dataesr/scientific-paragraphs-categorization huggingface dataset:
In particular, thanks to the high luminosity of the neutron beam, a wealth of fission data on actinides spanning from 230 Th to 245 Cm have been collected at the CERN n_TOF facility CERN in its 18 years of operation. The higher flux expected in the second experimental area (EAR-2) after the installation of the new spallation target in the near future will give a further boost to fission studies at n_TOF, allowing the collaboration to study actinides with half-lives as short as a few years. Stronger constraints on fission models may come in particular from measurements of neutron-induced fission cross sections and fission yields of an entire isotopic chain. In fact, a combination of data for various isotopes of the same element allows one to simultaneously study multiple-chance fission, thus better defining relevant model parameters.
In particular, the high resolution of EAR-1 allows one to accurately study the resolved resonance region (RRR), while the high flux of EAR-2 is fundamental for measurements with high-activity and/or low mass samples, as it minimises the relative contribution of the background related to the radioactivity of the sample and allows one to collect high-quality data in particular in the unresolved resonance region and for fast neutrons. In this sense, the two experimental areas can be considered complementary to each other and a combination of data collected in both areas can provide, in some cases for the first time, high-accuracy and high-resolution data in a wide energy range. Accurate measurements of neutron-induced reaction cross sections require very good knowledge of the various features of the neutron beam in the experimental area, in particular its resolution function, previously discussed, its energy spectrum, i.
In fact, PPACs allow the n_TOF Collaboration to study fission reactions up to 1 GeV, providing data in the high neutron energy region, which cannot be obtained at any other neutron facility in the world. Several interesting results have indeed been obtained so far with this unique beam-detector combination in an energy range covering almost 11 orders of magnitude, from thermal neutron energy to 1 GeV. Figure  16  shows the 237 Np cross section measured at n_TOF in the range of 0. 7 eV-1 GeV. A rather unique feature of the setup is that in the same measurement the resonance region and the high-energy region can be covered. An important factor in the measurement with the PPAC system is the detection efficiency. Since the coincidence between the two fission fragments is required to identify a fission reaction and because the backward-emitted fragment has to cross the sample backing, the efficiency is typically lower than in the case of an ionisation chamber.
In the RPT data analysis, a triple coincidence is required, with the effective solid angle determined by the middle (ΔE 2 ) detector, which has the smallest transverse dimensions of all three detectors. The ΔE 1 and the E detector are larger to ensure that all charged particles originating from the sample and passing through the middle detector also produce signals in the first and last detectors. The diameter of the E detectors is also sufficiently large to limit incomplete energy deposition to a tolerable level, thus avoiding "tails" in the shape of the recoil peak. The elongated design of this RPT results in a directional sensitivity of the telescope to events originating from the sample, suppressing background events originating elsewhere. The three recoil-proton telescopes were mounted in EAR-1 together with a fission ionisation chamber and a set of Parallel Plate Avalanche Counters, both equipped with 235 U samples, for the measurements of the fission reactions, and the setup was tested in the n_TOF neutron beam to verify its predicted performances.
Data acquisition system The data acquisition system used for the Phase-I and Phase-II campaigns was based on Acquiris (later Agilent) 8-bit flash-ADCs with a sampling rate of up to 1 GHz and an 8 Mb memory limit of the internal buffer. Fast electronics are of major importance at n_TOF in order to resolve short times-of-flight and high counting rates in the various detector setups. The trigger signal for the start of the data acquisition is given by a beam current transformer (BCT) from the PS and corresponds to the arrival of a proton pulse that hits the spallation target. The full output signal from the start time is recorded during a time window limited by the on-board internal memory within the range of 100 µs to 200 ms which, for the 185 m flight-path, corresponds to neutron energies down to 20 keV and 4 meV, respectively.
