dataesr/scientific-paragraphs-categorization huggingface dataset:
package of EURAD, the idea of conducting the blind test was presented by SKB. Several participants were interested and the idea was conveyed to others. 2. October 27, 2017, Joint Research Centre (JRC)-Geel, Belgium: A preparatory meeting was held in conjunction with a training course, "From nuclear data to a reliable estimate of spent fuel decay heat," organized by the JRC-Geel and the Belgian Nuclear Research Centre (SCK CEN). 3. April 6, 2018, Paris, France: Participants were invited to a meeting hosted by the Organisation for Economic Co-operation and Development/Nuclear Energy Agency (OECD/NEA). It was decided, with consensus, which input data should be provided to the participants and that the decay heat and content of 137 Cs and 148 Nd should be calculated for each fuel assembly. The content of the nuclides 137 Cs and 148 Nd were selected since these are good indicators of burnup (BU), being produced during irradiation as fission products without a complicated chain of neutron captures.
Uncertainties from the model used in the calibration fitting procedure as well as uncertainties in measured data were used in uncertainty propagation, including covariances Reference 3 describes the methodology to derive the decay heat rate from raw calorimetric data, while Ref. 2 addresses the uncertainty calculations. The raw data from the calorimetric measurements of the fuel assemblies in the benchmark exercise, available from Ref. 1, were used for this exercise. Four of the calibration measurements from Ref. 1 contained measurement data for the complete cool-down and heat-up cycle of the calorimeter, but only the data logged in the measurement time interval corresponding to the heat-up part a were used here. Besides this, the raw data from Ref. 1 were used unaltered as input data. Figure  2  displays the calorimetric calibration curve established using these data.
VI. RESULTS FROM CALCULATIONS OF DECAY HEAT AND COMPARISON TO MEASUREMENTS The calculated results are presented in Tables V through IX. They compare the measured and calculated decay heat rate for each assembly as well as calculated values of the content of 137 Cs and 148 Nd. Figure  8  illustrates the relative difference between the measured and calculated decay heat rate. The shaded background with a black border in Fig. 8  indicates the average estimated uncertainty of the measur ements. The relationship between the nuclide inventory and decay heat are the half-lives and Q-values (released heat per decay). The Q-values can also be understood as the values of energy released from the decaying nuclides which are provided in the decay data libraries. Different Q-values were used in different calculations, depending on the code and library used.
More (and better) experimental data, their in-depth analysis, and the thorough analysis of inputs, codes, assumptions, and ND are becoming the usual suspects in paving the way to our improved understanding of a quantity such as decay heat. Additionally, links between decay heat, source terms, and dose rates will help to tackle such problematic questions from a broader angle. The current exercise has been extremely profitable in defining the current and future projects, such as the European Union EURAD project (Horizon 2020) and the coordinated research project on SNF characterization from the IAEA, as well as the new working group on decay heat evaluation from the NEA/Working Party on Nuclear Criticality Safety. If one could add a request to the wish list for future open-minded industries, it would certainly be the availability of decay heat data given the amount of national proprietary programs.
Statistical neutron weights lost to capture and fission on all nuclides involved in the problem are multiplied by the corresponding fission and capture recoverable energies to get the total energy release. Fission (total release less the neutrino energy) and capture Q-values are taken from the ND library, i. e. , ENDF/B-VII. 1 used for blind test calculations. Explicit calculation of energy release in neutron capture reactions allows accurate treatment of the The DARWIN2. 3 code system 89 is devoted to the characterization of SNFs. It includes the 2D neutron transport code APOLLO2 (Ref. 10) that generates accurate reaction rates as a function of BU and the PEPIN2 code that solves the Bateman equations with a detailed irradiation history and almost complete decay chains (about 3800 isotopes).
A. I. E. CASMO-5 (2. 12. 00)/SNF (1. 07. 02) This methodology combines isotopic concentrations, fluxes, and cross sections calculated by the neutron transport and depletion code CASMO-5 with irradiation history data and tabulated isotopic decay data. 716 These data sources are used and processed by the SNF code to compute the SNF characteristics, including the decay heat power. The code's distributable versions are applied to the provided input data without modifications. The end-of-life assembly BUs [megawatt days/tonnes heavy metal (HM)] are determined by summation of the cycle BU computed as (assembly power in megawatts) multiplied by (time in power in days) divided by [initial HM mass in tonnes].
