dataesr/scientific-paragraphs-categorization huggingface dataset:
The inner ␤-sheet forms a deep cleft extending across the entire ␤-sheet in a direction nearly perpendicular to the strands. The bottom of the cleft is formed by the centers of the ␤-stands; one wall is formed from the loops connecting strands ␤3 to ␤4 and ␤5 to ␤6 (intersheet), whereas the other wall is made from the loops connecting ␤6 to ␤7 and ␤8 to ␤9 (intra-inner sheet). The cleft is lined predominantly with basic and polar side chains and displays a positive electrostatic surface potential as calculated with APBS software (17) (Fig. 1C ). Two phosphate molecules acquired from the crystallization solution are found in equivalent positions in both molecules. This cleft is likely the substrate-binding site of NLR48. A large positive difference map peak was identified in each molecule near the disulfide bond described above.
Putative substrate-binding and catalytic sites The ␤-sandwich jelly roll fold is not unique within the polysaccharide lyases. It is also observed in alginate lyase families PL7, PL14, and PL18; in heparin lyase family PL13; and in exoglucuronase family PL20  (18). Representative structures from these PL families were compared with NLR48. Representative structures for these families were: PL7, alginate lyase (A1-IIЈ; Aly) complexed with tetrasaccharide, Protein Data Bank (PDB) code 2ZAA  (19) ; PL13, heparin lyase I with octasaccharide, Pro- tein Data Bank code 3INA (20); PL18, alginate lyase aly-SJ02, PDB code 4Q8K (21); PL20, glucuronan lyase, PDB code 2ZZJ  (22) ; and PL14, Chlorella virus enzyme vAL-1, PDB code 3A0N (23). The number of ␤-strands in the inner and outer sheets varies between these enzymes, but the core structures (ϳ100 residues; Fig.
3B ) superpose well with that of NLR48 (Table  1 ). They differ mainly in the loop regions (Fig. 3A ). The PL14 lyase is the least similar and is excluded from further analysis. Despite sharing the same fold, the sequence identity between NLR48 and these other lyases is less than 14%. Nevertheless, despite low sequence identity, these enzymes have similar active sites and a shared catalytic mechanism belonging to the His/Tyr class  (18). The active site is located in the cleft extending along the inner ␤-sheet. To identify the putative catalytic site, we first utilized Con-Surf software  (24) , which showed the highly conserved residues among ϳ30 NLR48 homologs (Fig. 1D ). The solvent-accessible and conserved residues located within the cleft are: Glu 203 , Leu 178 , Gln 160 , and Arg 277 on the bottom of the cleft; Lys 162 , Asp 173 , and Arg 216 along one wall; and Tyr 157 , Tyr 281 , Arg 117 , Arg 80 , and Asp 78 along the other wall.
Comparison with other ulvan lyases Lyases that degrade ulvan polysaccharide have been identified and characterized only in the last several years. They have led to the addition of three new families to the CAZy classification, namely PL24, PL25, and PL28 families, in the CAZy database. We have previously characterized the structures and catalytic mechanisms of LOR107 (PL24) and PLSV3936 (PL25). Both ulvan lyases adopt a seven-bladed ␤-propeller fold. PLSV3936 utilizes the His/Tyr catalytic machinery with Arg 204 , Tyr 188 , and His 123 as neutralizer, catalytic base, and acid, respectively  (16). LOR107 uses Arg 259 to neutralize the C5 car-boxylic group, and His 146 appears to play both catalytic base/ acid roles aided by His 167 and Tyr 243  (28). Moreover, LOR107 binds the substrate in two stages with Arg 320 initiating substrate binding at the top of the cleft followed by substrate sliding deeper into the cleft toward the active site  (28).
Conclusions The marine genome sequencing project resulted in the identification of many ulvan-degrading enzymes. These are classified under PL24, PL25, and PL28 families in the CAZy database. Although PL24 and PL25 ulvan lyases have a seven-bladed ␤-propeller fold, PL28 lyases have a ␤-jelly roll fold, adding another family to the list of PL enzymes with this architecture. The catalytic mechanism of the PL28 representative lyase, NLR48 from N. ulvanivorans, is very similar to that of other lyase families with a ␤-jelly roll fold despite very low sequence identity and is a modification of the His/Tyr catalytic mechanism. The fold similarity of PL28 to several other families of polysaccharide lyases indicates their common evolutionary origin with adaptation to different substrates. Finally, the three families of ulvan lyases utilize a different mode of neutralization of the carboxylic group of the uronic acid.