Data analysis While the rather unique features of the n_TOF neutron beam and the high-performance detection and DAQ systems allow to collect high quality data, a large effort is required to extract high-accuracy results on neutron-induced fission from the raw signals. This procedure involves several steps, from signal identification and reconstruction, needed to extract related information such as signal amplitude, time-of-flight etc. , to the study of the detector response and interaction with the neutron beam that often relies on detailed Monte Carlo simulations of the neutron beam and of the experimental setup, and finally to a series of important corrections, such as the dead-time correction (related to the problem of signal pile-up), particularly severe in EAR-2. In this section, the various steps of the data reduction and analysis are presented and discussed, with particular emphasis on the new techniques specifically developed at n_TOF to address certain important issues that could hinder the attainment of high-accuracy fission results.
An alternative approach, described in Ref. [185] , is to use sophisticated signal generators to emulate the detector signals during the experiment and feed them to the acquisition system for a wide bandwidth of frequencies (true counting rate, R true ) in order to cover the measured counting rates in the experiment (experimental counting rate, R exp ). The ratio between the true and experimental counting rates f DT for each given frequency provides a correction function calculated by fitting the experimental points with a parabolic function, as can be seen in Fig. 38 , which can later be applied to the experimental counting rate spectra. The two proposed methodologies were benchmarked in the test case of the 238 U(n,f) cross section relative to 235 U(n,f) from data collected in EAR-2. The cross section values derived using correction factors estimated with the two methodologies are in quite satisfactory agreement, as can be seen in Fig.
39 , and they are furthermore in agreement Fig. 39  The two proposed correction methodologies described in the text were applied to derive the 238 U(n,f) cross section from data recorded in EAR-2. The agreement between the calculated cross section and the ENDF/B-VII. 1 is quite satisfactory in both cases with the ENDF/B-VII. 1 evaluation in the incident neutron energy range between 1. 8 and 4. 0 MeV where the 238 U(n,f) cross section is considered a neutron standard.
A large effort has also been made by the n_TOF Collaboration to measure the 235 U(n,f) cross section at high energy, i. e. above a few MeV. Although this cross section is considered standard up to 200 MeV, the evaluations above 20 MeV are based on a few datasets, while above 200 MeV they are based purely on theoretical predictions and on experimental results on the proton-induced fission reaction. The wide energy range of the n_TOF beam, extending up to ∼1 GeV neutron energy, has offered the unique opportunity to provide much-needed additional data on the 235 U(n,f) cross section up to 200 MeV and cover for the first time the region between 200 MeV and 1 GeV. For this high-energy measurement, the n-p elastic scattering which is a primary cross section standard up to 20 MeV, and known with good accuracy above this energy, is used as reference.
For this reason, the two recoil-proton telescopes described in Sect. 4. 6 were specifically built, one optimised for the energy region below 200 MeV, and the other one for neutron energies from a few tens of MeV up to 1 GeV. The data are currently being analysed, but preliminary results indicate that the goal of the measurement was fully reached and a new dataset covering the high-energy side of the cross section standard with high accuracy is expected to be available in the near future. The n_TOF Collaboration has provided important data at high neutron energies for another cross section standard: the 238 U(n,f) reaction. Prior to the n_TOF measurement, only two datasets were available above the fission threshold of this reaction, but they were discrepant by as much as 8% at 200 MeV neutron energy, the upper limit of those measurements.
With the aim of solving the existing discrepancy and extending the energy range to higher energy, data were collected both with the Fast Ionisation Chamber (FIC) and with Parallel Plate Avalanche Counters (PPAC), previously described. Several 238 U and 235 U samples were used in the measurements and the datasets were combined with each other in order to minimise statistical and systematic uncer-Fig. 49  The neutron-induced fission cross section of 209 Bi (top panel) and nat Pb (bottom panel) measured at the n_TOF facility from threshold to 1 GeV. The blue curve represents the new IAEA evaluation reported in Ref. [203] , while the dashed curve shows the previous evaluation, performed before the n_TOF results became available. For comparison, the proton-induced fission cross section is also shown in the figure as a dotted curve tainties.
