dataesr/scientific-paragraphs-categorization huggingface dataset:
Following on from previous versions of the radioactive decay data library, a recent update, JEFF-3. 3, is now available. Other sources of nuclear data, which contribute to this library, have been re-visited and updated. Specifically the 900 or so radionuclides converted from the Evaluated Nuclear Structure Data File (ENSDF)  [3]  have been updated, where necessary, along with new evaluations from the two UK libraries (UKPADD-6. 12 and UKHEDD-2. 6 [4] ), the IAEA Actinide Decay Data Library  [5]  with the remainder converted from the NUBASE evaluation of nuclear properties  [6]. In accordance with the assessment of fission product decay data for decay heat calculations.
Mission The DDEP aims to provide recommended decay data to non-specialists. Typical users are not nuclear structure experts, they are generally metrologists working in the field of alpha-and gamma-spectrometry, or with liquid scintillation techniques. Thus the goal of the DDEP is to provide all of the relevant data, i. e. , half-life, energy and emission intensities for the main decay radiations (alpha, beta and gamma) and the associated atomic data due to the internal conversion process, i. e. , energy and emission intensities for X-rays, conversion electrons, and Auger electrons, and to facilitate the access to these data in as convenient a way as possible. In this respect, the DDEP does not aim to compete with the more nuclear structure oriented evaluations from the ENSDF project, but sees itself as a complementary effort focussed on producing recommended decay data relevant to the wider user community.
e. population balance of each level. 4. Total decay energy should be conserved, such that the sum of all of the decay radiations is equal to the Q-value. The transition intensities for all γ -rays are calculated from the recommended emission intensities and the internal conversion coefficients, which are interpolated using the BrIcc code  [20]. These also allow the associated atomic data to be calculated by using the relevant ω K and ω L values and other relevant parameters. A comparison of the calculated X-ray data with measured data (if they exist) is always made. The recently developed BETASHAPE code  [21]  is now being used to calculate the log ft values and the mean beta energies included in the DDEP evaluations.
Access to decay scheme data The DDEP evaluations are placed on the website developed and hosted by the LNE-LNHB and available at http://www. nucleide. org. Included on this website are two PDF files which contain the data "Tables" showing the recommended values for the decay scheme parameters and a "Comments" file from the evaluator. This latter file includes complete details provided by the evaluator on the procedure undertaken to arrive at the recommended values, including data selection and/or rejection, adjustment of uncertainties, etc. and may also include recommendations for future measurements when the available experimental data are not deemed appropriate to enable a balanced decay scheme to be constructed. Three additional computer readable ASCII files are also made available in different formats: an ENSDF file, a PENNUC file and a simple comma separated values (CSV) file.
Background The JEF-2. 2 library, released in the early 1990s, was, for many years, the reference decay data library within Europe. However, identified shortcomings led to a change in strategy for the next generation of decay data libraries within the JEFF project. Hence, JEFF-3. 0 was constructed using a completely new approach compared to JEF-2. 2. A skeleton based on NUBASE was agreed upon, whereby all relevant radionuclides were identified. More detailed evaluations from specialised evaluated decay data libraries (UKHEDD, UKPADD, DDEP, IAEA, etc. ), with also a contribution from ENSDF, were then used to replace individual radionuclides. Only evaluations having an energy balance better than 2% were taken from ENSDF, thus differing from the philosophy adopted for ENDF/B-VII, where almost all evaluations are taken from ENSDF without this quality specification.
Inclusion of TAGS data and the JEFF-3. 1. 1 release The initial decay heat benchmarking of JEFF-3. 1, along with the work of the OECD/NEA Working Party on International Evaluation Co-operation subgroup 25 (WPEC-25)  [7]  highlighted some problems in the individual prediction of the gamma and beta decay heat components, the total decay heat prediction being satisfactory. It was believed that mean energy values determined through Total Absorption Gamma-ray Spectroscopy (TAGS) experiments could help correct this problem. Hence a limited number of twenty-nine nuclei (see Table  2 ) had their mean energies updated from the high quality work of Greenwood et al. [8]. The nuclei updated were only those where a detailed evaluation was not available, and hence the nuclei measured by this group were considered.
Conclusions The Decay Data Evaluation Project (DDEP), originally established within the metrology community to evaluate decay scheme data for use in detector calibration and international activity comparison exercises, has to date produced over 220 complete decay scheme evaluations. A methodology ensures that data are reviewed and detailed comments are provided on the evaluation process, to ensure the traceability of the recommended data. Shortcomings in the available data are documented and often lead to new measurement recommendations. The associated atomic data are calculated using the best available fundamental parameters and are included in the final evaluation tables. The evaluations are available from the website of the LNE-LNHB, in various tabulated formats, and through the LARAWEB online database.
