dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments We thank the patient and her family for participating in this research. We would like to thank also both the personnel of the Department of intensive care and neonatal medicine,  CHU Fattouma Bourguiba, Monastir, Tunisia  and all members of the team of the INSERM unit UMR_S910, GMGF,  Aix Marseille University, Marseille, France  ( Karim Harhouri ,  Cathy Bartoli ,  Guy Longepied ,  Françoise Merono ). We also thank  Pr Moncef Rassas  for his helpful comments.
Acknowledgements This work has been partially supported by the  Ministry for Higher Education and Research (France) , the  National Science Foundation (USA)  DMS-, a grant from  Research to Prevent Blindness (RPB, NY, USA) , the  Chair Gutenberg  funds of the  Cercle Gutenberg (France) , the  Labex IRMIA (University of Strasbourg, France) , and  Micron Semiconductor Italia SRL , statement of work No. "Modeling of tunneling and charging dynamics" by contractors  Micron Semiconductor Italia SRL  and  Department of Mathematics of the Politecnico di Milano (Polytechnic University of Milan, Italy ).
GINsim The GINsim software supports the definition, the simulation and the analysis of regulatory graphs, based on the (multi-valued) logical formalism. GINsim is freely available from its dedicated website (http://ginsim. org), along with documentation and a model repository. For this tutorial, we use the recent release 3. 0, which is available for all platforms with version 8 of the Java Virtual Machine. To get started with GINsim, download the corresponding Java ARchive (JAR file), with dependencies included, from the download section of GINsim website (http://ginsim. org/ downloads). On your computer, double-click on the file icon to start the application or launch it with the command: java -jar GINsim-♯version. jar in a terminal. Further instructions, troubleshooting and options are documented on the website.
The graphical appearance of the nodes have been modified using the Style tab. The Edit button on the top is selected and emphasized in blue, enabling the edition of the attributes of the selected node, including its id and name, its maximal level (Max, here set to 2), and also the insertion of annotations in the form of free text (bottom right) or of links to relevant database entries (bottom middle). with the mouse on each of the editing tools displays a message explaining the function of each tool. Clicking on the E icon enables further edition of an existing node or arc upon selection, while the garbage can icon serves to delete selected arcs and nodes. Clicking once on one of the remaining icons enables the drawing of a single node or arc. Clicking twice on one of these tools locks the corresponding editing mode, enabling the drawing of several nodes or arcs without clicking repeatedly on the same tool.
TROUBLESHOOTING The online documentation includes a troubleshooting page (see http://doc. ginsim. org) providing some solutions to common problems. The graphical interface can have some refresh issues after long or complex modeling sessions. Such issues are usually resolved after saving the model and restarting the GINsim software. For other issues, we encourage users to send a message describing their problem to the GINsim forum or directly to the GINsim team (see http://ginsim. org/contact). Because some issues are difficult to reproduce, the user should provide log traces (using the GINsim/support/export log files menu option), after launching GINsim from the command line to catch additional error messages. A few hints to solve issues that may arise in the course of this tutorial are provided below.
, 2015) , in which input nodes denote external signals, which are not regulated and often maintained constant. Such Input nodes can be specified as such in GINsim to enforce the maintenance of the levels specified at initial states. As the reduction of input and output nodes or cascades have a marginal impact on the dynamics  (Abou-Jaoudé et al. , 2016) , such reductions are facilitated in GINsim. Furthermore, a novel functionality Assess Attractor Reachability in the Tool menu enables to evaluate the reachability of attractors based on stochastic simulation algorithms (for more details, see  Mendes et al. , 2014). Taking advantage of the multiple export formats supported by GINsim, it is also possible to use complementary tools, including stochastic simulation software (e. g. , MaBoSS, see  Stoll et al.