The main difficulty in this case was related to a contamination of the sample with the short-lived 244 Cm isotope (T 1/2 =18. 1 y). This 6. 6% contamination was the main responsible for the high α-activity, of the order of 100 MBq, which constituted a very large source of background together with spontaneous fission. However, thanks to the high instantaneous neutron flux of n_TOF, both problems did not hinder the measurement, and at the end data affected by a relatively small uncertainty of 5% were obtained. For this reaction, very few measurements had previously been performed: below 30 eV only two datasets were reported in literature, highly discrepant from each other, while above 30 eV a unique high-resolution measurement, performed with the neutron field from a nuclear detonation, Nuclear explosion neutron source Fig.
53  Ratio of the resonance kernels of the 245 Cm(n,f) cross section measured at n_TOF and those extracted from evaluated data of two major libraries (see Ref. [127] ). Below 30 eV evaluations are based on two highly discrepant measurements, while above this energy they are based on a unique dataset, obtained with a neutron beam produced in a nuclear explosion. The very good agreement of the n_TOF data with evaluations above 30 eV demonstrates the unique features, in terms of flux and resolution, of the n_TOF neutron beam was available. The resonance kernels obtained at n_TOF are compared with the ones determined from two major evaluations in Fig. 53 , which are based on the three datasets mentioned above. Below 30 eV, large discrepancies can be seen between n_TOF results and evaluated data (and among evaluations themselves), indicating the need of significant corrections in the evaluations.
Introduction Extensive ice-penetrating radar data has been collected over the years in the Dome C region of the East Antarctic Plateau. These data were initially collected to characterize the Dome C ice core site. Subsequently, the Dome C region was revealed as one of the promising regions to have retained million-year-old ice, based on modeling thermodynamic results  (Van Liefferinge and Pattyn, 2013; Fischer et al. , 2013; Van Liefferinge et al. , 2018). The rare combination of thick ice, relatively low snow accumulation rate, low geothermal heat flux, slow ice flow and clear undisturbed englacial stratigraphy made this site one of the primary target drilling sites for the Beyond EPICA -Oldest Ice European project (BE-OI), with the added advantage of its proximity to the Concordia station for logistics.
, 2007 , 2011). Here we provide a spatially extensive IRH data set  (Cavitte et al. , 2020) , centered on the Dome C region of the central East Antarctic Plateau. The ages of the IRHs are established using the AICC2012 chronology  (Bazin et al. , 2013; Veres et al. , 2013). The radar transects were collected over a period of 10 years, by several institutes and under the umbrella of numerous projects.
Ice-penetrating radar systems The IRHs were traced across multiple ice-penetrating radar surveys that deployed several generations of modern ice-penetrating radar sounders over a decade, between 2008 and 2018, over the Dome C region (Fig. 1 ). The primary set was collected by the University of Texas at Austin Institute for Geophysics (UTIG) and the Australian Antarctic Division (AAD) as part of the ICECAP project (International Collaborative Exploration of the Cryosphere through Airborne Profiling,  Cavitte et al. , 2016)  between 2008 and 2015. This included the Oldest Ice candidate A (OIA) survey flown by ICECAP in January 2016  (Young et al. , 2017). Data were collected with the High Capacity Airborne Radar Sounder (HiCARS) 1 & 2 and its Multifrequency Airborne Radar-sounder for Full-phase Assessment (MARFA) descendant; in this paper we refer to these data as HiCARS.
By doing so, IRHs with slopes up to 10 o can be detected at depth. This processing comes at the expense of increased noise, and requires more accurate platform position information (which are sometimes unavailable) and computer time. However, we have found foc2 to be vital for tracking deep IRHs (Fig. 2 ). Focused SAR is therefore most useful when reflector geometries are complex (e. g. steep slopes), while pik1 is better suited to relatively smooth internal stratigraphy as it has the highest SNR of all processing products. The resulting post-processed radar data characteristics are listed in Table. 2. 2. 3. The IRH data set presented here has been traced using the pik1 unfocused SAR and foc2 2-D focused SAR products. The two processing types do not differ much in the Dome C region, due to the exceptionally continuous and relatively flat internal stratigraphy.
