dataesr/scientific-paragraphs-categorization huggingface dataset:
First, the K-matrix was generated using allele sharing similarity, and from this the Q-matrix with eight dimensions  (Dhanapal et al. 2015b ) was generated using multidimensional scaling  (Kruskal and Wish 1978; SAS Institute 2008)  to identify grouping patterns. However, the K-matrix used in the genome-wide association analysis was generated using identity-by-descent. Because the Q-matrix is derived from the K-matrix, part of the Q/K relationship is strictly due to this computation. Using both measures provides a more conservative accounting of population structure. The Null Model Likelihood Ratio Test (SAS ver. 9. 4; SAS Institute, Cary, NC) indicated that the Q-K model significantly (P # 0. 005) improved the description of variance between genotypes in all environments as compared to a model without adjustment for genetic relatedness.
Data availability File S1 contains the ureide means of the 374 plant introductions for the four environments. File S2 describes how to obtain the SNP data from www. soybase. org. File S3 contains the by environment probabilities, 2-environment joint probabilities and FDR adjusted 2-environment joint probabilities for all 33,397 SNPs tested for significant associations with ureide content. Table  S1  shows the SNP information for all SNPs identified as significantly associated with ureide concentration.
Environment and accessions Although environmental conditions were generally more similar between years in Columbia and in Stuttgart than between the locations, considerable variation in environmental conditions was observed among all four environments (Figure  1 ). Solar radiation generally was greater in Stuttgart than in Columbia for both years and generally greater in 2010 than in 2009 for Stuttgart (Figure  1A ). The relative maximum and minimum temperatures (Figure  1, B  and C ) indicated that Stuttgart in 2010 was the warmest environment and Columbia 2009 was the coolest environment. Overall, Columbia received more rainfall than did Stuttgart (Figure  1D ), but the experiments in Stuttgart were supplemented with irrigation as needed (data not shown). Ureide concentration data were obtained on a total of 374 accessions in each of the four environments.
SNP-ureide associations Potential marker associations with ureide concentration were evaluated by comparing the BLUP mean Log(ureide) concentrations of the two homozygous marker alleles for each of the 33,957 SNP markers with a minor allele frequency $0. 03 across all 374 accessions. Log values were used to equalize variances among environments and BLUP means were used to help reduce the effect of extreme values (see Figure  2 ). For each marker, data were analyzed independently within each of the four environments as well as for the overall mean across all four environments. To help control false-positive associations, analyses were conducted with adjustments for population structure (Q-matrix) and genetic relatedness (K-matrix)  (Yu et al. 2006; Zhu et al. 2008). On average the Q-and K-matrix adjustments reduced the number of significant associations detected by approximately 68% at P = 0.
10 up to approximately 99% at P # 0. 0001 across environments and for the overall mean (data not shown). Adjusting for population structure and genetic relatedness and using a stringent probability threshold of P # 0. 0001 identified 40 SNPs with significant associations with ureide concentration in at least one of the four environments (8, 14, 14, and 4 SNPs for C09, C10, S09, and S10, respectively) as well as 15 significant SNP associations with the overall mean. Of these SNPs, seven were significant both in one environment and for the overall mean. Thus, a total of 48 unique SNPs were identified as significant (P # 0. 0001) in at least one environment, with the overall mean, or both. A list of these SNPs and their details are provided in Table  S1. The above results considered associations within each individual environment and for the mean ureide concentration across the four environments.
ACKNOWLEDGMENTS We appreciate the assistance of  Dr. Randall Nelson , curator of the  USDA-ARS Germplasm Collection , in selecting the accessions evaluated in this study and the expertise of  Marilynn Davies  for ureide analysis. This work was supported by  United States Department of Agriculture-Agriculture Research Service  ( USDA-ARS ) project numbers  6066-21220-012-00D  and  8042-21000-275-00D  as well as  United Soybean Board  project numbers  1274 ,  8265  and  9274.
