dataesr/scientific-paragraphs-categorization huggingface dataset:
In this latter case, application of synergy decompositions separately in each individual task would lead to the identification of a larger set of synergies than those actually generating the taskdiscriminating muscle activations (we verified this intuition also by extracting synergies in one task at a time in our simulated datasets, which invariably led to incorrect identification of a larger set of synergies with lower task-discrimination power than the synergy set determined by our method; data not shown). Our findings parallel results recently obtained in frogs' experimental and modeling studies  (Kargo and Giszter, 2000, 2008; Kargo et al. , 2010). In these studies, the authors varied the initial configurations as well as the level of muscle vibrations applied to the frog's hindlimb and showed that flexible combinations of a small set of invariant muscle patterns can produce successful accurate targeting of the frog's hindlimb from a large range of starting positions.
Critical comparison of the validity of different synergy models An advantage of the derived decoding metric is that it allows a direct comparison of performance of different synergy decompositions in terms of task execution when using the same number of parameters in all decompositions. This is useful for testing the validity of various hierarchical motor control schemes or various mathematical representations of muscle synergies. For example, the synchronous synergy model may account for more variance than the time-varying synergy one (as happens in the EMG dataset considered here) but this may be due to the fact that synchronous synergies are potentially characterized by a larger number of parameters than time-varying synergies (because the former report the full time course of activation, whereas the single-trial activation of the latter is described by two parameters per synergy) (D'Avella and  Bizzi, 2005; D'Avella et al.
, 2006). Specifically, by applying this metric to our dataset we found that the two decompositions decode tasks equally well when using the same number of parameters. Moreover, our formalism can be used to evaluate the loss of task-discriminating information due to simplification of the time course of synergy activation. In our example dataset, our analysis suggested that a full representation of the temporal pattern of activation patterns of synchronous synergies is not crucial to encode the goal of the task. Only the average activation during two or three temporal phases seems sufficient to know what target will be reached. To shed more light onto the effectiveness of synergies as lowdimensional structures for motor control, future research could aim at extending our formalism to quantify the predictability of kinematic movement features in continuous time  (Corbett et al.
, 2010)  rather than just decoding which task (out of many) was performed. This would enable a proper comparison between the dimensionality of the instantaneous kinematics needed to perform tasks and the dimensionality of the muscle representations that explain all the kinematic range elicited by task execution. Furthermore, it would be of interest to apply our methods to experimental datasets containing a wider range of complex movements to determine which synergy decomposition is more effective in general and particularly in more "daily-life" situations. For example, in an entire reach-and-grasp motor task, we could expect that the time-shifts of the time-varying synergy model or a more detailed consideration of the temporal profile of the synchronous synergy activations would be more relevant to task discrimination.
Frontiers FIGURE 3 | Continued coefficients activating the four synergies across the 8 motor tasks performed. Histograms are plotted as means ± SDs across all trials to the given task. (C-E) VAF and decoding performance curves for datasets generated from 2 (D (E levels, we used the "reference" values (a = 0. 1, = 1). (F-H) VAF and decoding performance curves when generating data from four synergies and varying the simulated noise parameters as follows: increased signal-dependent noise (a = 0. 5, v = 1) (F); increased trial-by-trial variability of the activation coefficients (a = 0. 1, v = 5) (G); increased signal-dependent noise and trial-by-trial variability of the activation coefficients (a = 0. 3, v = 3) (H).
Other authors had similar findings in studies based on rats, mice, and bovine organs. Some studies, however, have shown an increase in DNA methylation in a particular gene or tissue as an organism ages  (Kwabi-Addo et al. 2007). Our results indicate that global DNA methylation patterns change as a chicken ages. It has been shown that DNA methylation is a tissue-specific process; overall methylation variation in different tissues as well as in different chicken breeds was reported by  Xu et al. (2007). Thus, there is a possibility that the global DNA methylation pattern in Polbar chickens is driven by the type and composition of tissues. Therefore, because our study was based on tissue samples for the embryonic period and on blood samples for the postembryonic period, we analyzed our data from the two periods separately in order to exclude tissue as a factor, leaving age as the only analyzed factor.