MCoRDS IRHs were traced on the L1B CSARP-standard product. Processing steps involved in creating the L1B CSARP-standard product are pulse-compression in the frequency domain, with a 20% Tukey window applied in the time domain and a Hanning window applied in the frequency domain, uniform resampling of the data, motion compensation, and finally SAR processing. The SAR processing uses f-k migration with an along-track wavenumber domain Hanning window. The multiple receiver channels are individually SAR processed and then averaged together coherently. Finally, a single image is created by combining the echograms from low (1 µs pulse duration) and high (3 µs and 10 µs pulse duration) gain channels. The effective along track Table  2. Ice-penetrating radar post-processed data characteristics. Vertical precision is provided for an IRH with 6 dB SNR; Fresnel zone diameter and along track resolution (after focusing and multi-looking) are calculated at 1000 m depth in ice and an altitude of 500 m above the ice in the case of HiCARS and MCoRDS.
DELORES After GPS-based precise positioning of the raw DELORES radar data, transects are processed using ReflexW (Sandmeier Geophysics) software. Several filters are applied, in the time and depth domains, to increase the SNR of the IRHs, including suppression of the direct air wave, bandpass filtering, a gain function to correct for spherical spreading loss and migration to collapse diffractions to their source points. The original sampling period of 4 ns is averaged to 12 ns in the post-processed data. Because the collection of ground-based radar data is dependent on the speed of the vehicle, which varies due to the terrain roughness during collection, the radar data are interpolated onto a 5 m regular horizontal spacing during post-processing. The resulting post-processed radar data characteristics are listed in Table  2.
2. 3. The absence of refraction through the air-ice interface allows for very steep IRH slopes to be imaged. The dense coverage of the ice-penetrating radar data in the Dome C region means that all radar transects used are directly connected at multiple crossovers. This implies that IRHs can be reliably extended across the whole region by transferring from one profile to the next using matching twtt at the crossover points. This also allows us to perform a check on the IRH tracing, and confirm the isochroneity of the chosen IRHs (see Sect. 4). 1 of the final data product 2 For a chirped system, the Fresnel zone diameter is calculated according to Haynes (2020, Equation S. 153):.
Age attribution Using the IRH depths measured at the closest point to the ice core site, we can assign ages to the IRHs using the AICC2012 chronology  (Bazin et al. , 2013; Veres et al. , 2013). We linearly interpolate the age-depth chronology to match our IRH depths and date the IRHs. Hereinafter, we refer to these as the "dated IRHs". Note that we use a deterministic approach to date the IRHs, however a Bayesian approach, such as used in  Muldoon et al. (2018) , could be applied equally to the IRH data. IRHs that cannot be traced all the way to radar transect MCM/JKB1a/EDMC01a, due to stratigraphic discontinuity or radar image quality issues, remain undated. We refer to these IRHs explicitly as "undated IRHs". As a result of their isochronal nature, these undated IRHs represent informative stratigraphic constraints that can be useful in modelling efforts, and we therefore include them in this data release.
5. 1. Additional, but not quantified, sources of uncertainty come from (1) the assumption of horizontal continuity of the IRHs between the EDC site and the radar transect, which corresponds to a distance of ∼ 94 m; (2) the complexity of tracing the same IRH across two radar transects from different systems (discussed in Sect. 4); (3) vertical advection over the 10 years of data collection, although, considering the radar resolutions and the surface accumulation rate, this (3) can be neglected; and (4) the assumption that only a single target is present in the range precision estimate for the IRH.