They are also published through the BIPM and as the Mini Table  of  Radionuclides. The Radioactive Decay Data library of the Joint Evaluated Fission and Fusion (JEFF) project has been updated, with the new release of JEFF-3. 3. Evaluations have been taken from various sources, mainly European, with a number from the ENSDF database. Data for the mean β and γ energies have been included from total absorption gamma-ray spectroscopy (TAGS) measurements, some of which have been produced recently by groups from the University of Valencia, Spain and SUBATECH, the University of Nantes, France, working at the University of Jyväskylä, Finland. Further TAGS data will be included, where appropriate, into future releases. Testing of this new release will be undertaken and published in due course. The dedication of the DDEP evaluators, past and present, is gratefully acknowledged.
Their efforts in providing high-quality recommended values is of paramount importance to the user community. The recent experimental work using the TAGS technique by the Valencia and Nantes groups has been shown to be invaluable in resolving the decay heat problem. The work of these two groups is highly appreciated. The JEFF-3. 3 Radioactive Decay Data Library is dedicated to the memory of Olivier Bersillon, whose untimely passing coincided with the release of this library, on which he worked so tirelessly over the past few years. His significant contribution is sincerely acknowledged.
215  [39] , • Herwig++ 2. 7. 1  [40, 41] , 2 • Sherpa 2. 2. 1  [45] , • Vincia 2. 001  [46] , • Deductor 1. 0. 2 [47]  (with hadronization performed by Pythia 8. 212), 3   1 Of course, the quantum numbers of the color singlet operator are not measurable event by event. The idea here is to have a fundamental definition of "quark" and "gluon" that does not reference QCD partons directly. 2 We use the default angular-ordered shower for these studies. Subsequent to this paper, Ref. [42]  performed a study to improve quark/gluon modeling in Herwig 7. 1  [43, 44]. 3 Note that this Deductor plus Pythia combination has not yet been tuned to data. • Ariadne 5. 0. β [48] , 4 • Dire 1. 0. 0  [50]  (with cluster hadronization performed by Sherpa 2. 1. 1). To test other generators, the analysis code used for this study is available as a Rivet routine  [51] , which can be downloaded from https://github.
Idealized quark/gluon discrimination We now turn to parton-shower studies of quark/gluon discrimination, starting with the idealized case of e + e -collisions. While far less complicated than quark/gluon tagging in the LHC environment, this e + e -case study demonstrates the importance of final-state evolution for quark/gluon discrimination, independent from initial-state complications arising in pp collisions. A Rivet routine  [51]  for this analysis can be downloaded from https: //github. com/gsoyez/lh2015-qg under MC_LHQG_EE. cc. To define the truth-level jet flavor, we use a simple definition: a quark jet is a jet produced by a parton-shower event generator in e + e -→ (γ/Z) * → uū hard scattering, while a gluon jet is a jet produced in e + e -→ h * → gg. Of course, an e + e -→ uū event can become a e + e -→ uūg event after one step of shower evolution, just as e + e -→ gg can become e + e -→ guū.
While we have extensive information about quark-jet radiation patterns from LEP event shapes, gluon-jet radiation patterns are largely unconstrained. This has important implications for parton-shower tuning strategies, since LHC data can and should be used to adjust final-state shower parameters. For example, the ATLAS A14 tune of Pythia has a 10% lower value of α s in the final-state shower compared to the Monash tune, which yields better agreement with charged-particle multiplicity distributions  [25]. However, A14 has not been tested on LEP event shapes, suggesting that a global tuning strategy is needed. In addition, it is worth mentioning that similar quark/gluon studies have been carried out in deep inelastic electron-proton scattering  [125] , which offer an intermediate step between pp and e + e -collisions, and this ep data could also be valuable for parton-shower tuning.
6. 3. Hadrons with rapidity |y| < 2. 5 are used for jet clustering, and the resulting jets are restricted to have |y jet | < 1. 5. We apply a minimum p T cut with default value p min T = 100 GeV, similar in spirit to the Q/2 value used in the e + e -study, though the precise meaning of p min T differs between the two samples. The specific analysis routines used for this pp study are available from https://github. com/gsoyez/lh2015-qg. For the Z plus jets analysis (with Rivet routine MC_LHQG_Zjet. cc), the selection criteria for the reconstructed Z boson and jet are: pp → Z + j ("quark-enriched") : p Z T > p min T , |y jety Z | < 1. 0. (6. 1).
