dataesr/scientific-paragraphs-categorization huggingface dataset:
The presence of pinkish tones varies considerably. Apothecia ranging from entirely pink to completely devoid of pinkish tones have been observed in the same locality, in KH. 09. 132 and KH. 09. 136, respectively. These two collections have identical ITS sequences (GenBank accessions KM010103 and JN942772). A consistent character, here reported for the first time, is the yellow reaction of the basal mycelium in KOH. Otidea unicisa resembles O. onotica macroscopically, but is distinguished by ornamented spores. Nomenclatural notes -  Carbone (2009)  revised the nomenclature of O. onotica. He considered the plate by Sowerby (1797, as Peziza leporina) the only element seen by Persoon, and thus, the holotype. However, Persoon did indirectly refer to two elements by giving the habitat in the protologue as beech forests (faginetis) and citing Sowerby's plate, which shows an oak leaf.
Otidea flavidobrunneola 29. Otidea lactea J. Z. Cao & L. Fan in Cao et al. , Mycologia 82: 735. 1990  Holotype. China, Heilongjiang province, Yichun City, on ground (rotten wood?) under broadleaf trees, 6 Sept. 1987, J. Z. Cao (HMAS 61359, ex-MHSU 1803). Notes -We were not able to get the material of O. lactea on loan, but it appears to be a distinct species based on the entire, cup-shaped, cream white apothecia and paraphyses with broadly clavate to subglobose apices  (Cao et al. 1990 ). Also, in our LSU phylogeny (including a GenBank sequence of the holotype, DQ443447 from  Liu & Zhuang (2006) ), O. lactea forms a distinct sister lineage (ML 71 %, PP 99 %) to a clade of seven collections of O. minor from Europe (ML 95 %, PP 98 %, Fig. 1 ). Otidea minor differs from O. lactea in the (most often) split apothecia, with a yellow outer surface and often more narrow, straight to bent, subclaviform to claviform paraphyses apices.
31. Otidea oregonensis K. Hansen & Olariaga, ; ITS barcode GenBank KM010048; Fig. 35  Etymology. Named after Oregon, the area where most of the specimens of this species have been collected. Holotype. USA, Oregon, Douglas Co. , Umpqua National Forest, Diamond Lake Ranger District, under Pseudotsuga menziesii and Abies concolor, 7 Nov. 2010, J. Moore, Moorefun 58 (OSC). Isotype (S). Apothecia gregarious to caespitose, 12-48 mm high, 23-80 mm wide, shallowly to deeply cup-shaped, sometimes elongated on one side or obconical, split, seldom entire, sometimes stipitate. Hymenium greyish white (2A2) to pale ochre (4A2-4A4), sometimes with rose stains or spots, when dried pale ochre (4A2 -4A4). Receptacle surface bright citrine yellow (2A6-2A8), slightly hygrophanous, fading to brownish ochre (4B5, 4B6) in age, when dried brownish ochre (4A4, 4B4, 5B4), furfuraceous, sometimes some apothecia wrinkled-veined at the base, seldom with short ribs reaching up 1/3 to the margin, partly covered by white tomentum from the base.
). Based on LSU sequences from GenBank: the holotype of O. crassa is nested within the O. leporina clade (= O. leporina and O. pseudoleporina); O. lactea is suggested to be a sister lineage to O. minor; O. sinensis is resolved as a sister species to O. caeruleopruinosa, but without support; O. yunnanensis forms a monophyletic group with O. kaushalii and O. unicisa; and the type of O. onotica var. brevispora (= O. brevispora) is supported as a sister lineage to O. onotica. The holotype of O. mirabilis is nested among other collections of O. mirabilis and the LSU sequence differs only in 1 bp from sequences of collections from Scandinavia and France.
Rehm 1883, Bresadola 1898, Seaver 1904)ates in O. leporina convert in MLZ into reddish particles and show no reaction in O. myosotis. In the material of O. leporina examined by us, the resinous exudates dissolve in part, can appear unchanged or can convert into reddish particles. Sometimes, small amber-drops have also been observed, though not as strikingly as in other species. Therefore, it seems that the reaction of the exudates in MLZ is variable within O. leporina, and cannot be used to separate O. myosotis from O. leporina. Otidea crassa is a synonym based primarily on the GenBank LSU sequence of the type collection (DQ443444). Nomenclatural notes -When Batsch (1783) described Peziza leporina, he referred to Schaeffer's plate (1763), being unaware or disregarding Schaeffer's later description of 'Elvela' auricula Schaeff.