BLIND BENCHMARK EXERCISE FOR SPENT NUCLEAR FUEL DECAY HEAT • JANSSON et al. 15 based SHEM-295 cross sections 717 were prepared using a subgroup approach, where the fuel region was divided into four annular rings with the following volumes: 50%, 30%, 15%, and 5%. Two-dimensional calculation in infinite assembly lattice was applied. All fuel pins were treated as one depletion mixture. In the DRAGON code, the EVO module performs the BU calculations. The constant power normalization technique was used to obtain the solution of depletion equations. In this case, the power released per initial heavy element at beginning of stage and end of stage is set to a constant value. In addition, the energy released outside the fuel was determined using the GLOB option. The energy released by fission in the DRAGON code is determined with the H-factor, which is used to calculate the recoverable energy from fission reactions.
A. I. G. EVOLCODE (MCNP + ACAB) WITH JEFF-3. 3 The simulation has been performed with the EVOLCODE system 18 using the JEFF-3. 3 data library for cross-section 1920 decay data (including heat emission), isomer branching ratios, and fission yields. These specifications also included the BU history, described in the simulations with irradiation steps of 10 and 40 days for the beginning of each cycle and general steps of 50 days for the rest of the irradiation. The energy released by fission in EVOLCODE is considered to be totally deposited in the place where the fission occurs, so the power in the neutronics process is driven by the Q-values present in the MCNP source code, which are based on ENDF/B-VI. However, the depletion process is done by ACAB, which uses an expression for the recoverable energy per fission that depends on the atomic number and the mass number of the fissioning actinide (following a semi-empirical formula from Ref.
A. I. H. MCNP-CINDER + NUKLEONIKA (2D) The calculations performed used the MCNP6. 1 code coupled with the CINDER BU module. The Bateman equation is solved based on a linearization approach 22  used in CINDER. The BU process is done by using 69 energy groups, which differs from the "classical" onegroup Bateman equation exponential solution. Further, in this study it was shown that for the MCNP-CINDER linear solver, the BU day numbers should be limited to about 50. The (2D) symbol indicates that for the BT03 Gd case, the full length of the rod according to the specification was introduced, which enhanced to some extent the inaccuracy due to additional statistical uncertainties. The decay heat calculations were done by transferring the decaying nuclide vector to the Nucleonica program, in which the decay heat includes isomers in a better manner and the heat is introduced with its decay radiation type.
A. I. I. MONTEBURNS V3 + CINDER WITH ENDF/B-VII. 1 Monteburns v3, which links the Monte Carlo transport code MCNP6. 1 with the isotope generation and depletion code CINDER90 (Refs. 28 and 29) , was used for these calculations. MCNP/Monteburns input files for neutron transport and irradiation of each of the five assemblies of interest were generated and calculations were performed over 34 to 36 different individual time steps, varying the soluble boron concentration during each step (and cycle), as given in the input definition. Albedo boundary conditions on an infinitely reflected assembly model in MCNP were used to simulate the contribution of surrounding assemblies. For CINDER, the Q-values are 202. 61 and 211. 41 MeV for 235 U and 239 Pu, respectively. 30.
A. I. J. MOTIVE (KENO-VI + VENTINA) WITH ENDF/B-VII. 1 The calculations were performed using KENO-VI from SCALE 6. 2. 2 as the external Monte Carlo code and Ventina as the depletion code. 3132 ENDF/B-VII. 1 library data 7 were used for both transport and depletion calculations. All fuel assemblies were modeled using an effective 2D model with single depletable material, i. e. , the same fuel material in all pins, and one fuel zone per pin, except for BT03 where for the Gd-rod the ten fuel ring zones were.
