dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements It is acknowledged that  Jacob L. Høyer  at  Danish Meteorological Institute  has kindly provided the complete dataset of Level 4 SST for this study. Section 4. 5. Space-based observations of surface signatures in the wake of the 2018 Eastern Pacific tropical cyclones Acknowledgements This work was supported by  CNES TOSCA program  (COWS and SILLAGE projects), by the  European Space Agency  through  S1-4SCI   Ocean Study  project (contract  4000115170/15/I-SBo ),  Sentinel-1 A Mission Performance Center  ( contract4000107360/12/I-LG ),  EUMETSAT   CHEF  project,  ANR (FEM)   CARAVELE  project. Section 4. 6. Record wave storm in the Gulf of Cadiz over the past 20 years and its impact on harbours Acknowledgements This work is supported by the  JERICO-NEXT  and  JER-ICO-S3  projects under the European Union's  Horizon 2020 research and innovation programme  with grant agreement no.
1 database, CERSAT sea ice concentration 3 GLORYS12v1 NEMO3. 1 ERA-interim Reduced-Kalman SEEK filter Reynolds ¼°AVHRR-only 0. 083°x 0. 083°5 (Pham et al. 1998) SST, AVISO SLA, in situ T/S 0 z-levels profiles from Coriolis CORA4. 1 (until 2003), CORA5. 0 (2004 -2015), CORA5. 1 (2016) database, CERSAT sea ice concentration 4 SODA3. 4. 2 GFDL-MOM5 ERA-interim Optimal interpolation WOD13 and COADS2. 1 ¼°x ¼°5 (Carton et al. 2018) 0 z-levels.
Recently a new climate data record from the European Space Agency Climate Change Initiative (ESA CCI) on sea surface temperature (Merchant et al. 2019) has been produced, covering the period late-1981 through to 2016. This is being extended as an interim climate data record by the Copernicus Cli- mate Change Service (C3S). These products have a high level of stability throughout the record (Berry et al. 2018) and hence they are ideal for evaluating changes in sea surface temperature over time. These datasets have been used here to examine changes since 1993, with a focus on temperatures in 2018.
3), which provided 10 days of 3D global ocean forecasts daily updated and used coastal runoffs from 100 major rivers from the Dai et al. 2009 database. (2) The Iberian-Biscay-Ireland Monitoring and Forecast Center (CMEMS IBI-MFC) (product reference 4. 10. 4), which produced near-real-time with river discharge inputs daily updated, including discharge for 33 rivers. Combination of daily observations from PREVIMER (Ebro River runoff not included), s162 COPERNICUS MARINE SERVICE OCEAN STATE REPORT, ISSUE 4.
I. INTRODUCTION Operation of CERN's accelerators can lead to the activation of equipment, which may require shipping to external workshops, institutes, or repositories for radioactive waste. The IAEA safety standards provide nuclide-specific activity limits, and criteria for the transport of radioactive equipment. However, the literature lacks data concerning non-standard radionuclides of interest which are produced at CERN's particle accelerators. Such radionuclides are assigned a conservative reference activity limit which needs to be evaluated based on the Q-System. Radiological quantities like external or internal doses must be assessed. In particular, the skin dose originating from beta emitters is difficult to estimate by analytic equations. The associate editor coordinating the review of this manuscript and approving it for publication was Zhanyu Ma.
IV. INPUT DATA FOR THE SOFTWARE The software tool requires two sets of input data files. One is the nuclear data evaluation, containing radionuclide progeny chains, emissions energy and intensity, as well as decay type and half-life. The second is the dose model for the accident scenario considered. The nuclear data is stored inside text files with the format established in ICRP-107: • A. NDX file contains general information of the radionuclides available, such as half-lives, decay types, but also pointers to the other files lines to easily find values of interest; • A. BET file contains the beta+/beta-spectrum; • A. RAD file contains all the discrete radiations emissions and intensities; • A. NSF file contains the neutrons multigroup spectrum. • Also, the databases contain a high number of radionuclides which do not have complete decay data.
