dataesr/scientific-paragraphs-categorization huggingface dataset:
html; AMO values: https:// www. psl. noaa. gov/data/timeseries/AMO/). Local environmental parameters included depth, phytoplankton biomass, sea surface temperature, salinity and bed shear stress. Sea surface temperature SST (°C) was extracted from the HadISST1 database of the Hadley Centre for Climate Prediction and Research  [54]. Surface salinity (SSS; PSU: Practical Salinity Unit) was obtained from the NORWECOM biogeochemical model (NORWegian ECOlogical Model)  [55]. Bed shear stress data (Bstress; water velocity over the bottom) were obtained from a 3D hydrodynamic model  [56]. Phytoplankton biomass was estimated with the Phytoplankton Colour Index (PCI), derived from a Continuous Plankton Recorder towed by ships. All PCI values were extracted from the Continuous Plankton Recorder Survey dataset (https://www.
Including a functional component in management plans would likely provide more relevant species conservation statuses with respect to ecosystem functioning and equilibrium  [81]. Ethics. All abundance data used in that study are collected and provided by the International Council for the Exploration of the Sea (ICES), which is a world leading marine science organization that aims to advance and share scientific understanding of marine ecosystems and the services they provide and to use this knowledge to generate state-of-the-art advice for meeting conservation, management, and sustainability goals. All trawling operations performed during the IBTS survey were authorized by local authorities in the various countries around the North Sea.
Acknowledgements. This research is supported by the  Fondation pour la Recherche sur la Biodiversité (FRB)  and  Electricité de France (EDF)  in the context of the  CESAB  project ' Causes and consequences of functional rarity from local to global scales ' (FREE). We especially would like to acknowledge all persons involved in the North Sea IBTS survey. We thank the reviewers who improved the quality of this paper.
To shed light on this, we look at the teleconnection and how it is represented. This is done by quantifying in each simulation the correlation coefficient between the summer ATL3 and Niño3 at different lags, to estimate how strong their covariability is and how it evolves in time (Fig. 2d ). Also, to evaluate the realism of this teleconnection, we compute the same correlations for the observational dataset HadISST. These correlations are negative, as expected from previous literature linking warm (cold) summer ATL3 phases with the later occurrence of cold (warm) winter ENSO events  9, 10. Their comparison shows that all models underestimate the teleconnection strength (i. e. , the magnitude of the negative correlation), with some models showing values close to the observed ones, while in others the correlation is close to zero.
A bottom boundary layer scheme, similar to that in ref. 50 , is used to improve the representation of dense water spreading. The Louvain-la-Neuve Sea-Ice Model version 3 (LIM3  51  ) is integrated into NEMO, with dynamics based on Beckmann and Döscher  52  and thermodynamics based on Semtner  53. The ocean sea-ice component NEMO-LIM3 uses a time step of 3600 s. The atmosphere and ocean sea-ice components of EC-Earth are coupled every 3 h with the Ocean Atmosphere Sea-Ice Soil coupler version 3 (OASIS  54  ). Protocol for the sensitivity study. Three sets of seasonal hindcasts, also referred to as retrospective forecasts, have been performed with EC-Earth using the Autosubmit workflow manager  55. The first one, labeled as "CTR," is the same one used in the multi-model analysis. Its atmospheric component is initialized from ERA-interim reanalysis data  56  , while the ocean component from the ocean reanalysis ORAS4  57.
For SST we use the monthly gridded dataset HadISST v1. 1 from UK Met Office  59. For surface winds, we use the ERA-Interim reanalysis  60. For consistency among the verification products, our reference velocity potential at different heights is computed from ERA-Interim velocity fields using the corresponding functions from the Climate Data Operators v1. 6. 3  61. Forecast evaluation of the multi-model ensemble is done using seasonal averages. Tools and metrics for the statistical analysis and significance assessment. The statistical analysis and the significance assessment have been performed with two R-packages, s2dverication  62  and SpecsVerification (https://cran. r-project. org/ web/packages/SpecsVerification/). ACC and RMSE metrics are calculated from ensemble means. In the correlation maps that involve simulations, the ensemble members are concatenated into a single time series prior to the computation.
