dataesr/scientific-paragraphs-categorization huggingface dataset:
On the other hand, the use of high-performance liquid chromatography (such as nanoLC) online with high-resolution mass spectrometers (such as TripleTOF 5600+ QqTOF mass spectrometer) has outperformed Western blot with greater sensitivity, selectivity, specificity and reproducibility, wider linear dynamic range, increased accuracy and precision, high-throughput of in-depth information  [41] [42] [43] [44] [45]. Despite these considerations, Western blot quality control alone highlighted the superiority of the RSPI-based Mascot -jTRAQx -CiR-C pipeline over the RPA-based Paragon -ProteinPilot -CiR-C pipeline, later confirmed thanks to the UPS1 spike-in experiments. A major point of iTRAQ data processing is the upstream tolerance for peptide characterization and identification. More peptides were identified with Mascot Server than with Paragon, mainly because mass tolerances were more stringent with the latter, due to the use of non-customizable manufacturer's parameters optimized for data generated by TripleTOF 5600+ mass spectrometers.
Mass tolerances with Mascot Server were chosen to be sufficiently permissive to provide enough data for further selection. The choice of stringent parameters for identification is in complete agreement with the RPA quantitation strategy, as implemented in ProteinPilot, where peak width is essential to reliable quantitation. Conversely, our approach postpones the application of stringent conditions to after quantitation. Another major point of iTRAQ data processing is the downstream management of irrelevant data. It can be done manually but it is time-consuming and error-prone due to the huge amount of information at the peptide level as well as the number of replicates. Just like with every high-throughput approach, the analysis of iTRAQ results needs to be automated. The CiR-C algorithm was designed to be the simplest in terms of data elimination and transformation.
Likely to exacerbate inherent issues -such as ratio-compressing variance-stabilizing normalization -heavy data transformation was not used after jTRAQx or ProteinPilot data processing. The biological significance of the results arose from: (i) a focus on peptide selection thanks to the probabilistic Mascot score or its Paragon counterpart (Confidence score); (ii) the restriction to selected peptides based on their occurrence among multiple biological replicates; (iii) the calculation of median and weighted mean ratios for each set of peptides obtained from a given protein. As mentioned above, upstream data processing was willingly permissive to sustain this statistical approach. It resulted in less loss of information and good data fitting. Paradoxically, stringent identification criteria also resulted in increased output, including a large amount of irrelevant data: when parsing peptide summaries, it appeared that irrelevant data were essentially null ratios, i.
e. , the technical impossibility to provide peptide quantitation from the MS2 mass spectra. The confidence threshold for the Mascot score was a compromise between the generation of aberrant information and the loss of information. This threshold highly depends on the number of peptides characterized by mass spectrometry. The probability of a random match was first set to 1 out of 1000 (s = 30, P=0. 001) and the test of scores 10-fold apart from our initial choice (s = 20, P=0. 01) confirmed how close it is from a potential optimum for the size of our datasets. Indeed, this threshold highly depends on the number of peptides characterized in MS/MS. The occurrence threshold was set to the largest possible values -the more peptides, the better -hence the restriction to ubiquitous peptides, i. e.
Significance of the study In this work, an in-house algorithm named Customizable iTRAQ Ratio Calculator (CiR-C) was implemented to process large datasets and compute final quantitation (median, weighted mean and standard deviation) for iTRAQ-based shotgun proteomics. This algorithm was used to retreat datasets in the comparison between two workflows based on the two strategies of MS/MS signal integration (RPA versus RSPI) for iTRAQ quantitation in the perspective of the proteome monitoring of tubular proximal cell lysates. RSPI was confirmed to be the best-suited strategy when using high-resolution MS platforms. The RSPI-based iTRAQ workflow happened to allow reliable and robust protein expression measurement. CiR-C proved to be a promising, simple and powerful, adjunct to iTRAQ data processing.
Cytotoxicity Test The cytotoxicity was determined on TIB-75 hepatocytes using the Alamar blue test. The cells were cultured at 37°C in DMEM + Glutamax containing 10% fetal bovine serum (FBS, Gibco Life Technologies), in 96-well plaques of 100 µM of streptomycin and 100 units/mL of penicillin. They were maintained in a 5% CO 2 -humified atmosphere and passaged twice a week by removing the adherent cells with 0. 05% Trypsin-EDTA. Fluorescence measurements at 570 nm were performed on a TECAN Infinite 200 plaque reader and IC50 was assessed from the normalized values using Graphpad Prism software.