Acknowledgments We thank  Marat Freytsis  and  Davison Soper  for contributing to the original Les Houches study [1] that formed the basis for this work. We particularly thank  Davison Soper  for contributing plots based on Deductor. We thank  L' École de Physique des Houches  and the organizers of the 2015 Les Houches workshop on "Physics at  TeV Colliders"  for a stimulating environment while this work was being initiated. We benefitted from helpful discussions and feedback from  Samuel Bein ,  Andy Buckley ,  Jon Butterworth ,  Mario Campanelli ,  Peter Loch ,  Ben Nachman ,  Zoltan Nagy ,  Chris Pollard ,  Stefan Prestel ,  Salvatore Rappoccio ,  Gavin Salam ,  Alexander Schmidt ,  Frank Tackmann , and  Wouter Waalewijn. The work of SH is supported by the  U. S. Department of Energy (DOE)  under contract  DE-AC02-76SF00515.
DK acknowledges support from the  Science Faculty Research Council, University of Witwatersrand. The work of LL, SP, and AS is supported in part by the MCnetITN  FP7 Marie Curie Initial Training Network , contract  PITN-GA-2012-315877. LL is also supported by the  Swedish Research Council  (contracts  621-2012-2283  and  621-2013-4287 ). SP acknowledges support from a  FP7 Marie Curie Intra European Fellowship  under Grant Agreement PIEF-GA-2013-628739. AS acknowledges support from  COST Action CA15213 THOR  and the  National Science Centre, Poland  Grant No. 2016/23/D/ST2/02605. PS is the recipient of an  Australian Research Council Future Fellowship ,  FT130100744. The work of GS is supported in part by the  Paris-Saclay IDEX  under the  IDEOPTIMALJE grant , by the  French Agence Nationale de la Recherche , under grant  ANR-15-CE31-0016 , and by the  ERC Advanced Grant Higgs@LHC  (No.
in the absence of their partner(s) (for a recent review on IDPs, see  22, 23  ). IDPs or proteins possessing intrinsically disordered regions (IDRs) are frequently involved in essential processes such as transcriptional and translational activation, chromatin remodeling, and signal transduction. Recent studies have investigated the abundance of intrinsic disorder (ID) in plant proteins  8, 24, 25. The inability of plants to move away from a danger has probably been a major driving factor in the development of their stress response. Plants exhibit a high ability to adapt to variable environmental conditions. Taking into consideration that ID serves as a determinant of interactivity, it has been proposed that it may contribute to such plasticity in plants  26. We have previously isolated the ASR genes and cDNA from durum wheat (TtASR1) and barley (HvASR1) seedlings under abiotic stress conditions (accession numbers KX660743 and KX660744, respectively).
1 ). We have previously reported  [28] [29] [30] [31]  , that such regions often correspond to Molecular Recognition Elements (MoREs), i. e. short order-prone regions within IDRs with a propensity to undergo induced folding upon binding to a partner  32. MoRFpred predicts five such regions (Fig. 1 ). By comparing the sequence composition of HvASR1 and TtASR1 to that of proteins within the SWISS-PROT database, both proteins were found to be enriched in the most disorder-promoting amino acids (A, G, R, D, H, Q, K, S, E and P) and depleted in order-promoting residues (W, F, Y, I, M, L, V, C and T) (Supplementary Fig. S1 )  19, 33. Five amino acids (EAHKG) constitute ~68% of the total TtASR1 and HvASR1 residues (Supplementary Fig. S1 ). This biased sequence composition is also mirrored by the occurrence of four low sequence complexity regions, as identified by the SEG program  19  (Fig.
5C ). Regardless of these subtle differences, the profiles indicated that both ASR1 proteins undergo temperature-induced folding, as already observed for other IDPs  48, 49. This heat-induced folding is reversible, with the spectra reverting to their initial appearance after re-cooling at room temperature (data not shown). To rule out any possible temperature-induced aggregation, we monitored the HT voltage associated with the transmission of We also recorded the CD spectra of HvASR1 and TtASR1 in the near ultraviolet region (250-350 nm). Near-UV CD spectra reflect the environment of the aromatic amino acid side chains and provide information about the tertiary structure of proteins  50. The near-UV CD spectra of both proteins are characterized by a weak intensity, and by the presence of a broad negative band (Fig.