Acknowledgements E. E. 's work was supported by the  FP7- PREFACE  project (grant agreement number:  603521 ) and the  H2020  project  TRIATLAS  (grant agreement number:  817578 ). C. P. was supported by a  Spanish Juan de la Cierva  ( JCI-2016-30802 ) fellowship and P. O. by a  Ramon y Cajal  ( RyC-2017-22772 ) fellowship. B. R. d. F. , T. L. , and I. P. are supported by the  European Union   Seventh Framework Program  ( FP7/2007-2013 ) under Grant Agreement  603521  ( PREFACE-EU  project) and the  Spanish  Project  CGL2017-86415-R. We are grateful to  Francisco J. Doblas Reyes  for his valuable feedback.
Data availability NMME data have been downloaded from the IRI database (http://iridl. ldeo. columbia. edu/SOURCES/. Models/. NMME/). EUROSIP and ERA-interim data have been downloaded from the MARS computing facility of ECMWF (https://www. ecmwf. int/en/ forecasts/). Data from EC-Earth predictions are available on request from the corresponding author (E. E. ). HadISST v1. 1 and ERSSTv4 are publicly available at: https://www. metoffice. gov. uk/hadobs/hadisst/data/ and https://www1. ncdc. noaa. gov/ pub/data/.
6d ), this contains 'anti pinch points' -'bow-ties' (finite intensity perpendicular to Q) rather than 'hour-glasses'(finite intensity parallel to Q) -reminiscent of some antiferromagnets. Such a re-construction from neutron scattering data on three dimensional spin ice materials would result in bow-tie patters strongly resembling those observed in the model pyrochlore antiferromagnets that were highly influential in the early days of frustrated magnetism  [35]. It is a pleasure to thank Y. Levin for a useful correspondence, A. Alastuey, B. Canals, T. Dauxois, D. McMorrow and T Roscilde for useful discussions and the following for financial support: EPSRC, UCL, the Leverhulme Trust, ANR grant FISICS, the IUF (Roscilde), the ENS de Lyon and the National Science Foundation under Grant No. NSF PHY-1748958 at KITP.
qi qj Eij qi ± q qj ∓ q Eij ± q/ 0 The simulations were run for 250,000 thermalization sweeps and 500,000 subsequent sweeps for a lattice of linear length L = 128 (N = 16384), with measurements taken every 20 sweeps. OpenMPI is used to perform identical simulations with different random seeds, in this case over 32 nodes. For each measurement various thermodynamic quantities are sampled and the current field configuration is Fourier transformed using the FFTW 2D real-to-complex transform. After each simulation, the Fourier-transformed correlation tensor S αβ (q) was eigendecomposed to extract the longitudinal and transverse eigenvalues, which were then used to construct the longitudinal and transverse field components S L (q) and S T (q). The code used can be found at http://github. com/cuamll/mr.
1, capillary-electrophoresis-ABI3500xl DX, Sequence-Navigator-1. 0. 1-Applied Biosystems) using forward and reverse custom primer pairs. Databases, such as ExACGenome browser (http://exac. b roadinstitute. org), dbSNP152 (National Center for Biotechnology Information [NCBI], Bethesda, MD, USA, http:// www. ncbi. nlm. nih. gov/projects/SNP/), ClinVar (www. ncbi. nlm. nih. gov/clinvar), DECIPHER v9. 29 (https://decipher. sa nger. ac. uk/), and FrExAC (http://lysine. univ-brest. fr/ FrExAC/), were also screened. A review of the literature was performed, based on PubMed (https://www. ncbi. nlm. nih. gov/pubmed), and all the published articles presenting mutations on FIG4, HSPB3, and REEP1-POLR1A were collected.
Copy number variations (CNVs) CNVs were assessed through CovCop-software-v. 1. 2. 1. 8 he REEP1 duplication was confirmed through multiplexligation-dependentprobeamplification (MLPA) (SALSA-MLPA-P213-HSP mix-2 probemix, MRC-Holland). Further investigation was performed through CGH-array on G3HumanCGHmicroarrays8x60K (Agilent Technologies).
Discussion We report here three patients harboring the FIG4p. Ile41Thr mutation at the homozygous state, among which two are the first confirmed cases. 6 Out of 764 patients screened for CMT-related mutations in our laboratory, 12 (1. 57%) presented with a FIG4-p. Ile41Thr mutation. 3/12 were homozygous for this mutation. The first surprising feature of this report is the presence of a high proportion of homozygotes in our cohort of FIG4-p. Ile41Thr patients. Indeed, as the prevalence of this mutation is estimated to be of 1. 10 -3 in the general population, 9 homozygous cases are expected to be relatively rare. The presence of three cases in a priori unrelated families in the French population could have suggested a possible increase of FIG4-p. Ile41Thr heterozygosity in this population. However, screening of the FrExAC database showed an allele frequency in accordance with the estimates in the literature.
