dataesr/scientific-paragraphs-categorization huggingface dataset:
RESP charges  49  were calculated following the recommended setup of the PyRED server  50  (http://upjv. q4md-forcefieldtools. org/REDServer-Development/). The atomic charges and modified parameters were included in Amber Tools to prepare the topology files of the different systems. Molecular dynamics simulations were carried out using the pmemd module of the AMBER12 code (http://ambermd. org). The AMBER-ff14SB  48  and GLYCAM06-j 51 force fields were used for protein and saccharides, respectively, together with the TIP3 water model. 52 he protonation states of titratable residues were assigned using the H+ + web server (http://biophysics. cs. vt. edu/H++). Standard protonation states were observed for each RSL variant. Short-range van der Waals interactions were switched to zero at a cutoff distance of 8 Å.
Flow cytometry Tumor cells (50,000 cells) were suspended in PBS supplemented with 2% BSA, 2% FCS, and FcR block (Miltenyi Biotec GmbH) at 4 °C for 20 min. Cells were then stained for 30 min at 4 °C with anti-CD24 PE (clone ML5, BD Biosciences), anti-CD44 APC (clone G44-26, BD Biosciences), and anti-CD45 PE-Vio770 (clone 5B1, Miltenyi Biotec GmbH) antibodies. Isotypic antibodies were used as a control for each fluorochrome (obtained from the same manufacturers). Cells were then washed twice in PBS supplemented with 2% BSA and 2% FCS and resuspended in PBS. To assess cell viability, cells were incubated with 7-AAD (BD Biosciences) for 10 min prior to cytometry analysis. Data were acquired using a Novocyte cytometer (ACEA Biosciences) and analyzed using FlowJo or Novoexpress software.
Microarray analysis RNA quality was assessed using an RNA6000 nano chip (Agilent). For each condition (fresh or freeze/thawed), 9 ng of RNA was reverse transcribed using the Ovation PicoSL WTA System V2 (Nugen, Leek, The Netherlands). Fragmented cDNAs were hybridized to GeneChip Human Gene 2. 0 ST microarrays (Affymetrix), which were scanned by a GeneChip Scanner 3000 7G (Affymetrix). Raw data and quality-control metrics were generated using Expression Console software (Affymetrix). Probes were mapped using Brainarray V23 CDF files (http://brain array. mbni. med. umich. edu/) and normalized by robust multi-array averaging with R software. Statistical analyses were performed using the limma R package; genes showing a twofold change in expression and a P value of 0. 05 were considered significant.
Gene Ontology terms enrichment analyses were performed using the ToppGene Suite (Chen J, Bardes EE, Aronow BJ, Jegga AG 2009. ToppGene Suite for gene list enrichment analysis and candidate gene prioritization. Nucleic Acids Research https ://doi. org/10. 1093/nar/gkp42 7). Hierarchical clustering was performed using Morpheus Matrix visualization and analysis software (https ://softw are. broad insti tute. org/morph eus/).
The current evaluation extends up to 150 MeV, which on its own poses a number of formatting issues. We refer to Sec, VI for the adopted file structure and explain our unusual choices (e. g. , our treatment of the (n, α) channel). Development of the new iron evaluations can be traced with the 'CIELO-iron' project on the NNDC GForge server (https://ndclx4. bnl. gov/gf/project/ cielo_iron). All elements of the evaluation, such as experimental datasets, EMPIRE inputs and outputs, intermediate ENDF files and plots can be found there in chronological order. This not only allows an interested person to follow all stages of the evaluation development but makes it possible to reproduce, and therefore also modify, the current evaluation. Although 56 Fe is the most important of the iron isotopes, the evaluation process for all the naturally occurring isotopes proceeded in parallel.
MACS(30 keV ) which is now 8% below the calculated value from gold reference cross section  [11]. That affects all renormalizations in KADoNiS and the affected values are marked. This, coupled with issues with the flux profile used in these measurements, lead us to use the MACS data for validation purposes only. We comment that R. Firestone et al. advocate for a lower thermal capture (2. 394 ± 0. 019 b) value based on EGAF results  [16]. Unfortunately this result became available only after the current version of the evaluation was complete. A preliminary version of this result advocated for a much higher result (2. 71 b), going in exactly the wrong direction from what is needed according to our integral benchmarking. However this new result, once included, may help to push our results into better agreement with the LCT benchmarks.
