dataesr/scientific-paragraphs-categorization huggingface dataset:
The error-independent CORMAP P-value for model fits correlated well with the 2 values, showing a much larger range of variation. Broader experience with a large number of examples is needed to provide a basis for understanding the significance of the absolute value of the P-values in the context of SAS modelling. We therefore encourage experimenters to use the CORMAP analysis and to report the Pvalues. Once a sufficiently large sample size has been acquired, a systematic review and evaluation of their utility in the context of SAS modelling will be possible. As biomolecular SAS continues to grow in popularity and further develop in this era of integrative/hybrid methods for the structure determination of increasingly complex biomolecular complexes and assemblies, it is essential to firmly establish publication guidelines with the goal of ensuring access to the information required for proper evaluation of the quality of SAS samples and data, as well as the validity of structural interpretation.
In addition to our recommended guidelines for data presentation in a publication, we recommend that SAS data and models be deposited and made freely available in a public data bank [currently there is SASBDB and BIOISIS (http://www. bioisis. net/)]. Ideally q, I(q) with standard errors should be deposited for each measured profile and the associated models plus details of how the experiment was conducted with the data and model validation parameters and analyses as outlined above. We strongly recommend that the sasCIF dictionary be expanded to include all of these data items in the recommended guidelines and encourage program developers to use the sasCIF as an export format which will significantly ease the burden on researchers in reporting, and will facilitate more automated deposition SAS databases that can support integrative/hybrid models  (Sali et al.
Acta Cryst. (2017). D73, 710-728 Trewhella et al. 2017 publication guidelines for solution SAS data 723 Figure 2Crystal structure modelling results. FoXS-derived models (red and black solid lines) for GI (PDB entry 1oad, tetramer), BSA (PDB entry 4f5s, chain A) and CaM (PDB entry 1cll with the additional N-and C-terminal residues modelled) fitted to I(q) versus q. The upper plot shows log I(q) versus q, while the lower inset plot is the error-weighted residual difference plot Á/ = [I exp (q) À cI mod (q)]/(q) versus q. The colour key for the data plots is the same as in Fig. 1.
Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface.
m. At the time of data acquisition, it was heading towards the east-southeast (heading 100°) at a speed of 2. 5 knots, following the drift of the oil slick. The released product is an emulsion of mineral oil in water, which was produced by NOFO and consists of a mix of water, Oseberg crude oil and a small addition of IFO 380 (Intermediate Fuel Oil or marine diesel oil, with viscosity of 380 mm 2 •s -1 ). The water content of the recovered emulsion was measured by NOFO and is equal to 60%. For the trial, 45 m 3 of mineral oil emulsion was discharged at sea and recovered by the MOS Sweeper system. During the experimentation, sea state information was provided by the Norwegian Meteorological Institute and is given in Table  1. This information is consistent with that measured from one of the vessels present during the offshore experiment and given in  [11].
Radar payload configuration flexibility allows full polarimetric and very high resolution modes (up MOS Sweeper trial began on 9 June in the early morning (06:00 a. m. UTC) and continued until 10:30 a. m. UTC. After a first phase of low flow discharge (06:00-06:30 a. m. UTC), the release continued between 06:30 a. m. and 08:00 a. m. at full regime. The boats were advancing towards the west-northwest (heading 290 • ) at a speed of 2. 5 knots. Around 08:00 a. m. , the lead vessel (Stril Mariner) had completed the release and Stril Luna, the boat towing the MOS Sweeper system, turned around and continued the cleaning process of the slick until 10:30 a. m. At the time of data acquisition, it was heading towards the east-southeast (heading 100 • ) at a speed of 2. 5 knots, following the drift of the oil slick.
Another issue that had to be considered concerned the vibrations inside the pod during acquisition. A specific study was carried out to measure the vibration spectrum and to eliminate its impact. First, low-frequency shock absorbers installed in the pod achieved a partial removal. The residual movement is generally at such a low frequency when it occurs that it is finally compensated by post-processing using the data from the IMU. To ensure a flight speed compatible with the cameras frame rates, at this altitude, the plane must fly with a ground speed around 120 m•s -1. This speed is quite slow for the Falcon 20, which is a jet plane, which induces a pitch angle of about 5°. This angle had to be mechanically offset to ensure a nadir line of sight. The assembly was done in France and the travel to Norway was at high altitude which implies quite low temperatures inside the pods.
Moreover, to cope with temperature issue inside the pod during measurements in Norway, the optical sensors were covered by an insulated material and were maintained in a correct range of temperature with a flat heating resistance triggered by a thermostatic sensor. This heating device is also used to avoid ice deposits on the glass of the porthole. Another issue that had to be considered concerned the vibrations inside the pod during acquisition. A specific study was carried out to measure the vibration spectrum and to eliminate its impact. First, low-frequency shock absorbers installed in the pod achieved a partial removal. The residual movement is generally at such a low frequency when it occurs that it is finally compensated by post-processing using the data from the IMU. Dedicated software has been developed by ONERA for processing and archiving image products such as georeferenced spectral radiance and spectral ground reflectance products.