A. I. N. MVP3 WITH JENDL-4. 0 Two-dimensional assembly calculations were performed with MVP3 (Ref. 35 ) using the JENDL-4. 0 library. 36 MVP3 is a continuous-energy Monte Carlo code coupled with a BU solver developed by the Japan Atomic Energy Agency. Twenty-four million neutrons were employed in an active run to tally the reaction rate in each BU step. In the depletion calculations, the detailed BU chain of ChainJ40 (Ref. 37) (named th2cm6fp193bp8T_J40 in ChainJ40) and the predictorcorrector option were applied to obtain the isotopic composition in the burnt fuel. The deposition energy per fission used in ChainJ40 are 202. 25, 205. 92, 210. 96, and 213. 27 MeV for 235 U, 238 U, 239 Pu, and 241 Pu, respectively. The decay heat was deduced by the products of the composition, the decay constant, and the energy release per decay.
A. I. R. SCALE 6. 2. 3: POLARIS, ORIGEN, AND TRITON/NEWT WITH ENDF/B-VII. 1 The calculations were performed using the Polaris, ORIGEN, and TRITON codes of the SCALE code system version 6. 2. 3 (Ref. 41). The ND are SCALE cross sections, fission yields, and decay data based on ENDF/B-VII. 1 ND (Ref. 7). The TRITON and Polaris models use the SCALE multigroup library of the 56-group structure. The ORIGEN models use one-group libraries at mid-BU values generated by TRITON for the 17 � 17 lattice and using also the ARP cross-section interpolation utility. The TRITON and Polaris models are 2D models of the southeast quarters of the assemblies along with reflective boundary conditions, and the ORIGEN models are zero dimensional. One depletion and decay model was made for each assembly, except for the BT03 assembly which was modeled using two 2D models for the BA section and the BA-free sections.
A. I. S. SCALE 6. 2. 3: TRITON/KENO WITH ENDF/B-VII. 1 The calculations were performed using the TRITON sequence of SCALE 6. 2. 3 (Ref. 41), coupling the ORIGEN module with KENO-V. a with multigroup option using ENDF/B-VII. 1-based cross sections. 7 The same ND library was used for the nuclide inventory calculations with ORIGEN. In this study, coarse time steps of 50 days were adopted, except for the first few time steps which were much shorter to accommodate the rapid changes in fission product concentrations.
A. I. U. SEADEP WITH JEFF-3. 1. 1 SEADEP is a calculation methodology based on the use of the MONTEBURNS 2. 0 (Ref. 29) calculation system, which is based on Monte Carlo transport code MCNPX and depletion code ORIGEN (Ref. 24). The use of the code has been modified as necessary to obtain the results of residual heat of the most significant nuclides. The contribution of 85 Kr and of other nuclides not having treatment in SEADEP have been estimated by calculation with SCALE 6. 1. The residual heat due to the activation of the structural components of the fuel assembly has been calculated with SCALE 4. 4. The SEADEP methodology is oriented to a detailed representation of the sample to be cut, dissolved, and finally measured. Therefore, the irradiation conditions are specific for that small fraction of the fuel rod.
A. I. X. SERPENT 2. 1. 31 WITH JEFF-3. 2-BASED CROSS-SECTION LIBRARIES AND JEFF-3. 1. 1-BASED RADIOACTIVE DECAY AND FISSION YIELD DATA The calculations were run using development version Serpent 2. 1. 31 (Ref. 47 ), with JEFF-3. 2-based cross-section libraries and JEFF-3. 1. 1-based radioactive decay and fission yield data. Each fuel pin was treated as a separate depletion zone and divided radially into a central zone and a 0. 3-mmthick surface layer. The BU calculation was run using a standard predictor-corrector algorithm and 50 steps per cycle. A total of 10 million neutron histories were run per each transport simulation. Normalization was fixed by setting the energy deposited per 235 U fission to 202. 27 MeV. The fission Q-values provided in the ACE data format do not represent the deposited energy, mainly because the secondary energy released in the capture of fission neutrons is omitted.