Acknowledgements. We would like to thank  Frédéric Parrenin  for his support with the 1-D ice flow model and modeling discussions. This publication was generated in the frame of  Beyond EPICA -Oldest Ice (BE-OI). The project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No. 730258  ( BE-OI CSA ). It has received funding from the  Swiss State Secretariate for Education, Research and Innovation (SERI)  under contract number  16. 0144. It is furthermore supported by national partners and funding agencies in  Belgium, Denmark, France, Germany, Italy, Norway, Sweden, Switzerland , the  Netherlands  and the  UK. Logistic support is mainly provided by  AWI ,  BAS ,  ENEA  and  IPEV. This publication also benefited from support by the joint  French-Italian Concordia Program , which established and runs the permanent station Concordia at Dome C.
We thank the staff of  Concordia Station  and the  Kenn Borek Air  flight crew. Additional support was provided by the  French ANR Dome   A  project ( ANR-07-BLAN-0125 ). We would like to thank  Mark Wiederspahn  for the endless IT support at  UTIG ,  Penelope M. Parr  for handling polar data in the Landmark DSD environment. This research contributes to the AntArchitecture action group of SCAR. This is BE-OI publication number #. This is UTIG contribution #.
This study used selected plant proteins and the tools available in the BIOPEP-UWM database to profile proteins and release antioxidant nutraceuticals from their primary structures. The frequency of the occurrence of fragments with antioxidant activity in a protein sequence (the A parameter) was determined. A simulated monocatalytic proteolysis was carried out using ficin or stem bromelain or pepsin (pH > 2), and the theoretical degree of hydrolysis (DH t ) and the frequency (including relative frequency) of the release of fragments with a particular antioxidant activity by a selected enzyme (the A E and W parameters, respectively). Both barley hordoindolines and the protein group of "actins and other rice proteins" were characterised by the best antioxidant potential. On the other hand, among the main analysed cereal protein groups or species, the best nutraceutical sources included kafirins, rice glutelins and α-gliadins.
The latter was developed by the U. S. Food and Drug Administration (FDA) and the Food and Agricultural Organization of the United Nations and World Health Organization (FAO/WHO) as a modified form of the PER index, and since 2013, the Digestible Indispensable Amino Acid Score (DIAAS) has been used for the bioevaluation of protein  [15] [16] [17] [18] [19]. Since various indices are applied for the biological evaluation of proteins and given the fact that each protein may be a source of biologically active peptides, as early as two decades ago, it was proposed to introduce a new criterion for the evaluation of protein as a source of biologically active peptides. Moreover, since computer methods and tools are increasingly applied in the processing of different biological data derived from various databases and are not only applied in molecular biology and genetics but also in nutrition and food sciences, the BIOPEP-UWM (Bioactive Peptides-University of Warmia and Mazury) database (http://www.
uwm. edu. pl/biochemia/index. php/ pl/biopep) has been established  [20, 21]. Currently, one of the four databases which make up the resources of the BIOPEP-UWM database is the "Bioactive peptides" database in which 3,820 bioactive peptide sequences have been deposited (data as at 10 December 2019) in the form of a single-letter amino acid code. In addition it contains a program that enables the construction of profiles of potential biological activity of proteins as well as the calculation of qualitative and quantitative descriptors for the assessment of the value of proteins as potential precursors of bioactive peptides, and forecasting sensitive peptide bonds for the performance of protein chain hydrolysis by proteolytic enzymes  [20, 21]. Currently, the BIOPEP-UWM database is commonly used in food and nutrition sciences as a source of information on biopeptides as potential nutraceuticals and components of functional food as well as compounds that serve an important role in the prevention of chronic diseases  [20, [22] [23] [24].
Bioinformatic tools available in the BIOPEP-UWM database enable the performance of protein hydrolysis simulation with the use of proteolytic enzymes of various origins available in the database, including certain enzymes whose counterparts are synthesized in the human gastrointestinal tract or used in the food industry  [8, 20, 25, 26]. The study used selected plant protein amino acid sequences and bioinformatic tools available in the BIOPEP-UWM database to evaluate the potential antioxidant activity of the analysed proteins and a proteolysis simulation using selected enzymes to obtain potential nutraceuticals.