dataesr/scientific-paragraphs-categorization huggingface dataset:
In order to verify that this approach did not produce idiosyncratic results  (Jones et al. 2001 ), a second highly experienced observer (TA) who was blind to the context of the recording controlled the classification of a subset of syllables (947 syllables produced by 2 subjects, corresponding to 14 % of the total dataset) and agreed in 894 cases (94 % agreement). We measured temporal parameters by manually delineating onsets and offsets of syllables in the oscillograms and created spectrograms to measure mean peak frequency (MPF) (FFT length, 1,024; frame, 100 %; overlap, 75 %; Hamming window) using the "automatic parameter measurements setup" with interactive element separation from section labels, that is, based on the manual delineation in oscillograms. Temporal parameters were measured with a resolution of 2.
Therefore, on the same dataset of the three most frequent syllable types, we estimated renditionto-rendition consistency of overall syllable shape by means of spectral cross-correlation. To this end, we used the spectrogram cross-correlation function (CCF) within the classification option of Avisoft and calculated the averages of all pairwise comparisons of syllable renditions (see Table  1 ). To rule out that our findings were influenced by seasonal or daytime effects, we tested whether those parameters for which we found context-specific modulation (lowest MPF, song density, and CV of MPF) changed with the time of the day (measured as minutes after sunrise) and the season (measured as number of days after the start of the experiment). All but 1 of the 12 correlations (3 parameters in each of 2 contexts) were nonsignificant (mean p=0.
Statistical analysis Statistical analyses were conducted using R2. 13. 0 (http:// www. r-project. org/). We tested for normality using Shapiro-Wilk tests. In cases of normal distributions, we used a paired t test to compare song parameters in spontaneous and reactive singing and Pearson's product-moment correlation to test for correlations with daytime and season. Where distributions were not normally distributed, we used paired samples Wilcoxon tests or Spearman's rank correlation. When entering several measures per subject into the analysis, we used generalized linear mixed models (GLMMs) implemented in R2. 13. 0 and the addon package nlme  (Pinheiro et al. 2009 ). The dependent variable was the relevant response measure (CCF, CV of  syllable duration, gap duration, sound density, and MPF); the independent variable was the context (spontaneous or reactive singing).
Acknowledgements Many thanks to  Juliette Linossier  for help with the fieldwork and to the farmers for allowing us to work on their land. François Chiron ,  Fabien Martayan , and  Dieter Schmidl  kindly helped us in trying to catch the skylarks. We thank  Hélène Courvoisier  and  Fanny Rybak  for discussions. Hélène Courvoisier ,  Henrik Brumm , and two anonymous reviewers deserve thanks for constructive comments on an earlier version of this paper. This work was supported by a grant of the  European Research Network in Neurosciences of the National Centre for Scientific Research (CNRS), France  and the  Max Planck Society (MPG) ,  Germany  ( GDRE CNRS-MPG Neuroscience grant ) to NG. Ethical standards All work conforms to the  ABS/ASAB  guidelines for the treatment of animals in behavioral research and teaching, and the.
TCTEX1D4 expression in different tissues By performing a NCBI EST database analysis with TCTEX1D4 mRNA (NM_001013632. 2) a total of 42 hits in Sus scrofa, Rattus norvegicus, Mus musculus, Homo sapiens and Danio rerio were retrieved. From the total ESTs identified, 45% corresponded to female reproductive tract related tissues (ovary, oviduct, placenta, uterus and embryonic tissue). Head related tissues (head, hypothalamus, brain, corpus striatum and tongue) corresponded to 21% and lung to 17% of the total ESTs. Moreover, in the databases no ESTs were found in testis, although it was already described in previous work by Northern blot  (Meng et al. , 2006). A tissue screen of TCTEX1D4 protein expression was consequently performed on several rat tissues and human testis (Fig. 4 ). The results show that TCTEX1D4 is highly expressed in ovary, spleen, lung, placenta and kidney.