In vitro Relaxivities Studies Samples of MNPs and UMLs were diluted in injection buffer (0. 108 M NaCl, 0. 02 M sodium citrate and 0. 01 M HEPES) at various concentrations of Gd (0, 0. 1, 0. 5, 1. 0, 3 mM). In vitro relaxivity experiments were carried out by recording T 1 and T 2 maps with a 7T MR imaging vertical spectrometer fitted with an ultra-shielded refrigerated magnet (300WB, Bruker, Avance II, Wissembourg, France) and equipped with a nominative 200 mT/m actively shielded gradient. The software Paravision 5. 1 allowed the acquisitions with the following parameters: for T 1 map: RARE images; TE = 13 ms; TR = 15 s, 8 s, 3 s, 1. 2 s, 0. 8 s, 0. 594 s, 0. 3 s, 0. 144 s, 0. 05 s, 0. 033 s, RARE factor 2; for T 2 map: multi-echo MSME images: hermitian pulse, TR/TE = 15 s/11 ms, 32 echos.
Additionally, magnetization measurements were performed on a single crystal of the slow-cooled Ni45Co5Mn37In13 alloy oriented with the magnetic field parallel to the c-axis. Neutron diffraction experiments were performed in D1B (λ=1. 28Å and 2. 52Å) and D2B (λ=1. 59Å), powder diffractometers, D9 (λ=0. 8Å and 0. 5Å) single-crystal diffractometer and D3 (λ=0. 8Å) polarized-neutron diffractometer at Institut Laue-Langevin in Grenoble. The polarized neutron diffraction measurements were carried out in paramagnetic austenite phase, with an applied magnetic field along the c-axis. The data treatment was carried out using the programs of the Fullprof Suite. [27]  The maximum entropy method,  [28]  as implemented in Dysnomia program,  [29]  was used to obtain spin density maps from the polarized neutron diffraction data.
The atomic order and the magnetic coupling in the austenitic phase of the studied alloys have been analyzed by unpolarized neutron diffraction. The results, in the form of occupancies of the different crystallographic sites and magnetic moments per site, are summarized in Table  1. The diffraction data obtained correspond to the Heusler 2 1 structure with 3 �  space group. The occupancies have been determined in the paramagnetic phase, assuming as starting point an ordered system. Then, using soft restraints according to the composition of the alloys to reduce the number of free parameters and taking advantage of the negative scattering factor of Mn, the different species were allowed in all crystallographic sites. Since for some of the species the refined occupancy recurrently gave negative or close-to-zero values, these were fixed to zero.
Acknowledgments: This work has been carried out with the financial support of the  Spanish "Ministerio de Ciencia, Innovación y Universidades " (Project numbers  MAT2015-65165-C2-R  and  MAT2014-56116-C4-1-R ). ILL and SpINS are acknowledgment for the beam time allocation: experiments  5-41-497 ,  EASY-379 ,  5-31-2484  (https://doi. org/10. 5291/ILL-DATA. 5-31-2484 )and  CRG-1905. J. López-Gacía  acknowledges ILL for Ph. D. contract.
Powder X-ray diffraction (PXRD) analysis Powder X-ray diffraction (PXRD) analysis was carried out on KLiMn-Mn 10 W 4 -P 8 W 48 to confirm the identity and phase purity of the crystalline material. As shown in Fig. 4 , the experi-mental pattern is consistent with the simulated one (on the basis of the single-crystal structure), which indicated the phase purity of the sample. The minor shift in the peaks reflects the changes in the unit cell due to the fact that single-crystal measurement was carried out at 100 K, whereas the PXRD data were collected at room temperature. There might be some loss of lattice water molecules during PXRD measurement.
Acknowledgements M. I. thanks  Prof. Annie. K. Powell  for her continuous support and guidance. M. I. acknowledges support from the  Helmholtz Society through the program Science and Technology of Nanosystems  (STN). M. I. also thanks the  University of Balochistan, Quetta, Pakistan , for allowing her to pursue her Ph. D. and postdoctoral work at  Jacobs University  and  KIT , respectively. We also thank  Sven Stahl  and  Dr Thomas Bergfeldt  for performing TGA measurements and elemental analysis, respectively. This work was partially carried out with the support from the  Karlsruhe Nano Micro Facility (KNMF) , a Helmholtz research infrastructure at the  Karlsruhe Institute of Technology. We also thank the  Université Paris-Sud  and the  CNRS  for financial support.
