dataesr/scientific-paragraphs-categorization huggingface dataset:
Shoreline data Two topographic datasets were gathered to produce a shoreline dataset that covers a 15-year study period from 2000 to 2014. From March 2000 to March 2005, single beach profiles were collected through various means (e. g. , theodolite, DGPS). From April 2005 to December 2014, with a 1-year gap in 2008, 2-4 week sampled topographic surveys were performed at Truc Vert at spring low tide using a centimeteraccuracy Trimble 5700 DGPS. The alongshore coverage increased over the years from about 350-750 m in early 2009 to about 1,500 m in October 2012 onward. The topographic surveys were averaged alongshore to derive a mean beach profile (for more details, see  Castelle et al. 2014 , 2015 and Splinter et al. 2014a). Figure  1c  shows the superimposed mean profiles surveyed from 2005 to 2013 where the elevation is given with respect to the local mean sea level, highlighting the large vertical and cross-shore variability.
Statistical weather regime-driven shoreline model To investigate the predictability of the interannual shoreline variability, a simple model linking seasonal shoreline change and weather regime occurrence is developed. A limited number of weather regimes is used in comparison with existing studies downscaling wave climatology from atmospheric data (e. g. ,  Camus et al. 2014; Laugel et al. 2014 ). Here, using a small number of well-defined circulation patterns is a necessary requirement both to ease interpretation and to achieve a robust statistical model setup as a higher number of circulation patterns would require a longer shoreline dataset. The model f Measured shoreline position using the mean high water level proxy at z=1. 5 m. Gray dots Shoreline positions calculated using single beach profiles, colored dots shoreline positions calculated by averaging the position of the mean high water level iso-contour over an alongshore distance of approx.
Weather regime-driven shoreline model To test the ability of the model to simulate the relationship between the seasonal weather regime occurrence and the interannual shoreline variability, randomization tests are performed. Model input data were replaced by a dataset of 16 random signals following a uniform law with mean and standard deviation similar to the time series of weather regime occurrence. Over 1,000 simulations were performed on random inputs, and the results indicate that the probability to increase model skill is less than 1%. This confirms that the model is not over-calibrated and that there is a physical relation between the combination and succession of the seasonal weather regime occurrence and the interannual shoreline dynamics. According to the above results, large-scale atmospheric fluctuations over the North Atlantic Ocean, described here through the weather regime paradigm, can explain up to 70% of the interannual shoreline variability measured at Truc Vert beach between 2000 and 2014.
shows the time series of shoreline position at Truc Vert combining the whole dataset. Error bars indicate the alongshore standard deviation of the 1. 5-m iso-contour, which is a measure of beach three-dimensionality, with a mean error bar length of 7. 9 m. The large variability in error bars starting in 2005 reflects the strong beach three-dimensional variability throughout the years. The shoreline positions prior to April 2005 are also included, despite their low accuracy blurring the seasonal variability. Nonetheless, this supplementary dataset further highlights a striking interannual shoreline signal within the entire 2000-2014 period. The seasonal cycles are generally characterized by a succession of accretional and erosional periods centered on the summer and winter, respectively. Spring and fall are both transition periods that can be either accretional or erosional, although a slight mean accretion trend is found for both seasons.
Acknowledgments This work was financially supported by the  Carnot-BRGM  scholarship (Carnot 2014 -Action 1) and by the  Agence Nationale de la Recherche  through the  CHIPO  project ( ANR-14-ASTR-0004-01 ). The ERA-40 and ERA-Interim reanalyses are available on the ECMWF Public Datasets web interface (http://apps. ecmwf. int/datasets/). The authors thank the colleagues, including  Stephane Bujan  and  Sophie Ferreira , and PhD students involved with the topographic data collection at Truc Vert over the last 15 years. Two anonymous reviewers as well as the journal editors are gratefully acknowledged for their constructive comments and corrections that greatly improved the manuscript.