Bioinformatics analysis Full protein sequences of intermediate chains (ICs), light intermediate chains (LICs) and light chains (LCs) were obtained from Ensembl database to check for PPP1 binding motifs. The ICs human homologues are: the axonemal inner arm IC1 (ENSP00000242317) and IC2 (ENSP00000308312), axonemal outer arm IC138 (ENSP00000360065) and IC140 (ENSP00000294664), and cytoplasmic DYNC1I1 (ENSP00000320130), DYNC1I2 (ENSP00000380308). The LICs human homologues are the cytoplasmic DYNC1LI1 (ENSP00000273130), DYNC1LI2 (ENSP00000258198) and cytoplasmic from intraflagellar transport DYNC2LI1 (ENSP00000330752). The LCs human homologues are the DYNLRB1/LC7/ Roadblock (NP_054902. 1), DYNLRB2/LC7/Roadblock (ENSP00000302936), DYNLL1/LC8 (ENSP00000376297), DYNLL2/LC8 (ENSP00000240343), TXNDC3/LC5 (ENSP00000199447), TXNDC6/LC5 (ENSP00000372667), DNAL1/LC1 (ENSP00000310360), DNAL4/LC6 (ENSP00000216068) DYNLT1/Tctex1, DYNLT3/RP3, TCTEX1D1, TCTEX1D2/Tctex2b, TCTEX1D3/Tctex2/Tcte3, and TCTEX1D4/Tctex2b.
Acknowledgements This work was supported by the  Centre for Cell Biology of the University of Aveiro , by grants from  FCT of the Portuguese Ministry of Science and Higher Education  to L. K. -G. ( SFRH/BD/42334/ 2007 ), S. I. V. ( SFRH/BPD/19515/2004 ), S. L. C. E. ( SFRH/BD/41751/ 2007 ),  J. A. ( SFRH/BPD/73512/2010 ), P. J. E. ( SFRH/BPD/27021/ 2006 ),  E. F. C. S. ( POCI/SAU-OBS/57394/2004 ;  PPCDT/SAU-OBS/ 57394/2004 ) and M. F. ( PTDC/QUI-BIQ/118492/2010 ), by a  Reequipment Grant  ( REEQ/1023/BIO/2005 ), by  CRUP  ( E-92/08 ; B-32/ 09 ) and by the  German Academic Exchange Service (DAAD)  with a grant to G. L. ( DAAD/50112116 ).
Acknowledgments We thank  Colette Berthey-Bongay  for her precious help in ceramide quantification. We thank all who participated in the experiments at  GSI  and GANIL. We acknowledge the contribution of the flow cytometry platform of  SFR BioSciences Gerland-Lyon-Sud  ( UMS3444/US8 ). This work was performed within the scientific framework of ETOILE and the  LABEX-PRIMES. It was supported by the  "Contrat-de-Plan-Etat-Region , the  "Ligue-contre-le-Cancer (Ain)", EURONS , and " Verein-zur-Förderung der Tumortherapie mit schweren-Ionen e. V".
PARTICIPANTS Seventy-seven preschool children (mean age 4;1; range 3;2 to 5;1, 41 females) participated in the experiment. Three additional children took part but their data were excluded due to lack of participation in either the give-a-number task (n = 1) or the number comparison task (n = 2). Children were recruited and evaluated in local preschools in Mexico City, Mexico. Children were tested individually in a quiet space such as the school library or a classroom. Prior to the tasks of interest, children were always tested first on the Count List Elicitation task with the aim of confirming that they could recite the counting list. After this task, the give-a-number task and then the number comparison task were performed. Children were assigned in a pseudo-counterbalanced manner with respect to one of the three visual control conditions of the number comparison task (density, total filled area, and correlated and anti-correlated area) to make sure that CP-knowers and non-CP-knowers were assigned equally to each visual control.
ACKNOWLEDGMENTS This research was supported by funds awarded to  N. Arias-Trejo :  Investigación Científica Básica CONACyT 167900 and Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica PAPIIT IG   300313-2. We acknowledge the contributions of the staff of the  Reino Infantil school , and thank the children and parents who participated in the present study.
Unlike spo11-6xHIS-3xHA, the SPO11-18xMYC did not affect spore viability of rec114-8D strains (data not shown). Spo11-myc ChIP was performed without the use of formaldehyde (FA) cross-linking to enrich for Spo11 proteins that had remained covalently bound to the break ends upon DNA-cleavage. To ensure the highest degree of comparability between the three REC114/rec114 allele Table  1. Spore viability of the different rec114 alleles in various genetic backgrounds. Relevant genotypes of the strains to which REC114, rec114-8A, or the four different rec114-phosphomimetic alleles in the ''REC114 allele'' column were introduced to assess potential genetic interaction(s). Relevant Genotype 2 None 3 ½rec1 1 4 rec1 1 4 D 4 spo1 1 -HA spo1 1 -HA spo1 1 -HA spo1 1 -DA spo1 1 -DA spo1 1 -DA pch2 D pch2 D REC114 Allele 1 REC114 0.
