dataesr/scientific-paragraphs-categorization huggingface dataset:
k. a. BRM)  [91]. In addition, cell lines carrying ARID1A-and PBRM1 mutants are sensitive to EZH2 inhibition  [92] [93] [94]. With this information, we aimed to identify more gene candidates as markers for sensitivity to PRC2 inhibition. In so doing, we generated a Python application to challenge a hypothesis of dependence between the growth inhibition upon knockout of EZH2, SUZ12, or EED, and the presence of each documented mutation (https://github. com/ genesolution/PRC2_data, uploaded on 25 March 2021). For the test hypothesis, a cell line was considered to be "sensitive" if it had a score <-0. 5 (inhibition of the majority of cells). This value was provided to us as the universal effect limit for the DepMap tables due to the normalization that had been previously done by the DepMap table authors.
Conclusions In summary, we performed bioinformatic analysis of genomic and transcriptomic data across multiple tumor types to identify clinically significant trends related to PRC2. With this analysis, we identified new tumors that could benefit from targeted PRC2 treatment. Moreover, DepMap interactive genes could present new potential markers of tumors that are more sensitive to PRC2 inhibitors. The next step would be to elucidate the functional role of identified genes in PRC2 oncogenic function and sensitivity to inhibitors directly. Furthermore, studies are needed to assess the cellular and molecular effects of PRC2 inhibitors. For instance, while PRC2 is frequently overexpressed in breast cancer, single-cell analysis suggests that drug-resistant cells may downregulate H3K27me3 at many loci  [126].
Funding: This study was supported by the  Russian Science Foundation (RSF)   20-74-10099  to  Maksim Erokhin  (DepMap data analysis); by grants from the  European Research Council  (Advanced Grant  3DEpi , under grant agreement No  788972 ), the  European Union 's  Horizon 2020 research and innovation programme (ChromDesign , under the  Martie Sklodowska-Curie  grant agreement No  813327 ), the  Agence Nationale de la Recherche  ( ANR-18-CE15-0010 PLASMADIFF3D ), the  Fondation pour la Recherche Médicale  ( DEI20151234396 ), the  MSDAVENIR  foundation (Project  GENE-IGH ), the  INSERM  and the  French National Cancer Institute  ( INCa   PLBIO18-362-PIT-MM ) to  Giacomo Cavalli ; by the  French National Cancer Institute  ( INCa   PLBIO18-362-PIT-MM  and  PLBIO19-098 INCA_13832  FATidique), the  Agence Nationale de la Recherche  ( ANR-18-CE15-0010 PLASMADIFF3D  and  TIE-Skip ;  2017-CE15-0024-01 ), the  ITMO PCSI 2020 SMOOTH-MM, Labex EpiGenMed  and  Institut Universitaire de France  to  Jerome Moreaux ; by the  2018-2.
We present the content and scripting of an active tectonic lab session conceived for third-year undergraduate students studying Earth sciences at Observatoire des Sciences de l'Univers in Lyon. This session is based on a research project conducted on the submarine Roseau active fault in the Lesser Antilles. The fault morphology is particularly interesting to map as this structure in the deep ocean is preserved from weathering. Thus, high-resolution models computed from remotely operated vehicle (ROV) videos provide exceptional educational material to link fault morphology and coseismic displacement. This class includes mapping exercises on geographical information systems and virtual fieldwork to provide basic understanding of active tectonics and active fault morphology in particular. The work has been conducted either in a full remote configuration via 3D online models or in virtual reality (VR) in a dedicated room using the Minerve software.
univ-lyon1. fr/, last access: 3 December 2021). Simultaneously, a team of researchers involved in projects aiming at understanding the active tectonics of the French Lesser Antilles  (Escartín et al. , 2016; Leclerc et al. , 2016; Istenič et al. , 2020)  developed an interactive free and open-source software (Minerve; see  Billant et al. , 2019)  to collaborate on very-high-resolution (∼ 1 m to 10 cm) DEMs and DOMs (digital elevation models and digital outcrop models, respectively) of the submarine active normal Roseau fault scarp that was reactivated during the 2004 Les Saintes earthquake (M w 6. 3)  (Escartín et al. , 2016). These submarine studies provided a unique opportunity to bring our students to the field, at 1200 m b. s. l. , through virtual reality, and we describe this experiment in this paper.