Processing consisted in applying calibration coefficients on the hyperspectral images to obtain radiance products in raw geometry (level 1a), which take into account the transmission through the glass of the pod. From level 1a, image is corrected for atmospheric effects (level 2a) using the ONERA atmospheric tool COCHISE  [15] , which is based on the use of hyperspectral information combined with the radiative transfer code MODTRAN  [16]. As scan lines are synchronized with altitude and position measured by IMU it is possible to get the position of each pixel in the image geometry map. These geo-referenced images are projected onto an UTM map grid to achieve levels 1b and 2b, i. e. , ortho-rectified images in units of spectral radiance or reflectance. As the time schedule was driven by the trial of the mechanical recovering boom during the exercise at sea, it was not possible to fit the images acquisitions to the best meteorological conditions.
Microwave Sensors SEHTI radar sensors operated during the OOW'2015 experiment where the L-and X-band ones. The waveform used for this airborne campaign of measurements is presented Table  3. Dedicated software has been developed by ONERA for processing and archiving image products such as georeferenced spectral radiance and spectral ground reflectance products. Processing consisted in applying calibration coefficients on the hyperspectral images to obtain radiance products in raw geometry (level 1a), which take into account the transmission through the glass of the pod. From level 1a, image is corrected for atmospheric effects (level 2a) using the ONERA atmospheric tool COCHISE  [15] , which is based on the use of hyperspectral information combined with the radiative transfer code MODTRAN  [16].
Campaign of Acquisition Optical and radar sensors used for this campaign have been presented above (see Sections 3. 1 and 3. 2); we focus now on the data acquisition process. SETHI was flying at an altitude of 9000 ft. , along a trajectory describing a racetrack, of which longest length measures approximately 10 km (see Figure  8 ). The hyperspectral acquisitions (nadir viewing) are made along the first major axis of the racetrack, vertically of the oil-covered area. Side-looking SAR imageries are acquired along the return axis. Trajectories are adjusted before each run of acquisition from the AIS signal of Stril Luna (vessel towing the MOS Sweeper recovering boom and supposed to be within the slick) received in real time Sensors 2017, 17, 1772 9 of 21 onboard the SETHI system. Flying at a ground speed of 120 m•s -1 , the time lags between optical and radar imagery is about a few minutes.
A description of each run of remote sensing data acquisition carried out during the MOS Sweeper trial is given Table  4. In this table, the lines in bold correspond to the acquisitions mainly analyzed in the following, namely dual-frequency SAR imagery at 10:01 a. m. UTC (run 8) and VNIR-SWIR hyperspectral imagery at 10:12 a. m. UTC (run 10). along a trajectory describing a racetrack, of which longest length measures approximately 10 km (see Figure  8 ). The hyperspectral acquisitions (nadir viewing) are made along the first major axis of the racetrack, vertically of the oil-covered area. Side-looking SAR imageries are acquired along the return axis. Trajectories are adjusted before each run of acquisition from the AIS signal of Stril Luna (vessel towing the MOS Sweeper recovering boom and supposed to be within the slick) received in real time onboard the SETHI system.
Flying at a ground speed of 120 m•s -1 , the time lags between optical and radar imagery is about a few minutes. A description of each run of remote sensing data acquisition carried out during the MOS Sweeper trial is given Table  4. In this table, the lines in bold correspond to the acquisitions mainly analyzed in the following, namely dual-frequency SAR imagery at 10:01 a. m. UTC (run 8) and VNIR-SWIR hyperspectral imagery at 10:12 a. m. UTC (run 10).
Imagery in Optical Domain Discrimination between oil slicks and other phenomena (look-alike) was shown to be feasible with the use of optical imaging technique  [18]. Furthermore, distinction between oil types and indications on oil volume can be achieved thanks to hyperspectral imaging  [19]. Airborne data collected by SETHI on 9 June at 10:12 a. m. UTC (run 10) were selected to study the potential of hyperspectral imaging. The VNIR and SWIR images in reflectance units were registered to get access for every pixel to the full spectral signature from 0. 4 to 2. 5 µm. This was done using the GeFolki toolbox developed by ONERA  [20]  based on the common spectral range in the.
Imagery in Optical Domain Discrimination between oil slicks and other phenomena (look-alike) was shown to be feasible with the use of optical imaging technique  [18]. Furthermore, distinction between oil types and indications on oil volume can be achieved thanks to hyperspectral imaging  [19]. Airborne data collected by SETHI on 9 June at 10:12 a. m. UTC (run 10) were selected to study the potential of hyperspectral imaging. The VNIR and SWIR images in reflectance units were registered to get access for every pixel to the full spectral signature from 0. 4 to 2. 5 µm. This was done using the GeFolki toolbox developed by ONERA  [20]  based on the common spectral range in the two images. A RGB (Red-Green-Blue) quick-look of the flight line is shown in Figure  9a. At the time of the acquisition, 10:12 a.