These radionuclides with incomplete information have been excluded from the final database used by the software. The total number of included radionuclides is available in Table  1. The radionuclides are excluded on the following basis: • A radionuclide contains a decay mode with no associated radiation type. This is the case in the libraries when the decay mode is known but the spectrum of the radiations is not; • A radionuclide contains a continuous gamma spectrum; • A radionuclide contains a continuous beta spectrum without any beta endpoint. • used in the simulation code, • used for decay emissions, Interpolation methods used: • to compute transfer functions from fluences, • to interpolate the dose at a specific energy emission, Daughters considerations, Material compositions, Shielding,.
etc. The principle of using transfer functions has been adopted by the working group and we will refer to this approach as a model. Consequently, a model groups different assumptions, summarized as a transfer function. These transfer functions are then used as input in the software to compute Q-Values under their respective assumptions. A transfer function describes the dose, or dose rate, relating to one of the scenarios in Figure  1 , for one primary particle emitted at a specific energy for the considered geometry. As the different models consist of transfer functions read from the input files, the general calculation method is similar for all models but the constitution of the transfer functions can differ according the assumptions adopted. The transfer function database contains all the transfer functions of each scenario.
1) GENERAL ASSUMPTIONS Some assumptions have been performed for the construction of the software and must be mentioned here to avoid misinterpretation of the results. • In ICRP-107, some beta spectra are mixed when they are beta+/beta-emitters. It is impossible to reconstruct the part coming from positron emission and electron emission separately. In this case, these beta spectra from ICRP-107 have been replaced by those from ENDFBVIII or JEFF3. • For JEFF and ENDF databases, the generation of the beta spectra with the FERMI equation is performed using BTSPEC tool. 1  We adapted this tool to read today's nuclear data but it can lead to inaccurate values for some radionuclides. The inaccuracies are small but should still be mentioned. These radionuclides are those for which forbidden transitions of types above 3 exist in the frame of beta emissions  [15].
3) IMPROVED MODEL DEVELOPED AT CERN ACCORDING TO WORKING GROUP DISCUSSIONS Following the discussion of the working group, it has been decided to build the new transfer functions set by considering irradiation geometries as described in ICRP-116. The construction of emission-to-dose curves from fluence in the case of ''CERN AP, PA, ISO'' models is performed to simplify the calculations in the software and limit the quantity of input data. It is easier to manipulate emission-to-dose transfer functions instead of fluences and this idea has been adopted by the working group. With FLUKA, simulations have been performed for different energies of incident particles (photons, electrons, positrons). We consider the fluence E,p E , p , Qx of particles p at energy E for a primary particle p emitted at energy E in the scenario Qx.
It uses different libraries: • Graphviz for plotting decay chains,  • QT for the GUI, • QCustomPlot for the different graphics that can be produced, • Boost libraries for a general purpose. The scope of the software was initially to provide information about doses, Q-Values and data related to radionuclides produced in some of CERN's installations which are not always tabulated in the dangerous goods regulation for the shipping of radioactive materials  [20]. Then, real advantages of using this software within the working group emerged, particularly to compare the different models. SOFT is currently based on nine modules performing different calculations. Figure  6  shows an overview of the software main window. The left part of the window (1) is the entry point for the user. It allows the user to add or remove radionuclides.
On the bottom of this part, the user can choose which decay database and model (denoted ''calculation type'') they want to use. For each radionuclide added, there is a quick summary giving the decay database, the half-life, the type of decay and the model selected. If a radionuclide doesn't exist in the evaluation or is stable, the following message will appear just above the drop-down menu of the decay database: Radionuclide: XX-YY not recognized or stable. The calculation methods are described in  [2]  regarding the current regulation limits and in paragraph IV of this document for the on-going work regarding the regulation update. The software will be modified during all the development process of the new models at IAEA, to include the latest decisions. Upon completion, the last release will keep only the model selected by the working group and the associated decay database.
The upper part of the results' view (  2 ) is made of 9 different modules, which show the values/data the user wants to see. These -Comparison tool: compares different models included in SOFT as well as different libraries, described later in this document For a radionuclide, the general overview of the Q-Values is shown in Figure  7. To display the Q-Values of a radionuclide, the user double clicks the desired radionuclide in the left column of the software. Results can be saved in CSV format using the right click button of the mouse. In case Q-Values and doses of all radionuclides from a database need to be computed, the user can write ''all'' in the radionuclide field.