and Table 4 Gene Model CHR a Start End Nearest Putative Locus (Table 4) Database Reference Annotation Glyma. 02g018700 2 1,608,638 1,614,322 2 UniRef100_Q8S3J3 Hydroxyisourate hydrolase Glyma. 02g096500 2 8,678,024 8,680,049 3 UniRef100_A9PGT3 Amidohydrolase family protein Glyma. 02g116300 2 11,326,566 11,332,842 3 UniRef100_G7JZ34 Ureide permease Glyma. 02g129800 2 13,316,095 13,324,448 3 UniRef100_B9HIU1 Adenosine deaminase Glyma. 02g276400 2 45,939,610 45,940,658 4 UniRef100_Q8H1P4 Urease accessory protein Glyma. 02g278600 2 46,109,001 46,113,962 5 UniRef100_G7K315 Dihydropyrimidinase Glyma. 03g013600 3 1,379,993 1,390,392 6 UniRef100_G7KQ26 Adenosine deaminase Glyma. 03g093200 3 27,618,965 27,624,224 9/10 UniRef100_I1JMC0 hydroxyisourate hydrolase Glyma. 05g132200 5 32,517,599 32,522,450 16 UniRef100_B9H494 Nucleotidase Glyma.
V. CONSTRUCTION OF LIKELIHOODS AND PARAMETER EXTRACTION With the detector level differential cross sections obtained in Eq. (  6 ) and Eq. (  10 ) in hand we can then go on to construct the full likelihood for a particular dataset. Before doing so, we must properly normalize the background and signal differential cross sections by performing the full integration over all twelve reconstructed X variables where from now on we drop the superscript R since we only deal with detector level observables in what follows. In this section we present a schematic overview of the normalization procedure. We also at this stage briefly discuss averaging over the production variables (Y, p T , φ) and the implementation of systematic uncertainties through the use of nuisance parameters in the likelihood functions.
D. Comments on Parameter Extraction As discussed in  [13, 17, 32]  the advantage of analytic approaches is that the likelihood can be maximized for a large set of parameters in the most optimal way without losing information. Our framework allows for the 'analytic' nature of these approaches to be maintained at detector level giving us the ability to perform fast and accurate multi-parameter fits for lagrangian parameters directly from the data. This is possible once the convolution in Eq. (  1 ) is performed and after normalization of the signal and background pdfs allowing us to obtain the full detector level likelihood L( A) for a particular dataset. With the likelihood in hand a maximization procedure to find the global maximum can be performed to obtain the value of the parameters for which the likelihood is maximized.
For this task we have incorporated the well established MINUIT  [63]  function minimization/maximization code into our framework. We find excellent rates of convergence and a high degree of stability in locating the global maximum of the likelihood as well as accurate extraction of the parameters as demonstrated in  [38] [39] [40] [41]  where more details can be found. One important feature of the procedure is that the computationally intensive component of evaluating the likelihood only needs to be done for the events in the final dataset used in the fit for a given experiment. Therefore the computationally expensive pieces can be calculated on the computing grid prior to the analysis of the data, and the fit for parameter extraction itself is then completed within a few seconds. This allows for a great deal of flexibility, including testing alternative parameterizations, when fitting the undetermined parameters.
Acknowledgments: The authors are grateful to  Artur Apresyan ,  Michalis Bachtis ,  Adam Falkowski ,  Patrick Fox ,  Andrei Gritsan ,  Roni Harnik ,  Alex Mott ,  Pavel Nadolsky ,  Daniel Stolarski ,  Reisaburo Tanaka ,  Nhan Tran ,  Roberto Vega , and  Felix Yu  for helpful discussions as well as the ATLAS and CMS collaborations for their encouragement and interest in this work. R. V. M. is supported by the  Fermilab Graduate Student Fellowship in Theoretical Physics  and the  ERC  Advanced Grant Higgs@LHC. Fermilab is operated by  Fermi Research Alliance, LLC , under Contract No. DE-AC02-07CH11359  with the  United States Department of Energy. Y. C. is supported by the  Weston Havens Foundation  and  DOE  grant  DE-FG02-92-ER-40701. This work is also sponsored in part by the  DOE  grant No.
In the ongoing debate about front-of-package (FOP) nutrition labels, little data exist regarding nutritionally at-risk populations, although they are critical targets of prevention programs. This study aimed to compare the impact of FOP labels on the ability to rank products according to their nutritional quality among French adults potentially at risk of poor dietary quality (N = 14,230). Four labels were evaluated: Guideline Daily Amounts (GDA), Multiple Traffic Lights (MTL), 5-Color Nutrition Label (5-CNL), Green Tick (Tick), along with a reference without label. Mixed models were used to assess how individual characteristics and FOP labels were associated with the ability to rank products. Older participants and those with a lower educational level, income, nutritional knowledge, and likelihood of reading nutrition facts were less skilled at ranking food products according to nutritional quality.
