dataesr/scientific-paragraphs-categorization huggingface dataset:
Such motions have been successfully used in the surgical context for a compliant device  [14]. Beyond this use, very little information exists on the properties of the mechanism. It is therefore a case study that is suited for the introduction of the proposed approach. The paper is structured as follows: the 3-US kinematic modeling is introduced in Section 2 to outline the available information on the mechanism. This sets the general formulation used in the method. The higher-order continuation method is introduced in Section 3: it is the core of the general analysis. We propose to use the Diamanlab software  [25]  and describe its main underlying principles. The analysis of the mechanism properties, including the workspace boundaries and interesting features such as screw motion and self-motion are discussed in Section 4.
Higher-order continuation method Under analyticity assumptions, the solution for nonlinear problems may indeed be carried out through a Taylorbased numerical method and higher-order Automatic Differentiation (AD)  [31, 32, 33, 34]. In a nutshell, AD is a set of techniques that enable to augment a given computer code with derivative computations, with an obvious advantage in terms of ease of implementation and generality since derivative computations, Jacobians and higher-order terms are performed in an automatic manner  [24, 35, 36]. The Diamant approach  [23, 24]  is a higher-order continuation method that automates the Asymptotic Numerical Method discussed in  [37, 38]. Diamant is of particular interest for mechanism analysis since it may be used from the constraint equations only. The related Matlab software is named Diamanlab  [25, 42].
Truncated Taylor series allow for the construction of accurate continuous solution branches and contain information for the detection of bifurcation and instability points  [40]. Bifurcation diagrams plot continuous solution branches comprising possible bifurcation points. These bifurcation points correspond to the intersection of branches of solutions. They may be detected either by monitoring a change of sign for the Jacobian determinant along the solution branch  [27]  or by implementing higher-order bifurcation indicators  [40, 41]  from Taylor series information. For the sake of generality, see subsection 3. 2, Diamanlab (Matlab implementation of Diamant  [25, 42] ) implements the detection and branch switching processes proposed in  [40]. Key points for the automation of the solution (5) are the generality of both the high-level nonlinear solver  (11)  and AD for Taylor coefficient computations.
Airborne GNSS-R campaigns are crucial to the understanding of signal interactions with the Earth's surface. As a consequence of the specific geometric configurations arising during measurements from aircraft, the reflected signals can be difficult to interpret under certain conditions like over strongly attenuating media such as forests, or when the reflected signal is contaminated by the direct signal. For these reasons, there are many cases where the reflectivity is overestimated, or a portion of the dataset has to be flagged as unusable. In this study we present techniques that have been developed to optimize the processing of airborne GNSS-R data, with the goal of improving its accuracy and robustness under non-optimal conditions. This approach is based on the detailed analysis of data produced by the instrument GLORI, which was recorded during an airborne campaign in the south west of France in June 2015.
Our technique relies on the improved determination of reflected waveform peaks in the delay dimension, which is related to the loci of the signals contributed by the zone surrounding the specular point. It is shown that when developing techniques for the correct localization of waveform maxima under conditions of surfaces of low reflectivity, and/or contamination from the direct signal, it is possible to correct and extract values corresponding to the real reflectivity of the zone in the neighborhood of the specular point. This algorithm was applied to a reanalysis of the complete campaign dataset, following which the accuracy and sensitivity improved, and the usability of the dataset was improved by 30%.
) was investigated. These measurements provided the first dataset that made the design and validation of dedicated bistatic GNSS scattering models possible  [13] [14] [15] [16]. Since the launch of TechDemosat-1 in 2014  [17]  and the CyGNSS constellation in 2016  [18] , there has been a shift in the sensitivity and potential retrieval of parameters such as soil moisture or vegetation cover, that can be achieved with spaceborne data  [19, 20]. Despite these crucial advances, since GNSS-R is a technique based on signals of opportunity (i. e. , with which there is little or no control over their geometry, signal power or modulation), analysis of the acquired data is not as straightforward as in the case of other microwave instruments, which have been designed with the specific objective of Earth observation in mind.
