dataesr/scientific-paragraphs-categorization huggingface dataset:
2-1. 2 mm). When comparing the clouds produced by PhotoSynth/PhotoSynth Toolkit and the ScanArm, an average deviation of 0. 62 mm has been calculated. Several experimentations have been performed, which confirmed these very good results. The highest deviations are again located at the boundaries of the headstone (green/cyan areas in Fig. 5 ), but not at the same place as in Figure  4. Consequently, both solutions provide accurate results, but with slightly different point clouds (Table  6 ). As a summary, it can be noted that for both software used for generating the point cloud, an accuracy of about 0. 7 mm has been reached. These results are satisfactory, because they prove that the millimeter accuracy required by the archeologists is respected. Table  6  shows also that in our case, Photosynth / Photosynth Toolkit provides the same accuracy as PhotoModeler Scanner.
Mesh creation Concerning the mesh process, several tools have been considered. The free software Meshlab (ISTI-CNR) is a mesh processing software that has been developed for pipelines modeling  (Pomaska, 2009). It contains a lot of tools enabling the edition, cleaning, inspection, registration of large meshes, etc. Applied on our point clouds, the results were not satisfying, probably because of the noise level of the data or of the nonhomogeneous density occurring on some parts of the headstones. This solution has been abandoned. After this, two software have been compared: Geomagic Studio (Geomagic GmbH) and 3DReshaper (Technodigit). 3D Reshaper proposes a mesh process in two steps, during which a number of parameters can be modified. Several tests must be planed in order to define the most adapted parameter values.
Texturing Texturing is the last step of the process leading to the 3D model. Here, texturing means the creation of a photorealistic model. This operation can be performed in the same software as those tested for the meshing step. 3DReshaper provides several solutions for texturing a mesh model: (a) application of photographs using homologous points in the image and in the mesh model, or (b) use of the orientation parameters of every camera, as produced by PhotoModeler. The last solution has been discarded, because the orientation parameters provided by PhotoSynth are expressed in relation to a non-specified reference. The solution (a) has been tested, but was not satisfying. In fact, it is difficult to find homologous points for every photograph covering a little part of the headstone. Even if points of interest can be found in the image, its homologous one in the point cloud does not necessary exist.
Moreover, the obtained mosaic presents radiometric differences due to slightly different exposition conditions from one image to another. Geomagic proposes a way to texture, which is based on the RGB information of the point cloud. This allows bypassing the problem of junctions produced by images matching, as well as the inaccuracies implied by the research of homologous points. Figure  9  presents the results obtained with both software. Figure  9. Textured model of a headstone obtained with the texturing tool of 3DReshaper (above) and Geomagic (below). Due to the small size of the headstone taken as example (50 cm x 1 m), one image covered the whole headstone. It was not necessary to create a mosaic of images. Therefore, the 3DReshaper model does not present radiometric problems. However, the geometric quality of the matched image is not satisfactory.
Delivery of the 3D models It makes no sense to produce high quality 3D models for archaeologists, if their use is limited to visualization. For this reason, we decided to generate a 3D PDF file for every headstone. 3D PDF File format is readable by all types of plateforms using Adobe Acrobat Reader and enables to navigate easily in a 3D model. It is not only easy to read but provides also many tools for zooming, rotating, measuring, cutting planes creations, etc (Figure  10 ). For instance, the Simlab Composer software (Simulation Lab Software) enables the automatic creation of PDF3D files from a model stored as. obj file. Using the whole processing chain explained in this paper, 13 headstones of different sizes and details have been acquired, modeled, textured and delivered to the archaeologists (see examples in Figure  11 ).
CONCLUSION Aim of this study was to determine the opportunity, with respect of the specifications of the archaeologists in charge of the project, to use low cost photogrammetric techniques for modeling headstones. For the point cloud generation, the use of PhotoSynth followed by PhotoSynth Toolkit for densification have been approved. The dense point clouds have been compared to professionnal and well-known software and showed that the final accuracy respects the requirements of the archaeologists. For meshing and texturing the models, other software have been used and evaluated (Cloud Compare, 3DReshaper, Meshlab, Geomagic, Adobe Acrobat). The final products are 3D photo-realistic models of 13 headstones. In a further study, the back of the headstones will be modeled and for those who have been found as several pieces, the anastylosis reconstruction technique is planned.