In addition, participants receive monthly email invitations to complete questionnaires about determinants of eating behavior, health status, etc. The study is conducted in accordance with the Declaration of Helsinki and all procedures were approved by the Institutional Review Board of the French Institute for Health and Medical Research (IRB Inserm n ˝0000388FWA00005831) and the Commission Nationale de l'Informatique et des Libertés (CNIL n ˝908450 and n ˝909216). All participants provide informed consent with an electronic signature. This study is registered in EudraCT (n ˝2013-000929-31).
Socio-Demographic Characteristics and Purchasing Habits Data At baseline and annually, thereafter, participants in the NutriNet-Santé study are asked to provide socio-demographic data, including sex, age (18-30, 30-50, 50-65, >65 years), educational level (up to secondary, some college or university degree), and income (<1200 C, 1200-1800 C, 1800-2700 C and >2700 C per consumption unit). Monthly household income is calculated per "consumption unit" (CU), where one CU is attributed for the first adult in the household, 0. 5 CU for other persons aged 14 or older, and 0. 3 CU for children under 14, following national statistics methodology and guidelines  [29]. For each participant, the most up-to-date available socio-demographic data were used. With regard to nutritional knowledge, participants were asked to self-estimate and report their level by choosing one of four options, ranging from "I know quite a bit about nutrition" to "I don't know anything about nutrition".
The three products were selected based on their differing nutritional quality, thus enabling ranking via the labels (except for the Tick format which enabled distinguishing only the top quality product). No other information on nutritional facts was provided and all quality labels (e. g. , organic certification) were removed from the product images. Nutrients 2015,  7 4  With regard to nutritional knowledge, participants were asked to self-estimate and report their level by choosing one of four options, ranging from "I know quite a bit about nutrition" to "I don't know anything about nutrition". Purchasing habits data comprised information about frequency of reading the ingredient lists and/or nutrition facts (always, often, sometimes, never) on the packages, as well as grocery shopping frequency (always, often, sometimes, never).
Missing covariate data for educational level and income/CU were imputed using the multiple imputation method. Interactions between correlates of FOP label understanding were assessed. Due to significant interactions, the multivariate logistic regression model was used to perform stratified analyses according to the individual characteristics presented above. Sensitivity analyses were performed on the whole sample, without excluding any participants. All tests of significance were two-sided, and a p-value < 0. 05 was considered significant. Statistical analyses were performed using SAS software (version 9. 3; SAS Institute Inc. , Cary, NC, USA).
Acknowledgments We thank all the scientists, dietitians, technicians and assistants who help carry out the  NutriNet-Santé study. We especially thank  Younes Esseddik ,  Yasmina Chelghoum ,  Mohand Ait Oufella ,  Paul Flanzy  and  Thi Hong Van Duong , computer scientists;  Veronique Gourlet ,  Charlie Menard ,  Fabien Szabo ,  Nathalie Arnault ,  Laurent Bourhis  and  Stephen Besseau , statisticians; and the dietitians. We are grateful to the volunteers of the  NutriNet-Santé study. We thank the  French Ministry of Health (DGS)  and the  French National Institute for Prevention and Health Education (INPES)  for supporting this project. The  NutriNet-Santé Study  is supported by the  French Ministry of Health (DGS) , the  French Institute for Public Health Surveillance (InVS) , the  French National Institute for Health and Medical Research (INSERM) , the  French National Institute for Agricultural Research (INRA) , the  National Conservatory for Arts and Crafts (CNAM) , the  National Institute for Prevention and Health Education (INPES)  and the  University of Paris 13.
Therefore, to prevent that nutrient becoming harmful to health awareness of its unique chemical structure and the dose to be administered is necessary. The analytical evaluations include: i) chemical characteristics: data relating to the chemical-nutritional food properties such as macro and micronutrients, minerals, fiber, vitamins, antioxidants during the processing stages; ii) physical characteristics: data relating to processes, such as any heat processing, pasteurization, killing organisms during thermal maturation and ripening; iii) microbiological characteristics: data on food symbiotic microorganisms, or probiotics that confer special properties (presence of particular strains of lactic acid-bacteria or molds and yeasts in dairy products). -Actions 2-5 Identification of Critical Control Point, Critical Limit, Corrective Actions.
Acknowledgement The NACCP process was approved by the  Italian Ministry of Agriculture, Food and Forestry , and  Italian Ministry of Health  (Sector of medicinal plants, D. D. 66563, December 20th 2013). The NACCP process was included in the strategic plan of the  Italian Ministry of Agriculture, Food and Forestry , for innovation and research in agriculture food and forestry (2014). The authors thank  Dr. Elaine Tyndall  for the English revision.
