dataesr/scientific-paragraphs-categorization huggingface dataset:
Most of the participants digitized the glaciers in this test region (O ¨tztal Alps) three times. This allows us to also determine the analysts' internal variability in interpretation for the same glaciers. The outline variability in the second and third digitization when comparing all analysts' results has the same characteristics as for the first digitization shown in Figure  6 , so we do not show again the related cross-analyst comparison. Instead, we show in Figure  7  for three analysts and four glaciers (Fig. 6a-d ) overlays of the multiple digitizations. These overlays reveal that the variability of the digitizing by the same analyst is similar to the multi-analyst variability. Considering the high variability seen in the interpretation of the high-resolution datasets, we decided to also derive the reference size for three glaciers from Ikonos (indicated in Fig.
The first digitization on the TM scene had STD of 2. 7-14. 6%, with a mean value of 3. 5%. The second and third digitizations had a very similar variability and mean. The digitization of all ten glaciers took 10-50 min. The mean difference of the automatically derived outlines and the reference value (from the manual digitizations) is only -1. 3% (range 0. 2 to -5. 7%). However, this value is biased by the good agreement with the largest glacier (No. 10 in Table  2 ). When that glacier is excluded, the mean difference is -3. 1%, very similar to the STD of the manual digitizations. Compared with the reference dataset from Ikonos (Fig. 8 ), the TM-derived glacier outlines in the O ¨tztal test region are 4-5% smaller. However, the STD of the multiple digitization of this reference dataset is of the same order of magnitude (up to 3%) so that differences in the interpretation and in the mapping of mixed pixels have about the same effects.
DISCUSSION The results presented above confirm previous accuracy assessments (e. g. Paul and Ka ¨a ¨b, 2005; Bolch and Kamp, 2006; Andreassen and others, 2008; Paul and others, 2011)  that reported relative area differences of the automatically derived outlines from manually digitized outlines on higherresolution datasets between 2% and 5%. These values also apply to the glaciers investigated here with sizes of a few km 2. The relative area differences tend to be larger for even smaller glaciers and smaller for larger glaciers  (Paul and others, 2003) , at least when they are mostly debris-free. For debris-covered glaciers the accuracy is more a function of the visibility of the debris cover rather than of glacier size. The problems of interpreting debris cover on glaciers have also been reported previously (e.
For example, $2 s per glacier are required for a TM scene with, for example, 600 glaciers and 15-20 min processing time (including threshold selection by visual comparison of the derived outlines in shadow regions). Manual digitization takes on average 3 min per glacier using TM and 7-10 min per glacier using the higher-resolution datasets, which is about 100-300 times slower. Of course, the automatically derived outlines need to be edited and this extra work is already included in the full manual digitization. However, depending on the region, only a small percentage of glaciers might require editing, so automated mapping will still be much faster in these regions. In a quantitative sense, automated mapping is at least as accurate as manual digitization, as the differences from a reference value are very similar to the precision of the manual digitizations (as expressed by their standard deviations).
However, glacier area is systematically a few per cent smaller in most cases, hinting at mixed pixels along the glacier perimeter that are omitted in the automated mapping but are considered during manual digitization. Of course, the reference value can also be too large compared to reality, but the comparison with the validation dataset from Ikonos also reveals slightly smaller areas with TM. We thus recommend selecting a threshold for the band ratio as low as possible (i. e. before the number of misclassified individual pixels increases) for the automated techniques to properly include most of the often slightly dirty glacier ice around the perimeter of a glacier, and also carefully checking the boundary of seemingly clean glaciers. For an improved interpretation of debris-covered glacier parts (beyond what can be achieved from the original image), we recommend checking with potentially available high-resolution remote-sensing data as available in Google Earth TM or similar tools providing access to these data.
g. debris cover, shadow). It is likely not feasible to perform a multiple digitization experiment as illustrated here for each glacier change study using manually or automatically derived glacier outlines from remote-sensing data. However, given the limited availability of reference datasets, the lack of contrast in natural colour images (from high-resolution sensors), and based on the results of this study, we recommend that each study on that topic should select a few (five to ten) differently sized glaciers (with and without debris cover) and digitize them three to five times. The standard deviation of such an assessment provides the analysts' internal precision that can be used as a measure of accuracy in any analysis related to glacier size, including determination of the significance of measured changes.