Cloning The gene encoding NLR48 (NCBI accession number KEZ94336), lacking the first 25 residues as they are predicted to be a signal peptide, was cloned into three expression vectors with different tags to improve solubility and to aid in purification. NLR48(26 -303) was inserted into pET28 vector using the restriction cloning method, whereas the ligation-independent cloning protocol (29) was used to insert NLR48(26 -303) into pRL652 (modified version of pGEX with N-terminal GST tag followed by TEV cleavage site). All mutants used in this study were based on GST-NLR48(26 -303) as a template by following the QuikChange site-directed mutagenesis protocol. All constructs were verified by DNA sequencing.
SeMet-incorporated NLR48 was concentrated to 16 mg/ml for crystallization experiments using the hanging-drop vapor-diffusion method. The crystals grown from 0. 49 M sodium phosphate monobasic monohydrate, 0. 91 M potassium phosphate dibasic, pH 6. 9, at 9 °C were cryoprotected with 30% ethylene glycol, and diffraction data were collected at the 08BM beamline at the Canadian Light Source. Data were processed with the XDS software package (30) to 1. 9-Å resolution, and the data collection statistics are shown in Table  2. These crystals diffracted significantly better and showed better spot shape than the native crystals and were used for structure determination and refinement.
Structure solution and refinement of WT NLR48 The structure of NLR48 was solved by the single anomalous dispersion method with the SeMet data set using the AutoSol procedure in Phenix software  (31). There are two molecules in the asymmetric unit. All six expected selenium sites were identified. The initial model contained ϳ90% of the expected residues. The remaining residues were built manually using Coot  (32). Because the SeMet-containing crystal diffracted better than WT NLR48, this data set was used not only for solving the structure but also for refinement. The refinement was performed with Phenix software interspersed with manual rebuilding using Coot. The final R work was 0. 169, and R free was 0. 201. Several N-terminal residues are not visible in the electron density. The model contains residues 44 -303 in both chains, two Ca 2ϩ ions, four phosphates, and 710 solvent molecules.
Enzyme activity The activity of NLR48 and its various mutants was measured by monitoring the absorption at 232 nm, indicative of the formation of an unsaturated double bond in the sugar on the nonreducing end of one of the two reaction products. The assay solution contained 0. 5 mg/ml ulvan polysaccharide in 20 mM Hepes, pH 7. 5, 150 mM NaCl. 1 g of the enzyme was added directly to the assay solution with constant stirring, and the absorbance was measured as a function of time. The absorbance of the substrate alone was used as a control. a The data set for structure determination was collected at the wavelength of 0. 97864. The data set used for refinement was collected at the wavelength 0. 98013 as shown in the table. b The numbers in parentheses refer to the highest resolution shell.
Structure determination of NLR48 -tetrasaccharide complex The K162M mutant crystals were used for soaking experiments with an ulvan tetrasaccharide, which contained a mixture of ⌬UA-Rha3S-GlcA-Rha3S␣/␤ and ⌬UA-Rha3S-IdoA-Rha3S␣/␤. Briefly, a drop containing 3 l of substrate solution (ϳ50 mM tetrasaccharide solution in water) mixed with 3 l of crystallization well solution on a coverslip was equilibrated against 1 ml of well solution. The tetrasaccharide was prepared as described before  (28). The crystals were soaked in the substrate solution for ϳ2 h, cryoprotected in well solution supplemented with 30% ethylene glycol, and flash frozen in liquid N 2. Diffraction data were collected at the 08ID beamline, Canadian Light Source. These crystals diffracted to 2. 2-Å resolution and were isomorphous with the WT NLR48 crystals.
One round of rigid-body refinement was done on the complex dataset with the Phenix refinement program. The tetrasaccharide was built into the positive difference electron density with Coot. Further refinement was done using Phenix software. The complex structure was evaluated for stereochemistry using MolProbity. The final model has 44 -303 residues in each molecule, 212 water molecules, two calcium ions, two tetrasaccharides, and four phosphate ions. Data collection and statistics are shown in Table  2. The coordinates and structure factors have been deposited to the Protein Data Bank with accession code 6D3U.