A circuit functionality context can be interpreted as the part of the state space where the circuit is functional, i. e. , generates the expected dynamical property  (Comet et al. , 2013). 5. The Compute interaction functionality option of the Tools scrolling menu allows to check if the signs of the interactions (graphically defined) comply with the regulatory rules. Inconsistencies arise when, for instance, a positive interaction has been drawn, while the regulatory rule of the target node defines an inhibitory effect or no effect at all. This is a convenient tool to check model inconsistencies. Note however that such inconsistencies do not prevent (inconsistent) model simulation or analysis. 6. GINsim allows the user to export logical regulatory graphs (or state transition graphs) toward various formats, facilitating the use of other software: • SBML-qual, the qualitative extension of the popular model exchange format  (Chaouiya et al.
ACKNOWLEDGMENTS The authors acknowledge numerous constructive comments from GINsim users over the years, in particular insightful feedback from  Laurence Calzone ,  Samuel Collombet ,  Karla Corral ,  Adrien Fauré ,  Swann Floc 'hlay,  Asmund Floback ,  Anna Niarakis ,  Elisabeth Remy ,  Otoniel Rodriguez , and  Gautier Stoll.
In this paper we investigate how the residuals in bundle adjustment can be split into a composition of simple functions. According to the chain rule, the Jacobian (linearisation) of the residual can be formed as a product of the Jacobians of the individual steps. When implemented, this enables a modularisation of the computation of the bundle adjustment residuals and Jacobians where each component has limited responsibility. This enables simple replacement of components to e. g. implement different projection or rotation models by exchanging a module. The technique has previously been used to implement bundle adjustment in the open-source package DBAT (Börlin and Grussenmeyer, 2013) based on the Photogrammetric and Computer Vision interpretations of Brown (1971) lens distortion model. In this paper, we applied the technique to investigate how affine distortions can be used to model the projection of a tilt-shift lens.
g. mm. The image coordinates are scaled from pixels to mm before the  Brown (1971)  polynomials are used to "correct" the measured image coordinates for lens distortion. The residual (thick circle) is computed as the difference between the projected ideal point and the corrected point. Figure  3 : The DBAT implementation of the Computer Vision formulation of the  Brown (1971)  lens distortion model  (Tsai, 1987; Heikkilä and Silvén, 1997; Zhang, 2000). The Brown polynomials are used to "add" lens distortion to the projected ideal point in normalised units before the coordinates are scaled directly to pixels. The residual (thick circle) is computed between the measured point and the ideal projected point with added lens distortion. The same modules have been used as in Figure  2. evaluation point.
USAGE The modular technique has previously been used in the opensource Damped Bundle Adjustment Toolbox (DBAT) 2  package  (Börlin and Grussenmeyer, 2013, 2016). In the 2016 paper, the technique was used to implement two bundle pipelines that used different adaptations of the  Brown (1971)  lens distortion model. In the Photogrammetric formulation, the Brown polynomials are used to "correct" for the effect of lens distortion on the measured image coordinates. In contrast, the formulation largely adopted by the Computer Vision community uses the same polynomials to "add" lens distortion to the ideal projection of object points  (Tsai, 1987; Heikkilä and Silvén, 1997; Zhang, 2000). The two pipelines are contrasted in figures 2 and 3. In this paper, we have used the modular technique to investigate the effect of the relative ordering of an affine transformation and lens distortion on the calibration of a tilt-shift lens.
Simulation experiment The first experiment was constructed to investigate the effect, if any, the difference in affine-lens distortion ordering had. Two sets of synthetic data were generated, where simulated error-free image observations were generated by back-projection of known 3D object coordinates and with known exterior orientation parameters (EO), and camera calibration parameters (IO) of a strong self-calibration network. The network consisted of 24 cameras at varying roll angles. About 100 targets were simulated in a 3D configuration with a largest dimension of 1000 mm (Figure  5 ). The following algorithms were used to simulate Model 3 and Model 4 (note that the order is reversed compared to Figure  4  as we are building image observations): Model 3 1. Collinearity equations (3D translation, 3D rotation, pinhole projection and optical scaling).