III. EXPERIMENTAL DATA IN THE FAST NEUTRON REGION There is an extraordinary abundance of experimental data for elemental iron and its four major isotopes 54 Fe, 56 Fe, 57 Fe, and 58 Fe. At the time of writing this paper, the EXFOR database contained 799 entries (papers) with 2552 datasets. Analyzing this amount of information is a daunting task and we greatly benefited from our Chinese collaborators sharing with us their detailed analysis of the experimental data. This CIELO-facilitated cooperation sped up the initial phase of the evaluation process and is reflected in the authorship of this paper. Table IX lists the most relevant of the 799 references grouped according to the physical quantities appearing in the evaluation. In doing this selection we favored: (i) broad energy range covered by the experiment, (ii) high energy resolution, and (iii) high (but reasonable) accuracy of the experiment.
Thus the measurements providing possibly wide and reliable picture were given precedence over single energy-point experiments, especially if the latter were taken within the energy range where strong fluctuations were observed. On the other hand, many single-or a few-point measurements ended up in Table  IX  when no extended datasets were available. Some of the measured datasets were renormalized to account for changes in the reference cross sections since they were used in the analysis of the experiments. These renormalizations are built into the EXFOR retrieval system and are documented in the descriptive part of the evaluations. In a few cases we took advantage of the existing high quality evaluations available from the IRDFF library  [55, 56]  and used these data instead of the actual measurements (these cases are indicated as IRDFF in Table IX).
Even in such cases we have tried to adjust parametrization of the models as to reproduce averages of the fluctuating experimental TABLE IX. Most relevant measurements used in the evaluations of the fast neutron region. "x-sect. " stands for cross section, "Double-diff. x-sect. " refers to energy-angle correlated distributions (e. g. , neutron emission spectra at a given angle) and "Partial ang. distr. " refers to components of the reaction measured at given angle(s) (e. g. , γ-transitions following inelastic scattering to a discrete level measured at a given angle). The data used in the resonance evaluations are not included here because they are described in the previous section. data in order to complete the file with quantities that were not experimentally available. The fast region calculations were performed using the EMPIRE code  [9] , which is a comprehensive package that integrates into a single system a number of impor-tant physical modules and evaluation tools.
The 12 MeV upper limit could be lower for the width fluctuation correction but we intentionally kept it at this level to extend the range of angular distributions of CN neutrons. In the EMPIRE code the T lj transmission coefficients are used only within the width fluctuation correction module while pure Hauser-Feshbach mode switches to T l 's, making Blatt-Biedernharn formalism inapplicable. Compound nucleus and direct cross sections were added incoherently, i. e. , the Engelbrecht-Weidenmüller transformation  [250]  was not invoked. As a matter of fact, there was no need for it since the direct component is relatively weak in the very spherical iron isotopes and then, at least for the most important 56 Fe, between the first inelastic threshold and 4 MeV the optical model cross sections were externally rescaled to bring calculated total cross section to agree with the average of the experimental results.
It is also a typical practice to tune PE γ-emission to simulate semidirect capture mechanism and bring calculated capture cross section in the GDR region to about 1 mb. These tune factors were 5. 1 for 55 Fe, 10. 97 for 57 Fe, 5. 68 for 58 Fe, and 5. 5 for 59 Fe. A detailed account of the reaction models choices and parameter adjustment is given in the descriptive part of the evaluation and even more details can be found in the input and output files available from the GForge server. The parameters that were not explicitly mentioned were taken from the RIPL-3 library and additional datasets included in the EMPIRE code. Occasionally, we resorted to energy-dependent parameter scaling or tuning factors, available in the EMPIRE code, to account for model deficiencies. Apart from the correction of the CC results for 56 Fe discussed above, these corrections were typically on the level of 1-2% or less and can be found in the input files.