MATERIALS AND METHODS Soil and litter samples were collected from different parts of Chaharmahal va Bakhtiari and Khuzestan Provinces. Mites were extracted from samples using Berlese funnels, cleared in lactic acid at 55 °C and then mounted in Hoyer's medium on permanent microscope slides. Line drawings were made using a phase-contrast Olympus BX52 microscope equipped with a drawing tube. Figures were performed with Corel X-draw software, based on the scanned line drawings. Measurements are expressed as mean (minimum-maximum) ranges in micrometers (µm). The dorsal setae notation and leg chaetotaxy followed that of  Lindquist & Evans (1965)  and  Evans (1963b) , respectively. Lengths of leg segments were measured dorsomedially, and tarsi were measured with the stalk and pretarsus. Specimens on which this paper is based on are deposited in the Acarological Laboratory, Department of Plant Protection, Agricultural College, Shahrekord University, Shahrekord (APAS) and some of them are deposited in the Acarological collection of Jalal Afshar Zoological Museum (JAZM), Department of Plant Protection, Faculty of Agriculture, University of Tehran, Karaj, Iran.
ACKNOWLEDGEMENTS We are very grateful to  Prof. Dariusz J. Gwiazdowicz  ( Poznan University of Life Sciences, Poznan, Poland ) and  Dr. Alireza Nemati  ( University of Shahrekord, Shahrekord, Iran ) for helping with identification of ameroseiid mites and  Maria Stanyukovich  ( Russian Academy of Sciences, Great Museum of Antropology and Ethnography, St. Petersburg, Russia ) for sending figures of type materials. We are also very grateful to anonymous reviewers for their valuable comments on earlier versions of manuscript.
In silico docking analysis. To understand the interaction between components of the cerPAC with LasR and LasI protein structures, we performed virtual docking using the Piecewise Linear Potential and Lennard-Jones algorithms that can identify steric and hydrogen bonding interactions, and the Coulomb potential for electrostatic forces. In silico docking analysis was performed using the Molegro Virtual Docker 6. 0 suite without the incorporation of water molecules. To maintain the search robustness, twenty rounds of iteration were used for each docking process. The S-adenosyl L methionine (NCBI Pubchem CID 34756) and the 3-oxo-C 12 -HSL (NCBI Pubchem CID 127864) molecular structures were used as native ligand molecules, for the LasI (RCSB Protein data base ID 1RO5  47  ) and LasR (RCSB Protein data base ID 2UV0) proteins, respectively.
Acknowledgements We thank  Christina Khoo  ( Ocean Spray Cranberries Inc. ) for providing the cerPAC sample,  Marie-Christine Groleau  for technical assistance and helpful discussions,  Sylvain Milot  for technical assistance in the LC-MS analysis, and  Mike Mitzel  for assistance in manuscript editing. N. T. acknowledges  Howard Lam  and  Che O'May  for preliminary work and helpful discussions. This work was supported by the  Natural Sciences and Engineering Research Council of Canada (NSERC) , the  Wisconsin Cranberry Board  and the  Cranberry Institute. N. T. holds the  Canada Research Chair in Biocolloids and Surfaces  and E. D. holds the  Canada Research Chair in Sociomicrobiology.
Limitations of the present study. Although the present study is the first to present data in differentiated cultured human myotubes of 12 different donors ranging vastly in metabolic health and with a relatively high time resolution (13 RNA sampling points within 72 hours), a couple of limitations deserve to be mentioned. First we did not quantify sleep quality, nor did we assess the circadian phase of the donor at the time of the biopsy. Hence, we cannot exclude a putative carry over effect of any abnormalities in sleep or rhythmicity to the cells in culture. We did, however, take all muscle biopsies between 8. 00 and 9. 00 PM from patients without recognized sleep abnormalities. Second, we assessed metabolic data just prior to taking the biopsy and did not follow-up the putative rhythmic profile of metabolic data of the donors for 72 hours, which would have permitted a direct comparison between in vivo data on rhythmicity with rhythmicity in the ex vivo cell model.