g. , Meshlab). Several of these systems also allow the user to interact with the 3D data on screens only and not in a virtual-reality (VR) environment (e. g. , MAT-LAB, QPS Fledermaus, Matisse,  Arnaubec et al. , 2021) , in addition to other limitations. Therefore, to precisely analyze and inspect structures from 3D models, in this case the fine scarp topography and texture of a fault rupture underwater, the Minerve Virtual Reality software was developed  (Billant et al. , 2019). Minerve is intended to be used as a quantifying tool and is provided as a free and open-source software (FOSS), which allows easy distribution in the teaching and research communities. In Minerve, the user can move freely in a georeferenced space at a 1 : 1 scale. The tools allow for measuring strike, dip, rake, and distances and mapping geological features that can be exported in geographical information system (GIS)-like format for further work.
Lastly, several users can meet remotely and collaborate in the same VR environment, allowing teamwork or facilitating training and teaching. The possibilities for interaction with the 3D models offered by Minerve are key skills that students in geosciences should master at the end of the third-year of undergraduate study. The Minerve software was used to perform a paleoseismological study of the Roseau fault outcrops  (Billant et al. , 2018). Although the fault was imaged in 2013, 13 years after the earthquake, the morphology and visual texture of the coseismic markers are astonishingly well preserved, since at this oceanic depth (∼ 1200 m) weathering and sedimentation rates are very low  (Escartín et al. , 2016)  and constitute textbook normal-fault outcrops. Such markers are much more ephemeral in subaerial environments.
Because of the wide variety of topics covered by the course, the course unit assessment may or may not include active tectonics each year. Because of the pandemic and resulting student difficulties during this period, we focus our efforts on the set up of virtual fieldwork. The assessment strategy remains to be properly settled (see Sect. 4). The teaching sequence, adapted for groups of up to 12 students, starts by mapping exercises and understanding the tectonic context using vector and raster images gathered on a GIS project on the free and open-source QGIS software. After identifying potential candidate faults for the 2004 Les Saintes rupture at a large scale using a 10 m resolution DEM covering the whole fault system  (Deplus and Feuillet, 2010; Leclerc et al. , 2016) , students ideally switch to VR immersion for a finer analysis using 1 m resolution DEM and the centimeter-scale resolved DOMs.
Student feedback was collected immediately after the lab session via an online inquiry, and its analysis will contribute to future improvements of both the virtual fieldwork for the students and the Minerve software itself (ergonomics, functionalities, tools). Because of the Covid-19 sanitary restrictions, we adapted the first session conducted in spring 2020 during full lockdown in France in a 100 % virtual lab session. In spring 2021, during partial lockdown, we conducted the sessions at the university with four reduced groups composed of four to six students each during short 2 h sessions, including 1 h dedicated to VR fieldwork.
Using GIS tools to analyze the tectonic context and geomorphology GISs are now used in a very wide variety of fields, including Earth sciences. This lab session is the first contact for the third-year undergraduate students with GIS software and aims to introduce basic digital mapping tools and familiarize the students with the tectonic context. The free and open-source QGIS software (QGIS Development Team, 2021) was used during our courses. In addition to standard documents extracted from the scientific bibliography (context figures extracted from  Feuillet et al. , 2002; Leclerc et al. , 2016 , and the USGS description of the 2004 Les Saintes mainshock, including the focal mechanism and intensity map; see https://earthquake. usgs. gov/ earthquakes/eventpage/usp000d8w3/executive, last access: 3 December 2021), students are provided with a zip file including a QGIS project file and associated layers (provided in the Supplement).