CONCLUSIONS We have presented a comparison of manually and automatically derived glacier outlines using high-($1 m) and medium-resolution (30 m) datasets. Results were provided by all co-authors of this study and are seen as a representative assessment of the common challenges in glacier delineation and the accuracy and precision that can be achieved. Our main conclusion is that automated mapping of clean glacier ice is at least as accurate as manual digitization, but glacier sizes tend to be a few per cent smaller than the reference datasets. Automated mapping has the clear advantages of being much faster, not generalized and generating reproducible results, i. e. the same threshold values always generate the same outlines. Manual digitization should thus focus on the correction of automatically derived outlines to cope with the typically problematic issues such as debris cover or ice in shadow.
Electron microscopy Nodules were harvested 4 weeks following inoculation, fixed with a solution of 2. 5% glutaraldehyde in 0. 1 M potassium phosphate (pH 7. 2) under vacuum, and post-fixed with a 2% OsO4 aqueous solution. The histological organization of nodules was observed on semi-thin sections (1 μm) of Epon-embedded nodules, stained by 0. 2% toluidine blue. Observations were performed using bright field microscopy with AxioPlan Imaging (Zeiss, Jena, Germany). Ultrastructure was studied on ultrathin sections (70 nm, Ultracut, Reichert, Germany) of Epon-embedded nodules stained with uranyl acetate and observed with a Hitachi HT7700 electron microscope (Hitachi, Tokyo, Japan). Measurements of IT wall thickness were performed using the ImageJ software (Perkin Elmer). Four to five measurements were made on the entire circumference of each IT measured; oblique sections in which the thickness of walls was clearly an artefact were avoided.
Acknowledgements This work was funded by the  ANR-09-BLAN-0033-01   HAPIHUB  project, including a post-doctoral grant to PL. This work is part of the  'Laboratoire d'Excellence' (LABEX)  entitled  TULIP  ( ANR-10-LABX-41 ). TEM was performed in the Electron Microscopy Applied to Biology Center at the  Université Paul Sabatier, Toulouse. Fluorescence microscopy analyses benefited from the  FR40  (now called FR AIB) microscopy/cell imaging platform equipment. The Mtnf-ya1-1 mutant.
The top-right plot shows the mMDT mass distribution obtained with the angular-ordered showers from Herwig 6. 520  [73]  and Herwig++ 2. 6. 3  [16, 74, 75]  in their default tunes. The Monte Carlo curves are obtained with a generation cut of p t > 2. 2 TeV applied to the qq → qq hard process, and the tagging analysis is then carried out on all jets with p t > 3 TeV. 19 All plots include the full leading order (LO) result obtained with the program NLOJet++  [64]. The fixed-order calculation is important in that it enables us to check the distributions for large masses, where resummation may not be appropriate. We ensure a high purity of quark-initiated jets in the fixed-order calculations by setting the incoming gluon parton distribution functions to zero. The plots in the top row figure  16  show that nearly all the Monte Carlo generators are in 19 While it is clear that having one generator cut and a higher subsequent jet selection cut is the correct thing to do, it is also computationally more expensive.
This significant difference relative to our calculations and the other generators appears to be limited to situations where the jet transverse momenta are close to the kinematic limit. We have checked that similar differences appear also for the other substructure tools considered in this paper. Following discussions with the authors of Pythia, they provided us with code for a modified version of the p t -ordered shower, which resolves an issue in which the hardness of the final-state shower could be affected by the presence (or not) of soft initial-state emissions. Results with this modified shower are shown in Fig. 16  (top-left) as a dotted curve, labelled v6. 428pre, and one observes a clear improvement in the agreement with other tools. This example illustrates the value of analytical understanding in situations such as this where Monte Carlo results from various generators differ noticeably.