Total Cross Sections 56 Fe(n,total) -The adopted cross sections above the resonance range up to 10 MeV were the ones from JEFF-3. 2, which is essentially the Vonach-Tagesen evaluation with superimposed fluctuations that correspond to the Berthold measurement  [61]. This ultra-high resolution transmission measurement on natural iron was taken on a 387. 739 meter flight path at the 150 MeV GELINA linac. The results extend from 0. 75 up to 22 MeV and are available from EXFOR Entry #22276 as a private communication since they have never been published in detail. Measurements of high resolution on an enriched sample of 56 Fe were made by Cornelis (1995, EXFOR #22316)  [253]. They are in good agreement with the Berthold data, except for a slight shift in energy. After careful review we realized that the energy calibration of the Berthold data is more reliable.
In this energy range the reduction has no effect on the evaluated total since it was defined either by the resonance parameters or by the experimental values. 54 Fe(n,total) -The cross sections were calculated with the EMPIRE code using an optical potential specified in Table  X. The energy-dependent scaling was applied below 2 MeV to reproduce elastic Guenther data  [193]  and to improve agreement with averaged ENDF-VII. 1 between 700 keV and 1. 2 MeV. The scaling applied below 4 MeV in 56 Fe was not used in the 54 Fe case. Fig. 6 , top-right panel, shows the comparison of the recommended total cross sections with existing experimental values. We note that data points above 10 MeV  [192]  deviate drastically from our coupled-channel calculations and are completely out of phase with the general shape resonance predictions of the optical model.
Inelastic Cross Sections 56 Fe(n,inelastic) -Two sets of inelastic cross section data were produced at Geel. The older one, by Dupont  [141] , was never published in a peer-reviewed journal, because the authors found normalization problems in the measurement that could not be resolved. A newer measurement by Negret  [144]  was performed with a new experimental set-up, but the resolution was lower than that of the Dupont data. In the current evaluation, data from both datasets were binned over a suitable energy mesh. A piecewise linear scaling parameter was constructed to adjust Dupont data such that they agree on average with the Negret data. It was also found that the energy calibration of the Negret data did not match the resonances in the total cross section. Since the evaluated elastic cross section is calculated as the difference between the total and the remaining partial cross sections, any mismatch in the position of resonances can have catastrophic consequences.
To force agreement in the resonance peaks the energy scale of the Negret data was scaled linearly, amounting to 2. 5 keV at 1. 8 MeV. The main concern was whether to trust the energy calibration of Berthold (done on a 400 m flight path) and Dupont, or to adopt the calibration by Cornelis and Negret. From a private communication with P. Schillebeeckx, it was found that a 2. 5 keV shift in the Negret data corresponds to an error in timing of 5 ns, which is possible. So, the obtained inelastic was subtracted from the total to produce the elastic cross sections. A comparison of the evaluated total, elastic and inelastic cross sections is shown in Fig. 8. We note that choosing an absolute scale according to Negret results in higher inelastic, and consequently lower elastic, compared to JEFF-3. 2 and ENDF/B-VII.
1. Fluctuations were imposed on the inelastic scattering to the first and the second excited state in 56 Fe. The Negret data show some structure also for the higher levels but the cross sections are small enough to disregard them (at a certain level it is difficult to judge whether the fluctuations represent physics effect or simply statistical noise). Up to 2. 5 MeV the rescaled Dupont data were used on MT=51 and 52. Between 2. 5 and 3. 5 MeV the lower resolution Negret fluctuations were applied. Smooth EMPIRE calculations were adopted above 3. 5 MeV for the first two inelastic levels and in the whole energy range for the remaining levels. [143]. Both experiments derived total inelastic cross sections from the intensity of the 847 keV γ-line through which the first excited state in 56 Fe decays to the ground state.