Acknowledgments-We thank Kevin Voth for comments. We acknowledge the Protein Characterization and Crystallization Facility, College of Medicine, University of Saskatchewan for access to the crystallization robot. Research described in this paper was performed using beamline 08ID-1 at the Canadian Light Source synchrotron, which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the  Canadian Institutes of Health Research.
Methods Data collection. A cross-sectional questionnaire-based study targeting dog owners across multiple countries was performed. The inclusion criteria included being an over 18 years of age and living with and taking care of at least one dog. The study was approved by the Ethical Committee of the University of Murcia (1374/2016), and by the local Ethical Committees in the participating countries, where required. All methods were performed in accordance with the relevant guidelines and regulations of each country. The questionnaire was inspired by previously described surveys from the disciplines of human and veterinary medicine  [41] [42] [43] [44] [45] [46]. After the initial drafting, a pilot study was performed in Spain. In total, 57 individuals were asked to answer the questionnaire and give their direct feedback to the authors, thus enabling validation of the responses.
The identity of the respondents was kept anonymous. The aim was to include at least 100 questionnaire responses from at least two representative countries from each of the different regions in Europe. This included Southern Europe: Spain, Portugal and Italy; Northern Europe: Denmark and Sweden; Eastern Europe: Lithuania, Romania and Serbia; Central Europe: Croatia and Poland. The translated questionnaires were set up online using Google Forms and links were distributed through email and social media. In addition, hard copies were distributed via veterinary clinics, personal contacts, etc. An unlimited number of responses could be collected from December 2016 to March 2017. Data editing for analysis. Dog owners were categorised into three groups according to their body mass index (BMI), as calculated from their self-reported weight and height using the formula: = BMI weight(kg)/(height(m))  2  where underweight included BMI < 18.
5, normal weight was 18. 5 ≤ BMI > 25, and overweight/obese was BMI ≥ 25. The body condition of the dogs was assessed by the owners, based on the provided body condition score (BCS) and body fat index (BFI) charts (see Supplementary Material 1, questions 38 and 39). Dogs were grouped according to the BCS as underweight (BCS, 1 and 2), normal weight (BCS, 3), or overweight/obese (BCS, 4 and 5); and according to the BFI as normal weight (BFI, 20%) or overweight to obese (BFI, 30-70%). The countries were categorised into four groups according to the Gross Domestic Product (GDP) based on the 2016 Eurostat data (http://ec. europa. eu/eurostat/tgm/table. do?tab=table&plugin=1&language=en&p-code=tec00114, accessed 9 th December 2017): Group 1 (Low) -countries with GDP < 60, which included Serbia (GDP = 36), Romania (GDP = 55) and Croatia (GDP = 59); Group 2 (Medium) -countries with GDP between 61 and 80, which included Poland (GDP = 68), Lithuania (GDP = 75) and Portugal (GDP = 78); Group 3 (High)countries with GDP between 81 and 110, which included Spain (GDP = 91) and Italy (GDP = 96); Group 4 (Very high) -countries with GDP > 110, which included Sweden (GDP = 123) and Denmark (GDP = 125).
Acknowledgements The authors would like to acknowledge all the owners for participating in the study and all those who helped to disseminate the questionnaire. This work was conducted in the framework of the  European Cooperation on Science and Technology  ( COST) Action TD 1404 "Network for the Evaluation of One Health ". Financial support was provided by a grant from the  Robles Chillida Foundation  through its support programme for the promotion of research in Health Sciences, and the  programme "Juan de la Cierva Incorporacion" of 'Ministerio de Economia y Competitividad' , Spain , through a postdoctoral grant. The  University of Murcia  funded AMP through a predoctoral grant. The funders had no role in study design, data collection and analysis, decision to publish or the preparation of the manuscript.
STUDY DESIGN This was an international, double-blind, placebocontrolled study of OCA monotherapy in patients with PBC. Doses investigated in this study were dosefinding and different from those later investigated in phase 3 studies of OCA. At the time of this study, only phase 1 data of OCA were available, testing doses of 25-500 mg in healthy volunteers. No substantial AEs were observed at 50 mg, which was therefore considered an appropriate potential dose. Patients meeting enrollment criteria were randomized 1:1:1 to OCA 10 mg, OCA 50 mg, or placebo, administered once daily for 3 months. The computerized randomization schedule used a block size of 3 at each center. Patients were assessed at week 2, month 1, month 2, and month 3 (end of the double-blind phase). All patients had a follow-up visit 2 weeks after study medication discontinuation.