Scanner tool: Using PhotoModeler Scanner for generating point clouds is certainly automated, but it requires user training, and is fairly complex for a novice, because -and this is rather an advantage-it enables the check of several steps during the process. The main steps are (a) the automatic extraction of smartpoints; (b) image orientation; (c) scaling; (d) densification. One limitation of the orientation step was the difficulty to process the whole dataset at once, although the 2012 version has been improved regarding this constraint (85% of the images against 53% in the previous version). For ensuring the scaling, linear patterns have been arranged around the stele. The densification operation is probably the less automated processing step. It is advised to select the appropriate pairs of images.
Images of the cells are acquired at regular time intervals over several hours using microscopes equipped with CCD camera. The locations (x,y,t) of each cell on the recorded sequence of frames then need to be tracked. Manual computer-assisted tracking is the traditional method for analyzing the migratory behavior of cells. However, this processing is extremely tedious and time-consuming. Most existing tracking algorithms require experience in programming languages that are unfamiliar to most biologists. We therefore developed an automated cell tracking program, written in Java, which uses a mean-shift algorithm and ImageJ as a library. iTrack4U is a user-friendly software. Compared to manual tracking, it saves considerable amount of time to generate and analyze the variables characterizing cell migration, since they are automatically computed with iTrack4U.
In this respect, it is logical that many software packages require fluorescently labeled cells  [8]. These packages very effectively identify fluorescent cells due to a high level of contrast between the cells and the background  [8]. However, one must not forget that excitation/emission of light induces phototoxicity that may slow and/or kills cells. Cell tracking by phase-contrast is more difficult to achieve than fluorescent tracking due to the lower contrast between the background and the cells. Moreover, many of the available developed packages for edge detection cannot be readily applied in our context since cell shapes may change rapidly and move into the close vicinity of other cells, rendering edgedetection and shape-matching algorithms ineffective. Finally, specific software, such as MATLAB  [10] , is not available to most biologists, and they are not familiar with program languages such as C++.
Migration assay The cells were followed using the iTrack4U software which is provided as a supplemental file (File S2) and which is also available from https://sites. google. com/site/itrack4usoftware/ home. The nucleus of each cell was manually tracked with the Manual Tracking plugin for ImageJ developed by F. Cordelières (http://rsbweb. nih. gov/ij/plugins/track/track. html).
This work was supported by the  Ligue Nationale Contre le Cancer (Equipe labellisée) ,  Ligue comité de l'Oise, INCa  and  Labex CelTisPhyBio  ( ANR-11-LBX-0038 ). The  PICT IBiSA -Curie Institute imaging facility  was supported by  FRM. MK and SG were supported by  Ligue comité de l'Oise  and by LNCC, respectively. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
PCR Sequencing and Markers The sequence of human FXN 39-UTR was retrieved from NCBI (NM_000144 and NM_181425) and Ensembl genome browser (ENST00000377270, ENST00000498653, ENST00000396366 and ENST00000484259). Variations of the FXN locus were retrieved from the dbSNP database, build 129 (http://www. ncbi. nlm. nih. gov/SNP). In addition to short genetic variations of the 39-UTR, rs3829062, also referred to as ITR3 due to location in intron 3 of the FXN gene, was also genotyped. This SNP has been previously shown to be associated with FRDA  [5]. Genomic DNA was kindly provided by Pr Jean-Paul Bonnefont, Hopital Necker, Paris, and the Centre de Ressources Biologiques, CHR Felix Guyon, Saint-Denis, La Reunion. For genotyping, the sequences of primers used are as follows: FXN_1F, 59-CCGCAGAGCT-CACTAAAGC-39; FXN_1R, 59-ATTCATTTTCCCTCCTG-GAA-39; FXN_2F, 59-TGTCGAAAGCAACTCACACG-39; FXN_2R, 59-GAACTATGTCTAGGACCAGG-39; FXN_3F, 59-TGTCCAGGGAGACCTAGTGC-39; FXN_3R, 59-AGGTTGCTTGACAGGACCAC-39; FXN_4F, 59-ATGGTT-GATTCCCAGCATTC-39; FXN_4R, 59-CAACCTC-CACCTCTGGGTTC-39; ITR3_F, 59-AAAATGGAAG-CATTTGGTAATCA-39; ITR3_R, 59-AGTGAACTAAAATTCTTAGAGGG-39.