Acknowledgments MD and SM would like to thank the  CERN Theory Group  for hospitality during parts of this work. SM would like to thank  Michael Spannowsky  for many useful discussions. We would all like to acknowledge useful discussions with  Matteo Cacciari ,  Steve Ellis ,  Steve Mrenna ,  Sebastian Sapeta ,  Mike Seymour ,  Torbjörn Sjöstrand ,  Peter Skands ,  Gregory Soyez ,  Jesse Thaler  and  Jon Walsh  and are grateful to an anonymous referee for insightful comments. We also thank  David Grellscheid  and  Leif Lönnblad  for assistance with ThePEG. Finally, we are grateful for support from the  French Agence Nationale de la Recherche , under grant  ANR-09-BLAN-0060 , from the  European Commission  under ITN.
Most macromolecular crystallography (MX) diffraction experiments at synchrotrons use a single-axis goniometer. This markedly contrasts with small-molecule crystallography, in which the majority of the diffraction data are collected using multi-axis goniometers. A novel miniaturized -goniometer head, the MK3, has been developed to allow macromolecular crystals to be aligned. It is available on the majority of the structural biology beamlines at the ESRF, as well as elsewhere. In addition, the Strategy for the Alignment of Crystals (STAC) software package has been developed to facilitate the use of the MK3 and other similar devices. Use of the MK3 and STAC is streamlined by their incorporation into online analysis tools such as EDNA. The current use of STAC and MK3 on the MX beamlines at the ESRF is discussed.
However, one can also envisage a miniaturized -goniometer instrument that would both reduce the size and increase the positional accuracy when compared with a full -goniometer. In Grenoble we decided to develop such an instrument. This resulted in a mini -goniometer head version 3 (MK3) that is fully compatible with the MD2 and MD2M suite of diffractometers installed on many MX beamlines  (Cipriani et al. , 2007; Brockhauser et al. , 2007). Indeed, similar miniaturized -goniometer instruments have also been developed elsewhere  (Wang et al. , 2008; Shi et al. , 2006; Rosenbaum & Westbrook, 1997; Rosenbaum et al. , 2006). Four MK3s are now permanently installed and available on the EMBL-ESRF Joint Structural Biology Group beamlines at the ESRF. In order to further facilitate their routine use, the STrategy for Aligned Crystals (STAC) software suite has been developed.
STrategy for Aligned Crystals (STAC) In order to facilitate the use of the MK3 on synchrotronbased MX beamlines, a standalone Java-based software suite, STrategy for Aligned Crystals (STAC), was developed. The program is based on object-oriented (OO) design patterns and takes advantage of the cross-platform support of the Java Virtual Machine for execution on different operating systems. The graphical user interface (GUI) elements can also be easily implemented in other Java applications or web applets, thus facilitating their integration with synchrotron data-collection programs such as automateD collectioN of datA (DNA) or Generic Data Acquisition (GDA). The software design has been guided by a few additional constraints: the ability to embed existing scientific codes and applications, flexibility for easy extension with new features or variants, parallel computational support, asynchronous user-request management and support for a variety of hardware implementations found at synchrotrons.
These are illustrated in Fig. 2. Since the implementation of these modules embeds existing scientific codes, the interface also has a declaration method to credit the original author contributions. Current implementations of the alignment module include GONSET from P. Evans (MRC-LMB, Cambridge) and the Python-based XOalign from P. LeGrand (PROXIMA 1, SOLEIL). The Strategy module is implemented using STRATEGY  (Ravelli et al. , 1997). A configuration file is used to set up the default behaviour of the application by activating and setting up the services as instances of the defined module implementations. The framework automatically manages the whole lifecycle of any service requests, including creation, maintenance (progress monitoring and error handling), control (starting and abortion) and response handling.
It supplies a thread-safe environment for asynchronous execution of processes and automatically synchronizes the output to the GUI. STAC can be run as a standalone GUI communicating with relevant beamline-control motors, as shown in Fig. 3 , or in a device-server mode. When launched without the GUI front end, the program reads the input 'from' and writes the output 'to' various xml files using the DNA data model. For proper calculations STAC must have a calibrated kappa instrument model. Hence, the GUI provides easy-to-use wizards for the rotational calibration needed for any alignment calculation and the translational calibration needed to maintain the sample in the X-ray beam and cryostream when changing the orientation on an inverse-system  (Brockhauser et al. , 2011).
