dataesr/scientific-paragraphs-categorization huggingface dataset:
e. , for volumes < 5 × 10 5 m 3 ) the initial volume V has a more prominent role. This is not rendered in empirical estimations of travel distances, for which the dependence of travel distance to volume is under-estimated, all the more so as small volumes are considered. The milestone of our work is the construction of a simulation database, where various landslide volumes, collapse geometries and mobilities are tested. The definition of the initial unstable masses can be time consuming, especially when little information is available to constrain collapse geometries. This aspect may be the main practical difficulty to tackle in the perspective of using our methodology for operational hazard assessment, especially in a regulatory framework. Indeed, though the statistical analysis of results must be interpreted with caution, its implementation can be automated to a large degree.
This could be done by systematic back-analysis of a landslide database, and/or by adapting the definition of landslide mobility indicators, such as µ e f f , to take into account the topography more precisely. However, we may expect that significant uncertainties will remain, as a result of the partial knowledge we have in practice of the process at stake during the landslide propagation. Thus, expert judgments are valuable to assess the representativeness of results. The selection, evaluation and aggregation of such judgments, e. g. ,  [55]  could also help constrain the estimation of runout. To conclude, let's note that the information in our simulation databases are greatly simplified for the purpose of this study, as we focused only on the estimation of travel distances. However, we could also extract thicknesses and dynamic pressure maps for various volumes as done for instance in tsunami hazard assessment  [56].
Acknowledgments: Numerical computations were performed on the S-CAPAD platform, IPGP, France. This is IPGP contribution 4168. We thank the staff of  OVSM-IPGP, BRGM Guadeloupe and BRGM Martinique  for their contribution to the work on the Prêcheur river and the staff of the  OVS (IPGP)  for insightful discussions. DEAL  Martinique  funded the LIDAR acquisition of the Prêcheur topography in August 2018. The  Joint Technical Committee on Natural Slopes and Landslides (JTC1) of the Federation of International Geo-engineering Societies (FedIGS)  provided the data for the Frank Slide and the  Fei Tsui debris slide. We thank  Bastien Colas  for his help recovering the landslide database from [3], as well as  Frank Ou  and two anonymous reviewers for their comments and suggestions.
µFigure A1. A1 Figure A1. Residuals VS predicted values for the different power laws deduced from empirical databases. The axis scale is logarithmic. (a) µ H = µ 1 H (V), with DB1. (b) µ H = µ 2 H (V), with DB2. (c) µ H = µ 2e f f (V), with DB1.
The corresponding data were obtained with a 160 GeV µ + beam impinging on a  6 LiD target shown vs. z in bins of x and virtual photon energy fraction y, staggered by a constant α. The bands correspond to the total systematic uncertainty for the range 0. 30< y <0. 50. for the contamination by the decay of diffractively produced vector mesons. As an illustration, K + multiplicities are shown in Fig. 1. Preliminary results have been obtained for K ± on a proton target  [5]. The extraction of the FFs is best performed by QCD fits taking into account a large number of hadron production datasets. For example, DEHSS  [6, 7]  consider e + e -and pp data in addition to SIDIS. SIDIS, in particular from COMPASS and HERMES  [8] , plays there a crucial role in the flavour and charge separation  [7]. In  [2, 3, 5] , we compare our results with those from other DIS experiments, viz.
HERMES  [8] , EMC  [9]  and JLab  [10]. While reasonable agreement is obtained with the latter two, discrepancies are observed with respect to HERMES, see Fig. 2  as an example. The comparison is done in terms of multiplicities integrated over the measured z range, M. The kinematics are different for the two experiments, with lower centre of mass energy for HERMES. But this alone cannot easily account for the discrepancies  [11] , particularly so for the M observable selected supra to evidence the problem, since it is little sensitive to the Q 2 scale. Several approaches have been pursued to handle the discrepancies. In DEHSS, they are absorbed in uncertainties arising in part from the normalisations of the datasets and otherwise, from the input PDFs. This latter observation underlines the sensitivity of the analysis of SIDIS data to the PDFs.