Computational Prediction of miRNA Targets and miRNA Expression miRNA sequences were retrieved from miRBase registry, release 13. miRNA targeting analysis on the FXN 39-UTR region from both FRDA patient and control were performed using miRDB (http://mirdb. org/miRDB/) and our in-house developed tool MiRiFix (http://mirifix. com). MiRiFix integrates predictions from Diana microT 3. 0  [18] , Target Scan 5. 1  [19] , micro-RNA. org (2008 release;  [20] ) and PicTar  [21] , as well as RegRNA  [22] , Rna22  [23] , FindTar3 (http://bio. sz. tsinghua. edu. cn/) and MiRTif, which is a support vector machine-based miRNA-target filtering-system to distinguish true predicted target sites from false ones  [24]. miRNA expression profiling data were accessed through   MirZ  [25]  and mimiRNA  [26].
Association between SNPs in the 39-UTR of Frataxin and FRDA To assess the existence of variants in the 39-UTR of the FXN gene, we sequenced 1. 5 kb of the gene 39 terminus, which encompassed the 1451 bp of its 39-UTR region, in a cohort of 57 FRDA patients and 58 controls (Figure  1 ). No mutations were found. Nineteen short genetic variations, which were already annotated in the dbSNP database were explored in our cohort in addition to rs3829062 (ITR3), a marker from the FRDA risk haplotype, already found to be associated to FRDA  [5, 7, 27]. Of those 19, 12 variations were monomorph whilst seven variations, namely rs60033969, rs10890, rs4745577, rs4744806, rs4744807, rs4744808 and rs11145043 were biallelic markers as in the HapMap CEU population panel (Figure  1 ). We calculated allelic frequencies of those polymorphic 39-UTR variations in our cohorts of FRDA patients and controls (Table  1 ).
-UTR of Frataxin as a Target of miRNA Regulation We searched for the miRNA(s) whose pattern of expression showed more consistency with the phenotype. To this end, we searched for the miRNAs that were endogenous to either cell lines used for functional assessment of the 39-UTR. Intersecting both patterns from public databases revealed miR-124 as the only common miRNA. We thus chose to assess the regulation by hsa-miR-124. Interestingly, miR-124 is also known as the most abundant miRNA in the nervous system making it worth studying in FRDA (reviewed by  [28] ). Overexpression of hsa-miR-124 in HEK-293 cells led to a reproducible and significant 32%-decrease of luciferase activity in cells transfected with plasmid FRDA-39-UTR compared to cells transfected with plasmid WT-39-UTR (Figure  4B , P-value = 0.
B. Analysis Simulations using the finite element method (FEM) are often used to explore different configurations of a system to determine the most effective ones. Different types of wave excitations in periodically poled lithium niobate are then compared for given transducer structures. In previous works  [3] ,  [4] , transducers were excited through Z faces and electromechanical coupling factors of about 1% were obtained. Simulations showed that a Y-side excitation could yield coupling coefficients in excess of 20%. Therefore, transducers excited on Y faces have been simulated to determine the optimal design (width and period). A homemade simulation software, based on finite element and boundary element methods, has been developed to study this kind of device  [9]. Fig. 2  shows the 2-D mesh of one PPT period allowing for the characterization of the transducer properties derived from the so-called harmonic admittance  [9].
OntoClean is a formal method for structuring and analyzing ontologies based on metaproperties of classes (identity, unity, rigidity and dependence)  [6]. To our knowledge, there is no effort to apply this method to the GO. Ko ¨lher et al. developed the GULO (Getting an Understanding of LOgical definitions) Java package for automatic reasoning on classes logical definitions  [7]. Its exploits the logical definitions and the explicit cross-references between ontologies to compare the relations in the ontology of interest with relations inferred from the references ontologies. This facilitates the systematic detection of omissions and incompatibilities. Shchekotykhin et al. proposed an entropybased approach for localizing faults when debugging ontologies  [8]. Yao et al. formally defined metrics of an ontology's fit with respect to published knowledge in the form of other ontologies and of scientific articles  [9].