They calculated the slamming load caused by the vertical velocity in hull cross-sections and added the strip theory to determine three-dimensional nonlinear ship motions. They also recommended not to implement the SPH method to study events that had a long duration because it requires significant computation time. Panciroli et al. [10]  studied the hydro-elastic effects of deformable wedges using the SPH method by utilizing a commercial code LS-Dyna. Numerical results were in good agreement with experimental data and they also observed that the different mode shapes dominated the structural deformation when there was an increase in the hydro-elastic effects. However, the divergence from experimental behavior recorded in their numerical results was attributed to the trapped air that occurred during the impact event.
For the slamming event with free surface flow, the classical Navier-Stokes equations need to be solved. Assuming the fluid was non-viscous, and the shear stresses were neglected, then Euler equations can be presented as follows  [8] : % ⃗ = & ⃗ - ∇ ⃗ P ρ ( 3 ) ' = -'∇ ⃗. % ⃗ (4) Where g ⃗ , ρ, P and v ⃗ are the body forces, density of the fluid, pressure and velocity of the fluid respectively. With interpolation of the points through the domain D, the particle can be introduced: ) ( ⃗ ) = * + , + + (5) Where i represents each interpolation point with the domain D, w / weight term and has the dimension of a volume. Using the Lagrangian derivative and Euler equations, the formulation of the momentum equations can be written  [8] : % ⃗ = & ⃗ -* 0 1 2 3 + ' + 2 + 3 1 ' 1 2 5 1 ∇ ⃗ ( + ⃗ -1 ⃗ , ℎ) (6) ' + = * 0 1 6% + ⃗ -% 1 ⃗ 7 1 " ⃗ ( + ⃗ -1 ⃗ , ℎ) (7) The numerical results for sandwich panels subjected to the slamming impact were obtained by implementing the above define smoothed particle hydrodynamics (SPH) approach in the commercial code ABAQUS/Explicit.
Model creating and meshing The slamming model was constructed similar to the experimental setup in three-dimension scheme based on the Smoothed Particles Hydrodynamic (SPH) using commercial software (Abaqus/Explicit). The full slamming model was decreased to a 3D quarter model to minimize the computational time, Fig. 6a. About 543388 particles were generated for fluid domain, and it should be kept in mind that the particles had to be intensive and uniform in all directions to ensure fewer densities toward the extremes, Fig. 6b. The sandwich panel consisted of 2918 elements with the element type SC8R linear quadrilateral elements.
FTIR FTIR analysis for extracted hemicelluloses were performed by a FTIR spectrophotometer (Thermo Scientific iD3ZnSe ATR-Nicolet iS 5 FTIR Spectrometer unit). Hemicelluloses powder was placed on a ZnSe crystal plate. Each IR spectrum was obtained over the wave number range of 400-4000 cm -1 with eight scans at resolution of 4 cm -1. The spectra were analyzed using ThermoScientific OMNIC software.
Acknowledgements L. L. and Z. Z. gratefully acknowledge financial support from the  National Key R&D Program of China  ( 2017YFA0303602 ),  3315 Program of Ningbo , and the  National Nature Science Foundation of China  ( 11774360 ). Calculations were performed at the  Supercomputing Center of Ningbo Institute of Materials Technology  and Engineering. W. L. and J. C. acknowledge the financial support from the  Singapore National Research Foundation  under CRP Award No. NRF-CRP10-2012-02  and  Singapore Ministry of Education   MOE2018-T2-2-043 ,  AMEIRG18-0022 , A* STAR IAF-ICP 11801E0036  and  MOE Tier 1-FY2018-P23. C. J. L. acknowledges the financial support from the  Lee Kuan Yew Postdoctoral Fellowship  through the  Singapore Ministry of Education Academic Research Fund Tier 1  (Grant No.
Acknowledgments: We thank  Z. W. Lin ,  A. Mueller ,  F. Q. Wang  and  F. Yuan  for useful discussions and comments. This material is based on the work supported by the  Natural Science Foundation of China (NSFC)  under Grant Nos. 11575070 ,  11775095 ,  11890711  and  11375072. CM and SYW are supported by the  Agence Nationale de la Recherche  under the project  ANR-16-CE31-0019-02.
Spectra were referenced against TMS (tetramethylsilane). XPS measurements were performed with a Kratos Axis Nova Instrument, using a monochromated Al Kα source (1486. 6 eV) operating at 300 W. The instrument base pressure was 5 × 10 -10 Torr. The sample area analyzed was about 700 µm × 300 µm. A pass energy (PE) of 80 eV, with an all over instrumental resolution of 0. 9 eV measured on Fermi edge, was used to acquire wide range survey spectra. A PE of 40 eV was used to acquire narrow spectra of the C 1s, O 1s, Si 2p, Cu 2p and Na 1s levels with an all over instrumental resolution of 0. 55 eV measured on Fermi edge. All data were acquired using charge compensation with low energy electrons gun in order to have homogenous surface potential. This is necessary to have accessible chemical information.