10 Moreover, the involvement of a new founder effect in the French population seems unlikely insofar as we observed no new haplotype common to our three patients. In addition, two variations in genes known for their implication in neurological disorders have been detected in two of our three patients. Although our bibliographic study did not suggest any clinical relevance of this particular HSPB3 variant, several articles and databases have related REEP1 duplications, involving or not POLR1A. 11, 12 xposed cases show different phenotypes, from spastic paraplegia to autism spectrum disorders. In the case of proband C, none of these symptoms were reported by the physician, neither in the patient nor in his mother and brother suggesting the noncausative effect of this REEP1-CNV. In the same fashion, pedigree analysis for proband B seems to exclude any causative effect of his HSPB3 variant.
, 2018 [17]. Single-end reads were paired (make. contigs command) and paired reads with more than 5 bases overlap between the forward and reverse reads were kept. Only 100-600 bases long reads were retained (screen. seqs). Chimeras were checked using Uchime in Mothur with more abundant sequences as reference (chimera. uchime, abskew = 1. 9). Sequences were clustered into OTUs at the 97% similarity threshold using the VSEARCH program in Mothur (cluster, dgc method). Individual sequences were taxonomically classified using the rdp classifier method (classify. seqs, consensus confidence threshold set to 80) and the greengenes database (13_8 release) for 16S rRNA data, the UNITE_public database (version 12_2017) for fungal ITS1 and the Pr2 (version 4. 10. 0) for oomycete ITS1. The PhiX genome was included in each of the databases to improve the detection of remaining PhiX reads.
Each OTU was then taxonomically classified (classify. otu, consensus confidence threshold set to 66), OTUs with unknown taxonomy at the Kingdom level were removed, as were low abundance OTUs (< 50 reads, split. abund). Sample alpha-diversity analysis was conducted on OTU abundance tables, using Shannon's H diversity index (estimate_richness function in phyloseq package). Data normality was checked (Shapiro-Wilk's test) and means were compared by ANOVA followed by Tukey's HSD (P < 0. 05). Beta-diversity analyses were conducted on transformed (log10 (x + 1)) OTU relative abundance tables. Bray-Curtis dissimilarities between samples were computed and used for non-metric multidimensional scaling ordination (NMDS, function 'ordinate', Phyloseq package). A PerMANOVA analysis on Bray-Curtis dissimilarities was conducted to identify the main factors influencing the structure of the leaf microbiota ('Adonis', Vegan package, 10 000 permutations, P < 0.
The taxonomical classification of core OTUs was used to compute pairwise dissimilarities (distances) between OTUs ('daisy' function, Cluster package in R, Gower's distance) which were used for hierarchical clustering ('hclust' function, Cluster package in R). The obtained dendrogram was modified in the browser version of iTOL (version 5. 5. 1) [22]. Network analysis. Bacteria, fungi and oomycete OTU tables were merged and used for correlations calculation using either the Spearman correlation coefficient in Co-Net  [23]  or the SparCC algorithm  [24]  which relies on Aitchison's log-ratio analysis and is designed to deal with compositional data with high sparsity like this data set (sparsity = 74%)  [25]. OTU tables were filtered to OTUs present in at least 5 samples with >10 reads per OTU (sparsity = 53%).
e. the fraction of shortest paths passing through a given node) and closeness centrality values (i. e. the average shortest distance from given node to each other node). Node-rewiring score (Dn-score) was calculated via the DyNet package in Cytoscape  [27]. For each node, its connected neighbors are compared between two networks and the changes (rewiring) are quantified. Microbial hubs were identified as top 5% OTUs showing maximum betweenness centrality and closeness centrality scores. Sequencing data is available under NCBI Bioproject PRJNA438596. OTU tables and scripts are available here https://github. com/IshtarMM/Dynamic_LeafMicrobiome.
A consequence of this taxonomic imprecision is that the generic placement of species is often doubtful. Most species are currently attributed to the pseudomelatomid genera Leucosyrinx and Comitas, with 26 and 53 valid Recent species, respectively (MolluscaBase), while the cochlespirid genera Comispira and Sibogasyrinx only include two and three species, respectively. Furthermore, while DNA sequences of only seven species of Leucosyrinx (four undescribed), three of Comitas (two undescribed), two of Comispira and two of Sibogasyrinx are available in GenBank, molecular data from Indo-Pacific material in the Muséum national d'histoire naturelle (MNHN) revealed the existence of numerous undescribed species of Sibogasyrinx, including several that cluster with the type species, S. pyramidalis  (Schepman, 1913).