Alterovitz et al. proposed an information theory-based approach to automatically organize the structure of GO and optimize the distribution of the information within it  [32]. Faria et al. proposed an association  rule-based algorithm for identifying implicit relationships between molecular function terms  [33]. Other works focused on the quality of terms definitions  [29]  and on the detection of semantic inconsistencies of gene annotations  [34]. Gross et al. studied  to what extent modifications of the GO and of gene annotations databases impacted the result of term enrichment analyses that describe experimental data by sets of GO terms  [35]. They demonstrated that the ''changes are unequally distributed and cluster in regions representing specific topics''. Interestingly, they also observed that these changes do not necessarily modify the result of term enrichment analyses since the terms are often semantically related.
Practical applications The main consequences of our results concern people maintaining GO annotations, as well as developpers of data analysis methods based on the GO. The regular addition of leaves or of classes close to leaves for BP and CC indicates that over time, more precise terms were being added to the GO hierarchy. Some of the former annotations that refer to the parents of these new classes could be transferred to the new classes. Because of the rule of annotations propagation to the ancestors, the former annotations would remain valid, but this would result in a gain in annotation precision. With the OnEX web application, Hartung et al. proposed a mechanism capable of semi-automatic migration of outdated annotations  [4]. Our results indicate that the addition of new low-level classes (mostly for BP and CC) has potential implications on former annotations, whereas higher level classes (mostly for MF) represent previously undescribed topics.
The latter situation is not compatible with the OnEX semi-automatic migration approach. Ideally, experts should decide whether these new high-level annotations are suitable for existing entities such as gene products. The parallel evolution of the GO and of annotations databases has consequences on the results of data analysis studies  [37]  as well as on the evaluation of GO-based data analysis methods  [38] [39] [40]. Gillis et al. reported that ''GO annotations are stable over short period of time'', but also that ''genes can alter their functional identity with 20% of gene not matching to themselves (by semantic similarity) after two years''  [25]. The direct implication is that all the results of analyses based on the GO should be re-assessed on a regular basis. By showing that complexity increased for BP and CC with the addition of leaves or of classes close to leaves and that MF complexity remained stable with uniform modifications, our study suggests that the conclusions of the previous analyses could remain valid but may actually be improved, although quantifying this assumption would be a separate work.
Similarly, the respective performances of GO-based data analysis methods should be reevaluated on a regular basis. These metrics could be integrated into at least three kinds of future applications. First, they could easily be integrated into ontology-development tools such as Protegeor OBOEdit. However, not all users may have the need to monitor such metrics. Furthermore, comparing the measures when only a few changes have been made may make it harder to identify general trends. We also computed the measures on daily snapshots of GO from July 2009 to July 2012 and observed successive increases and decreases on all values. The second option would then be to integrate our metrics on top of the ontology version control system. We have seen that computing the measures between commits is not very informative, whereas comparing their evolution between releases (i.
We decided to take a particular care about broadband velocity sensor insulation considering their sensitivity to noise induced by thermal and barometric variations (see  Zïrn and Widmer (1995) ,  Beauduin et al. (1996 ), Stutzmann et al. (2000) ). We detail in the Sect. 4 the aluminium cover that was designed for this purpose. The new instruments transmit continuous real-time seismograms using the Seedlink protocol  (Hanka et al. , 2000)  to gather and share data flows in realtime with other observatories (GéoSciencesAzur/OCA, IPGP/Goscope, DIPTERIS, SED/ETHZ. ). These signals are used at ISTerre for data quality control and seismic event detection. We have implemented software solutions such as EarthWorm  (Johnson et al. , 1995)  for automatic detection purpose, Seiscomp3 (see  Weber et al.