EFFICACY ANALYSES The primary endpoint was the percent change in ALP from baseline to EOS (month 3 or ET in the case of premature discontinuations or the last observed ALP level for patients who did not complete the study). The last observation carried forward method was used for missing data for the primary endpoint only. For secondary and exploratory endpoints, month 3 values included ET data in the cases of discontinuations when ET data were available. Secondary endpoints included change in ALP, c-glutamyl transpeptidase (GGT), ALT, AST, conjugated bilirubin, and achieving previously developed response criteria in PBC. (6) Exploratory endpoints included change from baseline in high sensitivity C-reactive protein (hsCRP), tumor necrosis factor-a (TNF-a), transforming growth factor-b, immunoglobulin M (IgM), glutathione, osteopontin, albumin, nonesterified fatty acids, FGF-19, enhanced liver fibrosis score, PBC-40 questionnaire, Short Form 36 survey, and achieving different thresholds of ALP decrease.
For categorical and exploratory variables, each OCA group was compared to placebo using a Fisher's exact test. All tests were evaluated at a 5 0. 05 with no adjustments for multiplicity. Post hoc comparisons between each OCA group and placebo for the UK-PBC and Global PBC prognostic models were obtained using a rank analysis of covariance model with baseline value as a covariate. Analyses were performed using SAS version 9. 1. 3 or newer. All graphs and figures were produced in GraphPad Prism version 6. 0.
The improved predicted survival using both prognostic models reflects improvements in ALP together with other variables within the models. The utility of survival predictions in this study was limited by the short OCA treatment period and small patient population. Furthermore, these prognostic models were developed to predict clinical outcomes following 1 year of UDCA treatment and have not yet been validated for use with OCA. A phase 3 study evaluating clinical outcomes with OCA in patients with PBC (COBALT; ClinicalTrials. gov identifier NCT02308111; EudraCT no. 2014-005012-42) is ongoing and may be used to test the utility of these prognostic models with OCA. Nevertheless, the results are promising given that 3 months of OCA monotherapy resulted in measurable and significant improvements in predicted survival.
Since the investigation of van Ingen et al. , attempts were undertaken to search for laminar parts within the boundary layer of wind turbines operating in the lower atmosphere with much higher turbulence levels than seen in wind tunnels or at higher altitudes where airplanes usually fly. Based on the results of the DAN-Aero experiment and the Aerodynamic Glove project, a special work package Boundary Layer Transition was embedded in IAEwind Task 29 MexNext 3rd phase (MN3). Here, we report on the results of the application of various CFD tools to predict transition on the MEXICO blade. In addition, recent results from a comparison of thermographic pictures (aimed at detecting transition) with 3D transitional CFD are included as well. The MEXICO (2006)  and NEW MEXICO (2014)  wind tunnel experiments on a turbine equipped with three 2.
CFD comparison of NEW MEXICO experimental data 2. 3. 1. Overview of CFD Codes A short overview of the used codes (elsA, CFX, EllipSys, FLOWer, OpenFOAM and TAU) is given. For more details, see the comprehensive summary of MN3  [20]  and references therein, especially appendix F and section 4. 4 Convergence of CFD simulations. Three of the codes come from aerospace research institutions: elsA from ONERA (France) and FLOWer and TAU from DLR (Germany). CFX  [21]  is the only commercial code used (ANSYS), EllipSys was developed by the Danish Technical University and OpenFOAM by the openFOAM community  [22]. All have been tested and validated extensively and represent state of the art RANS-CFD codes. Mesh size ranges from 15 mio (CFX) to 140 mio (elsA) and the computational domain from 5 rotor diameters (elsA) to 30 rotor diameters (TAU).
Transition on a 37 m blade In addition to the MexNext project, the TAU code was used to simulate 3D transition on a 37 m blade at partial load. For this specific blade thermographic images exist  [6]. The comparison of thermographic images with CFD simulations  [26]  showed a discrepancy in the position of the laminar-turbulent transition. Thus, in this case it is not possible to confirm the large extension   of an assumed laminar state (more than 40 % relative chord along almost the whole blade) by this specific transition prediction tool. However, some of the operating conditions of the turbine, e. g. , wind velocity and pitch angle, were not known accurately. Therefore, it might be possible that the optical findings can be reproduced with appropriate simulation parameters.