Cytological methods Surface spread meiotic chromosomes were prepared as described  [14]. Staining was performed as described  [14]  with the following primary antibodies: rabbit polyclonal anti-Rec1141 (1: 100, F. Klein, MFPL), mouse monoclonal anti-HA (12CAS, 1:100, S. Ley, NIMR), mouse monoclonal anti-MYC (9E10, 1:100, S. Ley, NIMR goat polyclonal anti-Zip1 (1:50, SantaCruz Biotechnology). Secondary antibodies (Invitrogen) were used at a 1:500 dilution: chicken anti-mouse Alexa-488, anti-goat Alexa-488, chicken anti-rabbit Alexa-594. Chromosomal DNA was stained with 1 ug/ml 4,6-diamino-2-phenylimide (DAPI). Images were recorded and analyzed using a Deltavision (DV3) workstation from Applied Precision Inc. with a Photometrics CoolSnap HQ (10-20 MHz) air cooled CCD camera and controlled by Softworx image acquisition and deconvolution software.
Statistical analysis of the Chip on CHIP data was done as described  [17]. Briefly, CEL files were converted using Affymetrix's ''tiling array software'' (TAS) and expressed as ChIP relative to WCE (whole cell extract) or as ChIP relative to another ChIP. The output of TAS (intensities per chromosome position) was smoothed using bandwidths between 250 and 1000 bp (ksmooth, statistic package R) and plotted for all chromosomes. For microarrays ''decile normalization'' was used. It is often a good choice for automatic background correction  [17]. For the profiles to be compared in this work, a single correction factor was determined per profile F = 1/(0. 1 percentile). These factors were usually very close to 1. After multiplying all profile intensities with their correction factors, they were precisely superimposing on all background peaks (compare Fig.
Acknowledgments We are grateful to  V. Bo ¨rner ,  N. Kleckner ,  S. Keeney , and  S. Roeder , for strains, plasmids, and antibodies. We thank  A. Spanos ,  P. Thorpe  and  R. Lovell-Badge  for advice on experimental design and techniques and for helpful comments on the manuscript. We thank  S. Gamblin  and  A. Carr  for valuable support and advice.
Variant detection Patients' blood samples were drawn and DNA was extracted from peripheral blood lymphocytes using standard protocols. PCR primers for the 25 exons and flanking intron regions of NPC1 (RefSeq NM_000271) and the five exons and flanking intron regions of NPC2 (RefSeq NM_006432) were designed with the ExonPrimer software (http://ihg. gsf. de). Primer sequences and PCR conditions are summarized in Tables  S1  and S2. Variant screening was performed using IdahoH's LightScanner TM high-resolution melting (HRM) curve analysis according to standard protocols (Idaho Technology Inc. , Salt Lake City, UT)  [29]. Samples with altered melting patterns were Sanger sequenced. In addition, Sanger sequencing of the entire NPC1 or NPC2 coding regions and flanking intron regions ensued when a known disease-associated mutation was identified, respectively.
Data were analyzed under the assumption that the flow structures are isotropic, as verified by test measurements at different distances from the chamber bottom. Commercial particle tracking velocimetry (PIV) software (Dantec Flow Manager) was used to determine the bacterial flow velocity (v x , v y ) from bright-field images (Fig. 1a, b ), corrected for systematic pixel-locking errors  [28]. Data shown in Figs. 2  and 3  are based on 7 movie segments (40 fps, each 50 s long) corresponding to 7 different activity levels. Global bacterial flows were quantified by the in-plane kinetic energy E xy (t) = (v 2 x + v 2 y )/2 and in-plane enstrophy Ω z (t) = ω 2 z /2 , where ω z = ∂ x v y -∂ y v x is the vertical component of vorticity and • is a spatial average. While E xy and Ω z fluctuate, their time averages (E xy , Ω z ) are approximately constant during the 50 s time interval used in the data analysis (Fig.
We infer the flow of the solvent medium from particle tracking velocimetry (PTV) analysis of the fluorescence images, which only show the tracer particles, assuming that they are passively advected. Data shown in Figs. 2  and 3  are based on 7 movies (40 fps, length 100 s) at different activities. Trajectories of individual tracer particles were found with a custom algorithm which, depending on seeding density and tracer dynamics, was able to identify up to 10 4 in-plane tracks, the longest typically lasting 5 -8 s. The effective sample size was insufficient to determine reliably the tracer VACFs, but did yield global flow properties, velocity histograms and equaltime VCFs. The velocity PDFs, calculated directly from individual tracer velocities, are approximately Gaussian with a peak at small velocities from tracer accumulation near the vortex centers (Fig.