STAC alignment procedures A successful alignment procedure depends on two conditions: the position of the MK3 and sample-centring motors and the initial crystal orientation. The former can be retrieved from the beamline-control software, while the latter requires a simple crystallographic characterization. Enhanced DNA (EDNA) is an online diffraction-characterization and data-collection strategy algorithm that is now widely used  (Incardona et al. , 2009). We therefore recommend that EDNA, or a similar characterization program such as RAPD, is used to determine the initial orientation of a crystal. STAC can also read all of the commonly used crystallographic orientationmatrix file formats, including those from XDS  (Kabsch, 2010)  and MOSFLM  (Leslie & Powell, 2007). The relevant information can then be retrieved by STAC for the calculation of the alignment protocols in the 'Input for Re-Orientation' tab (Fig.
3 ). At the ESRF, we have now implemented the use of workflows into the beamline-control software MxCuBE  (Gabadinho et al. , 2010)  to facilitate the routine use of crystalalignment procedures  (Brockhauser et al. , 2012). A number of standard options, as shown in Fig. 3 , are available and are described below. STAC also contains a simple option to tilt crystals using an on-axis viewer. Note that this is only valid if the axis is initially in the plane of the beam and spindle. This option is particularly useful for increasing the data completeness by minimizing the 'blind' zone of fortuitously aligned crystals  (Dauter, 1999). 2. 3. 1. Standard cell alignment. The standard cell-alignment protocol is the most commonly used and results in the creation of a table containing all of the relevant orientation possibilities for a reciprocal cell axis alignment.
Experimental results from crystal-alignment strategies The ultimate success of an MX experiment is dependent on the accurate measurement of a complete set of reflections. The collection of such X-ray diffraction data from aligned crystals should improve the data quality achievable and should be considered in all data-collection strategies. To provide such an option, the MK3 and its associated STAC software suite have been made available on most of the MX beamlines at the ESRF since 2008. We now routinely use the MK3 for crystal alignment and actively encourage its use. More users are making use of this device and a recent search in ISPyB  (Delageniere et al. , 2011)  revealed that alignment strategies were used in 6. 7% of all data collections on ID14-4 in 2011  (Brockhauser et al. , 2012).
‡ ‡ Resolution used for the heavy-atom search. § § The correlation coefficient calculated between the structure-factor amplitudes of the 'observed' data and the modified map using SOLOMON  (Abrahams & Leslie, 1996)  for the correct versus the incorrect hand. aligned data set (Fig. 5 ). As we could not obtain good phases with SHELXE  (Sheldrick, 2010) , we turned to SHARP (de La  Fortelle & Bricogne, 1997). The experimental phases calculated using the SAD procedure in SHARP (de La  Fortelle & Bricogne, 1997)  were further improved using the densitymodification package SOLOMON  (Abrahams & Leslie, 1996)  and resulted in clearly interpretable electron-density maps. Since the randomly oriented data set was collected after the aligned data set, we cannot rule out that radiation damage also contributed to the differences.
Discussion In this paper, we have described the alignment options currently available with an MK3 using STAC at the ESRF. A manual is available on the ESRF structural biology beamline webpages for help with such experiments. MX beamlines at other synchrotrons use a variety of different protocols. One example of this is the implementation of STAC in the RAPD data-analysis webserver on NE-CAT at the APS (J. Schuermann & F. Murphy, personal communication). At the ESRF we have recently developed a Data Analysis WorkBench (DAWB) to enable alignment strategies to be executed through MxCuBE. After the deployment of this integrated solution, a significant increase in the use of the MK3 on  ID14-4 (McCarthy et al. , 2009)  was observed, increasing from about 6. 7 to 13% in the last two months of user operation in 2011  (Brockhauser et al.