Conclusions and outlook COMPASS has collected SIDIS data on a liquid hydrogen target in 2016 and 2017. Multiplicities extracted from these data will provide interesting information on the FFs, complementary to that obtained on an isoscalar target and published in  [2, 3]. An improved treatment of radiative corrections, based on the event generator DJANGOH  [19] , is expected to help reduced systematic uncertainties. Our results on the charge ratio of single hadron multiplicities, R h = M h -/M h + , show that the applicability of the pQCD formalism to SIDIS becomes questionable at high z and low values of the virtual photon energy, ν. The effect is all the more pronounced as the mass of the observed hadron is larger. In COMPASS, the problematic domain is restricted to a corner region of phase space.
canadensis cf. 'sibiricus' (Fig. 4A ). Taking into account the individual age and the robustness of the pedicles of the deer from Saint-Hippolyte, one can assume that its antlers attained the stage of full development but not reached the potential maximum size according to the available data on the ontogenetic development of antlers in modern red deer and wapiti  (Sokolov, 1959; Danilkin, 1999; Bender et al. , 2003). The antlers maintain the typical for wapiti bauplan with six tines: two proximal tines (brow and bez tines), a middle tine (trez tine), and three crown tines  (Figs. 5, 6). The distal part of the third crown tine is not preserved. The antler measurements are generally similar to measurements of Asian fossil wapiti (Table  2 ). The total length of the left antler (measured from the antler base to the tip of the second crown tine) amounts to 114 cm.
Acknowledgements I am very thankful to  Michael Lebras  and  Charles Lemarchand  ( Museum of Natural History Henri-Lecoq, Clermont-Ferrand ) for the granted access to the fossil specimen that is under their care and for the kind assistance during my work. I thank  Prof. Wei Dong  and an anonymous reviewer for their comments and suggestions that improved the manuscript. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
A two-part inter-comparison campaign was conducted at L'Observatoire de Haute Provence (OHP) for the validation of lidar ozone and temperature profiles using the mobile NASA Stratospheric Ozone Lidar (NASA STROZ), satellite overpasses from the Microwave Limb Sounder (MLS), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), meteorological radiosondes launched from Nîmes, and locally launched ozonesondes. All the data were submitted and compared "blind", before the group could see results from the other instruments. There was good agreement between all ozone measurements between 20 and 40 km with differences of generally less than 5% throughout this region. Below 20 km SABER and MLS measured significantly more ozone than the lidars or ozone sondes. Temperatures for all lidars were in good agreement between 30 and 60 km with differences on the order of ±1 to 3 K.
8 ). To plot the scatter between datasets we further integrated the ozone profiles to 2 km resolution to reduce the high frequency components. The three panels show generally good tracking of ozone measured by each of the different instruments against ozone measured by the LiO 3 S, over a substantial range of ozone concentration values. Some of the systematic differences appearing in Fig. 4  can further examined in the scatter plots. One prominent example is the sharp onset of a high ozone concentration bias in SABER data below 20 km with respect to the other instruments. Looking at the left panel of Fig. 8  which represents the ozone concentration in the UTLS (0 to 20 km) we can see that the SABER (magenta) bias occurs most strongly at the lowest ozone concentrations. SABER profiles appear to have a lower ozone concentration limit of 2 to 3 * 10 12 cm -3 and cannot match other instruments measuring below 2 * 10 12 cm -3.
We can see five tight clusters of data points which correspond to data points every 2 km. It is important to note that the real differences in the ozone concentration at these altitudes is low, so we have a very low variance associated with each cluster of points. The right hand panel of Fig. 8  shows the tracking of ozone concentrations from 30 to 50 km and much like the central panel can be characterised by low variability and low variance. It is important to note that neither MLS nor SABER exhibit strong biases at these altitudes. Also, note that the comparison between the ECC and LiO 3 T (black) is only present in the left hand panel as the upper limit of the tropospheric lidar is around 12 to 15 km. A complementary method for tracking the 'goodness' of the match between the various LAVANDE instruments is presented in Fig.