Acknowledgements The authors thank the study participants. J. H. is supported by  NUTRIM-School of Nutrition and Translational Research in Metabolism -NWO  Graduate Program financially supported by  Netherlands Organization for Scientific Research  ( 022. 003. 011 ). This work also was partially funded by a  Vici grant  ( 918. 96. 618 ) for innovative research from the  Netherlands Organization for Scientific Research  (to P. S. ). B. S. and H. D. are supported by the  FP7-HEALTH EURHYTHDIA  (grant number  278397 ) and  RESOLVE FP7-HEALTH  (grant number  305707 ) and  EFSD  and  FFRD. B. S. is a member of the  Institut Universitaire de France.
Extreme hydrological events are a direct threat to society and the environment, and their study within the framework of global climate change remains crucial. However, forecasts present numerous uncertainties. This study investigates the modification of precipitation characteristics over East Asia, a region densely populated and vulnerable to extreme rainfall. The performance of the models and the confidence in their projections are analyzed using data derived from an ensemble of models from Phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different factors that can affect the confidence of the projection are considered, such as the resolution, the response to radiative forcing, and the modification of large-scale atmospheric circulation. The resolution and response in radiative forcing do not exhibit a clear correlation with the change in precipitation.
A brief review of the historical CMIP5 ensemble performances First, the capability of the ensemble to simulate the precipitation and monsoon circulation over Asia is reviewed briefly. Figure  2  shows the annual signal of precipitation in Asia for the 1976-2005 period (HIST) for the ensemble mean and the GPCP daily data (averaged over 1997-2007). The 99th percentile is also computed for each grid point over the entire period and then averaged for the Asia domain (5°-45°N, 65°-160°E). Another observational dataset is used for the 99th percentile (PERSIANN,  [42] ), which has a 0. 25° resolution. The mean signal of the ensemble is relatively consistent with observations, and it can detect the seasonal signal for each region, although it tends to overestimate (underestimate) the precipitation over WNPR (EAR) during the summer.
A significant delay in the onset of the monsoon over IR is also visible. The signal of extreme precipitation (99th percentile) is also adequately represented in a comparison between the CMIP5 mean and the GPCP. However, the signal intensity is stronger with a higher-resolution dataset (PERSIANN). This impact of the resolution could also affect the individual model results. Thus, for the 99th percentile, we separated the 10 models with the highest resolution (triangles) and the 10 models with the lowest resolution (circles). The effect of the resolution is clearly apparent, establishing an increased estimation of the 99th intensity according to the highest-resolution models during the Asian summer monsoon (the triangles are closer to the observation line. ). Regarding the spatial distribution (Figure  3 ) for the mean precipitation and wind circulation, biases are more readily apparent.
The result was considered negative when the ratio (threshold/OD) was <0. 9. For the measurement of HDV viral load, total nucleic acids were purified from plasma (Qiagen EZ1 DSP kit), and cDNA (High Capacity cDNA Reverse Transcription Kit; Applied Biosystems) was subjected to real-time PCR according to Ferns et al. ,  5  with minor modifications. The detection limit was 1000 genome equivalents per milliliter of plasma. Anti-HDV prevalence was described with a 95% confidence interval (CI). Fisher's exact test and the Wilcoxon rank sum test were used to compare individual characteristics at ART start between anti-HDV-positive and negative individuals. Analyses were done using SAS version 9. 3 software (SAS Institute, Cary, NC, USA).
Acknowledgements We thank all patients and staff for their participation. The Kilombero and  Ulanga Antiretroviral Cohort  and the  Chronic Diseases Clinic of Ifakara  receive financial support from the  Government of the Canton of Basel, Switzerland , the  Swiss Tropical and Public Health Institute , the  Ifakara Health Institute , the  Government of Tanzania , and  USAID through TUNAJALI-Deloitte. GW was supported by an  Ambizione-PROSPER fellowship  from the  Swiss National Science Foundation  ( PZ00P3_154730 ). The members of the KIULARCO Study Group are:  Aschola Asantiel ,  Manuel Battegay ,  Adolphina Chale ,  Diana Faini , Ingrid.