Introduce the principal point [pixel]. Both simulations used a skew (shear) parameter of b2 = 0. The algorithms were implemented in software developed in-house at FBK and not by DBAT. Each synthetic data set was analysed by a self-calibration bundle adjustment using DBAT models 2, 3, and 4. The datum problem was solved by fixing the EO parameters of one camera and one coordinate of another. No control points were used and the prior weight for the image observations corresponded to a sigma of 0. 1 pixels. The following parameters were estimated; the focal length, the principal point, the radial distortion parameters K1-K3, and the tangential distortion parameters P1-P2. For models 3 and 4, the affine parameters b1-b2 were also estimated. The quality of each analysis was evaluated in image space (σ0 and 2D image point RMS) and object space (3D RMSE between the true and estimated OP coordinates).
Camera calibration of a tilt-shift lens In the second experiment, models 2, 3 and 4 were used to calibrate a camera with a tilt-shift lens. A tilt-shift lens allows the following movements of the lens  (Ray, 2002 ): • a tilt, i. e. a rotation of the optical axis around either the exit pupil or the center of the sensor plane, • a shift, i. e. a translation of the optical axis, and • a rotation, i. e. a rotation about the optical axis. The data set from Nocerino et al. (  2016 ) was used for the calibration. The data set was acquired by a Nikon D750 full-frame DSLR camera with a PC-E Micro NIKKOR 45mm f/2. 8D ED tilt-shift lens (Figure  6 ) in two different configurations: NORMAL The normal configuration where neither tilt nor shift was applied. TILTED The lens was tilted in the vertical plane by 4 degrees.
The calibration target was a 3D photogrammetric calibration test object (Figure  7 ) with about 170 coded targets with a largest dimension of 900 mm. A high redundancy photogrammetric camera network was realised, consisting of up to 48 convergent images, with a diversity of camera roll angles to enhance the determinability of the IO parameters  (Fraser, 2001). The NORMAL data set was analysed and used as a reference for the processing of the TILTED data set. The TILTED data set was analysed by a self-calibration bundle adjustment in DBAT using models 2, 3 or 4. The datum and prior weights were the same as in the synthetic experiment. Furthermore, the parameters b1, b2, and P were individually included or excluded from the estimation (P1 and P2 were always estimated together). The quality of the estimation was evaluated as in the synthetic experiment with the results of the NORMAL data set used as the reference.
DISCUSSION In this paper we discuss how the residual computations used by bundle adjustment can be split into modules. If each module is responsible for computing Jacobians with respect to each parameter, in addition to the function value proper, Jacobians of complex expressions can be computed using the chain rule. Furthermore, the analytical Jacobians of each module can be validated independently of the other modules. The modular technique has previously been used in the Damped Bundle Adjustment Toolbox (DBAT) to model the Photogrammetric and Computer Vision adaptations of the  (Brown, 1971)  lens distortion models  (Börlin and Grussenmeyer, 2016). In this paper, the Photogrammetric pipeline was extended by an affine transformation. Two models with different placement of the affine transformation compared to lens distortion were implemented with minimal effort.
Results Modelling the tilt table and LBNP chamber. Previously, an LBNP chamber integrated with a tilt table was constructed at the Military Institute of Aviation Medicine, Poland, and the preliminarily data were presented  17. Although the intention of those authors was to implement the device into the selection process of candidates for military pilots, deeper investigations were suspended, mainly due to the use of fast aging components causing frequent failures. The previous experiences as well as a comprehensive literature review, briefly shown in the Discussion section, were elementary for designing the prototype of the ORTHO-LBNP system, in which durable elements and modern measurement modules have been utilised. In order for the device to be used both for carrying out selection procedures and researching clinical aspects, the tilt table must meet two main requirements: • range of tilt angles: -45° to +80°, • rate of tilt changes: up to 45°/s.
36. Their paper shows how to achieve a tilt in the range from -15° to +60° and a pressure of down to -60 mmHg at low cost. Those authors cite unpublished data from another research team, according to which predicted times to presyncope were determined in 63 subjects depending on gender and age group. They declared that unlike automatic tables, their solution allowed for rapidly transitioning from standing to supine position, however they did not list the maximum or typical rates of tilt changes achieved. Moreover, those authors attempt to argue that tilt testing with combined LBNP can be considered as a "gold standard" to study orthostatic intolerance. Although the tilt table testing is the most commonly applied test  37  , it has its limitations  38. The main of them is the fact that it may be false positive, i.