The aim of this publication is the clarification of the diagnosis of Sibogasyrinx and a taxonomic revision of the genus based on molecular and morphological data. Table 1 (continued on next three pages). List of examined material included in molecular phylogenetic analysis. ABGD PSH = Automatic Barcode Gap Discovery, primary species hypothesis; BOLD = Barcode of Life Datasystem; GB = Genbank. New BOLD and GB sequences are highlighted in red. Reg. no.
Acknowledgments Specimens were obtained during research cruises and expeditions organized by the  MNHN  and  Pro-Natura International  as part of the  Our Planet Reviewed program , and by the  MNHN  and the  Institut de Recherche pour le Développement  as part of the  Tropical Deep-Sea Benthos program  (DongSha 2014 and NanHai 2014 in the South China Sea; AURORA 2007 and PANGLAO 2005 in the Philippines; SALOMON 2 and SALOMONBOA 3 in the Solomon Islands; BIOPAPUA, KAVIENG 2014, MADEEP and PAPUA NIUGINI in Papua New Guinea; BOA1 and SANTO 2006 in Vanuatu; EXBODI, KANADEEP and TERRASSES in New Caledonia; EBISCO in the Chesterfield Islands; MIRIKY in Madagascar; GUYANE 2014 in French Guiana), and we are grateful to numerous cruise leaders and co-PIs:  Wei-Jen Chen ,  Philippe Bouchet ,  Marivene Manuel Santos ,  Laure Corbari ,  Stephane Hourdez ,  Ludivina Labe ,  Peter Kee Lin Ng ,  Karine Olu-Le Roy ,  Bertrand Richer de Forges  and  Sarah Samadi.
If the diversification model is lineage-homogeneous, the total time complexity of this computation is quadratic with the size of the phylogeny (i. e. , its total number of nodes) and linear with the total number of constraints. Its memory space complexity is quadratic with the size of the phylogeny. In practice, it can deal with phylogenetic trees with hundreds of tips on standard desktop computers. This computation can be used to obtain the divergence time distributions of a given undated phylogeny with temporal constraints, which can be applied to various questions. First, it can be used for dating phylogenetic trees from their topology only, like the method implemented in the function compute. brlen of the R-package APE  (Grafen, 1989; Paradis et al. , 2004). It also enables us to visualize the effects of the model parameters on the prior divergence times distributions, to investigate consequences of evolutionary assumptions etc.
A natural application of this computation is to test diversification shift in undated Gilles Didier phylogenies. It is used to define a likelihood ratio test for diversification shift which is compared with three previous approaches studied in  Wertheim and Sanderson (2010). Last, the approach presented here can be extended in order to take into account fossils. In  Didier and Laurin (2020) , we started to work in this direction by determining divergence time distributions from tree topologies and fossil ages under the fossilized-birth-death model in order to obtain better node-calibrations for phylogenetic inference. C-source code of the software performing the computation of divergence time distributions and their sampling under (piecewise-constant-)birth-death-sampling model and the shift detection test is available at https://github.
Patterns In this section, we shall consider diversification processes starting at origin time s and ending at time e following a birth-death-sampling model Θ = (s, e, λ, µ, ρ). A pattern is a part of the observed diversification process starting from a single lineage at a given time and ending with a certain number of lineages at another given time, these ending lineages being either observable or special, where "special" means "only known to be alive at the end time (and selected for some reason in the dataset)". It consists of a 3-tuple (t, t , T ) where t and t are the start and end times of the pattern and T is the resulting tree topology. We shall consider two types of patterns: standard and special patterns. Standard patterns ends with only observable lineages. All the ending lineages of a special pattern are observable except one which is special (Fig.
In the case where the general birth rate is 0. 4 and the the shifted one is 1, the ability to distinguishes between phylogenies with or without diversification shift is almost as good with our likelihood ratio as with that of the perfect information. In the case where the general birth rate is 0. 6, the likelihood ratio test Λ N obtained from Theorem 3 outperforms the other tests for all positive discovery rates lower than 40%. In order to illustrate the diversification tests on a biological dataset, let us consider the calibrated phylogeny of Cetacea from  Slater et al. (2010) , which is displayed in Figure  9. Slater et al. (2010)  detected a diversification rate increase in Delphinidae using MEDUSA, a detection method developed in  Alfaro et al. (2009). The general idea of MEDUSA is to fit birth and death models with increasing numbers of diversification shifts by stopping when the improvement in the Akaike Information Criterion (AIC) is smaller than a fixed threshold.