Olariaga & K. Hansen, sp. nov. -MycoBankMB808972;ITSbarcode GenBank: KM010112;  Fig. 5e, 11Etymology. From ancient Greek ψευδο-, which means 'false, fake', referring to a close relationship with O. leporina. Holotype. USA,Oregon, Douglas Co. , E of Mill Creek, under Pseudotsuga  menziesii, Abies concolor, Pinus lambertiana, 19 Oct. 2010, R. Helliwell,  rh101910 (OSC). Otidea cantharella var. minor sensuKanouse, Mycologia 41: 667. 1949.
Olariaga & K. Hansen, sp. nov. -MycoBankMB808972;ITSbarcode GenBank: KM010112;  Fig. 5e, 11Etymology. From ancient Greek ψευδο-, which means 'false, fake', referring to a close relationship with O. leporina. Holotype. USA,Oregon, Douglas Co. , E of Mill Creek, under Pseudotsuga  menziesii, Abies concolor, Pinus lambertiana, 19 Oct. 2010, R. Helliwell,  rh101910 (OSC). Otidea cantharella var. minor sensuKanouse, Mycologia 41: 667. 1949. Misapplied names -.
Otidea brunneoparva K. Hansen, M. Carbone, Olariaga & Van Vooren, sp. nov. -MycoBank MB537590; ITS barcode GenBank: KM010026; Fig. 13, 14 Apothecia ear-shaped, or cup-shaped and entire, usually clearly stipitate. Spores exceeding 20 µm, biguttulate and with several additional small guttules (except in O. brunneoparva). Paraphyses often strongly notched. Associated with Picea. Species -Otidea brunneoparva, O. cantharella, O. propinquata. 10.
Huesca, Bielsa, Ermita de Nª Señora de Pineta, 1270 m, 42. 638039, 0. 180532 (decimal format), under Pinus sylvestris and Abies alba on calcareous ground, 13 Oct. 2012, J. C. Campos & J. Herranz (S-F242696). Olariaga, Van Vooren, M. Carbone & K. Hansen, sp. nov. -MycoBank MB809252; ITS bar- code GenBank: KM010054; Fig. 19, 21 Etymology. Referring to its similarity to O. formicarum. Holotype. Spain,.
These data were validated by ChIP-qPCR analysis at the Scn4b locus (Supplementary Fig. 8c ). Similar results were obtained with ILC87 cells transduced to constitutively express non-tagged Ikaros (Supplementary Fig. 8d ). To determine whether increased H3K27me3 correlates with decreased gene expression, we generated microarray data from ILC87-Ik1-ER cells treated with 4OHT or vehicle and evaluated the mRNA level of the 61 genes that exhibited increased H3K27me3. Most of the genes showed reduced mRNA expression (Fig. 6a ), which was confirmed by reverse transcriptase-qPCR analysis for Scn4b (Fig. 6b ), suggesting a correlation between H3K27me3 and gene repression. To determine whether increased H3K27me3 is required, we analysed 4OHT-treated ILC87-Ik1-ER cells treated with an Ezh2 inhibitor. This strongly reduced both the global H3K27me3 levels and the 4OHT-induced H3K27me3 increase at Scn4b (Fig.
Acknowledgements We thank  J. Ghysdael  for the pMCSV-mBcl2-DsRed vector and discussions;  W. Pear  for the MigR1 vector;  G. Nolan  for the Eco-Phoenix cells;  A. S. Geimer Le Lay  for the Ik1-ER vector;  P. Marchal  for technical support; members of the  Kastner/Chan lab  for help and discussions;  C. Thibault  for the IGBMC microarray and sequencing platform;  M. Gendron  and  S. Falcone  for animal husbandry; and  C. Ebel  for cell sorting. S. C. and P. K. received grants from the  Agence Nationale de la Recherche  ( ANR-11-BSV3-018 ),  La Ligue Contre le Cancer  ( Equipe Labellise  ´e  2006-2012 ,  2015-2017 ), the  Institut National du Cancer  (INCa # 2011-144 ), the  Fondation ARC  ( SFI20101201884 ,  CR309/8511 ) and Institute Funding from  INSERM ,  CNRS ,  Universitede Strasbourg  and the  ANR-10-LABX-0030-INRT grant.
2  and Supplementary Fig. 2 , linear regression lines were calculated for each WT/mutant pair, and the equation of the line was used for normalization. HOMER was used to generate coverage plots and the data matrices for tag density heatmaps that were normalized using the 10% trimmed-mean for Figs 1b, 3a and 4a, and Supplementary Fig. 1a. Clustering was performed using Cluster 3. 0 and visualized with Java Tree View. For motif analysis of Ikaros peaks, enriched motifs were identified with the MEME software and matched to transcription factor-binding sites in the Jaspar data base with the Tomtom algorithm. The labelling of GGAA-containing motifs as Ikaros motifs derives from ChIP-seq studies for Ikaros in T and B cells  5, 6, [24] [25] [26]. The identity of the Ets1 motif was inferred from the study by Hollenhorst et al.