The market also offers a device with a motorised tilt table and a manually or automatically controlled LBNP chamber produced by Physiology Research Instruments. While the tilt is specified in the range from 0° to +65°, the authors have not been able to obtain information on the level of negative pressure generated. Photographs of several other devices can be found in the literature  23  and on the Internet, but no further data is available. In order to easily compare the proposed prototype system with other existing tilt tables with combined LBNP chambers, their most important features and research outcomes are shown in Table  3. With regard to the aforementioned devices, the prototype of the ORTHO-LBNP system is technologically advanced equipment that meets the high demands of the aviation simulators.
Future work. The novel system provides the opportunity to carry out experimental procedures in a much wider range than described above. The authors are planning to extend the current analysis to a bigger cohort in the future and consider gender comparison to assure population wide acceptability of the developed system. Data from a larger population of pilots will also allow for differentiating between pilots of fighter aircraft, transport aircraft and helicopters. Efforts will also be made to work out the final form of the OTI. The effect of muscle pump on facilitating venous return and degree of blood pooling achieved during orthostatic challenge was not measured. Astronauts returning from long duration spaceflight often experience orthostatic intolerance due to cardiovascular deconditioning and skeletal muscle atrophy  43, 44.
Methods Experimental protocol. The experimental protocol complied with the Declaration of Helsinki, and was approved by the Ethics Committee of the Military Institute of Aviation Medicine (Decision 18/2015), in which the study was carried out. The pilot study was registered at https://clinicaltrials. gov/ on 27/11/2017 under number NCT03354234. All activities during the study were performed in accordance with the relevant guidelines and regulations. The subjects were informed in detail on the purpose and nature of the study using the prototype of the ORTHO-LBNP system and signed their informed consent for study participation and publication of identifying information/images, including online open-access publications. The pilot study was carried out in an isolated room in the presence of a physician (physiologist), a paramedic and an ORTHO-LBNP system operator.
The software runs on the Microsoft. Net Framework 4. 0 platform. It was prepared in the C # language using the Visual Studio environment. The source code was developed according to the applicable design principles and software engineering principles. A set of tests for the individual software units and integration tests were also prepared. Similar to the medical monitoring subsystem, the computer application complies with the requirements of the standards harmonised with Directive 93/42/EEC and has been certified with a CE marking. Finally, the prototype system developed at technology readiness level 9 was deployed in a room with medical approvals, and prepared for pilot-based studies. A photograph of a subject being examined with the prototype of the ORTHO-LBNP system is shown in Fig. 7 (a).
This approach matches the OGC SE standard which is the standardized styling language  (Lupp, 2007)  in question here: a style is applied on a dataset to render a map considering a composition of possible symbol elements (called Symbolizer) that carry graphical properties (equivalent to visual variables). So as to complete the definition of cartographic portrayal interoperability, Fig. 2  shows that such a styling language is at the core of the third stage of the cartographic pipeline, the one dedicated to the style rendering. Thus it is to notice that the map layout design which configures a title, a legend, a north arrow, a scale bar, etc. (Peterson, 2009) , is out of our scope, as well as the preprocessing stage which is dedicated to the preparation of the dataset to visualize. As an example, building an anamorphic map requires a preliminary processing to generate consistent geometries with preserved shape and topology before styling them.
Use case "catalog" Going further than using a simple WMS GetMap request to get a ready-to-visualize map layer, the deprecated implementation specification (version 1. 0, released in 2002) of the WMS/SLD standard  (Lalonde, 2002)  does offer style management requests like GetStyles. So you get also the underlying symbology instructions of an internal style that has been predefined and used by the server to show a prepared cartographic facet of some spatial data of the underlying datasets. Thus, the retrieved style is ready to be reworked by the user client within a cartographic tool (Fig. 7 ). While such an ability is already interesting for the use case level 2, the SLD 1. 0 style management offers not only GetStyles operation but also PutStyles operation. Together, these operations are a good start for the use case level 3 to build a catalog of styles.