As expected, the center of the slick is the part with the highest spatial abundance of oil emulsion. However, the obtained classification map shows that all spectral variations within the oil slick cannot be explained only by the changes in areal fraction. In the microwave domain, studies based on data acquired by the SIR-C/X-SAR imaging radar system flown aboard the space shuttle in 1994 and operating at L-(1. 275 GHz), C-(5. 172 GHz) and X-bands (9. 677 GHz) have assessed performances of multi-frequency SAR imagery for maritime pollution monitoring. As an example, it has been demonstrated in  [27]  the capability of such data to distinguish between mineral oil and biogenic films (look-alike). As no multi-frequency instrument has been launched in space since this mission, researchers have had little opportunities to pursue multi-frequency analyses over slick-covered areas.
The acquired dataset is therefore unique because of the overall high resolution, the low noise levels and the quasi-simultaneous acquisitions at L-band, X-band and over the full hyperspectral range. In this paper, dual-frequency SAR data and hyperspectral images have been shown to provide information on the quantity and the nature of oil discharged in oceans. It has also been reported how multi-wavelength remote sensing data can assess the efficiency of the cleanup operations. The work on this dataset has just began with a separate analysis of the potentials of both radar and hyperspectral imagery. They provide different information: the relative concentration and the nature of the oil. However, because the acquisitions are almost simultaneous, the dataset provides a unique opportunity to explore the synergy between the two types of imagery.
The calculation of the Higgs mass in general renormalisable field theories has been plagued by the so-called "Goldstone Boson Catastrophe," where light (would-be) Goldstone bosons give infrared divergent loop integrals. In supersymmetric models, previous approaches included a workaround that ameliorated the problem for most, but not all, parameter space regions; while giving divergent results everywhere for non-supersymmetric models! We present an implementation of a general solution to the problem in the public code SARAH, along with new calculations of some necessary loop integrals and generic expressions. We discuss the validation of our code in the Standard Model, where we find remarkable agreement with the known results. We then show new applications in Split SUSY, the NMSSM, the Two-Higgs-Doublet Model, and the Georgi-Machacek model.
The new version of SARAH 4. 12. 0 therefore now offers the possibility to calculate two-loop masses for neutral scalars in non-supersymmetric models, as well as substantially improving the calculation in supersymmetric ones. As the only non-supersymmetric model for which comparable results exist is the Standard Model, in section 3 we compare our new calculation against the public code SMH  [54]  and the results of  [55] , finding excellent agreement (even if our results do not include all of the contributions included in those references). We then illustrate our new routines by computing some new results in Split SUSY in section 5. On the other hand, in section 4 we show how our new approach improves our previous calculation for supersymmetric models through the example of the NMSSM, for which our results should now be considered state of the art.
(2. 15) All of these functions are implicitly dependent on the renormalisation scale Q, typically containing factors of log x ≡ log(x/Q 2 ). Expressions for all of these functions expanded up to O(1) in the external momenta (or the reference for them) were given in  [36]. However, the functions Ṽ (0, y, z), Ṽ (0, 0, z) were given in terms of the regularised function V (u, v, y, z) defined in  [37] ; unfortunately, however, no closed-form expression for this function was available, nor is it straightforward to evaluate it simply using the numerical package TSIL  [58]. Hence in appendix A we derive expressions for this functionfirst with full momentum dependence, and then expanded up to O(1) in the external momenta. In our practical implementation in SARAH we have extended the available routines for calculating two-loop integrals with the missing ingredients to address the Goldstone boson catastrophe.
(2. 17) Here δ MS is one for MS masses and zero for DR. In addition, routines to calculate the consistent tadpole solution are generated during the output of SPheno code. This is fully automatised beginning with SARAH version 4. 12. 0 and the user can obtain a SPheno version for non-supersymmetric models as before -with the difference that two-loop mass corrections are now included. We refer for more detailed explanations of how to use the code to the standard references such as  [46]. The only requirements are recent versions of SARAH and SPheno which are available at www. hepforge. org. The new features can now be adjusted in the Block SPHENOINPUT in the Les Houches input file: Note that the solution to the Goldstone boson catastrophe exists only for the diagrammatic calculation (flag 8 → 3), but not for the effective potential calculations using numerical derivatives to obtain the tadpoles and self-energies (flag 8 → 1,2).