For example, this strategy was used to collect the anomalous data sets for the full-length and ÁCTD RIG-I structures used to verify the molecular-replacement solutions  (Kowalinski et al. , 2011). Other known examples of anomalous data collected from aligned crystals include the structural solution of human mitochondrial mTERF in complex with DNA (Jimenez-Menendez et al. , 2010) and the structure of an outer membrane complex of the type IV secretion system  (Chandran et al. , 2009). Several possibilities now exist for optimizing MX datacollection experiments using crystal-alignment strategies. These include the ability to minimize the total oscillation range necessary to help mitigate against radiation damage, the experimental measurement of systematic absences for spacegroup determination, the possibility of minimizing the number of overlapping reflections when a dense reciprocal-lattice plane crosses the Ewald sphere, the misalignment of nearly perfectly aligned crystals to minimize the blind zone and the ability to avoid defects or maximize the illuminated diffraction volume.
Lastly, we would like to thank  U. Kapp ,  E. Cora  and  N. Aleksandrova  for the use of their precious crystals as well as  A. Kelley  and  V. Ramakrishnan  for the 70S ribosome crystals. Part of this work was supported by the  FP6 EU BIOXHIT  grant under contract No. LHSG-CT-2003-503420. RBGR acknowledges financial support from  NWO  under project No. 016. 072. 321. AMC dedicates his contribution to the memory of  James McCarthy.
The smart cards are increasingly used in several fields with critical data that require security. We cite, as example, the medical field and payment shopping with smart card. Therefore, the hardware and software security of smart cards is one of the key elements of the security of sensitive information handled. Currently, several scientific researchers are interested in studying and enhancing the smart cards security. The study of vulnerabilities is a prerequisite for building security guarantees of this type of devices. Indeed, each vulnerability can easily lead to an attack. In this paper, we generate vulnerability test cases based on models of Europay-MasterCard and Visa (EMV) specifications. We used SysML language to model the EMV transaction through machine state diagram. Then, we generated Event-B model that we exploit it to generate vulnerability and robustness test cases.
They pay very attention to the safety of their products, especially, when attackers of security systems are constantly developing new techniques to access information. Smart cards are devices made to ship potentially critical data and are therefore intended to be inviolable. As example, a case of an attack on a smart card is to determine the value of its cryptographic key by exploiting system vulnerabilities. To avoid such attack, we should ensure that the system is not vulnerable. The verification process is done through a series of tests performed on a real smart card. Our contribution is particularly interested to this axis. In this paper, we propose a new approach for testing payment application based on EMV specifications using model based testing integrated into a SysML development process.
Tools used to apply our approach SysML (System Modeling Language) is a general-purpose modeling language for systems engineering applications. It reuses a subset of UML2. 0 and defines additional extensions by using UML's profile mechanism  [7]. Rodin is an open source platform and an Eclipse-based IDE for Event-B which provides effective support for refinement and mathematical proof. It contributes to the Eclipse framework and is further extendable with plugins like UML-B. UML-B  [3]  is a graphical formal modeling notation which relies on Event-B for its semantics. It is a plug-in for RODIN toolkits and implemented by the Eclipse Modeling Framework (EMF)  [5]. UML-B has its own meta-model and provides tool support, including drawing tools based on UML and a translator to generate Event-B models  [6].
Result and our new approach As part of our research, we are interested in security and vulnerability tests which aim to ensure that the behavior rejected by the model is also rejected by its implementation. We started by modeling EMV transaction using SysML language. We chose SysML because it is easier to express requirements with SysML diagrams. Indeed, starting with formal models in complex task, so we used less formal models, then, we proceeded to the generation of Event-B model usable to automate tests generation. Our methodology is divided into three main steps detailed in the diagram below:.
Modeling EMV Transaction using SysML language We assume that the customization phase of the Card has already been done. In our work, we treat the use phase of the EMV card represented by EMV transaction. Based on EMV specifications  [2]  summarised in section 2. 2 of this paper, we propose our model using SysML language. Indeed, we created Machine state diagram which details the EMV transaction process from initialization to completion of the transaction (see figure  2 ). The cryptograms AAC ARQC and TC mean respectively Translation declined, online authorization requested and transaction approved.