Filtering is generally applied to GNSS-R datasets, and more stringently to airborne datasets, in order to remove data acquired under non-optimal conditions, such as that derived from signals from low-elevation satellites, or during aircraft maneuvers such as takeoff, landing and turns  [8, 10]. In this context, the present study was designed to assess different approaches that could be used to improve the data processing, and to allow data to be retained for scientific analysis, which would otherwise have been deemed unusable as a consequence of noise or contaminating signals. In the present paper we present a methodology designed to mitigate the effects arising from the use of GNSS-R receivers in aircraft. Section 2 briefly describes the GLORI airborne instrument, campaign dataset and processing scheme, whilst focusing on potential sources of error or signal corruption.
Filtering is generally applied to GNSS-R datasets, and more stringently to airborne datasets, in order to remove data acquired under non-optimal conditions, such as that derived from signals from lowelevation satellites, or during aircraft maneuvers such as takeoff, landing and turns  [8, 10]. In this context, the present study was designed to assess different approaches that could be used to improve the data processing, and to allow data to be retained for scientific analysis, which would otherwise have been deemed unusable as a consequence of noise or contaminating signals. In the present paper we present a methodology designed to mitigate the effects arising from the use of GNSS-R receivers in aircraft. Section 2 briefly describes the GLORI airborne instrument, campaign dataset and processing scheme, whilst focusing on potential sources of error or signal corruption.
Airborne Campaigns The GLORI airborne campaigns took place during the period from June to July 2015, and included a total of five flights over the south of France. Fifteen hours of data were acquired during these measurements, which involved three types of surface: agricultural areas, forest areas, and bodies of water. Simultaneously to these airborne measurements, various ground truth measurements were carried out in numerous test fields. These included measurements of soil parameters such as moisture and roughness and vegetation parameters such as Leaf Area Index (LAI), water content, height or Above Ground Biomass (AGB). Figure  2.
Airborne Campaigns The GLORI airborne campaigns took place during the period from June to July 2015, and included a total of five flights over the south of France. Fifteen hours of data were acquired during these measurements, which involved three types of surface: agricultural areas, forest areas, and bodies of water. Simultaneously to these airborne measurements, various ground truth measurements were carried out in numerous test fields. These included measurements of soil parameters such as moisture and roughness and vegetation parameters such as Leaf Area Index (LAI), water content, height or Above Ground Biomass (AGB).
Optimizing the Detection of Waveform Maxima Using the extensive dataset provided by the GLORI 2015 airborne campaign, we analyzed the reflected waveforms and evaluated several different methods designed to improve the tracking of the waveform peak, corresponding to signal contributions generated by the area surrounding the specular point. In particular, we focused on signals recorded with short integration times and/or originating from low reflectivity surfaces, which could lead to a poor SNR, as well as those recorded under conditions of low elevation angles and/or altitudes, which could be contaminated by the direct signal.
Optimizing the Detection of Waveform Maxima Using the extensive dataset provided by the GLORI 2015 airborne campaign, we analyzed the reflected waveforms and evaluated several different methods designed to improve the tracking of the waveform peak, corresponding to signal contributions generated by the area surrounding the specular point. In particular, we focused on signals recorded with short integration times and/or originating from low reflectivity surfaces, which could lead to a poor SNR, as well as those recorded under conditions of low elevation angles and/or altitudes, which could be contaminated by the direct signal. Four approaches to the improvement of peak detection are described in this section:.
Improvements in Data Availability Figure  15  shows the data availability vs SNR (antenna gain corrected) and elevation angle for the whole GLORIE 2015 campaign. On the top panel, the values from the initial processing are shown, showing a rather constant distribution of the measurements vs. SNR at high elevation angle, and a drop towards low SNRs at elevation angles below 45°, proving a degradation of the maximum tracking method. For this reason, elevations angles below 45° where filtered out in the initial dataset. In the lower panel, the same data availability is shown for the dataset using the new direct mitigation algorithm. It can be seen that the distribution vs. SNR remains constant at all elevation angles, showing the good performance of the specular point tracking algorithm. In Figure  14b , the same transect is shown using the new technique with direct signal mitigation.