High-resolution statistics of recombination Sequence polymorphisms between the parental strains gave more than fifty thousand segregating sites for the two-way cross, and more than eighty thousand for the four-way cross. Segregating sites were dispersed fairly uniformly across the genome (see Text S1 for more information on the data). Combining our likelihood calculation with optimisation routines from the widely used recombination rate estimation program LDhat  [9] , we obtained an estimated recombination rate for each interval between two consecutive segregating sites. These estimates were mapped onto uniform grids at varying scales D res (0. 5, 1. 0, 2. 0, 5. 0 and 10. 0 kb). Genome-wide, a broad spectrum of recombination rates was observed for genomic regions within all three crosses. Figure  4  shows recombination rates for these crosses measured at 10 kb resolution.
Discovering the hottest and coldest regions of recombination Application of our inference method to the two advanced intercross datasets allowed us to investigate both the coldest and hottest regions of recombination with satisfactory true positive rates. Inferred landscapes from sets of ten simulated replicate experiments were used to measure the accuracy with which the hottest and coldest regions of recombination could be annotated. For each simulation, the two-way cross landscape was used as an input. Relative to a single generation cross, the advanced intercross design performed substantially better in identifying both the hottest and coldest regions (see Figure  8 ). From these results, The two-way landscape shows some deviation from the others. Simulations were used to calculate the expected variability between landscapes inferred from replicates of a single crossing experiment.
Acknowledgments We thank  Isabel Lam  and  Eugenio Mancera  for critical reading of the manuscript, and are grateful to the referees of this text for their valuable suggestions and advice. We thank the  Sanger Institute sample logistics , library preparation, sequencing, and sequencing informatics teams for performing the sequencing. We thank  Richard Durbin  and  Francisco Cubillos  for pre-publication access to four parent intercross data (to be described elsewhere (Cubillos et al. )) that are available from the  Short Read Archive , accession ERS024* and ERS025*, and are part of a SGRP-46 resource.
For EM analysis of actin bundles, cosedimentation assays were prepared as described in the previous paragraph in a total volume of 15 µl. After 1 h of incubation, reactions were diluted 1:10 in KME buffer, and 3 µl aliquots were applied to Formvar-and carbon-coated 200 mesh copper grids prepared as in  Jansen et al. (2011). After 30 s, grids were blotted to remove excess solution, stained with 1% (wt/vol) uranyl acetate for 1 min, blotted, and dried. Samples were viewed in a transmission electron microscope (Tecnai 20) at an accelerating voltage of 200 kV. Images were captured on a charge-coupled device camera (UltraScan Model 894 US1000; Gatan). Interfilament distances in actin bundles were calculated by using the intensity profile function on Elements (Nikon) and Excel (Microsoft ) software, with distances between peaks on the intensity profile being taken as the distances between the centers of actin filaments.
Peptides were resolved by reversed-phase chromatography on a 75 µm C18 EASY column using a linear gradient of acetonitrile in 0. 1% formic acid. The gradient was delivered to elute the peptides at a flow rate of 300 nL/min over 60 min. The eluate was ionized by nanoelectrospray ionization using an Orbitrap Velos Pro running Xcaliber software (version 2. 1. 0 SP1 build 1160; (Thermo Fischer Scientific)) using Higher-energy C-trap Dissociation (HCD) for identification and collision-induced dissociation/multistage activation (CID/MSA) for optimized phosphopeptide analysis. The instrument was operated in automated data-dependent switching mode, selecting precursor ions based on their intensity for sequencing by HCD in a top 10 method. The MS/MS analyses were conducted using higher than normal collision energy profiles that were chosen based on the mass-to-charge ratio (m/z) and the charge state of the peptide.
Drebrin deletion constructs Subcloning and PCR were performed using standard methods. Human drebrin E isoform (available from GenBank under accession no. D17530; GeneCopoeia) and drebrin deletion constructs were amplified by PCR with EcoRI and XhoI sites added to the 5 and 3 ends, respectively, using the following primers: forward primers for drebrin, ADFH, ADFH-CC, and ADFH-CC-Hel constructs, 5-CTCGAATTCATGGCCGGCGTCAGCTTC-3; for CC, CC-Hel, and CC-Hel-PP-BB constructs, 5-CTCGAATTCATGGGGCT-GGCGCGACTCT-3; for Hel and Hel-PP-BB constructs, 5-CTCGAATTC-ATGTTTGGTGACCATCGGGATGAG-3; for PP-BB construct, 5-CTCGAA-TTCATGCTGGATGAGGTCACCTCC-3; for BB construct, 5-CTCGAATTC-ATGCTGGCTGCTCCCGTGGAG-3; reverse primers for drebrin, BB, PP-BB, Hel-PP-BB, and CC-Hel-PP-BB constructs, 3-GCCTCGAGAAATCAC-CACCCTCGAAGCC-5; for Hel, CC-Hel, and ADFH-CC-Hel constructs, 3-GCCTCGAGAAGGCCCGCTCTATCTGCT-5; for CC and ADFH-CC constructs, 3-GCCTCGAGAGGATAGACTGCTCCTTCAACC-5; and for ADFH construct, 3-GCCTCGAGAAGTTAGAGAGCCGCTGCC-5 (Sigma-Aldrich).