). Guidance on this first use of SIG software is provided via online discussions on the Discord app forum and teacher-made video tutorials in the 100 % remote strategy, while oral explanations are provided in the classroom for the two other strategies. As a second step, students work on the interpretation of the shaded and textured 10 m local DEM. They explore the DEM via the "identify features" tool to get absolute bathymetry value at each pixel and the "terrain profile" additional plugin (https://github. com/PANOimagen/profiletool, last access: 3 December 2021) that allows on-the-fly drawing of topographic profiles (see Fig. 1 ). This additional plugin is activated directly by the students via the "manage and install plugin" window as it is included in the Qgis Official Plugin Repository.
Name Type Description Seismic catalog vector, points January 2004 to December 2016 regional seismicity including the Les Saintes mainshock and aftershock sequence (0 < M w < 7. 5). Extracted from IPGP's seismological and volcanological observatories datasets, http://volobsis. ipgp. fr (last access: 3 December 2021)  (Bazin et al. , 2010)  Plate boundaries vector, lines Plate boundary locations and styles  (Bird, 2003, and   (M w 6. 3) requires a ∼ 15 km long fault segment to rupture if agreeing with standard scaling laws and that (ii) the epicentral location is often shifted from the surface fault trace due to fault dip and depth of the rupture (here 12 km), and therefore (iii) the students have to take into account a fault dip, in theory between 60-65 • for normal faults  (Anderson, 1951; Olive and Behn, 2014).
The use of a free Sketchfab account limited in features imposed a reduction in the size of the model, preventing a detailed analysis of some fine structures and forcing the students to explore a limited part of the global DEM (for instance, the model is cut in the middle of a dejection cone that is therefore difficult to identify). Scale and orientation markers were not provided at the time but could be loaded in the 3D model directly via free software like 3D Builder or Blender (see https://skfb. ly/onW7t (last access: 3 December 2021), for instance). Interactive tools were not used at that time, but some promising new functions have been developed and could be used in the future (see https://labs. sketchfab. com/experiments/measurements/ #!/models/3070ae00d83844e680ead63292140e43 (last access: 3 December 2021) for distance measurements on a 3D model or associated V3Geo platform tools  (Buckley et al.
We initially wanted the students to make an observation diagram of the outcrop directly in their notebook that could eventually be assessed, but this task requires time to go in and out the VR environment. We also wanted the students to load the measurements made in VR into their QGIS project. This last step could be easily done in a standard 4 h lab session and would probably help the students synthesize 3D and 2D data together by giving them the skills to properly map their own field measurements.
Perspectives In general, the together in the field or multi-user option appears to be the more promising option and should be developed in the coming years. However, both the 100 % virtual and alone in the field strategies could be improved and useful in the future depending on the intended use. If homework is expected, then it appears more appropriate to make the students work on a 3D model hosted directly on the web if interactive tools are available rather than asking them to in-stall the Minerve software and providing them with a VR apparatus, especially since the software requires an expensive computer with a powerful graphics card. To evaluate one student's technical skills at the end of the class, the alone in the field configuration could be adapted so that no interaction could easily be done with classmates, while the teacher can follow the behavior of the student in the field.
Finally, the sound environment could be improved using spatialization technologies that provide perception of the sound depending on the distance. These techniques are often used in video games and VR and could be implemented in Minerve (e. g. ,  Tsingos et al. , 2004 Tsingos et al. , , 2009)). These first lab sessions using VR and the Minerve software have been conducted during time-limited sessions that required being nearly continuously immersed in the virtual environment. This continuous immersion has two severe drawbacks: it favors physical discomfort and prevent students to taking notes or reporting observations in their notebooks, the latter being often considered as a technical skill by itself  (Lonergan and Andresen, 1988). Software development will allow for taking snapshots and notes; in order to limit motion sickness, better management of the teleportation could be implemented in addition to other techniques aimed at limiting this discomfort, such as the reduction of the field of view during displacement (e.