While the addition of Zn 2+ and 10% TFE does not promote an additional gain in α-helicity in HvASR1 (Fig. 10A ), the reverse is observed for TtASR1, where the effects appear cumulative (Fig. 10B ). These differences in folding propensities might reflect subtle functional differences between the two proteins. In agreement with a zinc-induced gain of structure, zinc binding also results in a decreased susceptibility of both ASR1 proteins to trypsin digestion (data not shown), as already reported for tomato ASR1  11, 59. To gain further insights into the precise character of this structural transition, and to precisely identify the protein region where this transition takes place, we performed Hydrogen/Deuterium eXchange-Mass Spectrometry (HDX-MS) analysis. The unlabeled ASR1 proteins were first digested with both A.
saitoi protease Type XIII and pepsin to obtain peptides for monitoring local-level effects. Sequence coverage maps of all peptides of TtASR1 and HvASR1 selected for HDX-MS analysis are displayed in Supplementary Fig. S8. Excellent sequence coverage was achieved in both cases. Digestion of TtASR1 gave rise to 33 unique peptides identified from their accurate masses and   product ion spectra. A total of 20 peptides were brought forward for HDX data analysis, corresponding to a sequence coverage of 92. 2% (Supplementary Fig. S8 ). Similarly, for HvASR1, from a total of 29 identified peptides, 21 were selected for HDX-MS analysis, covering 93. 7% of the total protein sequence (Supplementary Fig. S8 ). Amide hydrogen exchange rates within a protein are determined by both the solvent accessibility and structure of the protein.
Methods Disorder predictions and in silico analysis of amino acid composition. Sequence accession numbers are KX660743 for HvASR1 and KX660744 for TtASR1. Disordered regions within HvASR1 and TtASR1 were identified using the MeDor (http://www. vazymolo. org/MeDor/)  72 , and the Genesilico MetaDisorder (http:// iimcb. genesilico. pl/metadisorder/metadisorder. html)  73 metaservers for the prediction of disorder. These metaservers collect disorder and secondary structure predictions from servers available on the web. Beyond canonical predictors, MeDor also incorporates HCA  74. DorA (Disorder Analyser) is a predictor that identifies regions of disorder based on the combined use of a disorder scoring matrix and HCA. It works by first detecting regions that exhibit an amino acid composition bias towards disorder-promoting residues and then by filtering them to eliminate segments rich in hydrophobic clusters.
pondr. com/cgi-bin/PONDR/pondr. cgi). Analysis of sequence attributes, as defined in  38  , were carried out using the CIDER server (http://pappulab. wustl. edu/CIDER/). The letter was also used to generate the phase diagram plots. Deviations in amino acid composition of HvASR1 and TtASR1 were analyzed and computed as already described  78  using the average amino acid frequencies of the SWISS-PROT database (as obtained from http:// us. expasy. org/sprot) as the reference value. The average amino acid frequencies of the SWISS-PROT database roughly corresponds to the mean composition of proteins in nature. If the average composition of an amino acid X in SWISS-PROT proteins is CSP X , and CP X is the composition of X within a protein P, deviation from the composition of X of SWISS-PROT proteins was defined for P as (CP X -CSP X )/CSP X.
5 mg/mL) was loaded onto a Superdex 75 16/60 column (GE, Healthcare) using a fast protein liquid chromatography (FPLC) Äkta system (GE, Healthcare) and eluted in PBS pH 7. 3. Protein concentrations were calculated using the theoretical absorption coefficients at 280 nm as obtained using the program ProtParam at the EXPASY server. For both proteins, typical purification yields were of 0. 5 mg of purified protein per liter of bacterial culture. Size Exclusion Chromatography and calculation of hydrodynamic radii. The hydrodynamic radii (Stokes radii, R S ) of the HvASR1 and TtASR1 proteins were estimated by analytical SEC. Typically 2. 6 mg mL -1 of purified protein was injected. The SEC buffer was PBS pH 7. 3. The Stokes radii of proteins eluted from the SEC column were deduced from a calibration curve obtained using globular proteins of known molecular mass (MM, in Daltons) and whose R S (in Å) was calculated according to 79 : =.