Improvements in Data Availability Figure  15  shows the data availability vs. SNR (antenna gain corrected) and elevation angle for the whole GLORIE 2015 campaign. On the top panel, the values from the initial processing are shown, showing a rather constant distribution of the measurements vs. SNR at high elevation angle, and a drop towards low SNRs at elevation angles below 45 • , proving a degradation of the maximum tracking method. For this reason, elevations angles below 45 • where filtered out in the initial dataset. In the lower panel, the same data availability is shown for the dataset using the new direct mitigation algorithm. It can be seen that the distribution vs. SNR remains constant at all elevation angles, showing the good performance of the specular point tracking algorithm. Figure  16  is a histogram showing the distribution of the measurements versus SNR for the whole GLORI 2015 dataset.
As stated above, in the original version of the dataset, measurements were filtered out below 45° of elevation to avoid SNR issues. Thanks to the direct mitigation algorithm, we avoid the SNR issues, and measurement from all elevations angles down to 30° can be kept. In total there are more than 955,000 individual 240 ms measurements that can be used with the new algorithm, when with the initial processing technique, only 633,000 were kept after filtering. This represents 33% of the dataset that was not used and that is now available.
Conclusions We describe the importance of correctly detecting specular area contributions in noisy and direct-signal contaminated reflected waveforms. Following a description of the effects of low-pass filtering (Savitsky-Golay running average) and incoherent averaging on standard peak detection techniques, we propose an empirical algorithm designed to monitor the variations in delay resulting Figure  16  is a histogram showing the distribution of the measurements versus SNR for the whole GLORI 2015 dataset. As stated above, in the original version of the dataset, measurements were filtered out below 45 • of elevation to avoid SNR issues. Thanks to the direct mitigation algorithm, we avoid the SNR issues, and measurement from all elevations angles down to 30 • can be kept. In total there are more than 955,000 individual 240 ms measurements that can be used with the new algorithm, when with the initial processing technique, only 633,000 were kept after filtering.
This represents 33% of the dataset that was not used and that is now available. Figure  16  is a histogram showing the distribution of the measurements versus SNR for the whole GLORI 2015 dataset. As stated above, in the original version of the dataset, measurements were filtered out below 45° of elevation to avoid SNR issues. Thanks to the direct mitigation algorithm, we avoid the SNR issues, and measurement from all elevations angles down to 30° can be kept. In total there are more than 955,000 individual 240 ms measurements that can be used with the new algorithm, when with the initial processing technique, only 633,000 were kept after filtering. This represents 33% of the dataset that was not used and that is now available.
Step 3: assessment of theoretical foundations and empirically evaluated methods and strategies for behaviour change. Step 4: translation of methods and strategies into an organised intervention. Step 5: planning of the adoption, implementation, and sustainability of the intervention. Step 6: formation of an evaluation plan. All these six steps were applied in order to develop a systematic, theory-based arttherapy intervention for people with PD to promote their self-and emotion regulation. Steps 1, 2, and 3 were carried out by performing a comprehensive review of the literature on art therapy and PD. The CINAHL, ERIC, PUBMED, SCIENCEDIRECT, and WEBOFSCIENCE databases were searched for English articles published until 2016. Search terms were: 'personality disorder*' or 'personality patholog*', 'art therap*' or 'arts therap*', or 'creative therap*', or 'emotion regulation'.
These operators have been implemented in LNT and are used in Appendix C of the present article. Beyond these languages, the multiway rendezvous paradigm has not spread as largely as one would wish. One reason for this is the influence of CCS, which promotes an incompatible paradigm of binaryonly communication. Another reason is the high difficulty to properly implement multiway rendezvous, either in a sequential setting or in a distributed setting; for the latter point, which is even more difficult, let us mention recent work that implements the LOTOS multiway rendezvous among a collection of distributed processes interconnected by POSIX sockets  [25]  [24]  [23]. However, concepts similar or close to the multiway rendezvous are indeed present in certain computer languages or models: • The mCRL2 process algebra  [38]  also contains multiway synchronization.