We can see that LTA (green) has a clear aerosol-induced cold bias in the lower half of the panel as it is systematically colder than every other measurement. We can also see that most data points for the other instruments are below the black reference line indicating that in this altitude range NASA-STROZ reported reliably colder temperatures. The central panel of Fig. 16  represents measurements from 35 to 60 km and exhibits tight correlation between all measurements except MLS. As was noted in Fig. 15 , MLS (magenta) has an oscillation in the sign of the temperature bias with respect to the other measurements which is seen here as increased scatter. We can also see the cold bias of NCEP (cyan) in the upper stratosphere. The right panel of Fig. 16  represents measurements from 60 to 80 km and includes only NASA-STROZ (refernce), LTA (green), MLS (magenta), and SABER (blue).
Although this may improve with further corrections of the ECC in the stratosphere, it is related to the increasing uncertainty of the LiO 3 T near its upper measurement range. Improvement of the lidar data processing and removal of this potential bias will be investigated in future work involving Optimal Estimation Techniques  (Farhani et al. , 2019). Future tropospheric ozone lidar campaigns for NDACC lidars would be required to assess the new technique and fully characterise any residual biases. MLS and SABER ozone profiles agree with the profiles produced by lidars and ECCs from about 20 km to above 40 km. Below 20 km, both sets of satellite profiles deviate significantly from the lidars and the ECCs. Above 40 km, ozone measurement uncertainties become large for the lidars, and differences increase while their significance goes down.
For SABER, sampling uncertainty is substantially larger than single ozone profile uncertainty at all altitudes above 30 km. Above 35 km, MLS and SABER sampling uncertainty was less relevant, because lidar ozone uncertainties become larger. Agreement for temperature was within ±5 K for all instruments between approximately 25 and 80 km. Below 30 km, the LTA operating at 532 nm has a well-known aerosol-induced cold bias relative to the other instruments. This bias will be corrected in the future with the installation of a rotational Raman channel for lower atmospheric temperatures. The LiO 3 S reports significantly higher temperatures below 23 km, which will be corrected in future data releases. NASA-STROZ has an apparent warm bias above 70 km, likely due to a priori assumptions or background estimations made in the profile retrieval.
Acknowledgements. This work is supported by  Institut National des Sciences de l'Univers/Centre National de la Recherche Scientifique  ( INSU/CNRS ),  Université de Versailles Saint-Quentin-en-Yvelines (UVSQ) ,  Centre National d'Études Spatiales (CNES) , the  NASA   Upper Atmospheric Research Program , and  ARISE2. The authors would particularly like to thank the technicians at  La Station Géophysique Gérard Mégie  at  OHP , who are so important for running the long-term measurement program.
Data availability. The data that support the findings of this study are openly available in the [1] The data used in this publication were obtained from LATMOS as part of the Network for the Detection of Atmospheric Composition Change (NDACC) and are publicly available ftp://ftp. cpc. ncep. noaa. gov/ndacc/station/ohp/, last access: 17 June 2018 [2] local radiosondings from Nîmes http://weather. uwyo. edu/ upperair/sounding. html, last access: 10 June 2018 [3] NCEP model profiles ftp://ftp. cpc. ncep. noaa. gov/ndacc/ncep/temp/, last access: 1 June 2018 [4] MLS temperature and ozone profiles https://disc. gsfc. nasa. gov/datasets?keywords=MLS, last access: 17 June 2018 and [5] SABER.
FUTUREVOLC project overview The FUTUREVOLC project grew from the need for a more holistic approach to volcanic hazard monitoring, assessment and eruption response for volcanoes in Iceland following the eruptions of Eyjafjallajökull in 2010 and Grímsvötn in 2011. The project was funded by the FP7 Environment Programme of the European Commission and ran from October 2012 to March 2016, with 26 project partners from academia, civil protection and industry groups. The project was led by the University of Iceland together with IMO and it combined European expertise across the full spectrum of volcanic processes, monitoring, modelling and civil protection response. The main objectives of FUTUREVOLC were to (i) establish an integrated volcanological monitoring system for Icelandic volcanoes through European collaboration; (ii) develop new methods to evaluate volcanic crises; (iii) increase scientific understanding of magmatic processes, and (iv) improve delivery of relevant information to civil protection and other authorities.