2a ). Estimates from PTV for the medium VCF and enstrophy were obtained by interpolating tracer velocities on a 450 × 450 pix subwindow in the center of the imaging plane using MATLAB's Delaunay triangulation with a lattice spacing ∆ = 90 pix/N f , where N f is the mean number of tracers detected per frame. The accuracy of this reconstruction procedure is controlled by the tracer concentration, which was kept low to limit effects on the bacteria motion and to avoid tracking ambiguities (typically N f ∈  [47, 144]  for data shown in Figs. 2  and 3 ). As a result, the uncertainties for the PTV data are considerably larger than for PIV data (see Fig. 2d ). The interpolated tracer flow fields were used to estimate the kinetic energy E xy , enstrophy Ω z , and spatial correlation functions of the in-plane medium flow components.
Background: In stark contrast to the wealth of detail about C. elegans developmental biology and molecular genetics, biologists lack basic data for understanding the abundance and distribution of Caenorhabditis species in natural areas that are unperturbed by human influence. Methods: Here we report the analysis of dense sampling from a small, remote site in the Amazonian rain forest of the Nouragues Natural Reserve in French Guiana. Results: Sampling of rotting fruits and flowers revealed proliferating populations of Caenorhabditis, with up to three different species co-occurring within a single substrate sample, indicating remarkable overlap of local microhabitats. We isolated six species, representing the highest local species richness for Caenorhabditis encountered to date, including both tropically cosmopolitan and geographically restricted species not previously isolated elsewhere.
Pattern of C. briggsae genetic diversity at different spatial scales To test for local population structure within a species, we focused on the C. briggsae isolates resulting from the above small-scale spatial analysis, then considered these together with isolates from the entire Nouragues area and from other sampling sites in French Guiana. We further placed the results in the context of worldwide diversity of this species. We first investigated the global pattern of C. briggsae diversity with a multi-locus dataset of 189 isolates, including 57 new isolates derived primarily from tropical sites (Additional files 3 and 4). Our broad-scale analysis (Figure  5A ) is consistent with previous reports indicating most C. briggsae isolates partition into two main groups that largely separate by latitude, the "Tropical/I" and "Temperate/II" phylogeographic groups, in addition to a few genetically distinct isolates from geographicallyrestricted localities that do not follow this latitudinal dichotomy  [6, [16] [17] [18] [19] [20].
Sequence analyses We analysed a total of 99 new wild isolates of C. briggsae (53 from French Guiana, 46 from other world-wide localities). Note that four French Guiana isolates (NIC88, NIC106, NIC107, NIC108) were analysed in Jovelin & Cutter  [19]. Based on a set of six nuclear loci used previously  [6, 16, 17, 19] , we investigated the relationships of the 57 new isolates for which data were collected for all six loci, relative to a collection of 132 isolates that were used in previous studies on C. briggsae diversity  [6, 16, 17, 19]. We also obtained sequence data for up to five of these loci for the remaining new isolates, which informed some analyses (Additional file 3). Multiple sequence alignments were constructed for each locus in BioEdit  [35]  and manually edited for indel polymorphisms.
We inferred the relationships among isolates with concatenated sequences from the set of six loci using unrooted neighbournetworks generated with a Jukes-Cantor distance in the program SplitsTree 4. 10  [36]. Neighbour-networks are useful for representing the relationships among individuals of the same species for which recombination events may be non-negligible  [37]. We then measured differentiation and divergence between phylogeographic groups using F ST  [38]  and D xy , the average number of nucleotide substitutions per site between groups  [39]. We also measured nucleotide polymorphism  [39]  at each locus taken separately using DnaSP v. 5  [40]  and took the average across loci in order to investigate nucleotide diversity at multiple spatial scales in C. briggsae.
Acknowledgements MAF and CB acknowledge financial support by the  CNRS , including a grant for research at the Nouragues field station, and would like to thank the staff at the station and the  CNRS in French Guiana , in particular,  Patrick Châtelet ,  Philippe Gaucher  and  Jérôme Chave. We also thank those who provided access to sampling sites ( Bruno Le Vessier ) and information on sampled fruits (Pierre-Michel Forget). We are grateful to  Matt Rockman  for the New Jersey isolates and to  Patrick Châtelet ,  Mathieu Joron ,  Didier Peigne ,  Christopher Nelson ,  Amir Yassin  for collecting samples. CB is funded by the  CNRS ,  Agence Nationale de la Recherche  and the  Fondation Schlumberger pour l'Education et la Recherche. ADC received support from the  Natural Sciences and Engineering Research Council (NSERC)  of  Canada  and from a  Canada Research Chair.