Labeled cultures were viewed using an confocal microscope (FluoView; Olympus) equipped with argon and HeNe lasers. Cells were imaged with a 100×/1. 4 Plan-Apochromat oil-immersion objective lens and recorded at 1,024 × 1,024 pixels per image. Fluorescent images in TIFF format were manipulated using Photoshop (Adobe). COS-7 cell filopodia were identified as that population of processes that extend as finger-like projections >1 µm from the cell edge and counted using Photoshop software. COS-7 cell perimeter was assessed by measuring the length of a line manually drawn around the cell edge using ImageJ software. To measure F-actin levels, single confocal optical sections of COS-7 cells taken close to the ventral surface, so as to include stress fibers, were collected using a 100× 1. 3 NA oil-immersion objective lens.
We are grateful to  Anthony Brown  for supplying centrifuge tubes bought on eBay,  Britta Eickholt  and  Rita Hendricusdottir  for help with raising a pS142 drebrin pAb,  Nadia Elkhatib  and  Elena Rostkova  for skeletal muscle actin,  Asier Jayo  for fascin, and  Alice Warley in the King's Centre for Ultrastructural Imaging  for help with EM. We thank the  Eickholt laboratory  for correcting some point mutations in drebrin cDNA. This work was supported by grants from the  Biotechnology and Biological Sciences Research Council, Medical Research Council , the  Wellcome Trust , and  Research into Aging. Sara Geraldo 's PhD studentship was funded by  Fundação para a Ciência e Tecnologia, Portugal. Submitted: 1 March 2013 Accepted: 18 July 2013.
For each worker, the primary data included (i) the time of day and day of week of the injury, (ii) the work start and scheduled work end time on injury day as well as the two days prior to the injury, (iii) the frequency and timing of each rest break, (iv) current and previously scheduled working hours, (v) sleep duration and sleep quality in three previous sleeps to the injury, and (vi) alertness/sleepiness (using the Karolinska Sleepiness Scale) at the time of injury and in previous days. The Liberty Mutual Research Institute for Safety Institutional Review Board, the Fudan School of Public Health Institutional Review Board, and the Harvard School of Public Health Human Subjects Committee approved the study.
Sleep duration, quality, and alertness/sleepiness Each worker was asked, "What time did you fall asleep and what time did you wake up directly on the day (or night) of the injury?" The total sleep duration was calculated as the amount of sleep obtained between onand offset of sleep. Workers were also asked when they normally fell asleep and woke up. A follow-up question was asked regarding their sleep quality directly before the injury (as well as their usual sleep): "During this time, how well did you sleep?" Subjective sleep quality was assessed using a self-reported 5-point scale as: 1="extremely badly", 2="quite badly", 3="in between", 4= "quite well", 5="extremely well". Due to the limited number of cases in the extremes of this scale, prior to data analysis the data was collapsed into three categories as: "slept badly", "in between", and "slept well".
To evaluate effect modification by shift start time, we used a similar Cox regression model comparing those starting their shift in the morning and earlier in the day (06:00-13:59 hours) to workers starting later in the afternoon or night (14:00-05:59 hours), after controlling for age, gender, weekly work hours, shift duration, day of injury, last sleep quality, and rushing at the time of injury. All statistical analyses were conducted with SAS version 9. 2 (SAS Institute, Cary, NC, USA).
To evaluate for patterning abnormalities of the ventricular conduction system, Rb, p107 and p130 individual knockout mice were backcrossed into CCS-LacZ reporter mice. No discernible patterning defects were noted in the His bundle, bundle branches, or Purkinje fiber network of individual pocket protein knockout hearts (Fig. 3C ). S1 ). Cell cycling characteristics of individual p107 and p130 knockout hearts were then evaluated in a FUCCI background. The trabecular myocardium of p107 and p130 single knockout hearts retained the ability to arrest in G1 phase compared to littermate controls (data not shown). We next evaluated the protein levels of pocket proteins and cyclins A and E in individual p107 2/2 and p130 2/2 ventricles to assess for compensation and/or perturbation of G1 and S phase cyclin expression (Fig.