Time-lapse microscopy For the visualization of early embryonic development in live specimens, embryos were obtained by cutting open gravid hermaphrodites using two 21-gauge needles. Embryos were handled individually and mounted on a coverslip in 7 ml of egg buffer  (Shelton and Bowerman 1996). The coverslip was placed on a 2% agarose pad. Time-lapse Differential Interference Contrast (DIC) images were acquired by an Axiocam Hamamatsu ICcI camera (Hamamatsu Photonics, Bridgewater, NJ) mounted on a Zeiss AxioImager A1 microscope equipped with a Plan Neofluar 100•/1. 3 NA objective (Carl Zeiss AG, Jena, Germany), and the acquisition system was controlled by Axiovision software (Carl Zeiss AG, Jena, Germany). Images were acquired at 10-sec intervals. The timing of cytokinesis in P0 (measured at the time of cleavage furrow initiation) as well as that of Nuclear Envelope Breakdown in AB and P1 (measured at the time of nuclear membrane disappearance) was determined.
The time separating cytokinesis in P0 from NEBD in either AB or P1 corresponds to interphase. Live imaging was performed at 23°using a spinning disc confocal head (CSU-X1; Yokogawa Corporation of America) mounted on a Ti-E inverted microscope (Nikon) equipped with 491 nm and 561 nm lasers (Roper Scientific) and a charge-coupled device camera (Coolsnap HQ2; Photometrics). Acquisition parameters were controlled by MetaMorph software (Molecular Devices). In all cases a 60•, 1. 4 NA PlanApochromat lens with 2 • 2 binning was used, and four z-sections were collected at 2-mm intervals every 25 sec. In Figure  5  and Figure  6 , each image results from a single focal plane (performed with ImageJ/Fiji software).
ACKNOWLEDGMENTS We thank  M. Sarov  and  A. A. Hyman  for providing the fosmid, allowing the generation of the C. elegans line expressing GFP::CDC-7. We thank  R. Sonneville  and  K. Labib  for sharing results prior to publication and  J. Dumont  for generously sharing his microscopy equipment. We acknowledge the  ImagoSeine core facility  of the  Institut Jacques Monod , associated with  Infrastructures en Biologie Santé.
(5. 5) Using Normaliz package in Macaulay 2  [18] , this leads to 104 solutions. The associated covariants form a family of covariants of maximum total degree d + k = 18. The Hilbert series of Cov(S 4 ⊕ S 3 ), computed using Bedratyuk's Maple package  [9] , is given by   [17]. Table  2. Covariant bases of S 3 ⊕ S 4 H(z) = 1 + z 2 + 2 z 3 + d/o 0 1 2 3 4 5 6 # Cum 1 ---1 1 --2 2 2 1 1 1 1 1 1 -6 8 3 1 1 2 2 1 1 1 9 17 4 1 2 2 2 1 -- 8.
We already know one relation on Cov(S 4 ) (see example 7. 5):. Now, writing f = f (a 0 ,. , a 6 , x, y) we compute the exact expression of those monomials in (a i , x, y) and, by computing a kernel, we directly obtain the relation 36h 2  3,12 + h 2,0 f 4 -6f 3 h 3,6 -9h 2,4 f 2 h 2,8 + 18h 3 2,8 = 0. We do in the same way for all other relations. R 1 : 12k 2 3,6 = -6k 3 2,4 -2jv 3 + 3iv 2 k 2,4. (8 We are now able to compute a minimal covariant bases of Cov(S 6 ⊕ S 4 ): • As a first step, we use Normaliz package  [18]  developed in Macaulay2  [37]  to compute irreducible solutions of the linear Diophantine system associated to the covariant basis A and B of Cov(S 6 ) and Cov(S 4 ). To get such a system, we only have to deal with non-invariant covariant of each bases, which then leads to a system of 21 + 3 + 3 = 27 unknowns      2( = u + r 4(β 1 + β 2 ) + 6β 3 = v + r.