Core chronology The chronologies of the studied sediment core intervals are based on 22 AMS (Accelerator Mass Spectrometry) 14 C-and 210 Pb-dates of which 13 have previously been published for cores JM09-KA11-GC  (Rüther et al. ,   2012), and MD95-2011  (Risebrobakken et al. , 2003)  (Table  2 ). The dates were calibrated to calendar years BP (present = 1950 AD) applying the software Calib 6. 1. 0 (Stuiver and  Reimer, 1993)  and the marine calibration curve marine09  (Reimer, 2009)  using a reservoir correction of ∼ 400 yr ( R = 0). This reservoir correction was chosen as a further fine-tuning of the signals and would result in age models differing from published paleoclimate datasets using the standard variations. Nevertheless we are aware of a possible shift of our age models due to the R effect, especially in areas with "old" Arctic/Polar waters.
The chronologies were established using the calibrated mean ages for the 2σ interval of highest probability and assuming a constant sedimentation rate between each radiocarbon dated level of JM09-KA11-GC (linear interpolation) and a second order polynomial fit for core HH11-134-BC (Fig. 2 ). The sedimentation rates of the three studied cores range from 5 to 146 cm kyr -1 , which according to the sampling resolution, lead to a temporal resolution of our micropaleontological dataset of 10 to 105 yr. A decadal to multi-decadal resolution has been found sufficient in the present study to identify major centennial-scale changes in paleocirculation along our transect.
The published surface sediment sample dataset by  Baumann et al. (2000)  only included a few sites far west of the continental margin with coccolith assemblages dominated by C. pelagicus (E / C < 1). This excess C. pelagicus abundance stands as a contrast to our own results from surface sediment assemblages in the northern cores HH11-134-BC and JM09-KA11-GC, as well as to the composition of extant populations northwest of Bjørnøya  (Baumann et al. , 2000)  and across the Fram Strait  (Dylmer et al. , 2013) , which both indicate an expected clear dominance of E. huxleyi below and within AW dominated areas. Based on these evidences we use the definition of the AF (a frontal salinity and temperature gradient separating surface AW masses from mixed ArW) to infer that the E / C ratio (ie. deviations from the threshold of 1) characterizes surface sediments deposited below Atlantic or Arctic surface water masses, when considering pluriannual conditions.
Though barely found in modern plankton communities of the Nordic Seas  (Andruleit, 1997; Dylmer et al. , 2013) , coccoliths of Gephyrocapsa muellerae and Calcidiscus leptoporus commonly contribute together up to ∼ 20 % of the fossil assemblages in surface sediments of the eastern Nordic Seas. Drifting with the poleward flow of surface to intermediate NAC waters from the temperate North Atlantic, where these species are preferentially thriving, was proposed as a possible explanation for this discrepancy by  Samtleben and Schröder (1992). Based on new datasets on living and fossil communities,  Giraudeau et al. (2010)  revisited the distributional pattern of G. muellerae in the North Atlantic and restricted the ecological niche of this species to the eastern North Atlantic, south of the Iceland-Scotland Ridge.
The correspondence between our G. muellerae abundance datasets and foraminiferal records is particularly obvious in core HH11-134-BC off western Svalbard, where foraminifera are assumed to represent subsurface waters within the main core of Atlantic-derived waters  (Carstens et al. , 1997) , thus confirming the reliability of this coccolith index as a proxy of Atlantic water flow. The following discussion compares our data with previous marine and terrestrial proxy records of sea ice distribution, atmospheric circulation (NAO index), and sea surface and subsurface temperatures in the northern North Atlantic region in order to provide a thorough insight into the paleoceanographical and paleoclimatological development of this climatic sensitive area during the late Holocene. In the final part we will zoom in on the major climatic changes during the last 700 yr covering the interval from the MCA-LIA transition to the modern period.
, 2011) , and west of Spitsbergen  (Spielhagen et al. , 2011) , and evidences herein of high amplitude, rapid temperature increases during the last century, has intensified the ongoing debate on temperature changes in the Arctic. Spielhagen et al. (2011)  used foraminiferal assemblages and geochemical measurements to reconstruct a ∼ 2 • C temperature increase in the subsurface waters of the eastern Fram Strait at the transition from the LIA to the modern period. Our dataset obtained from core HH11-134-BC not only confirms the high amplitude warming of subsurface waters at the turn of the 19th century (Fig. 7 ), it also shows that such a warming was primarily induced by an excess flow of AW along western Svalbard as depicted by our G. muellerae proxy record (Fig. 7d ). Our coccolith results also indicates that this modern strengthening of AW flow across Fram Strait was unprecedented over the last 3000 yr, and was associated by an exceptional AW shoaling (Fig.