, 2014)  and FPKM values (generated by FPKM count  Wang et al. , 2012)  were processed using the Cufflinks  (Trapnell et al. , 2012)  pipelines that identified statistically significant gene expression differences between the sample groups. Following identification of differentially expressed genes (at an FDR < 0. 05) we focused on identifying differentially expressed pathways using a significance threshold of FDR < 0. 05 unless otherwise specified. The gene lists used for GSEA were as found on the BROAD institute GSEA MSigDBv. 7 'molecular signatures database'. The deposited data set (BioProject, accession PRJNA421806) can be accessed through the following link: https://www. ncbi. nlm. nih. gov/bioproject/PRJNA421806.
Acknowledgements This study has been supported by the  Medical Research Council  ( MR/L016729/1 ,  MR/T012153/1 ) (CLA), The  Lister Institute of Preventive Medicine (CLA) , the  Deutsche Forschungsgemeinschaft (DFG German Research Foundation ) (Project Number  314061271 -TRR 205 ) (CLA), the  Howard Hughes Medical Institute (RN) , the  Agence Nationale de la Recherche  ( ANR-18-CE14-0017 ), and  Fondation pour la Recherche Medicale  ( DEQ20150331732 ) (PM). JPR was supported by a  Dianna Trebble Endowment Fund Dental Institute Studentship , EJL by the  King's Bioscience Institute  and the  Guy's and St Thomas' Charity Prize PhD Programme in Biomedical and Translational Science , and YK by a Project Support Grant from the  British Society for Neuroendocrinology. We thank  Dr AF Parlow  and the  National Hormone and Peptide Program  ( Harbor-University of California, Los Angeles Medical Center ) for providing some of the antibodies used in this study and  Prof.
J Drouin  and  Prof. S Rhodes  for TPIT and PIT1 antibodies respectively. We thank the  High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics  (funded by  Wellcome Trust  grant reference  090532/Z/09/Z ) for the generation of the sequencing data. For flow sorting and analysis, this research was supported by the  National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. We thank.
This study combined phenotypic data from eld-based visual ratings, re ectance data, and greenhouse evaluations to identify genome-wide associated (GWAS) marker-trait associations (MTA) using genotyping-by-sequencing (GBS) data. Several MTAs were identi ed for sugarcane aphidrelated traits across the genome, with a few common markers that were consistently identi ed on SBI-08 and SBI-10 for aphid count and plant damage as well as for re ectance indices-based traits on SBI-02, SBI-03, and SBI-05. Candidate genes encoding leucine-rich repeats (LRR), Avr proteins, lipoxygenases (LOXs), calmodulins (CAM) dependent protein kinase, WRKY transcription factors, avonoid biosynthesis genes, and 12-oxo-phytodienoic acid reductase are identi ed near SNPs that had signi cant associations with different SCA traits.
S. sorghum breeding lines  39. Our objective was to examine the hypothesis that there may be multiple genomic regions associated with aphid resistance other than the RMES1 locus and other QTL identi ed on SBI-06. To identify new regions of the sorghum genome that confer resistance to the sugarcane aphid, we used 276 accessions from the existing SAP database plus 7 additional inbred lines with resistance to sugarcane aphid or other insects, to perform genome-wide association (GWAS) for sugarcane aphid resistance using different insect-related phenotyping traits such as the number of aphids, plant damage rating, and other physio-morphological traits. To facilitate the rapid assessment of plant damage across all accessions we used UAS multi-spectral imagery to corroborate the damage assessed through visual inspection.
Wall-to-wall coverage of the index values was used to score aphid damage more accurately across the entire eld. Only the UAS-based data collected on August 25, 2020, was used for analysis as it had a high correlation to manual phenotyping and high heritability values. The NDRE value ranged from 0. 12 (high aphid damage) to 0. 51 (low or no aphid damage) with a mean of 0. 28. The NDVI scores ranged from 0. 16 to 0. 78 with a mean of 0. 46, while the SAVI score ranged from 0. 07 to 0. 41 with a mean of 0. 16 (Supplementary Table  S1-c ). The average plant height for the two growing seasons was 106 cm, ranging from 39 to 285 cm (Supplementary Table  S1-c ). Flowering time ranged from 41 to 97 days after planting, with an average of 59 days after planting.