For instance, we have 365 order 0 covariants (which are invariants) from degree 3 up to degree Then, using scripts written in Macaulay2  [37]  and algorithm explained in subsection 7. 1, we get a finite minimal family of 60 invariants. We then do in the same way for each order. We give now transvectants expression of this minimal covariant bases. d/o 0 2 4 6 8 10 12 # Cum 1 --1 1 ---2 2 2 2 1 3 1 2 -- 9 Order 0 : 5 invariants from S 6 , 2 invariants from S 4 and 53 joint invariants Degree 3 (h 2,4 , v) 4 Degree 4 (h 2,8 , v 2 ) 8 (h 2,4 , k 2,4 ) 4 (f , k 3,6 ) 6 Degree 5 (h 3,8 , v 2 ) 8 (h 4,4 , v) 4 (h 2,8 , v • k 2,4 ) 8 (f 2 , v 3 ) 12 Degree 6 (h 3,8 , v • k 2,4 ) 8 (f 2 , v 2 • k 2,4 ) 12 (h 2,8 , k 2 2,4 ) 8 (h 3,6 , k 3,6 ) 6 (h 3,12 , v 3 ) 12 (h 5,4 , v) 4 (h 4,4 , k 2,4 ) 4 (h 3,2 • f , v 2 ) 8 Degree 7 (h 2 3,2 , v) 4 (h 5,4 , k 2,4 ) 4 (h 5,8 , v 2 ) 8 (f • h 3,6 , v 3 ) 12 (f 2 , v • k 2 2,4 ) 12 (h 3,2 • f , v • k 2,4 ) 8 (h 4,6 , k 3,6 ) 6 (h 3,12 , v 2 • k 2,4 ) 12 (h 3,8 , k 2 2,4 ) 8 continued on next page continued from previous page Degree (h 3,2 h 2,4 , k 3,6 ) 6 (h 3,12 , v • k 2 2,4 ) 12 (h 3,2 h 3,6 , v 2 ) 8 (h 2 3,2 , k 2,4 ) 4 (h 7,4 , v) 4 (f • h 4,6 , v 3 ) 12 (f • h 3,6 , v 2 • k 2,4 ) 12 (h 3,2 • f , k 2 2,4 ) 8 (h 5,8 , v • k 2,4 ) 8 Degree (h 7,4 , k 2,4 ) 4 (h 3,2 • h 5,2 , v) 4 (h 5,2 • f , v • k 2,4 ) 8 (h 3,12 , k 3 2,4 ) 12 (h 3,2 • h 2,8 , v • k 3,6 ) 10 (fh 4,6 , v 2 • k 2,4 ) 12 (h 2 3,6 , v 3 ) 12 (h 3,2 • h 4,6 , v 2 ) 8 Degree (h 9,4 , v) 4 (h 3,2 • h 2,8 , k 2,4 k 3,6 ) 10 (h 5,2 • h 3,6 , v 2 ) 8 (f • h 6,61 , v 3 ) 12 Degree (h 2 5,2 , v) 4 (f • h 6,62 , v 2 • k 2,4 ) 12 (h 3,2 • h 6,61 , v 2 ) 8 Degree (h 3,2 h 8,2 , v) 4 (h 3,2 h 6,62 , vk 2,4 ) 8 Degree (h 8,2 h 3,6 , v 2 ) 8 Degree (h 3,2 h 10,2 , v) 4 Order 2 : 6 covariants from S 6 and 62 joint covariants.
Using scripts written in Macaulay2  [37] , we thus checked all homogeneous spaces for the finite family already obtained. This leads to no irreducible invariants for this degree. Such computations had thus been done to homogeneous spaces up to degree 21. We now give joint invariants of S 8 ⊕ S 4. For that purpose, we write v ∈ S 4 and k 2,4 := (v, v) 2 , k 3,6 := (v, k 2,4 ) 1. 53 joint invariants of Inv j (S 8 ⊕ S 4 ). Degree 3 (f 3 , v) Lemma C. 2. Let V be a space of binary forms, α, β and γ be three atoms of respective valence n, p, q. Let r be an integer such that r ≤ min(n, p, q); then and we just have to multiply each side of the equation by σ n-r α σ p-r β σ q-r γ. Recall here that, for f ∈ S n and for a given integer k ≥ 0, we have In the same way: Lemma C. 4. If n = 4k, then H 2k is of order n and the family B = {H 2k } is relatively complete modulo I 2k+2 + ∆ where ∆ is the invariant given by: f f f n 2 n 2 n 2.