Acknowledgments The authors Schaffarczyk and Reichstein acknowledge the  North-German Supercomputing Alliance (HLRN)  for providing HPC resources that have contributed to the research results reported in this paper. 1234567890 ''"" The Science of Making Torque from Wind (TORQUE 2018) IOP Publishing IOP  Conf. Series: Journal of Physics: Conf. Series 1037 (2018) 022012 doi : 10. 1088/1742-6596/1037/2/022012.
I. FOREWORD The Nuclear Energy Agency (NEA) of the Organization for Economic Cooperation and Development (OECD) supports the need for high quality nuclear data for nuclear applications. These applications encompass not only energy production, but also handling of waste, radiological protection and medical isotope production. Several of these are still very demanding upon adequate and accurate nuclear data for design purposes and demonstration of safety. For many years the NEA has supported international collaborative advances in evaluated cross-section nuclear databases via its Working Party on Evaluation Cooperation (WPEC). The work described in this article presents the CIELO project as an example of a recent important advance made by the international nuclear reaction data community, under WPEC Subgroup 40.
We felt that this could best be accomplished by establishing a more formal collaboration arrangement for experiments, and for theory and simulation components. The intention was to document open questions and issues that were resolved through the collaboration, and create evaluated data files that embody the advances. From the very beginning we have considered the collaboration process to be as important as the new evaluations being produced. Since nuclear criticality applications are impacted by the integrated effects of neutron reactions on many nuclides, our goal was also to create data files that (neutronically) perform well together as a suite. This was summarized in an article developed at the beginning of the CIELO collaboration  [1]  in 2013. It was anticipated that the data files that we would produce would be available for adoption -in part or as a whole -by the major evaluated database efforts of ENDF, JEFF, JENDL, CENDL, and so on.
And indeed, the CIELO-1 and CIELO-2 sets of cross section data described in this report have been adopted by the ENDF and JEFF communities, respectively. Other papers in this issue of Nuclear Data Sheets describe the CIELO efforts in more detail  [3] [4] [5] [6] [7] [8]  and also describe the major ENDF/B-VIII. 0 database release  [9]  that adopts CIELO-1 including the new standards  [3]. Computational nuclear science and computing advances have played a key role in CIELO's progress. Fast computers have enabled large-scale nuclear criticality and transport simulations, mostly with the MCNP R version 6 code  [10] , to assess the performance of proposed evaluation changes, with a feedback loop leading to the optimization of the reaction model parameters and ultimately of the evaluated data files.
In practice, CIELO-1 has been adopted by the ENDF community in ENDF/B-VIII. 0, and CIELO-2 by the JEFF community in JEFF-3. 3. These are illustrated in Table  II. TABLE II. Lead laboratories evaluating CIELO-1, -2 databases. CIELO-1 is being adopted by ENDF, CIELO-2 by JEFF. Many other labs contributed, including with data measurements. For each isotope we separately tabulate the work done on the resonance range and the fast region (e. g. , keV and above for actinides).
16 , and 14 MeV transmission data is shown in Capote's paper  [5]. The measured and MCNP R version 6 simulated neutron spectra leaking from the outer surface of this sphere are shown in Fig. 16. It is evident that both CIELO-1 (ENDF/B-VIII. 0) and ENDF/B-VII. 1 reasonably reproduce the measured data, providing a useful validation of the evaluated data for neutron transport applications. 8Q ν S $YHUDJH 3URPSW 1HXWURQ 0XOWLSOLFLW\ QI ,QFLGHQW 1HXWURQ (QHUJ\ 0H9 7DLHE 6PLUHQNLQ %R\NRY 0DO\QRYVNL\ )UHKDXW %DR =RQJ\X ,$($ &,(/2 (1')%9,, - (1'.
V. Additional improvements must follow this pilot project. In the coming years we expect to see new plutonium prompt fission spectra (PFNS) and fission cross section data from the Los Alamos Chi-nu and TPC experiments and consideration of newly evaluated (softer) thermal PFNS from the IAEA CRP for 233 U and 239 Pu  [11] ; as an interim step we included the Neudecker PFNS spectrum for incident energies above 5 MeV, which provides an improved treatment of the effects of multi-chance fission and preequilibrium processes. Also, the recent Mosby et al. DANCE capture data should impact a future plutonium resonance analysis in the unresolved and resolved resonance regions, analogous to how DANCE data influenced the 235 U CIELO-1 evaluation described above. In the fast region above 30 keV, these data  [7].