The Nelson results were corrected for the contribution of the 57 Fe(n, 2n) reaction and monitor cross section updated in 2004. For the more recent Negret measurement carried out on an enriched sample these corrections were not needed. Both experiments agree perfectly up to around 6 MeV while at higher energies the Negret data tend to be lower. Authors consider, however, their data accurate only up to 4. 5 MeV where there is no model-dependent contribution from the continuum. Above that limit the Negret data represent a lower limit. Our new evaluation reproduces very well the Negret data up to about 7 MeV and then follows the results of Nelson. In the plateau of the inelastic cross section no adjustment of the model parameters was needed. Above 12 MeV EMPIRE calculations, adjusted to reproduce the 56 Fe(n, p) reaction, were slightly lower than measurements and other libraries.
This experiment makes use of the very precise mass spectroscopy method, but being still preliminary, has not been used in the evaluation procedure. 54 Fe(n, 2n) -Again, the 54 Fe(n, 2n) channel was fitted simultaneously with (n, p) and (n,α) reactions. In this case, since the IRDFF  [55, 56]  dosimetry evaluation was available for all three reactions, IRDFF was used as fitting guidance instead of actual experimental data. As can be seen in the lower panel of Fig. 15 , around 15 to 20 MeV the experimental data present two conflicting trends. Our evaluation follows the lower trend and the data above 20 MeV. Ultimately, the total 54 Fe(n, 2n) (ground plus meta-stable states) was replaced by the IRDFF evaluation. In the energy region close to the reaction threshold the new evaluation is significantly lower than all other evaluations, which is again well supported by the results of Wallner's experiment.
501 MeV in Fig. 19 , upper-left panel. We note that the similar-resolution Perey data do not show such discontinuity. Unfortunately, the Perey data do not cover the upper range of the Kinney experiment so we used the latter trying, within the experimental uncertainties, to follow the pattern at lower energies by lowering the anisotropy. In addition, an increase of the backward scattering also improved fast plutonium criticality benchmarks. In general, we have found that elastic angular distributions have a significant impact on criticality. There are several experimental data sets for elastic angular distributions. Out of these only Perey and Kinney were taken with high energy resolution (apart from the Cierjacks measurement  [256]  which, due to unfortunate mislabeling in data classification, was not taken into account in our evaluation).
B. Fast Region Covariance It is important to clarify that covariances in the fast neutron region assigned to the new iron evaluations refer to the averaged cross sections and by no means reflect the amplitude of the experimentally observed fluctuations. The uncertainties of such fluctuations, which were imposed on the averaged values, were assumed to be of purely statistical nature and negligible compared to the uncertainties of the averaged values. This surmise has two practical implications. First, it allows for taking into account physics constraints resulting from the reaction modeling. Then, it avoids unmanageable size of the covariance matrices that would be needed to account properly for experimental datasets with thousands of points. Covariances were determined using Kalman filterinspired Bayesian update procedure originally coded by Kawano and Shibata in the KALMAN code  [257]  and more recently rewritten by S.
We do provide, however, covariances for the sum of all the remaining channels (MT=5). We also calculated cross-correlations among all reactions mentioned above. We used experimental uncertainties reported in EX-FOR and determined, if possible, the long range correlations in the experimental covariance matrices from the ratio of reported systematic uncertainties to the total ones. If such information was not available from EX-FOR we used default 45% correlation between different energy points for the same reaction. Since our aim was to determine covariances for the averaged cross sections, the experimental datasets showing pronounced fluctuation structure were subject to the iterative smoothing procedure before being used. In addition, datasets with excessive number of energy points were thinned to keep the total number of points below 1000 per experiment.
Because this operation was performed on the already smoothed dataset there was no information loss related to dropping even 90% of the original data points. We note that several measurements that were instrumental for establishing the recommended cross sections were not used in the uncertainty determination. This was the case for Berthold's data that defined the fluctuating structure of the total cross section in 56 Fe as well as for Dupont data which shaped inelastic scattering. These high energy resolution measurements were renormalized to the averaged cross sections determined by other experiments and, therefore, did not bring any information on the absolute values. Also, outliers and single energy experiments (if not of significant value) were not taken into account in determining covariances.