Probe sequences and further details on the microarray platform can be found on the GEO database under accession number GPL15124. Sample labelling and hybridization were carried out following the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Low Input Quick Amp Labelling)  [31]. For each individual, 100 ng total RNA were linearly amplified and labelled with the fluorescent dye Cy3-dCTP. In order to monitor microarray analysis work-flow, Agilent Spike-in Mix (a mixture of 10 different viral poly-adenylated RNAs) was added to each RNA sample before amplification and labelling. Labelled cRNA was purified with Qiagen RNAeasy Mini Kit and sample concentration and Cy3 specific activity were measured using a Nanodrop ND-1000 spectrophotometer. A Cy3 specific activity between 8 and 17 pmol Cy3 per μg cRNA was considered adequate for hybridization.
The two linked images generated were analyzed together. Data were extracted and background subtracted using the standard procedure in Agilent Feature Extraction (FE) software v. 9. 5. 1. Data was normalized using a quantile normalization procedure using R (http://www. rproject. org/). Normalized fluorescence data from the arrays have been deposited in the GEO database (http://www. ncbi. nlm. nih. gov/geo) under accession number GSE56040. Differentially transcribed genes across samples were identified using the program SAM (Significance Analysis of Microarrays) version 4. 0  [32] , with the FDR cutoff of 5%. Groups (pools of individuals from each of three segments) were compared using the two-class unpaired test and up-and-down regulated Each pool corresponds to 3 individuals from the same segment.
Quantitative RT-PCR validation of microarray results A total of 6 genes showing different transcription levels among segments (claud4, cfl1, s100a1, s100a6, s100a11, thy1) were chosen to validate the microarray results by means of quantitative real-time Reverse Transcription Polymerase Chanin Reaction (qRT-PCR). For each gene, specific primer pairs were determined using the Primer3-Plus software  [33]  (see Additional file 1: Table  S1 ). Gene transcription level was measured by quantitative real-time Reverse transcribed-Polymerase Chain Reaction (RT-PCR), using the β-actin gene as reference. Amplification of cDNA was monitored using the DNA intercaling dye SyberGreen. Real-time PCR reactions were performed in a MX3000P (Stratagene) following the manufacturer's instructions (one cycle at 95°C for 10 min, and 40 amplification cycles at 95°C for 30 s, 60°C for 30 s and 72°C for 30 s).
Acknowledgments We thank  Lorenzo Zane ,  Stefania Bortoluzzi ,  Alessandro Coppe  and all members of  AGC (Anguilla Genomics Consortium)  for their contribution to the ca. 15. 000 contigs microarray of European eel and their permission to use the EELBASE 2. 0 (The European eel transcriptome database version 2, http://compgen. bio. unipd. it/eeelbase/). We are very grateful to  Alice Laharanne  and other members of  Fédération de Pêche de Gironde ,  Nicolas Deligne ,  Romaric le Barh  ( Irstea Bordeaux ) and  Sebastien Dufour  ( Syndicat Intercommunal d'Aménagement des Eaux du Bassin Versant des Etangs du Littoral Girondin ) for their help in sampling, and we truly acknowledge  Christian Rigaud  ( Irstea Bordeaux ) for his field work help and many valuable remarks throughout this study. This work has been supported through the  "HYNES" collaborative project between Irstea  and the  French Electric Company (EDF).
Methods: The research set comprised all posts on the board (n=3645) for each of 3 months selected at 4 monthly intervals over 2011. The data were analyzed using content analysis and multiple coders. Results: A total of 586 relevant posts were identified, 453 (77. 3%) reporting advantages and 133 (22. 7%) reporting disadvantages. Positive personal change (335/453, 74. 0%) and valued social interactions and support (296/453, 65. 3%) emerged as perceived advantages. Other identified benefits were valued opportunities to disclose/express feelings or views (29/453, 6. 4%) and advantages of the BlueBoard environment (45/453, 9. 9%). Disadvantages were negative personal change (50/133, 37. 6%), perceived disadvantages of board rules/moderation (42/133, 31. 6%), unhelpful social interactions/contact with other members (40/133, 30.