The exercise methodology Two types of collaboration exercises were conducted within FUTUREVOLC: (1) a communication exercise in 2014 and (2) an end-to-end exercise in 2016. The specific objectives for both exercises are described below. In both cases all project participants (either science/data providers or users) were included and they were required to act and respond as if the volcanic event was real. The second exercise also included key stakeholders such as the London VAAC, the media and international civil protection interests. The planning and execution of these exercises drew heavily on the institutional experience of IMO, NCIP and the UK Met Office gained from the VOLCICE and other thematic exercises.
The exercise was led and coordinated by IMO and was run over 1 day, timed to coincide with a planned VOLCICE exercise. This brought more realism to the situation and allowed the end-to-end processes at IMO to be tested. The exercise scenario involved a large (20 km column height) but short-lived (4. 5 h) eruption at Hekla volcano in south Iceland. A post-exercise questionnaire was sent out to all participants to enable the exercise to be evaluated. The questions included if and how partners had received the notifications, what additional information they would have liked (if any), how they responded, who they communicated with and how, how they reacted in real-time to notifications from IMO when activity was changing and any lessons that had been learnt. Based on the findings, five key areas for improvement were identified -notification, response, communication, data sharing and data discussion -and an action plan was formulated to address these.
2015) , which required a real response from the project and operational partners  (Barsotti et al. 2019) , it was decided that this exercise needed to test the project's response to a large ash-rich eruption for which specific tools were developed during the project (e. g. Dürig et al. 2018; Woodhouse et al. 2016). Specific objectives identified for the 2016 exercise were to test: (1) the notification system and internal communication (including the response level/preparedness of each partner); (2) data sharing through the new FUTUREVOLC data portal and associated scientific exchanges between the volcano observatory and academia; (3) the field activity coordination within Iceland for the scientific community; (4) the dissemination of timely information to end-users including civil protection and the VAAC.
2008; Thordarson and Larsen 2007). Katla is one of the highest risk volcanoes in Iceland due to the relatively high number of people (locals and tourists) potentially exposed to volcanic hazards in the area and the fact that access to the region is limited to the Iceland ring road  (Gudmundsson et al. 2008). A team of Icelandic and international scientists was tasked with defining a realistic scenario and providing a consistent multi-disciplinary dataset that would be streamed in (near) real-time during the exercise. The timeline of the main geophysical events specified by this team to characterize the volcanic unrest at Katla is summarised in Fig. 4. Full details on how the exercise was designed and how the volcanological scenario evolved through the 3 days are provided in the additional file 1.
During the 3 days the aviation sector was kept informed through the standard notification and alerting procedures, which included phone calls from IMO regarding changes in the aviation color code. This information meant that the London VAAC was able to produce timely Volcanic Ash Advisories (VAA) for the appropriate parts of exercise. Two scientific advisory board (SAB) meetings (including representatives from IMO, NCIP and UI) were held at IMO on the first 2 days to discuss the observational data and assess the on-going event. To ensure that there was no confusion with a real eruption, caution was taken during the whole exercise and all documents and data released were tagged with a message stating that they were related to a FUTURE-VOLC exercise. Examples of the types of data produced during the exercise by the players as a result of analysis and processing are given in Fig.
Data sharing During the exercise, discussions on instrumentation and data took place successfully between individuals and their existing contacts in Iceland or abroad through various communication channels such as personal emails, videoconference meetings, phone calls and blog posts. Three main web-based systems were used during the exercise: the project management software, a blog and the FUTUREVOLC data portal. FUTUREVOLC's web-based project management software Basecamp (https://basecamp. com/) was designed to facilitate daily routine management of the project, work package discussions, general announcements, and also allow document and report sharing. It allows the user to send communications to the entire project community or to subgroups related to specific work packages, with emails sent each time a new message is posted.