By Eq. (  4 ), an 82 % gain loss translates to a factor 1. 21 count rate reduction during the characterization tests. Since the species calibration sensitivity factors s f used to date have assumed a factor 1. 27 increase, rather than a reduction, we find here that these sensitivity factors should be reduced by 1. 21 ± 21 % times 1. 27, i. e. , β = 1. 55 ± 21 %. Gain measurements on the flight unit during the  T23, 25, 29, 40, 41, 49, 51, 55, 77, 84, and   approximately unchanged since launch. The INMS team plans to update the factors on the Planetary Data System, pending publication of the results reported here.
g. Camelbeeck et al. 2007). The Quaternary activity of the North Artois shear zone is still debated, as no conclusive field evidence of recent tectonic deformation has yet been associated with any of its fault segments. Indirect    Everaerts & Mansy 2001; Camelbeeck et al. 2007 ). The Bouguer anomaly was calculated using the gravity database of the Royal Observatory of Belgium. For France and United Kingdom the data were provided by the French and British Geological Surveys respectively. All gravity data are referenced to the gravity datum Uccle (1976) (IGSN71-0. 048mGal). The density reduction used for the calculation of the Bouguer anomaly on land was 2. 67. Above the sea, the free-air anomaly was used. Grey coloured circle: epicentre of the 2007 Folkestone earthquake  (Ottemöller et al.
M E T H O D O L O G Y A N D AVA I L A B L E D ATA This study is based on the interpretation of several sets of bathymetric and seismic-reflection data (Fig. 4 ) collected across the gravity anomaly observed by  Everaerts & Mansy (2001)  traversing the Dover Strait (see Fig. 2 ). The principal seismic-reflection dataset comes from three geophysical campaigns organized by the Royal Observatory of Belgium (ROB) in collaboration with the Renard Centre of Marine Geology (RCMG) in 2010 and 2012 on board of RV Belgica (cruise reports 2010/09, 2012/03 and 2012/25 available from www. mumm. ac. be). These campaigns consisted of the acquisition of 17 multichannel (total 309 line km) and 48 single-channel (total 487 line km) seismic-reflection profiles over the entire width of the strait and more than 300 km 2 of multibeam bathymetric data from its central part.
These data were complemented with 20 other high-resolution seismic-reflection profiles acquired from the central part of the Dover Strait by the RCMG and Lille University in 2002 on board of RV Sepia II (Dangeard I Cruise), as well as with parts of two bathymetric datasets provided by Imperial College London. The seismic dataset mainly consists of parallel lines. This was due to limitations of collecting lines across the Dover Strait due to strong tides and shipping lane restrictions. The high quality bathymetric data was therefore invaluable to correlate between the seismic profiles. Notably, the high resolution of this (horizontal resolution 1. 5-5 m) and the single-channel seismic-reflection (vertical resolution 1-3 m) datasets permitted the visualization of features as small as 1. 5 m in the centre of the strait.
The Quaternary palaeobasins and palaeochannels are the easiest features to identify in the seismic-reflection data due to the distinct unconformity formed by their basal erosional surfaces (BES). The seismic facies infilling the largest features (i. e. the Fosse Dangeard) comprise several subfacies composed of seismic reflections with low to moderate amplitude. These subfacies are separated (and truncated) by thin packages of high amplitude reflections that seems to correspond to erosional surfaces carved into the sedimentary infill (Fig. 9 ). During this study, we mapped the various Quaternary deposits, constructing isopach maps along the different seismic-reflection profiles by subtracting the two-way times (TWT) of the BES and seabed and assuming a velocity of 1750 m s -1 , as proposed by  Arthur et al.
7a ). The boundaries between the three Chalk formations themselves are much less evident because their seismic facies vary significantly from one profile to another. In this study, we have therefore mapped these boundaries by combining our seismic-reflection and bathymetric datasets with the BRGM borehole descriptions and the bedrock-geological map shown in Fig. 3. All of the sedimentary formations described above outcrop at the seafloor, where they define several subparallel WNW-ESE ridges and sharp slopes resulting from differential erosion  (Figs 5, 6 and 8). Especially marked in the bathymetry are some of the units composing the Lower Greensand and Chalk Groups, which withstand erosion better than the Gault Clay and Wealden Beds formations. For instance, the Hythe Beds form a prominent ridge (in this paper referred to as Greensand ridge) on the seafloor that can be followed over almost the entire width of the Dover Strait (see Figs  8  and 9 ).