Single molecule tracking (SMT) is a powerful technique to study molecular dynamics, and is particularly adapted to monitor the motion and interactions of cell membrane components. Assessing interactions among two molecular populations is classically performed by several approaches, including dual-color videomicroscopy, which allows monitoring of interactions through colocalization events. Other techniques, such as fluorescence recovery after photobleaching (FRAP), Förster resonance energy transfer (FRET), and fluorescence correlation spectroscopy (FCS), are also utilized to measure molecular dynamics. We developed MTT2col, a set of algorithmic tools extending multi-target tracing (MTT) to dual-color acquisition (https://github. com/arnauldserge1/MTT2col). In this protocol, we used MTT2col to monitor adhesion molecules at the contact between leukemic stem cells and stromal cells, a process involved in cancer resistance to chemotherapy and in relapse.
Our dual-color single molecule protocol includes the following steps: (i) labeling molecules of interest with fluorescent probes, (ii) video-acquisition, (iii) analyses using our MTT2col in-house software, to obtain positions and trajectories, followed by (iv) detailed analyses of colocalization, distribution, and dynamic motion modes, according to the issues addressed. MTT2col is a robust and efficient SMT algorithm. Both MTT and MTT2col are open-source software that can be adapted and further developed for specific analyses.
Data analysis A. Running MTT2col (Figure  1 )  (Gorshkova et al. , 2021)  1. Start Matlab (or Octave, alternatively, at least for MTT). 2. Within the Matlab environment, navigate to the folder containing the data to be analyzed (either on a local drive or on the network). Evaluating a given dataset with Matlab or Octave essentially requires selecting the path to the directory containing the video files. 3. Then, type the command MTT_2_colors in Matlab, which first displays a graphic interface listing all the parameters used, then runs the fully automated analysis (Figure  3 ). 4. Of note, when analyzing a mix of one-and two-color datasets, the supplementary Matlab function MTT_1_or_2_colors can determine if the data correspond to one color (square images, such as 512 x 512 pixels), two colors (double square, meaning that the width is double the height, such as 1024 x 512 pixels) or any other possibility.
Analysis The main function of the MTT2col algorithm is called MTT_2_colors. Below is a list of the main Matlab functions and sub-functions in MTT2col. Key steps are in bold, variables are in purple, and comments are in green. This fully automated procedure allows to build trajectories from dual-color video acquisitions (Figure  2 ), and to extract several descriptors (Figure  4 ), as explained in the main text. See the original articles  (Sergé et al. , 2008; Rouger et al. , 2012; Gorshkova et al. , 2021)  for an extensive description of the algorithmic processes and input/output parameters. given frame. Thus, the matrix has as many columns as trajectories, and 8 times more lines than frames in the video. The dat file contains all trajectories, and the mat file is filtered for trajectories with length and diffusion coefficient above the thresholds defined in the list of input parameters.
Acknowledgments We thank  Jessica Chevallier  ( TAGC, CIML, LAI, Aix-Marseille Univ ) for critical reading of the manuscript. We thank  Martine Biarnes-Pelicot  ( LAI, Aix-Marseille Univ ) for providing technical help for cell culture. We thank  Dr. Dalia El Arawi  and  Dr. Laurent Limozin  ( LAI, Aix-Marseille Univ ) for providing technical help for the microscopy setup. We thank  Rémi Torro  and  Dr. Pierre-Henri Puech  ( LAI, Aix-Marseille Univ ) for providing technical help for Github. We also thank the microscopy, cytometry, and statistics research facilities at  CRCM , as well as  Thi Tien Nguyen  for the cell culture facility at  LAI , for excellent technical support. This work was supported by the  Fondation ARC pour la Recherche sur le Cancer  ( PJA 20131200238  to A. S. ), the  Institute Marseille Imaging , and institutional grants from  INSERM and Aix-Marseille Univ.
These methods are very effective for gathering information about what participants are doing in this organized space, including intentional interruptions. However, they can only represent a rough sketch of what they actually do in their own environments. Another approach to collecting data that reflects students' natural behaviors with their computer in class has been proposed by  Kraushaar and Novak (2010). In their study, the behavior of students was collected using spyware (monitoring software) installed on their laptops to gather information about what they were doing during a lecture. This method makes it possible to collect very precise information concerning the use of the computer but does not allow researchers to gather information regarding the use of other media or information relating to other sources of distraction.