Used regularly on Fig. 4  Overview of the event evolution during the exercise. Most FUTUREVOLC partners participated during normal business hours only (08:00-17:00 UTC). The dashed area corresponds to the working hours during which the FUTUREVOLC community was asked to respond to the exercise. The coloured arrows provide information on the nature of the hazardous events: dark blue is used for magmatic processes, light blue is for hazardous phenomena involving water, red is for hazardous phenomena impacting the atmosphere, e. g. explosions, and green indicates surface processes such as rock-fall a weekly to monthly basis by the project members, people were familiar enough to launch discussions and make sure the information/data were spread to the whole or any subgroups of the project consortium.
The heavy usage of such a web tool was however unexpected and created an unnecessary load of emails. Conversely, the official blog website which was created during the project to promote data sharing and scientific discussions within the consortium was underutilised, mostly due to difficulties with tracking new and specific posts. The FUTUREVOLC data hub (http://icelandicvolcanoes. is/), a data sharing platform that was one of the main objectives of the project, was tested for the first time during the exercise. This hub was intended to be the place where all the IMO monitoring data would have been hosted in order to be shared with the wider community. Project members were also authorized to upload data. Different kinds of data (from raw to processed data) could be downloaded by any users registered beforehand.
This data hub was least used reflecting that this channel did not fulfil the needs and expectations of users for sharing their data through the community in times of crises and that there were some technical problems. With these three data sharing systems, in addition to IMO's official email dissemination list, the information flow rapidly became confusing and overwhelming with information distributed in a poorly organised manner. The data sharing in almost real-time by a variety of partners is a very positive result, but this experience reinforced the importance of metadata covering time/date/ validity to facilitate urgent searches.
2008). The contours show the tephra loading in kg/m 2 at the end of the eruption. c Students at the University of Iceland testing new ASH-SIZER instruments  (Marchetti et al. 2014)  in Reykjavik during the exercise. The instruments were streamed in real-time to both UI and IMO. d Estimate of the mass eruption rate (MER) made using the PlumeRise model  (Woodhouse et al. 2016 ). e Range of MER estimates from the REFIR integrated system  (Dürig et al. 2018)  in which Iceland can be reached by air from Europe makes it a particularly attractive destination for researchers during eruptions, adding to the number of people who may wish to go into the field. Existing procedures for managing these individuals mean that as soon as the volcanic area is closed, each foreign scientist/institution that wants to take part in data collection or volcano monitoring should follow a process involving filing an application with NCIP and passing through check-points on route to the field.
Dissemination of information to end-users Any volcanic unrest in Iceland is likely to trigger international interest. To ensure that authoritative information is being shared, IMO openly provides as much information and data as possible via its website and existing dissemination routes. The three-day exercise was the first real test of the newly implemented Volcano Observatory Notice for Aviation (VONA) reporting system at IMO. The VONA report follows a standard template provided by the International Civil Aviation Organization (ICAO 2014;  Lechner et al. 2009)  and is designed to be issued whenever there is an update of the aviation color code for the target volcano. During the exercise the VONA was distributed by email and contained information about the eruption status and changes in activity.
The SAB report is designed to be different to the VONA as it aims to transmit a joint multi-disciplinary interpretation of the observation datasets and provide possible eruption scenarios as agreed by the three national institutions. This report is then shared externally. The lack of this report created confusion between partners who expected it to be released. This demonstrates how important it is that all established procedures are carefully checked and followed during any type of training or exercise. The FUTUREVOLC exercise gave the London VAAC an opportunity to test its procedures in the most realistic situation possible outside of a real event, with the changing nature of the scenario providing a realistic context. Communication between IMO and the London VAAC was very good with regular telephone contact and the VAAC was first to know of any changes in activity or colour code.