The Graphical Simulator of the Production Cell A graphical simulator  [9]  [10], written in Tcl/Tk, enables prototype controllers to be validated and provides a reference to compare the controllers obtained from executable formal methods. Unfortunately, Figure  1 : Screenshot of the graphical simulator the Tcl/Tk source code of this simulator is no longer available today, as the FTP server ftp. fzi. de hosting the original version of the simulator does not seem to respond any more. Luckily, a copy of the simulator was archived at INRIA Grenoble, improved in a few points, and regularly adapted to the latest versions of Tcl/Tk and operating systems (Linux, MacOS, Windows, etc. ). A screenshot of this simulator is shown in Figure  1. The simulator has two functioning modes: asynchronous or synchronous.
Sensor Values and Data Abstractions To remain as close as possible to the notations given in  [58]  and  [10] , we keep the same names S1,. , S14 for the 14 sensors. The reference books is ambiguous with respect to the meaning and role of sensors 13 and 14; we resolve this ambiguity by applying the corrigendum described in Appendix B. To manipulate sensor values, the controller requires only basic types: BOOL, REAL, and STRING. The LNT language provides them as predefined types; this is a clear advantage with respect to LOTOS, in which floating-point numbers and character strings are missing and must be defined explicitly (e. g. , by integration of external C code, as it is done in CADP). The authors of the simulator mentioned that a precision of 10 -2 is enough when comparing real numbers; this is implemented in the approximate equality function " ~" defined over real numbers (cf Appendix C.
Code Generation from the LOTOS and LNT Specifications Following a "model-driven" approach, most of the code of the controller implementation is generated automatically from the LOTOS or LNT specification. This is done using the compilers and the EX-EC/CAESAR software framework  [35]  provided in the CADP toolbox  [32]. The LOTOS specification is translated to sequential C code (about 7340 lines of C, including blank lines and comments) using the CAESAR and CAESARADT compilers of the CADP toolbox. The LNT specification is first translated to LOTOS and C code using the LNT2LOTOS compiler, then the generated LOTOS code is translated to C using CAESAR and CAESARADT (about 8150 lines of C in total). The generated C code is generic, so that it cannot directly connect to the Tcl/Tk simulator. According to the principles of EXEC/CAESAR, two auxiliary C modules are needed to interface both worlds.
The first module (750 lines) provides, for each externally visible LOTOS or LNT gate, a corresponding C function. The skeleton of this module can be automatically generated by CAESAR, so that only the bodies of these gate functions have to be filled in manually. This is straightforward for the functions corresponding to actuator gates (e. g. , PRESS_UPWARD, etc. ), as it is sufficient to emit the corresponding simulator command to the standard output. The function for gate GET_STATUS is a bit more complex, as it parses the standard input and converts character strings to LOTOS or LNT values; the most involved parsing task concerns the string containing a list of error messages. The second module (90 lines) contains the main function, which explores a (possibly infinite) execution path, following the transitions that are both fireable in the LOTOS or LNT specification and accepted by the Tcl/Tk simulator; if several transitions are possible in a current state, one of them is selected.
The CADP toolbox provides a standard version of this second module, which in most cases can be used as is. However, in the production cell example, it was necessary to slightly adapt the code in two ways: (i) to send a react command to the simulator at the end of each reaction step, only after all actuator commands have been emitted, and (ii) to ensure that the get_status command occurs, and only occurs after a react command. These two constraints express that react and get_status have somewhat a lower priority than the commands sent to the actuators; because LOTOS and LNT do not provide priority between transitions, these constraints have been implemented in the main C program, where the choice between available transitions is actually resolved.
g. , by adding new devices or removing existing ones -this is the flexibility requirement mentioned in  [58, Section 2. 3. 3]. The software controller was successively specified in LOTOS, then in LNT. The complete LNT specification, which is more readable than the LOTOS one, is provided in Appendix C. For both specifications, the CADP toolbox generated an implementation in C that was connected, using the EXEC/CAESAR interface, to the Tcl/Tk simulator and used to drive the production cell. Although the LOTOS and LNT specifications pass the compile-time checks of the CADP compiler and the run-time checks of the Tcl/Tk simulator, they have not been yet formally verified using, e. g. , model checking or equivalence checking. Their verification thus remains a challenging problem for future work.