We take advantage of the very detailed bathymetric study conducted by the ODEMAR and SUBSAINTES French cruises in the Lesser Antilles over the Les Saintes plateau, and the Roseau fault in particular, and of the imagery and high-resolution bathymetry acquired there. This submarine fault produced the 2004 Les Saintes M w 6. 3 normal fault earthquake and is exceptionally well preserved in the bathymetry. In a first step, the students explore the seismotectonic context of the Les Saintes earthquake using georeferenced data gathered on a QGIS project and results coming from scientific publications. In doing so, they acquire basic skills in GIS mapping that are often considered as secondary during classical fieldwork but are widely used in geosciences. Following this, we use both the Sketchfab online utility and the Minerve open-source virtual-reality software developed by  Billant et al.
(2019)  to explore the detailed DEM and DOM of the fault scarp with the students. We chose three different configurations to conduct this virtual fieldwork that all present advantages and disadvantages that we analyze from teacher and student feedback. Based on the student and teacher feedback, we find that the Minerve virtual-reality software, when used in multi-user mode (i. e. , the students are sharing the same virtual environment together with the teachers), provide a very satisfactory framework that could still be technically improved. Students can measure strike, dip, rake, and orientation and save their observations in a file that could be imported in any GIS software afterwards. Teachers find this mode very flexible. Expected learning outcomes therefore include technical skills often acquired during classical field camps, GIS mastering, and the ability to work in group.
Interestingly, it is possible to combine various scales of observation from large landscape view to very fine observation on the outcrop and offer a good interactivity with the students. Moreover, a specialist of the outcrop or of the thematic can be virtually present providing that they are equipped with headset and controllers and have the Minerve software locally installed. In the future, students skills should be evaluated in a systematic way before and after the VR lab session to measure its teaching efficiency. The students surveyed were in general enthusiastic to experiment with virtual fieldwork, and it is therefore a proper tool to increase their empathy with the discipline  (Lonergan and Andresen, 1988) , even if physical discomfort is common. This could be reduced by shortening the duration of the sessions in immersion in the virtual environment, ensuring breaks, and adding software solutions.
Even if it is clear that a virtual observation does not replace a field observation, virtual reality could be a fantastic tool to bring students to remote or even inaccessible places such as submarine fault scarp or planetary bodies. It therefore opens new perspectives for teaching Earth sciences, and we plan to use the Minerve software in other contexts in the coming years. Code and data availability. The Minerve software is developed by Jérémy Billant under an open-source under an open-source license and is available on request. The centimetric DEM and DOM are not open-source but can be made available on request and is described in  Billant et al. (2019). Data used during the QGIS mapping exercise are available in the Supplement, including a subset of the different 3D textured models acquired along the Roseau Fault https://doi.
JB developed the Minerve software. JB, MM, and JEM designed the teaching experiment and actually taught. AM helped during the lab session and the class conception. JE and FL processed and gave access to the scientific data, provided an expert external view, and were beta testers for the Minerve software. The ICAP team took care of the technical issues and helped with the use of the virtual lab. MM and JB led the writing process of this article. All authors contributed and approved its final version. Competing interests. The contact author has declared that neither they nor their co-authors have any competing interests. Disclaimer. Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Special issue statement.
This article is part of the special issue "Virtual geoscience education resources". It is not associated with a conference. Acknowledgements. The authors would like to thank all the researchers, technicians, and crew involved in the ODEMAR and SUBSAINTES cruises, whose findings are open for educational purposes. We thank Christine Deplus and Nathalie Feuillet for sharing the large-scale 25 m DEM from Bathysaintes, and Aurélien Arnaubec, Klemen Istenic, and N. Gracias for their role in processing 3D data used here. We thank Julia Bozzinio and Loïc Dornel for their participation in the development of Minerve. We are grateful to L3 students from 2019-2020 and 2020-2021 promotions for their feedback and resilience during this very difficult period. Special thanks are due to Felix Moquet and Nora Van Reeth from the ICAP team (U.