B. PARTICLES CONTRIBUTIONS MODULE The particle contribution module allows for plotting bar charts in which each particle contribution to the dose is displayed for the scenario linked to QA, QB, QD, QEye. In the example presented in Figure  10 , we observe the contributions of particles for Es-254m radionuclide with the ICRP-107 decay database and the IAEA2012 model. For example, in the QB scenario, beta minus radiation is predominant for the dose contribution (78. 70 %) and then, the 21. 30 % of the remaining dose come from discrete electrons (Auger and Internal Conversion).
D. EMISSION GRAPH MODULE This module will plot all the emission data related the radionuclide selected in the drop-down menu in the top right part of the window. The data coming from ICRP-107, JEFF3. 3 or ENDF BVIII can be directly plotted in the software. As for the progeny/ancestry module, the user can save emission data plotted as an image file for a selected radionuclide or for all the radionuclides selected in the left part (Figure  12 ). Plots can be saved with a right-click.
E. PROGENY / ANCESTRY MODULE The progeny / ancestry module generates graphs of decay chains / ancestry chains for a radionuclide. The decay chain goes down until the latest stable nuclides are reached, and the ancestry chain links from all the parents who can at one point generate the specified radionuclide. The radionuclide chosen is shaped into two circles, and the stable radionuclides are dark-coloured. The type of decay follows a specific colour code to have a better overview of the decay chain. Branching ratios are printed next to the arrow representing the type of decay. Progeny and ancestry graphs can be generated using all the decay databases (ICRP-107, JEFF3. 3 and ENDFBVIII). If several radionuclides have been chosen by the user, they can display the one desired using the drop-down menu in top-right of the window.
F. EMISSION VALUES MODULE This module provides the emission data for the radionuclides selected using the top-right drop-down menu. It corresponds to data from ICRP-107, JEFF3. 3 or ENDF BVIII used in the Emission graph module. In Figure  14  an example of emission values for Co-60decay database ICRP-107 can be seen. The data is divided into emission types (Beta+, Beta-, discrete e-, gamma, alpha). If an emission is present in the decay database, the module will provide: 1) the energy of the emission in MeV, and 2) the intensity. Data can be saved for a selected radionuclide or for all the radionuclides added in the left part as an html file.
H. COMPARISON TOOL The comparison tool compares the dose values coming from the different scenarios, with the different models and nuclear databases. The user selects a radionuclide using the top-left field, the models and the evaluations to compare (Figure  16 ). Then, they can choose how to compare the results: • ''Doses (Sv/Bq)'' compares absolute dose values for the selected models; • ''Particle contribution to dose (%)'' evaluates, for each model, the contribution of each particle to the dose; • ''Doses vs model 1'' computes the ratio of dose between each model to model 1. The model 1 is defined by the user as the reference model and can be each of the aforementioned model; • ''Particle contribution to dose vs model 1'' computes the ratio of the particle dose contribution to model 1. All the data are listed in the table below and displayed in the bar charts for the whole set of scenarios.
VI. CONCLUSION CERN has developed an efficient software tool to calculate data related to radioactive shipping (Q-values, A1 /A2 limits) for a large scope of radionuclides. An innovative technique of calculation makes the determination of the values simpler, by associating particle/energy/scenario dependent transfer functions with nuclear decay data of a radionuclide. This technique is more efficient and less time-consuming than referring to Monte-Carlo simulations for each Q-Value and each nuclide. Different decay databases (JEFF3. 3, ENDFBVIII. 0, ICRP-107) can be used, but the IAEA working group recommends ICRP-107. Due to the extensive features exposed in this tool (comparison of different models, free choice of model and database for calculating specific Q-Values, detailed analysis of contributions originating from various particles, mixture of radionuclides etc.