The moderators do not, however, participate as members. Although BlueBoard is a formal service rather than a research intervention, all members of BlueBoard consent to the analysis of BlueBoard posts at the time of joining the board, according to an Australian National University (ANU) Human Research Ethics approved protocol. Members learn of the board primarily through online searches and links from other websites. The data were extracted in the form of board posts and reported posts, the latter being messages sent to the board moderators, for example, when reporting a post the member perceived to be inappropriate. These data were analyzed using content analysis, multiple coders, and an inductive approach  [10].
Training Sets In the first instance, three researchers (JR, SV, LB) independently identified and developed a classification system for posts in Training Set 1, which consisted of all posts for October 2010 (n=1220). The coders subsequently discussed and agreed on a common classification system for the positive and negative posts. Two of the coders (JR, LB) then recoded the posts according to the common classification system, further refining it by consensus. Training Set 2 consisted of all posts for September 2010 (n=1295). The refined system was then tested by the two raters on approximately half of the posts in Training Set 2 (599/1295, 46. 25%). Since the raters found it difficult to code the large dataset directly into categories, a two-stage coding process was developed and tested on the second half of the posts in Training Set 2 (696/1295, 53.
Overview A total of 586 posts were found by rater consensus to refer to the advantages and/or disadvantages of participating in XSL • FO RenderX BlueBoard. A total of 212 members contributed to the total research set and 103 to the posts rated as relevant. Of the latter, 97 provided demographic data at registration of whom the majority were women (74/97, 76%), lived in Australia (89/97, 92%), and resided in a city (77/97, 79%). Participant age was recorded in age bands. Using midpoints of the bands for the purpose of calculation, mean participant age was found to be 37. 2 (range 18-19 years to 60-65 years). Of the 94 participants who provided information about their clinical status, 69 (73%) were consumers.
The French research community on the Mediterranean Sea modelling and the French operational ocean forecasting center Mercator Océan have gathered their skill and expertise in physical oceanography, ocean modelling, atmospheric forcings and data assimilation, to carry out a MEDiterranean sea ReanalYsiS (MEDRYS) at high resolution for the period 1992-2013. The ocean model used is NEMOMED12, a Mediterranean configuration of NEMO with a 1/12 • (∼ 7 km) horizontal resolution and 75 vertical z levels with partial steps. At the surface, it is forced by a new atmospheric forcing dataset (ALDERA), coming from a dynamical downscaling of the ERA-Interim atmospheric reanalysis by the regional climate model ALADIN-Climate with a 12 km horizontal and 3 h temporal resolutions. This configuration is used to carry a 34 year free simulation.
Observations are used to constrain the model trajectory to be near as possible from the "real" state of the ocean. Several techniques have been used in the past to produce large-scale reanalysis but regional reanalysis are challenging because observational datasets are scarcer and the use of high resolution model requires to adequately represent fluxes through the air/sea interface. This is even more important for Mediterranean Sea models in a region surrounded by a various and complex topography. Many small-size islands and a particularly complex coastline limit the low-level air flow, channeling potentially strong and recurring regional winds  (Mistral, Tramontane, Bora, Etesian, Sirocco; Herrmann et al. , 2011). The role of the spatial resolution of the forcing has been highlighted as a key aspect of the representation of Mediterranean Sea phenomena such as local winds  (Sotillo et al.
The first results of these reanalyses pointed out for example that such products allow to better simulate the AW salinity inflow, the sea surface height variability, and current-jet pathways. In the same way of these previous studies, we present in this study another reanalysis of the Mediterranean circulation, MEDRYS, performed with different tools and covering the altimetry 1992-2013 period. Our ocean model used is NEMOMED12  (Beuvier et al. , 2012a)  We first present the configuration of the reanalysis in Sect. 2, with the experimental set up, detailing the specifications of the regional configuration of the ocean model, the ALDERA atmospheric forcing and the assimilated dataset. Section 3 presents validation diagnostics and some scientific assessments. Finally, a discussion is conducted on main results and on improvements to be included in further versions of MEDRYS.
, 2005)  in the Mediterranean side and from ORAS4 monthly anomalies  (Balmaseda et al. , 2013)  in the Atlantic side. The exchanges with the Atlantic basin are performed through a buffer zone. From 11 to 7. 5 • W, 3-D temperature and salinity are relaxed toward ORAS4 fields. The restoring term is weak west of Cadiz and Gibraltar areas and increases westwards. As the Mediterranean Sea is an evaporation basin, the model volume is conserved through a damping of the Sea Surface Height (SSH) in the buffer zone toward prescribed SSH anomalies with a very strong restoring. The SSH from ORAS4 is set in the Atlantic according to a strong damping with a very small characteristic time-scale (τ = 2 s). We use the climatological averages of the interannual dataset of  Ludwig et al. (2009)  to compute monthly runoff values, split in two parts  (Beuvier et al.