XPS data were analyzed using the CasaXPS software (version 2. 3. 19) using Gaussian/Lorentzian (30% Lorentzian) line shapes and Shirley background correction. All spectra were calibrated with Hydrocarbon C1s photoemission set to 285. 0 eV binding energy. In order to check for reproducibility, all XPS measurements are carried out in three independent areas of the samples. All NMR, IR and XPS characterizations were done on samples dried at 100°C under vacuum.
The overall synthesis process is presented in Scheme 1. The composition was determined by thermal gravimetric analysis (TGA) and differential scanning calorimetry (DSC) using an analyzer model TGA-7 series (Perkin Elmer, Waltham, MA, USA,) in the temperature range of 30-1000 • C in air at a heating rate of 10 • C min -1. Elemental analysis was performed using a CHNOS analyzer (Elementar Analysen Systeme GmbH, Langenselbold, Germany). The structure of the samples was analyzed by X-ray diffraction (XRD) using a X'Pert diffractometer (Philips, Hamburg, Germany) equipped with a CuK α X-ray source (λ = 1. 54056 Å). Data were collected in the 2θ range of 10-80 •. The particle morphology was examined by scanning electron microscopy (SEM) (JEOL microscope, Akishima, Japan). Raman spectra were collected at a spectral resolution of 2 cm -1 with a double monochromator (Jobin-Yvon model U1000) using the 514.
Totally Determined Structures and Implications. To represent the class of I-Au144X60 compound, chemists demand rigorously to see at least one case of total-structure determination by single-crystal X-ray crystallography. In early Spring (2018), two such reports were submitted to journals. 2, 3 Each distinguished both enantiomeric structures and noted profound chirality for the surface (ligand) layer. The abundant detail provided by such crystallographic datasets provides rich material for comparison to predictions of theoretical models, and thus to stimulate further refinements. These are essential steps toward the ultimate goals, namely: (i) to achieve a fundamental understanding commensurate to the broader significance of the material-in-practice; (ii) to provide guidance to future high-level experimental work that confirms and complements such theoretical comprehension; and (iii) to assure those who prefer simply to use such compounds that the fundamentals are soundly understood.
ACKNOWLEDGMENT Calculations were performed at the  DGTIC-UNAM Supercomputing Center  under Project  LANCAD-UNAM-DGTIC-049. ILG thanks support from  DGAPA-UNAM  under Project  IN108817  and  Conacyt-Mexico  under Project  285821. RLW acknowledges support from the  Welch Foundation  ( AX-1857 ). We thank  Prof. Zhikun Wu  and  Prof. Quan-Ming Wang  for useful discussions and for providing us with useful crystallographic data of the protected Au144 clusters.
Acknowledgements The authors thank  Magali Fradet  from the  ImagoSeine core facility -Paris Diderot University  ( ANR-10-INBS-04 ) for flow cytometry analysis,  Christine Péchoux  from the  MIMA2 -1196 GPL INRA unit  for TEM preparation and analysis (Jouy-en-Josas, France), and  Mathieu Receveur  from the  MSC -Paris Diderot University  for the conception and realization by means of a 3D printer of the thermostated curve, which was necessary for the thermal experiments starting at 37 °C. Fluorescence microscopy was performed at the imagery platform of the  Muséum National d'Histoire Naturelle (MNHN) , with the help of  Dr. C. Djediat. ICP-OES measurements were performed at the  Chemistry Department -Paris Diderot University , with the help of  Gurvan Le Faucheur  and under the supervision of  Marie-Eveline Pinart.
The chosen strain level (4%) corresponds to the work hardening stage during which twinning is the predominant deformation mechanism  [8]. Interrupted tensile tests were performed parallel to the rolling direction (RD) of the sheet at the strain rate of The samples for EBSD analysis were prepared by mechanical grinding until 1 µm diamond paste, followed by a final electrolytic polishing using a solution of glycerol, perchloric acid and ethanol at a voltage of 20 V. The EBSD data were obtained using the ZEISS Supra 55 system operating at 20 kV with a 0. 2 µm step size. The microscope was equipped with the TSL/EDAX data acquisition software and the CDD camera DigiView 3. The data were collected from different scans covering the total surface area around 0. 5 mm 2  , allowing the analysis of 500 grains.