) it can be used for carrying out detailed comparison studies very efficiently. This is of high importance for carrying out the standardization process with which the IAEA working group has been mandated. Later, a lighter version of this software could be produced to be distributed with the then-defined regulation. This step is intended to be discussed once the Q-System review has been completed: currently planned for 2021. THOMAS FROSIO received the Engineering degree in energies and nuclear reactor physics from École des Mines, France, in 2012, the Ph. D. degree in neutron and nuclear physics in 2015, and the master's degree in applied and fundamental mathematics in 2016. During his Ph. D. , he was working on developing frameworks in order to propagate nuclear and manufacturing data uncertainties on different neutron physics parameters in the coupled numerical simulations transport/depletion (deterministic and Monte-Carlo).
At the same time, he took up the responsibility for the radioactive source service and the radioactive shipping service. In 2003, he improved databases and web interfaces with the RP Group, which permitted the creation of an interface and associated database for managing industrial radiographies performed on site, radioactive sources lent to users, and shipment of radioactive goods by air and road. In 2010, he conceived and developed a software solution for calculating the radiological characterization of packages for the shipment of radioactive material. This software is currently a part of the computation tools available in Nucleonica portal. In 2012, he took a position as a Scientific Assistant to the Head of the radiation protection. He had also the responsibility for the management of electronic documents on a departmental level, as well as for data protection within the RP group.
A. NUCLEAR DATA EVALUATIONS Currently 3 nuclear decay data evaluations are available in SOFT: • ICRP-107 • ENDFBVIII. 0 • JEFF3. 3 JEFF3. 3 and ENDFBVIII. 0 are generated based on the NEA databases and have been set up with the same format as the one related to ICRP-107 with a python script.
9 modules are respectively: -Q-Values: this module provides Q-Values for a given radionuclide, in accordance to the database and the model chosen. -Dose and dose rate: it gives information of dose and dose rate for a given radionuclide, in the specific scope of the Q-System. -Particle contributions: this part describes the contribution of each particle to the dose originating from a selected radionuclide, for each Q-Value, in percent. -Mixture: allows for the computation of radionuclide mixture limits with an overview of the main contributor radionuclides. It also determines if a package can be shipped as Type-A or not. -Progeny & ancestry: this module generates the progeny's and ancestry's chain of a radionuclide with a graphical representation. -Emissions graph: all the information regarding the decay emissions (photon / alpha / beta / mono-energetic electrons) are summarized here.
1446 cm 3 bar K -1 mol -1 is the gas constant, and ν CH 4 is the partial molar volume (cm 3 mol -1 ) of CH 4 calculated from  Rettich et al. (1981). The fugacity coefficients were calculated using the methods described in Ziabakhsh-Ganji and Kooi (2012). A Maple script was provided by the authors, which was transcribed to Matlab code by  Schmid (2019). The script calculates, among other things, the fugacity coefficients for CO 2 and CH 4 , including the interactions between both gases.
Results and discussions In Fig. 4  an example of a consecutive downward and upward profile of dissolved CH 4 measured by the Sub-Ocean sensor is reported. CH 4 concentrations are expressed as mixing ratio with respect to the total dissolved gas. The sensor was lowered at a speed of ∼ 6 m min -1 , reaching 100 m depth in only  18 min. The response time of the sensor during the campaign expressed as τ 90 was ∼ 10 s, which corresponds to a vertical resolution of 1 m. On the right-hand side, dissolved CH 4 is plotted against depth, showing the reproducibility of the sensor during descent and ascent. A total of eight continuous profiles (downward and upward) were obtained with the Sub-Ocean instrument during the campaign. They are reported in Fig. 5  together with dissolved CO 2 , CTD data (temperature, conductivity and dissolved oxygen) and total dissolved gas pressure (TDGP).
However, in these conditions, a dry gas flow of only ∼ 0. 065 cm 3 STP min -1 is delivered by the extraction system. The large uncertainty in this dry flow measurement directly affects the accuracy of the retrieved concentration. The uncertainty represented by the grey lines in Fig. 6  represents the measured variability over the eight vertical profiles from 0 to 80 m and was fixed to ±22 % at larger depths. The CO 2 data are from  Schmid et al. 2005  and are calculated from alkalinity and pH measurements. TDGP measurements are discrete measurements at seven different depths measured with the HydroC ® HP sensor which have been interpolated to match the depth resolution of the Sub-Ocean data. The nitrogen (N 2 ) mixing ratio was retrieved assuming that the main gas is composed of N 2 , CO 2 , CH 4 and O 2 (pN 2 = TDGP -pCH 4 -pCO 2 -pO 2 ).