Measurement of pressure and thermal insulation We have tested the pressure insulation efficiency of the TANK using three different methods: (i) numerical simulation of the deformation due to a pressure load, (ii) pressure response to a step variation, (iii) natural pressure variation response. For the first method we use the software SolidWorks to study the mechanical response of the TANK to an air pressure load. During the numerical simulation (finite element method) (Fig. 4 , bottom) we simulate a +25 hPa variation of the external pressure, assuming constant internal temperature. We calculate the maximum deformation of the cover bolted due to this over-pressure and observe a maximum deformation of 0. 316 mm on the top plate of the cylinder. This deformation would induce an internal over-pressure of 0.
Noise comparison A different way to evaluate the efficiency and the benefit of the TANK is to perform noise comparisons on the sites where the shielding has been deployed. We evaluate the benefit of the TANK by comparing the data recorded before and after the installation of this barometric/thermal insulation. This comparison has been achieved for five different stations, over at least one year of data recordings. The period of observation without and with the insulation are different for each site. We present in Fig. 7  one example for site SURF that is demonstrative of all observations. The three steps of the analysis are (i) conversion from mseed+dataless in SAC format (RD-SEED software provide by IRIS), (ii) deconvolution of the instrumental response to acceleration and decimation (SAC  Goldstein et al.
Acknowledgements. We gratefully acknowledge the members of ISTerre-OSUG who activally participated to the  RISE  project:  N. Cotte ,  I. Douste-Bacqué ,  L. Jenatton ,  L. Piard ,  R. Bethoux. We also thank  S. Bonaimé  and  J. M. Saurel  for fruitfull technical discussion about broadband sensors insulation methods.
M. Langlais: Broadband seismic network improvement at ISTerre-OSUG Rhône-Alpes , the  Isère, Ain and Haute-Savoie General Councils  and the  FEDER (Fonds Européens de Développement Régional)  in the framework of the  RISE  project in the  ALCOTRA (Alpes Latines COopération TRAnsfrontalière ) program (2007)(2008)(2009)(2010)(2011)(2012)(2013). This work has also been supported by a grant from  LabEx OSUG@2020  (Investissements d'avenir  ANR10 LABX56 ). Vol. 1, p. 0236, 2006. Pedersen, H. : RESIF: a  French Integrated Antenna for the Observation of Earth Deformation , in: AGU Fall Meeting Abstracts, Vol. 1, p. 03, 2009. Péquegnat, C. , Guéguen, P. ,  Hatzfeld ,  D. , and Langlais, M. : The  French accelerometric network (RAP)  and national data centre (RAP-NDC), Seismol. Res. Lett. , 79, 79-89, 2008.
In this article, we propose a domain specific language, Gubs (Genomic Unified Behaviour Specification), dedicated to the behavioural specification of synthetic biological devices, viewed as discrete open dynamical systems. Gubs is a rule-based declarative language. In contrast to a closed system, a program is always a partial description of the behaviour of the system. The semantics of the language accounts the existence of some hidden non-specified actions that possibly alter the behaviour of the programmed devices. The compilation framework follows a scheme similar to automated theorem proving, aiming at improving synthetic biological design safety.
In this framework, the components are selected and organized automatically or semi-automatically to generate a structural description of the device at compile phase whose behaviour complies with the specified function. One such approach has been already achieved in hardware by using languages as Vhdl  [1]  or Verilog  [37]  to overcome the growing complexity of electronic circuits. However, the major difference in synthetic biology relates to the openness of biological system. Hence, we propose to define a language dedicated to synthetic biology based on a behavioural specification that handles the openness of system. More precisely, Gubs is a rule-based declarative language dedicated to the behavioural specification of discrete open dynamical systems for synthetic biology interacting with its environment.
Gubs symbolically defines the behaviours to provide a relative independence from structures by postponing the biological component selection at compile phase. Within this GUBS, a Behaviour-Based Language for Design in Synthetic Biology 3 framework, the compiler translates the behavioural specification to a structural description of a device whose behaviour carries the functional features defined by a program. The proposed compilation method is inspired by automated theorem proving. After introducing related works(Section 2) on languages dedicated to systems and synthetic biology, we introduce the main features of Gubs language (Section 3), we define the semantics of Gubs based on hybrid logic. Then, we detail the proof-based principles governing the compilation (Section 5) illustrated with a complete example (Section 6).