The fraction of twinned grains was measured, one twinned grain being considered as a grain that contains at least one visible twin. The extent of twin formation regarding the grain orientation and the grain size area was determined. The grain size orientation is defined in the present work as the misorientation angle between the c-axis of the grain and the direction of the macroscopic stress applied to the samples. The calculation of the area of the grain includes any twinned regions. The twin area fraction was determined, as well. Grain area and twin area data are based on 2D analysis of the material. For each twinned grain the number of variants was also determined. Table  1  shows the shear stress associated to some twin mode and other crystallographic parameters. Tenupol5, with an electrolyte consisting of 90% glacial acetic acid and of 10% perchloric acid at a voltage of 50 V.
Grain orientation effects on twinning In order to investigate the orientation effect for each grain, the angle between the c-axis and the load axis was determined. This orientation data allow us to determine whether a grain is favorably oriented to deform by generating tensile twins. Regarding the orientation of grains, it was observed that grains that have their c-axis almost parallel to the direction of the applied load are all twinned (Figure  7a ), and contain tension twins as expected. However, about 35% of grains are not conveniently oriented for twinning. These grains with their c-axis perpendicular to the loading axis also contain tension twins, which is unexpected, since their Schmid factor is in average lower than the values corresponding to grains with their c-axis parallel to the loading axis.
The Al-Si-Cu W319 alloy (Al-5. 50Si-3. 40Cu-0. 87Fe-0. 27Mg, weight percent) used in this study was provided by Ford Motor Company. A cylinder sample of diameter 1. 8 mm was machined by wire-electrical discharge machining. The temperature gradient stage was set up at ID19, European Synchrotron Radiation Facility. The details about the temperature gradient stage, similar to the one in Ref  [15]  are provided in the supplementary material A pink beam with peak energy at 35 keV was used at ID19, ESRF. A high-speed CMOS camera (PCO. DIMAX, Germany) was used for X-ray imaging. The field of view (FOV) of the camera was set to 2. 2 by 2. 2 mm and the pixel size is 2. 2 m. The sample was rotated at 2 s per rotation for tomographic data collection. A tomogram with 1000 projections over 180 ° was taken in 1 s and there were 15 s waiting time between two consecutive tomograms for data downloading.
Volumetric data with 30 slices at each chosen height were used for the measurement. As shown in Fig. 3d , the curves ( volume fraction as a function of time (t) at different heights (h)) were almost linear with very similar slopes. The intercept of these curves with the x-axis corresponded to the time ( ) at which β phase just appeared at the chosen height. The at different heights of the sample is then plotted in Fig. 3e. A slope of about 11. 7 µm/s was obtained after a linear fitting, which means that the isotherm moved upwards at a speed of 11. 7 µm/s as the sample was cooling down. The speed of the isotherm can also be calculated by the ratio of the cooling rate to the temperature gradient, resulting in a very close value of ~12. 2 µm/s. This indicates that our temperature estimation was relatively accurate.
The overall behaviour of β phase with respect to the average volume, total number and volume fraction was linear with decreasing temperature. However, the behaviour of individual β intermetallics remained unclear. To examine this, a particle-tracking algorithm was developed in-house in Matlab (see supplementary material). The volume change ( , V is the volume) of several individual particles which first appeared at t =t 0 + 240 s is shown in Fig. 4a. The growth dynamics of the intermetallics varied significantly, but most of them grow linearly. We then fitted the curves of the tracked particles' volume vs time with linear functions. The slopes are the volume growth rate of the β intermetallics. Fig. 4b  shows the histogram of the volume growth rate of the intermetallics on a log x-axis, which shows a normal distribution.
Acknowledgement This work was supported the  EPSRC-UK  ( EP/I02249X/1  and  EP/K007734/1 ). The authors thank the  European Synchrotron Radiation Facility  for providing the beamtime (MA2989) and staff at ID19 beamline for support. B. C. acknowledges the support from the  Diamond Birmingham Collaboration  and the  Alan Turing Fellowship.
In this paper, the purpose is to introduce a transfer function that can be directly used with source nuclear data to compute the desired value of beta skin dose in accordance with the Q system. To validate the method based on transfer functions, some radionuclides will also be calculated with the FLUKA particle transport code  (Ferrari et al. 2005; Battistoni et al. 2015)  as a predefined radiation source with the HI-PROP option. This kind of calculation will be referred to as the source method in the next sections.