DKO hearts are grossly elongated and display infundibular pulmonary stenosis and left ventricular outflow tract (LVOT) obstruction We next evaluated dKO newborn pups for cardiac abnormalities. Postnatal day 1 (N1d) dKO hearts demonstrated bi-ventricular outflow tract obstruction, IVS elongation with over-riding aorta, and right ventricular hypertrophy (Fig. 5B, D, F ). In the right ventricular outflow tract (RVOT), marked thickening of the septo-marginal and parietal trabeculae resulted in variable degrees of infundibular pulmonic stenosis (IPS) (Fig. 5B , arrowheads). Significant right ventricular hypertrophy (RVH) was also seen (Fig. 5D , asterisk). As IPS may be a secondary response to pulmonary valvular stenosis, detailed inspection of the pulmonary valve was performed, which revealed no evidence of pathology (data not shown).
Histology, immunofluorescence, and confocal analysis Immunfluorescent and H&E staining were performed on formalin-fixed, paraffinembedded samples and 4% PFA-fixed, cryosectioned samples, as previously described  (Gutstein et al. , 2001). Antibodies used were mouse anti-p107 (SD9, Santa Cruz), rabbit anti-p107 (C-18, Santa Cruz), mouse anti-Rb2/p130 (BD Transduction Labs), mouse anti-phospho-Histone H3 (Millipore), rabbit anti-Nkx2. 5 (Abcam), anti-mouse Cx40 (Alpha Diagnostics Int), rabbit anti-Tbx3 (Abcam), rabbit anti-Cx43 (Sigma). b-galactosidase staining and whole mount visualization were performed as previously described  (Rentschler et al. , 2001). p107 and p130 positive nuclei were quantified in trabecular and compact myocardial regions as a percentage of total propidium iodide positive nuclei per region using Image J software  (Collins, 2007).
Acknowledgements We wish to thank  Dr Lili Yamasaki  for the generous gift of the pocket protein mouse lines;  Alice Liang ,  Chris Petzold  and  Kristen Dancel  of  NYULMC OCS Microscopy Core  for their assistance with TEM work; and  Cindy Loomis  and  Mark Alu  of the Histopathology Core, which is supported in part by grant  5P30CA016087-32  from the  National Cancer Institute. This work was supported by  National Institutes of Health  grants  R01 HL05983  and  NYSTEM N08G-132  to G. I. F. ;  T32-HL007854-13  and the  Heart Rhythm Society/The Michael Bilitch Fellowship in Cardiac Pacing and Electrophysiology  to D. S. P.
Data collection and processing The data set of the crystal was collected at 100 K under a cold nitrogen stream with an oscillation range per image of 1 , using a Rayonix MX225HE detector on beamline BL41XU at SPring-8. The Se-Met Cex1p crystals diffracted up to 2. 2 A ˚resolution. The resulting data set was processed with the program suite HKL2000 (HKL Research). The crystals belong to the primitive monoclinic space group P2 1 , with unit-cell parameters a = 34. 1, b = 182. 6, c = 112. 3 A ˚, = 98. 9.
Structure determination The phases of the Cex1p crystals were determined from multiple anomalous diffraction data sets collected from a single crystal of selenomethionine-derivatized Cex1pÁC-SER, which diffracted up to 2. 2 A ˚resolution. The peak data set was used to determine the locations of the selenium atoms, using the program SHELXC/D  (28). Several trials revealed 12 peaks among the 14 potential selenium sites expected in the asymmetric unit. Subsequent refinements of the heavy atom parameters and phase calculations were performed with the program SHARP  (29). The data collection and phasing statistics are shown in Table  1. The initial phases were improved by density modification with RESOLVE  (30). The initial model, containing 75% of all residues, was automatically built with RESOLVE.
The model was further built manually using Coot  (31). The diffraction data set analysis using the program Phenix. xtriage  (32)  indicated that the crystal was pseudomerohedrally twinned with a twining fraction of 0. 43. The structure was refined using the twin target function implemented in the program REFMAC5  (33). The resulting twinning fraction was 0. 425 for the twinning operator (Àh, Àk, h+l). Refinement statistics are provided in Table  2.