03-0. 025 Ma) (e. g. Gibbard 1995). Therefore, with the data presently available we can only state that the Sangatte Fault system has produced deformations less than 1-3 m since the Holocene started. The cumulated offset since the Fosse Dangeard was formed in Middle Pleistocene appears to be of ∼5 m. However, this could be smaller, as the buried scarp on which we measured this offset could have been caused or exaggerated by the erosional process that originated the Fosse Dangeard. In summary, earthquakes of magnitudes equal to or higher than 6 seem to have been very rare in this area since Middle Pleistocene. This makes the AD 1580 an exceptional event. As a matter of fact, assuming that the cumulated deformation accommodated by the Sangatte Fault system during the Holocene epoch is just below the maximal resolution of the geophysical data (1.
, 2013). The lineage cocktail for adult BM, liver, lung, and gut included CD3e, CD4, CD8a, CD19, B220, CD11c, CD11b, Ter119, Gr1, TCRb, TCRgd, and NK1. 1. For ILC1 staining in BM, liver, and gut, NK1. 1 and CD11b were not added to the lineage cocktail. The lineage cocktail for FL, E15. 5 guts, and LN included Ter119, TCRb, CD3e, CD19, NK1. 1, CD11c, CD11b, and Gr1. Samples were sorted on a FACSAria I or FACSAria III and analyzed on a LSRFortessa (BD). Flow cytometry data were analyzed with FlowJo 8. 8. 7 software (Tree Star). Sorted populations were >95% pure. A complete description of all populations analyzed and sorted is available in the Supplemental Experimental Procedures.
ACKNOWLEDGMENTS We thank the  Bioimaging, Rodent , and  Flow Cytometry  facilities at  IMM  and  Institut Pasteur  for technical assistance. We thank  Sreerama Chaitanya Sridhara  and  Sergio Almeida  for technical help and  Francina Langa Vives  ( CIGM ) for Nfil3 BAC microinjection. R. G. D. , D. F. -P. , and M. F. were supported by Fundaca ˜o para a Ciência e Tecnologia, Portugal; H. V. -F. by Fundaca ˜o para a  Ciência e Tecnologia, Portugal ,  EMBO  ( 1648 ) and  ERC  ( 207057 ); and J. P. D. by grants from the  Institut Pasteur, Inserm, LNCC (Equipe Labellisee Ligue Contre le Cancer)  and the  Agence National pour la Recherche  ( Program ''Blanc'' Gut_ILC ). J. P. D. is a founder and stakeholder in the biotechnology company  AXENIS (Paris, France ).
Major societal changes have been observed across the Mediterranean basin during the Mid-Holocene, and in particular, a catastrophic desiccation ca. 4200 yr BP has been suggested to be the trigger of the collapse of the Akkadian Empire in Mesopotamia, the Old Kingdom in Egypt and the Early Bronze Age civilizations of Greece and Crete  (Weiss and Bradley, 2000; Weiss et al. , 1993; Wiener, 2014). These studies have been stimulating an increasing number of debates on climate-culture relationship (e. g. ,  Coombes and Barber, 2005). Uncertainty regarding the societal impact of such an event is still large, due in part that climatic evidence, in many cases, has been derived from regions far from the distribution of ancient settlements (e. g. ,  Cullen et al. , 2000). Although the 4200 yr BP dry event has been observed in several mid-latitude sites, the database remains incomplete and conflicting observations of climatic conditions between seemingly adjacent regions exist  (Magny et al.
7 ka ago  (Kherbouche et al. , 2014). The area is covered by a thin layer (< 10 cm) of soil derived from the limestone bedrock, wind-blown silicate dust, and organic matter from local vegetation such as Pistacia lentiscus, Quercus ilex, Buxus sempervirens, typical Mediterranean Garrigue type plant assemblage (C3 dominated). Local climate is Mediterranean semi-arid type, characterized by hot-dry summers and mild-wetter winters. From the ERA-interim reanalysis data between 1979 and 2013 (http:// apps. ecmwf. int/datasets/) the annual total rainfall is 516 mm, and the annual mean temperature is 17. 2 • C. Rainfall occurs rarely in the summer (37 mm) but relatively evenly through the autumn (155 mm), winter (178 mm) and spring (147 mm). Gueldaman GLD1 Cave is well ventilated with the outside atmosphere due to its larger opening and shorter extension.