Standard Model 3. 1 A first comparison of our results with existing calculations Now that two-loop corrections to scalar masses are available in SARAH, free of the Goldstone boson catastrophe, it is important to compare the results we obtain to other computations available in the literature, as a verification of our results and as a way to estimate the impact of missing corrections. We consider in this section the Higgs mass calculations in the Standard Model, and we will compare the results obtained with SPheno with the computations performed at complete two-loop calculation in  [55] , and the full two-loop (plus leading three-loop) Higgs mass calculation implemented in the public code SMH  [54]. These works take into account two-loop electroweak corrections, which are not available for generic theories and are not included in our code, hence we will quantify the size of these effects, together with effects from momentum, and investigate the discrepancy in masses coming from the different determination of the top Yukawa coupling.
Computations are made with SARAH-4. 12. 0, SPheno-4. 0. 3 and SMH-1. 0  [54]. the SPheno code generated by SARAH version 4. 9. 3 -in which y t is only determined at one-loop order -are approximately 2 -2. 5 GeV below those shown in table  1 , and hence illustrate the importance of the precise determination of the top Yukawa coupling for calculations of m h. The small size of the difference between the values found with the couplings computed by SPheno or taken from  [55]  -a few tens of MeV at two loops -tend to indicate that the precision of the extraction of y t in SPheno is now comparable to that in  [55]. Considering now the effect of the consistent tadpole solutions -that appears only in the two-loop masses -we observe a small shift of about 30 MeV to m h , indicating that the perturbative expansion we perform in the tadpole equation is valid for the SM.
Acknowledgements We thank  Pietro Slavich  for helpful discussions and many comments on the draft. JB and MDG acknowledge support from  French  state funds managed by the  Agence Nationale de la Recherche (ANR) , in the context of the  LABEX ILP  ( ANR-11-IDEX-0004-02 ,  ANR-10-LABX-63 ), and MDG acknowledges support from the  ANR  grant " HiggsAutomator " ( ANR-15-CE31-0002 ). JB was supported by a scholarship from the  Fondation CFM. FS is supported by  ERC Recognition  Award  ERC-RA-0008  of the  Helmholtz Association.
The development of the research process is closely oriented to the modelling process developed in the EU funded OCOPOMO project (Scherer et al. , www. ocopomo. eu) but has been adapted and extended by an interpretative perspective. While for the analysis perspective the process of conceptual modelling, model transformation and implementation of declarative rule-based models has been extended by an initial qualitative data analysis (extending the scenario input proposed in OCOPOMO), for the modelling perspective the traceability concept (Scherer et al. , ) is utilized for developing virtual narratives that facilitate interpretative research (i. e. referring back to the initial qualitative analysis). This enables the use of simulation as a means for a qualitative data exploration that reveals how actors make sense of the phenomenology of a situation to finally enable growing criminal culture in the simulation lab.
This is a standard tool and others (e. g. ATLAS. ti or NVivo) would have been equally valuable. Next, the interface between interpretative research and development of agent rules in formal modelling draws on the tools that have been developed in the OCOPOMO project, more specifically CCD (Scherer et al. , ) and DRAMS  (Lotzmann & Meyer ) , which enable to preserve traceability of agent rules to the empirical evidence base  (Lotzmann & Wimmer ). These tools are part of the OCOPOMO toolbox developed in previous research to achieve empirically founded simulation results. Here, ) for the conceptual model and NetLogo for implementing the simulation model, at the price of not having tool-support for semi-automated model-to-code transformation and for generating and visualizing traces. The important criteria for the conceptual modelling is that the (graphical) language used needs to be comprehensible to the stakeholders (i.
Simulation model implementation. If the conceptual modelling approach and language provide capabilities of model-driven architecture as in this example, then the implementation starts with a transformation step from the conceptual model to program code. With the OCOPOMO tool-box used in our research (as mentioned in Section. ), this step is performed by the CCD DRAMS tool for which the CCD provides an interface that supports a semi-automatic transformation of conceptual model constructs into declarative code for the distributed rule engine DRAMS and Java code for the simulation framework RepastJ. (North et al. ). Since DRAMS is implemented in Java, it entails the premises for close integration with Java-based simulation frameworks to extend their functionality.
The main objective of using these tools rather than standard tools (e. g. Python, Matlab) or typical simulation so ware (e. g. NetLogo, Mason) can be seen in the fact that these tools enable using simulation as a means for exploration of qualitative textual data by providing traceability information, an untypical application of social simulation. This is in particular the case since the structure of DRAMS code follows a similar logical approach to the action diagram of the CCD. Conditions in the CCD become facts in DRAMS, and actions become rules. This makes it possible that the formal code can precisely reproduce the conceptual model. Hence, the code of a simulation model with DRAMS as technological basis consists mainly of declarative rules describing the agent behaviour. From a more technical perspective, these rules are evaluated and processed by a rule engine, according to Lotzmann & Wimmer ( ) a so ware system that basically consists of: • Fact bases storing information about the state of the world in the form of facts.