Atmospheric forcing: ALDERA The most recent long-term hindcast simulations using the NEMOMED12 ocean model  (Beuvier et al. , 2012b; Soto-Navarro et al. , 2014; Palmiéri et al. , 2015)  were driven by the ARPERA2 dataset  (Herrmann et al. , 2010). This forcing was obtained by a dynamical downscaling using the stretched-grid Regional Climate Model (RCM) ARPEGE-Climate and a spectral nudging technique. ARPERA2 covers the period 1958-2013 with a daily temporal resolution and a 50 km spatial resolution over the Mediterranean Sea. It may include temporal inhomogeneities in the 1970s, a period known for ERA-40 humidity deficiency and in 2001 when the large-scale driving fields changes from ERA-40 to ECMWF analysis. In order to overcome the main deficiencies of the ARPERA2 dataset (relatively coarse spatial and temporal resolution, temporal homogeneity issue), we have developed a new forcing dataset for the MEDRYS reanalysis.
This dataset called ALDERA is based on a dynamical downscaling of the ERA-Interim reanalysis  (Dee et al. , 2011)  over the period 1979-2013 by the RCM ALADIN-Climate  (Radu et al. , 2008; Colin et al. , 2010; Herrmann et al. , 2011). We use here the version 5 of ALADIN-Climate firstly described in  Colin et al. (2010). For the model definition, we used a Lambert conformal projection for pan-Mediterranean area at the horizontal resolution of 12 km centred at 14 • E, 43 • N with 432 grid points in longitude and 288 grid points in latitude 1979-2013. Before starting this simulation, a two-year long spin-up is carried out allowing the land water content to reach its equilibrium. Land surface parameters and aerosols concentration are updated every month following a climatological seasonal cycle coming from observations.
All variables required to drive regional ocean models using bulk formula or flux formulation are available. For the MEDRYS reanalysis, the various fluxes have been interpolated every 3 h on the NEMOMED12 grid using a conservative interpolation scheme. All the ALDERA outputs are openly available through the Med-CORDEX database (www. medcordex. eu). Within the frame of the Med-CORDEX initiative, the RCM ALADIN-Climate is also run at lower spatial resolutions (150, 50 km) with exactly the same setting as ALDERA in order to prove the 12 km added-value as illustrated below in Tables  1  and 2  and Figs. 1  and 2.
3. 2. 5). However some individual terms show biases. This is especially true for the shortwave radiation, the latent heat flux (and consequently the evaporation) and the precipitation averaged over the sea surface. Note that ALDERA and ARPERA2 show very similar results, what is expected as they share most of their physical parameterizations. This also means that increasing the spatial resolution in the RCMs does not fundamentally change the mean biases at least from 50 to 12 km. This is confirmed when comparing ALDERA to the ALADIN-Climate simulation at 50 km resolution. ALADIN-Climate ran at 150 km is however closer to ERA-Interim with a weaker latent heat loss. Note that  Pettenuzzo et al. (2010)  dataset also achieves the Mediterranean sea heat budget balance but with lower values both for the shortwave radiation and the latent heat loss.
Variability: from the synoptic scale to multi-decadal trends At the basin scale, the interannual variability of the various terms of the heat fluxes can also be evaluated over the period of the reference dataset  (1985 ( -2004 ( , Sevault et al. , 2014)). For example, for the basin-averaged net shortwave radiation flux, the interannual standard deviation in ALDERA (1. 6 W m -2 ) is underestimated with respect to ISCCP observations (2. 8 W m -2 ) whereas the interannual temporal correlation is equal to 0. 84. For the latent heat loss, the 1985-2004 interannual standard deviation is equal to 5. 6 W m -2 in ALDERA within the range of the observations (4. 7 W m -2 for NOCS and 6. 7 W m -2 for OAFLUX) and the interannual temporal correlation is good (0. 83 with NOCS and 0. 81 with OAFLUX). Interannual standard deviation are lower for the net longwave radiation flux (1.
Conclusions Figures Back Close Full configuration. As the main part of the assimilation scheme used in this paper is already described by  Lellouche et al. (2013) , we will sum up the assimilation methodology and focus on the specifications inherent to the Mediterranean configuration. The SAM2 data assimilation method relies on a reduced-order Kalman filter based on the singular evolutive extended Kalman filter (SEEK) with a 7 day assimilation window (hereafter referred as the assimilation cycle). For each assimilation cycle in MEDRYS, SAM2 produces increments of SSH, temperature, salinity and velocity (zonal and meridional components) from the model and the observations, weighted by the forecast error covariance and the specified observation error. Increments are then applied as a tendency term in the model prognostic equations.