varied between five and 35 with a median of 14. Phylogenetic, demographic, life history and conservation status data. Phylogenetic data were downloaded from the 10k trees website  46  and plotted using ggtree  47. The three ringed seal subspecies were added according to their separation after the last ice age  48.
Data cleaning and preliminary population genetic analyses. In order to maximise data quality, we checked all datasets by eye and generated summary statistics and tables of allele counts to identify potentially erroneous genotypes including typographical or formatting errors. In ambiguous cases, we contacted the authors to verify the correct genotypes. As several of the datasets included samples from more than one geographical location, we used a Bayesian approach implemented in STRUCTURE version 2. 3. 4  41  to infer the most likely number of genetic clusters (K) across all datasets. For computational and practical reasons, we used the ParallelStructure package in R  50  to run these analyses on a computer cluster. For all of the species for which the best supported value of K was more than one, we recalculated genetic summary statistics and repeated the bottleneck analyses based on individuals comprising the largest cluster and calculated repeatabilities including confidence intervals for all variables using the rptGaussian function in the rptR package  51.
Genetic diversity statistics. In order to examine patterns of genetic diversity across species, we calculated observed heterozygosity (Ho) and allelic richness (Ar) with strataG {Archer:2017vj} as well as the proportion of low frequency alleles (LFA), defined as alleles with a frequency of <5%, using self-written code. For maximal comparability across species with different sample sizes, we randomly sampled ten individuals from each dataset 1000 times with replacement and calculated the corresponding mean and 95% confidence interval (CI) for each summary statistic. Heterozygosity-excess. We quantified heterozygosity-excess using the approach in  18  implemented in the program BOTTLENECK version 1. 2. 02  53. BOTTLENECK compares the heterozygosity of a locus in an empirical sample to the heterozygosity expected in a population under mutation-drift equilibrium with the same number of alleles as simulated under the coalescent  15, 16.