Special treatment has been reserved for the reactions for which IRDFF recommendations were adopted. In these cases, IRDFF cross sections were used in the evaluation procedure in place of the experimental datasets and eventually EMPIRE calculated cross sections were replaced with the IRDFF values. Therefore, it was desirable to retain, as far as possible, also IRDFF covariances. While doing it with the cross sections is straightforward, inserting IRDFF covariances in the KALMAN determined covariance matrix would break physical and mathematical consistency of the matrix. Instead of doing this we preserved KALMAN created covariances but during the procedure we adjusted weights of the IRDFF cross sections to reproduce, as closely as possible, original IRDFF uncertainties. Our off-diagonal part of the covariance matrix necessarily differs from the IRDFF since the latter is purely based on 56 Fe(n, p) experimental data while ours includes also physics constraints and the correlations with other reactions.
In the calculations, we adjusted the weights of each experiment to ensure that each measurement contributes about 1 to the total χ 2 independently of the number of points in the dataset. This condition turned out to be instrumental in ensuring a reasonable magnitude of the uncertainties that usually tend to be severely underestimated for the datasets with many points. The initial uncertainties of the model parameters were set large enough so that their further increase had no effect on the calculated covariances of the cross sections. It means that the final parameter covariances were fully determined by the experimental data and physics constraints and not by our prior knowledge of the parameter uncertainties. This has been possible for most of the reactions since existing measurements were sufficient to constrain model parameters.
1 irons). On the other hand, we concluded that experimental data, even though we can't complain about their scarcity, do not constrain sufficiently elastic angular distributions below 4 MeV, which we found to be important in calculating criticality and deep penetration experiments. It is astonishing that four major experimental datasets which determined a large part of the current evaluation (Berthold  [60] , total cross section; Dupont  [141]  and Nelson  [143]  inelastic scattering; and Kinney  [74]  elastic angular distributions) were never published in peerreviewed papers. Fortunately, thanks to the commendable effort of the Nuclear Reaction Data Centers network, the respective data are available from the EXFOR  [14]  library. Berthold's and aforementioned, and potentially important, Cierjacks' measurements are listed there as private communications.
1. There is, however, some uncertainty regarding partition of the fusion cross section between elastic and inelastic in the energy range from 4 to 8 MeV. Comparison of the group-averaged evaluated cross sections with the smoothed experimental data indicates that the inelastic could be lowered by 3 to 5% between 4 and 5 MeV. This would increase our elastic cross sections bringing them closer to the JENDL-4. 0 and JEFF-3. 2 recommendations. Between 4 MeV and 5 MeV our elastic is 120 to 150 mb lower than the average of other evaluations and a decrease of the inelastic would eliminate about half of this difference. In general, our elastic cross sections, although supported by the Kinney measurement, are lower than ENDF/B-VII. 1, JENDL-4. 0 and JEFF-3. 2 up to 9 MeV where they merge with JENDL-4.
0. Development of a nuclear reaction data library is an iterative process combining results of the differential experiments with reaction modeling and benchmarking. Seeking to optimize library performance in the integral experiments we inevitably introduce correlations between materials. Reaction modeling brings physics related correlations among different reactions and to some extent also among materials. These correlations are mathematical representation of the fact that the same result might be obtained in various ways, i. e. , adjustment performed by the evaluator, or data user, is only one of many (infinite) possibilities. In the present evaluation work we were guided by sensitivity profiles available through the DICE package of the NEA Data Bank to find the most effective ways of adjusting our data to integral experiments while observing differential constraints.
ACKNOWLEDGMENTS Work at  Brookhaven National Laboratory  was sponsored by the  Office of Nuclear Physics, Office of Sci-ence of the U. S. Department of Energy  under Contract No. DE-AC02-98CH10886  with  Brookhaven Science Associates, LLC. ORNL is managed by  UT-Battelle, LLC , for the  U. S. Department of Energy  under Contract No. DE-AC05-00OR22725. The  U. S. Department of Energy Nuclear Criticality Safety Program  sponsored the work presented in this paper. Authors are grateful to the referee for a very detailed review and a number of comments and suggestions that not only increased value of the paper but also indicated possible improvements in a future evaluation. In particular, we are thankful for the data presented in Table XII.