The molar concentrations as a function of depth for the average continuous profile recorded by the Sub-Ocean sensor and for the discrete measurements obtained with the HydroC ® HP sensor are reported in Fig. 6. A good agreement between the two independent measurements is observed. The measurements were obtained during the same field campaign at the measurement site location near Goma (the two vessels were a few hundred meters away from each other). However, the measurements were not performed simultaneously. In the graph, results from previous campaigns are also reported. Data from the University of Liege obtained during a longterm monitoring campaign of the lake are reported in orange. Data were collected from June 2011 to August 2014 at different periods of the year (both dry and rainy seasons) and at different locations (northern and southern basin)  (Roland et al.
, 2017 (Roland et al. , , 2018)). The large variability of these measurements is reported by the orange lines (Fig. 6 ) defining the 3σ distribution. Data from the works of  Pasche et al. (2011)  and  Schmid et al. (2005)  are also reported in green and blue, respectively. The measurements from ULiege and  Pasche et al. (2011)   2011 ). Blue rhombuses correspond to measurements from  Schmid et al. (2005)  in the northern basin using a commercial Capsum Met sensor  (Schmid et al. , 2005). In the inset a zoomed-in view of the shallow data is presented with a log scale on the concentrations allowing a better comparison of the different datasets. were obtained by sampling the water using Niskin bottles and analyzing the dissolved gas in the laboratory by a headspace technique followed by GC analysis.
(2011) , which were obtained at a similar time of the year but at different locations  (May 2006 and 2007 in Kibuye, Gisenyi and Ishungu). A stronger similarity can be found with the dataset from the same location  (Gisenyi, 2007)  in the northern basin. CTD measurements (Sea & Sun Marine Tech, CTD-90M) performed a few months prior to the campaign at the research platform (Fig. 7 ) confirmed a typical behavior of the lake stratigraphy while going from a dry into a rainy season  (Roland et al. , 2017)  and therefore justified the high concentrations measured in this work. The lake was mixed down to at least 50 m depth during the previous dry season and started to stratify in mid-December, leading to a 25 m depth seasonal thermocline. Below the thermocline, O 2 was rapidly consumed by mineralization of organic matter and oxidation of reduced compounds (e.
Molecular phylogenetic sampling To infer broad relationships of the Weda Bay material, we generated orthologous sequences of plastid rbcL and trnL-F (trnL intron and the 3′ intergenic spacer), and performed a preliminary analysis in the context of the full 179-tip Euphorbiaceae backbone phylogeny of  Wurdack et al. (2005) , which indicated nested placement in Crotonoideae. Our final taxon sampling of 102 tips (97 taxa) focused on Crotonoideae and included 47 of ca. 52 genera potentially belonging to clade C2, using sequence data from  Wurdack et al. (2005) , GenBank, and 149 newly generated sequences. A small outgroup sampling (seven taxa) represented the three other subfamily lineages without greatly increasing trnL-F alignment complexity. To improve resolution, especially for the Ricinocarpeae s.
l. subclade with which the Weda Bay material grouped, we added nuclear ribosomal internal transcribed spacer (ITS) region and external transcribed spacer (ETS) region data. External transcribed spacer aims to resolve species-level relationships using recently designed primers that amplify multiple groups of Euphorbiaceae  (Cardinal-McTeague et al. , 2019; Wurdack, unpublished data). To reduce alignment problems with increasing sequence divergence, the ITS taxon sampling was limited to clades C1 and C2 (77 tips, 65 with data) and the ETS to Ricinocarpeae s. l. (28 tips, all with data plus two other clade C2 taxa). In addition, a fragment of plastid matK was sequenced for the Weda Bay material to produce DNA barcode reference data. Voucher information and GenBank numbers are provided in the Appendix I.