Design of real-time PCR primers and hydrolysis probe In their work on the genomics of Foc, Li et al. [8]  described a genetic locus from mutant W2987 expected to be associated with Foc TR4 virulence. Based on in vitro pathogenicity tests,   [8]  d  [10]  e  [13]  f  [26]  g  [47]  h  [46]. doi:10. 1371/journal. pone. 0171767. t001 Li et al. [8]  suggested that the target gene may be involved in the pathogenesis of Foc TR4, although further characterization by gene deletion and complementation was still needed to confirm its function. The authors did not name the gene and they refer to it as a "putative virulence gene" that encodes a hypothetical protein with unknown function. The present work took this gene as a basis for the development of the test. A selected panel of 34 isolates was sequenced in this study using the primer set 356F/357R (see S1 Table for GenBank accessions), which was designed to specifically amplify this locus (Table  1 ), following the PCR conditions recommended by Li et al.
[8]. Sequences were analyzed together with those published by Li et al. [8]  in GenBank (accession numbers JX090599-JX090603) using the MUSCLE aligning tool  [48]  implemented in GENEIOUS R6 (BIOMATTERS, Auckland, New Zealand). PRIMER 3  [49] , available in GENEIOUS R6, was used to manually design three pairs of Foc TR4-specific forward and reverse primers, as well as hydrolysis probes, which were evaluated for their respective thermodynamic characteristics and potential secondary structures. A first evaluation of the analytical specificity (i. e. the ability of the test to identify target from non-target) of the three candidate primer pairs and probes was performed in silico using the PRIMER BLAST algorithm  [50]  and the Broad FGI Fusarium Comparative Database (http://www. broad. mit. edu/annotation/ genome/fusarium_group/MultiHome.
oxysporum -- -- - - - - - - LSVM 1026 F. oxysporum -- -- - - - - - - LSVM 1027 F. oxysporum -- -- - - - - - - LSVM 1028 F. oxysporum -- -- - - - - - - LSVM 1029 F. oxysporum -- -- - - - - - - LSVM 1030 F. oxysporum -- -- - - - - - - LSVM 1031 F. oxysporum -- -- - - - - - - LSVM 1032 F. oxysporum -- -- - - - - - - LSV M 942 F. oxysporum -- -- - - - - - - LSV M 1079 F. oxysporum -- -- - - - - - - LSV M 1082 F. oxysporum -- -- - - - - - - NRRL13566 F. fujikuroi -- -- - - - - - - LSVM 895 F. ananatum -- -- - - - - - - LSVM287 F. concentricum -- -- - - - - - - NRRL 22402 F. solani -- -- - - - - - - LSVM 878 F. poae -- -- - - - - - - LSVM286 F. proliferatum -- -- - - - - - - (Continued) (Ct) values were computed using the Rotor-Gene software 1. 7. 75, setting the threshold line at 0. 02. The experiments were designed following a balanced orthogonal array of 18 experimental combinations (Table  3 ).
Performance values Performance of the test was evaluated according to the European and Mediterranean Plant Protection Organization (EPPO) standard PM7/98  [53]. According to EPPO, a test is considered as fully validated when it provides data for the following performance criteria: analytical specificity, analytical sensitivity, reproducibility and repeatability. The robustness, i. e. ability of the test to remain unaffected by small but deliberate variations of some reaction parameters, was also included in the validation procedure. All validation and performance experiments were carried out in duplicate for each DNA sample, unless indicated otherwise. Six NTCs were systematically included at different steps to check the absence of contamination in all reactions of conventional or real-time PCR.