Participants In total, 74 participants were recruited for this study (57 females, M age = 22. 16 years; SD = 2. 35). All participants were native French-speakers and none had a language or attention disorder or suffered from dyslexia. Two participants were removed from the data because their error rate in reading comprehension was above 80%, suggesting that they were not engaged in the task. Three participants were removed because they did not complete the grid correctly. Our final sample therefore included 69 participants. Participants had all completed high school, on average they had completed 2. 23 years of university studies. All participants freely gave their informed consent in accordance with the Declaration of Helsinki. A full review for ethical approval was not required according to our institution's guidelines and national regulations.
Apparatus Participants used their own devices for the experiment in order to read the text and report interruptions. Even if the devices differed from participant to participant, the reading condition was always similar. The participants were instructed to read the text on a computer equipped with a microphone and an audio device. They were also required to activate their internet connection in order to (1) be directed to a webbased experiment built using Qualtrics, a software platform for experience management which requires the use of a web browser to collect survey data online, and (2) communicate via Teams with the experimenter if any question should arise during reading. The texts, the reading comprehension questions, and the grid used to report interruptions were all presented using Qualtrics.
Procedure The participants performed the experiment in their own environment. After a recruitment phase, the experimenters contacted the participants using the Microsoft Teams videoconferencing software. After scheduling the call, they sent them a personal Qualtrics link to allow them to access the experiment. The experimenter remained available remotely throughout the entire experiment in order to answer any questions from the participants and ensure that the experiment was carried out correctly. After reading the instructions, the participants had to complete a questionnaire that collected socio-demographic information and their media utilization habits. They then had to read a text and answer the reading comprehension questions. They were instructed to read the text in their usual reading environment.
An analysis revealed no relation between attentional disruption and the pleasure experienced when reading the text. However, our data show a positive correlation between pleasure when reading the text and reading comprehension. Our study reveals very frequent attentional disruptions during a computer reading session in an ecological context. Considering all the types of attentional disruptions measured in our study (i. e. , interruptions and mind wandering), participants reported a diversion of attention away from the text every 4 mins on average. Interestingly, these attentional disruptions occurred Number of interruptions reported as a function of the source of the interruption (media-unrelated or media-related) and the multitasking profile of the participants (high or low media multitaskers).
Simulation Design and Model Evaluation Simulations were designed and model evaluation was carried out to determine whether (i) CoSMo-based ModVege solutions simulated the relative abundance of plant (grass) functional types and species, and (ii) differences in simulated AGB were caused by the explicit simulation of plant diversity, by comparing the CoSMo-based and stand-alone ModVege solutions. Standalone (ModVege) and coupled (ModVege-CoSMo) modelling solutions were configured using daily weather data retrieved from the CLIMATIK database (through the INRAE portal, https://www6. paca. inrae. fr/agroclim/Les-outils, accessed on 7 October 2022) and management data as determined at the experimental site, and parameterised for each treatment of both blocks (Supplementary Material). In particular, simulations were performed with common sets of ModVege and CoSMo parameters (Tables  S5  and S8 ) and type-and plant-specific parameters for either ModVege (Tables  S6  and S7 ) or CoSMo (Tables  S9  and S10 ).
Some ModVege parameters were extracted from published literature for (grass-based) functional types  [25]. Otherwise, the datasets described in Section 2. 3 were used for the calibration of model parameters. ModVege stand-alone was first run for each functional type separately (A, B and b) and then the daily community AGB was obtained as a weighted mean of the three functional types, using for each treatment the mean abundances of each type over the period 2006-2018 (Table  3 ) as a weighting factor. The calibration work was carried out through a trial-and-error process comparing the model estimates with observational data while ensuring biologically interpretable plant parameters by modifying their values within plausible ranges. For instance, the parameters ST1 = 800 • C-d and ST2 = 1200 • C-d of G.
Acknowledgments: This work was undertaken under the auspices of the project  MODIPRAS (Modelling relationships between species diversity , the functioning of grassland systems and their ability to deliver ecosystem services;  2018-2019 ) of the former  INRA  ( French National Institute for Agricultural Research ) meta-programme ECOSERV (Ecosystem services). We wish to acknowledge the commitment of  Benjamin Muñoz  (MS student in 2021 at the  University of Clermont Auvergne, Clermont-Ferrand, France ).