For instance, despite all the good intentions, there are several limits that come out from the introduction of the categorize function (defined by SE 1. 1 standard as the transformation of continuous values to distinct values, e. g. , useful to build choropleth maps): The definition seems to only match a requirement emphasized by Jenks  (Slocum et al. , 2009)  that classes must cover all the possible values of the dataset and must not be discontinuous. However, such a definition has limits considering optimal methods like the Jenks-Fisher classification or Maximum Breaks classifications that may produce intervals with gaps  (Slocum et al. , 2009)  and that it is often better to use the lowest value of the dataset as the minimum value of the first interval rather than negative infinity; The categorize function is redundant with the concept of Rule of the SE standard.
Moreover, the latter does offer wider possibilities to define precisely value intervals (minimum/maximum values instead of negative/positive infinite, non-contiguous intervals, interval as singleton); Similarly, the RasterSymbolizer concept used to control the styling of raster data has been reduced because of the ColorMapEntry concept from SLD 1. 0 has been replaced by the categorize transformation function; Finally, the introduction of categorize function has also removed from SLD 1. 0 the capability to associate a label to an interval when it is an important requirement to have such an information to build a map legend. Along the same lines, the many proposed extensions of SLD and SE standards have to be analyzed. The purpose is to identify how these cartographic enhancements are relevant for the redesign of the SE standard.
By way of other examples, Sae-Tang &  Ertz (2007)  describe four new possibilities to generate thematic maps (CategoryThematicSymbolizer, SimpleThematicSymbolizer, MultiThematicSymbolizer, ChartThematicSymbolizer). A similar approach appears in Dietze & Zipf (2007) (DiagramSymbolizer and ChoroplethSymbolizer) and in Iosifescu-Enescu, Hugentobler & Hurni (2010) to support various diagram types (e. g. , pie charts, bar diagrams) to fulfill the complex visualization requirements coming from environmental management. Also, the specific options introduced within the XSD schemas by some off-the-shelf geospatial software (e. g. , "GeoServer") have to be considered. Of course the extensible nature of XML is convenient to add cartographic capabilities to implement in the software, but it may at the same time also create some non-interoperable defects.
Clearly, it seems SE 1. 1 has never been designed with modularization and extensibility in mind and there are no explicit extension points defined in the underlying symbology model. Moreover, the SE standard does currently only offer one XML-based encoding and strongly linked to XML modeling principles (Fig. 9 ). As a consequence, it may be difficult for cartographic communities and developers having different encoding preferences (e. g. , CSS-like or JSON-based) to get a chance to observe conformance. Indeed, while there is a general trend to dislike XML, other encodings seem to be in fashion, like the YAML-based YSLD styling language proposed by GeoServer (2017) in addition to the support of OGC SLD standard, or the CSS-derived styling languages MapCSS (OpenStreetMap, 2017) or CartoCSS styling language from Mapbox (2017), although it seems already old-fashioned (MacWright, 2016).
Then, given that the geometry parameter is defined with a dependency on the ValueReference extension, the ValueReference specialization of the ParameterValue core concept is introduced. In a general way, when a parameter has to be assigned with a value, ValueReference does introduce the ability to reference the value extracted from a data attribute of a feature. This is useful when a FeatureType does hold many geometry properties and allows to reference the one to be used by the renderer. Finally, the AreaSymbolizer extension itself is required, holding the AreaSymbolizer specialization of the Symbolizer core concept. Called PolygonSymbolizer in SE 1. 1 and correctly renamed AreaSymbolizer by  Craig (2009) , it does introduce: The symbology ability to draw a surface area according to a filling and an outline; The dependency on the FeatureTypeStyle, Fill and Stroke extensions; The ability to reference the geometry data attribute to be drawn (by means of its dependency on the FeatureTypeStyle extension).