, 2011). In an effort to identify genes likely to encode enzymes optimized for transforming wood fiber,  Scully et al. (2013)  applied hierarchical cluster analysis of Pfam abundances to compare the gut metagenome of a woodboring pest, Anoplophora galbripennis, to 19 herbivore-related metagenomes  (Scully et al. , 2013). Distinct clusters representing different herbivore biome-types were identified, including herbivore gut communities, fungal gallery communities, and communities associated with insects that feed on heartwood. In contrast to grass-fed mammalian herbivores, North American moose (Alces americanus) and Canadian beavers (Castor canadensis) are iconic Canadian foragers of coniferous and deciduous trees in riparian zones of the boreal mixedwood forests  (Hood and Bayley, 2009). North American moose is the largest browsing ruminant of the deer family Cervidae  (Ishaq and Wright, 2012) , while Canadian beavers Abbreviation: BD, beaver droppings; C, cellulose; CAZyme, carbohydrate-active enzyme; CL, cellulose + lignosulphonate; COD, chemical oxygen demand; CT, cellulose + tannic acid; MR, moose rumen; OTU, operational taxonomic unit; PH, poplar hydrolysate; PCoA, principal coordinate analysis; UPGMA, unweighted pair group method with arithmetic mean.
Data Analyses of Pyrosequences Pyrosequencing flowgrams were converted into sequence reads and quality scores using Roche 454 Life Science propriety software 1  and then analyzed by Quantitative Insights Into Microbial Ecology (QIIME) 1. 8. 0  (Caporaso et al. , 2010). Sequences were quality checked by filtering those with (i) quality scores less than 25, (ii) lengths less than 200 bp, and (iii) longer than 1000 bp. Uclust then clustered highquality 16S rRNA sequences into OTUs at the threshold of 97% sequence similarity  (Edgar, 2010). Representative sequences from each OTU were aligned to the 16S rRNA sequences archived in the Greengenes Database for taxonomic inference  (DeSantis et al. , 2006). Based on the OTU tables, alpha diversity analysis was used to generate rarefaction plots in QIIME.
Biodiversity Indices in Enrichment Cultures Overall, 179,801 high-quality reads were retained for downstream analyses of community structure, richness, and diversity estimators (Supplementary Table  S5 ). Despite extraction of highquality DNA and successful PCR amplification, few reads (less than 15) were retrieved for BD cultivations enriched on CT (data not shown), and so this dataset was removed from downstream analyses. In total, recovered sequences were assigned to 5800 unique OTUs at 97% similarity threshold. In the MR enrichments, the decrease in Chao I (richness) and Shannon (diversity) indices compared to the original inoculum were consistent with enrichment of microorganisms best suited to transform amended carbon sources (Supplementary Figure  S1 ). A similar trend was reported recently in soil microbiota following enrichment with wheat straw  (Jimenez et al.
FUNDING This work was financially supported by  Government of Canada through Genome Canada  and the  Ontario Genomics Institute  as part of the  Bioproducts and Enzymes from Environmental Metagenomes (BEEM)  project (Grant  2009-OGI-ABC-1405 ), as well as the  Government of Ontario  as part of the  Applied Genomics for Functionalized Fibre and Biochemicals (FFABnet)  project ( ORF-RE-05-005 ). MW was funded by a  University of Toronto  Fellowship. MC was funded by a  Marie Curie International Outgoing Fellowship  within the  7th European Community Framework Program (ZyBiom project ).
Results We characterized genotypic data at 24 microsatellite loci and DNA sequences from two mitochondrial, 2 Z-linked and one autosomal gene from 286 sparrows from 32 marshes across the caudacutus-nelsoni hybrid zone and surrounding allopatric populations (Fig. 1 ). We obtained morphological data (plumage, bill, and structural measurements) from 254 of these individuals. Microsatellite loci were highly polymorphic with allelic richness ranging from 4 to 33 alleles per locus (mean = 12. 7). Allelic richness was greater in pure caudacutus populations (mean = 8. 5 alleles per locus, range = 2 -21) than in pure nelsoni populations (mean = 7. 3 alleles per locus, range = 1 -14). Mean observed heterozygosities ranged from 0. 531 to 0. 704 (Table  1 ), with heterozygosity generally increasing from North to South.