SAXS measurements and calculation of the radius of gyration. All SAXS measurements were carried out at the European Synchrotron Radiation Facility (ESRF) on beamline BM29 at a working energy of 12. 5 KeV. The sample-to-detector distance of the X-rays was 2. 847 m, leading to scattering vectors q ranging from 0. 028 to 4. 525 nm -1. The scattering vector is defined as q = 4π/λ sinθ, where 2θ is the scattering angle. The exposure time was optimized to reduce radiation damage. SAXS data were collected at 20 °C using purified protein samples (30 μL each). Protein concentrations were as follows: 1. 0 and 1. 5 g/L for HvASR1 and 1. 0 and 1. 5, 2. 0 and 3. 0 g/L for TtASR1. Both proteins were in PBS pH 7. 3 buffer containing 5 mM DTT. Samples were loaded in a fully automated sample charger. Ten exposures of 10 s each were made for each protein concentration and data were combined to give the average scattering curve for each measurement.
Any data points affected by aggregation, possibly induced by radiation damages were excluded. The profiles obtained in the range 1. 0-1. 5 g/L for HvASR1, and 1. 0-3. 0 g/L for TtASR1 had the same shape and were flat at low q values indicating the absence of significant aggregation. Then, we used the higher concentration (1. 5 g/L for HvASR1 and 3. 0 g/L for TtASR1) to obtain maximal information at high resolution. The data were analyzed using the ATSAS program package  83. Data reductions were performed using the established procedure available at BM29, and buffer background runs were subtracted from sample runs. The Rg and forward intensity at zero angle I(0) were determined with the program PRIMUS  84  according to the Guinier approximation at low q values, in a q. Rg range up to 1. 3: = - Ln I Q Ln I Q R [ ( )] [ ] 3 (9) g 0 2 2 The forward scattering intensities were calibrated using bovine serum albumin as reference.
One-mm or 1-cm thick quartz cuvettes were used for far-and near-UV CD measurements, respectively. Proteins concentrations were 0. 1 mg mL -1 and 1 mg mL -1 for far-and near-UV CD studies, respectively. Far-UV CD spectra were measured between 190 and 260 nm, while near-UV CD spectra were recorded between 250 and 350 nm. Unless differently specified, CD spectra were recorded in 10 mM sodium phosphate pH 7 at 20 °C. The scanning speed was 20 nm/min, with data pitch of 0. 2 nm. Each spectrum is the average of three acquisitions. The spectrum of buffer was subtracted from the protein spectrum. Spectra were smoothed using the "means-movement" smoothing procedure implemented in the Spectra Manager package. Far-UV CD spectra were also recorded in the presence of increasing concentrations (from 20 to 50%) of TFE.
Mass spectrometry (MALDI-TOF). Mass analysis of the purified ASR1 proteins was performed using a MALDI-TOF-TOF Bruker Ultraflex III spectrometer (Bruker Daltonics, Wissembourg, France) controlled by the Flexcontrol 3. 0 package (Build 51). This instrument was used at a maximum accelerating potential of 25 kV and was operated in the linear mode with m/z range from 600 to 3500. Samples (1 µL containing 15 pmol) were mixed with an equal volume of α-Cyano-4-hydroxycinnamic acid matrix solution, spotted on the target, then dried at room temperature for 10 min. Mass spectral analysis of the protein fragments, as obtained upon thermolysin limited digestion of the purified HvASR1 and TtASR1 proteins, was performed as follows. After SDS-PAGE separation, the bands of interest were excised from the gel.
0 (Waters). Oxidation of methionines and carbamylation of N-terminal and lysine residues were set as variable modifications. The sequence coverage map was plotted using DynamX 3. 0 HDX software (Waters). D 2 O uptake at the peptide level was extracted and visualized in uptake charts, difference plots, and heat maps, also performed in DynamX. HDX-MS results were further analyzed using MEMHDX  91.
Acknowledgements This work was supported jointly by French and Tunisian funding/research agencies. On the French side, this work was carried out with the financial support of the  CNRS  to S. L. E. S. is supported by a  joint doctoral fellowship  from the  Direction Geńeŕale de l' Armement (DGA)  and  Aix-Marseille University. D. O. B, S. B. and A. C. are supported by the  CNRS ,  CACSICE  ( Equipex   ANR-11-EQPX-0008 ),  Fondation Recherche Médicale  ( FRM DBS20140930771 ) and  Institut Pasteur  ( PasteurInnov2015-197  and  PTR451 ). On the Tunisian side, this work is supported by  L'Oreal-Unesco for women in Science program-(Pan Arab  Fellowship 2013), the  Tunisian Ministry of Higher Education and Scientific Research and AUF (Collège en Biotechnologies  végétales et agroalimentaire). We thank  Patrick Fourquet , from the mass spectrometry platform of the  Centre de Recherche en Cancérologie de Marseille (CRCM ) for mass spectrometry analyses.