Lyon) for their patience in explaining VR to beginners, to Antoine Triantafyllou for useful discussions and perspectives, and Amandine Minjollet for help with the figures. The thorough comments of Gaël Caravaca and an anonymous reviewer helped us in improving the manuscript. This project was partially supported by ANR Sersurf (ANR-17-687 CE31-0020). We also thank the scientists, crew, and officers of the different cruises that acquired data used here. We also thank the QGIS development team, and we use base map and data from OpenStreetMap and the OpenStreetMap Foundation. Financial support. This research has been supported by the Agence Nationale de la Recherche (grant no. ANR-17-687 CE31-0020). Review statement. This paper was edited by Marlene Villeneuve and reviewed by Gwénaël Caravaca and one anonymous referee.
The concurrent availability of Sentinel-1 (synthetic aperture radar) and Sentinel-2 (optical) data offers a great opportunity to utilize them jointly; however, optimizing their synergy has been understudied with deep learning techniques. In this work, we analyze and compare three fusion strategies (input, layer, and decision levels) to identify the best strategy that optimizes optical-radar classification performance. They are applied to a recent architecture, notably, the pixel-set encoder-temporal attention encoder (PSE-TAE) developed specifically for object-based classification of SITS and based on self-attention mechanisms. Experiments are carried out in Brittany, in the northwest of France, with Sentinel-1 and Sentinel-2 time series. Input and layer-level fusion competitively achieved the best overall F-score surpassing decision-level fusion by 2%.
The contribution of remote sensing is demonstrated in studies related to land cover mapping  [6] [7] [8] , urban studies  [9] , forest inventories [10], and burnt area mapping  [11]. They are the backbone for diverse large-scale operational services (e. g. , European Copernicus services), addressing issues concerning land, disasters, marine, and atmosphere. In agriculture, they have been used for crop classification  [12] , phenology studies  [13, 14] , yield estimation  [15, 16] , and insurance applications  [17]. The availability and access to open satellite data archives (e. g. , moderate resolution imaging spectroradiometer (MODIS), Landsat, and Sentinel) is advancing methodologies to solve environmental and societal challenges. One interesting context, especially in crop studies and land cover mapping, is the use of satellite image time series (SITS) where images of the same area are acquired at different dates.
Today, the consistent acquisitions of ESA's Sentinel-1 and Sentinel-2 images has allowed their exploitation in unison. According to  [54] , multi-modal image fusion can be grouped into pixel, feature, and decision levels. In deep learning, the pixel-and feature-level fusions have been redefined as input-level and layer-level, respectively  [55]. The input level fundamentally combines image bands from multi-source data (usually through resampling and concatenation, or image to image co-registration). This is the simplest and common form of fusion, but it might suffer some drawbacks due to the resulting high dimension of stacked data  [56]. Layer fusion requires the extraction and concatenation of high-level features allowing each modality to learn individual feature representations. At the decision level, each modality is independently processed by a network to generate class confidence scores (in the case of classification), which are combined statistically (e.
g. , averaged) to yield a final fused decision. An interested reader can also refer to  [57, 58]  for a general review of data fusion in remote sensing and its main challenges. In multi-modal (typically optical and radar) SITS, fusion has been commonly applied using traditional machine learning algorithms. Most of the studies used an early fusion strategy with a random forest classifier, where optical and radar time series are stacked together in one data cube  [7, 11, 12, 24, 29, 34, [49] [50] [51] 53, 59]. A late fusion strategy was also adopted in  [7, 56] , where class probability vectors obtained by training two independent random forest models are combined together to obtain the final prediction. The combined use of Sentinel-1 and Sentinel-2 has been shown to improve accuracies compared to a single sensor but has mainly been explored with random forests.
Crop Type Labels Farmer declarations, which form the basis of subsidy disbursement under the European Union Common Agricultural Policy, have resulted in a huge archive of publicly available crop labels (Land Parcel Identification System). In France, this information is collated under the Registre Parcellaire Graphique (RPG), a comprehensive geographical depository allowing the identification of land use on agricultural parcels. RPG is obtained from the French open data platform (www. data. gouv. fr, accessed on 16 February 2021) for the year 2019. It is published, for each France region, with a hierarchical nomenclature of more than 300 categories for the lower level and 28 for the higher level. In Finistère, 20 out of the 28 categories of agricultural land use are identified. Although subject to some issues (e.