Analytical ultracentrifugation Sedimentation velocity experiments were performed with an Optima XL-I analytical ultracentrifuge (Beckman-Coulter). Samples (400 ml) in 20 mM Tris-HCl, pH 8. 0, 150 mM NaCl, 5 mM MgCl 2 and 1 mM DTT were loaded into double sector centerpieces mounted in a Beckman An-50Ti rotor. The concentration profiles of the samples were monitored by the absorbance at 280 nm, without intervals between successive scans. The data were analyzed by the SEDFIT program  (35)  to obtain the c(s) profiles. On the basis of the assumption that the frictional ratio f/f 0 was common to all of the molecular species, c(s) was converted to obtain the molecular mass distribution function, c(M), using the implemented function in SEDFIT. Sedimentation equilibrium experiments were carried out in an Optima XL-I analytical ultracentrifuge, using a 4-hole An60Ti rotor at 20 C with a standard double sector centerpieces and quartz windows.
A quantity of 120 ml of each sample with the absorption of 0. 2, 0. 3 and 0. 5 at 280 nm was applied in the sample hole, and the corresponding dialysate was loaded in the reference hole of the cell. The concentration gradients of the samples were monitored by absorption at 280 nm. The rotor speeds were 8800 r. p. m. for 24 h, 12 600 r. p. m. for 20 h The numbers in parentheses are for the last shell. and 22 000 r. p. m. for 20 h. Scans were made every 2 h, and the equilibrium of the system was assumed when the last three scans were identical. Totally, nine data sets were globally fitted to a single species model to determine the weight-average molecular weight by the non-linear least-square fitting, as implemented in the Beckman Coulter software package.
FUNDING Japan Society for the Promotion of Science (JSPS)  through its ' Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST) program ' (to O. N. , K. N. and Y. A. );  Core Research for Evolutional Science and Technology (CREST) program  'The  Creation of Basic Medical Technologies  to Clarify and Control the  Mechanisms Underlying Chronic Inflammation ' of the  Japan Science and Technology Agency (JST)  (to O. N. );  Grant-in-Aid for Scientific Research  from the  Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan  (to R. I. and O. N. );  Universite´de Strasbourg , the  Centre National de la Recherche Scientifique , the  Agence Nationale de la Recherche  [ ANR-09-BLAN-0091-02 ];  National Program 'Ivestissement d'Avenir' (LabEx MitoCross ).
Methods For all twenty host countries that have been involved at some point in a public fishing access agreement with the EU, we retrieved all related official texts (namely, 'council regulations/ decisions', 'agreements', 'protocols', and 'information on the date of entry into force') from the EU law database (http://eur-lex. europa. eu; also available in print). From these documents, we extracted the following data and information: (i) EEZ access fees and development aid (paid by EU taxpayers); (ii) fishing fees (paid by EU industry, either per tonne of fish or per unit of vessel capacity); (iii) fleet capacity; and (iv) specific 'quotas' and 'limits of reference' (both referred to as 'quotas' throughout this paper, although 'limits of reference' can be exceeded in exchange for Figure  1.
pone. 0079899. g001 additional payment), if available. This was done for each gear type or target species, country, and year (see Table  S1  and References S1 for each country's references). This information was mostly collected from the 'protocols', although some of this information was only found in the 'agreements' for the earlier time-period. 'Council regulations/ decisions' were mostly used to determine whether a renewed agreement was similar to its previous iteration, and 'information on the date of entry into force' documents were used to determine whether an agreement was active or not during any given year. To produce a harmonized database, we then standardized the following units:.
Furthermore, most tuna vessel capacities were provided only in number of vessels. To convert these numbers to GRT capacities, we used the correspondences between these two units provided for the 1980s in a handful of agreement documents (purse seiners: Guinea 1983  [50] , Guinea-Bissau 1983 and 1986  [51] [52] , Senegal 1988  [53] [54] , Gambia 1990  [55] [56]  (we used the combination of the two consecutive protocols to estimate the mean GRT per purse seiner in the cases of Senegal and Gambia); 'liners', i. e. , pole-and-line and longline vessels: Guinea 1983  [50] , Guinea-Bissau 1983 and 1986  [51] [52] , Angola 1989  [57] ). In order to get an additional anchor point for 2012, we calculated the geometric mean of the GRT per seiner, based on the list of seiners active in 2012 under EU agreements (provided by the Observatoire Thonier, Institut de Recherche pour le Developpement, Sete, France), and GRT data available in the United Nations Food and Agriculture Organization's 'fishing vessels finder' database (http://www.