dataesr/scientific-paragraphs-categorization huggingface dataset:
Classically, slides are analyzed with microscope and follicle count is generated manually on multiregistered cell counter  35. Subsequently, the data is recovered and transferred to a computer database. This technique is laborious, costly, time consuming and highly operator-dependent. As a result, over the past decades, efforts were made to improve this procedure and different ovarian follicle counting protocols were investigated. At first, authors proposed to count follicles not in all sections but only in every fifth to tenth sections. For example, a study compared the efficiencies of various sampling paradigms to define sensitive and less tedious means to obtain differential follicle counts and concluded that follicle counts from 1% to 5% random samples may provide a good estimation of ovarian toxicity in mice  35.
Thus, a mode matching technique  [38]  is here proposed. Previously, approaches of this kind have been devoted to efficiently analyze the dispersion characteristics of strongly interacting corrugated surfaces  [39] ,  [40]  and holey surfaces with square holes  [41] ,  [42] , including glide-symmetric ones  [43]. These recent works have provided information on the behavior of the fields excited inside the holes and demonstrated that considering only the dominant mode inside the hole, as in non-glide holey structures  [44] , does not model the structure accurately  [41] ,  [42]. In addition, the presented results in these works have proved that the proposed mode-matching method is faster and more efficient than commercial software based on the finite-method algorithms such as CST Microwave Studio, especially when the hole is large or the gap between the two surfaces is very small.
We demonstrate that the analysis of a glide-symmetric holey unit cell with the distance g between the layers (Fig. 1(a) ), has the same complexity of its corresponding non-glide unit cell consisting of one layer holey surface with a perfectly electric conductor (PEC) plane at the distance of g/2 above it (Fig. 1(b) ). Note that the non-glide structure is considered here with a gap of g/2 since we show later that the analysis of the two unit cells can be carried out similarly. Our formulation is validated for the specific case of cylindrical holes by comparing our mode matching with the results obtained from the commercial software CST Microwave Studio for different values of the unit cell parameters. The results confirm the possibility of tuning the effective refractive index by adjusting the geometric parameters, as well as, the lack of the frequency dispersion for the first propagating mode due to the absence of the stop-band between the first and second modes.
IV. RESULTS As mentioned in Section I, all-metal glide-symmetric mesurfaces tailored with cylindrical holes are a good candidate for designing low-loss graded-index planar lenses. In these lenses, by changing the radius or the depth of the holes, a spatial variation of the refractive index is achieved. In this section, these structures are analyzed through their dispersion diagrams using the mode matching formulation presented in Section II. In addition, the possibility of tuning the effective refractive index is demonstrated. The code is implemented in Matlab and the results are compared with the ones obtained from commercial software CST Microwave Studio. Our reference case has a gap between the surfaces with g = 0. 2 mm, its period is d = 4 mm, a hole depth of h = 1. 5 mm, and a hole radius of a = 1.
The comparison between the dispersion diagrams of the reference case and two values of gap, g = 0. 3 mm and g = 0. 5 mm, are depicted in Fig. 4. As in the two previous cases, a good agreement between the mode matching and CST results is achieved. By decreasing the thickness of the gap, the interaction between the surfaces becomes stronger, which causes a higher equivalent refractive index. To show the full potential of our method, the dispersion diagram of the reference glide-symmetric structure and its corresponding non-glide structure over the irreducible Brillouin zone is depicted in Fig. 5  and compared with CST simulation results. This type of simulation is typically carried out for designing EBG structures, which find application, for example, in gap waveguide technology. In order to give an estimation of the speed of our method, we launched the simulations of CST and our code in the same computer.
V. DISCUSSION AND CONCLUSION Here, we have proposed a general mode-matching formulation for developing dispersion analyses of holey surfaces in 71748  VOLUME 6, 2018  the vicinity of a metal plane and a glide-symmetric holey surface. Our method can be applied to an arbitrary shape of the holes. As in our previous work presented in  [43] , for the case with glide symmetry, the higher symmetry of the structure and the generalized Floquet theorem are applied to reduce the computational cost. The formulation was tested and verified for cases with cylindrical holes, which is of interest, in practice, for designing of low-cost and low-loss graded-index planar lenses and EBG structures. The code was checked for different values of geometrical parameters and for propagation in different directions, obtaining the irreducible Brillouin zone.
The influence of the gas-to-liquid density ratio (DR) on the global wave shape before impact is studied through numerical simulations of the propagation of two different waves in a rectangular wave canal. Two different codes are used: the first one, named FSID, is a highly non-linear 2D bi-fluid potential code initially developed in the frame of SLOSHEL JIP (Kaminski et al. (  2011 )) to simulate incompressible inviscid free-surface flows without surface tension thanks to a desingularized technique and series of conformal mappings; the second one, named CADYF, is a bi-fluid high-fidelity front-tracking software developed by Ecole Polytechnique Montreal to simulate separated two-phase incompressible viscous flows with surface tension.
This limitation can be largely alleviated by using mesh adaptation. Comparisons between wave shapes captured with a high speed camera during sloshing tests and wave shapes as calculated by CADYF in the same conditions showed good agreement for forced motions of a rectangular tank with a low filling level of water and air as ullage gas, at least until the development of local perturbations on the interface  (Hay et al. (2016) ). The ability of the code to capture adequately the growth of free surface instability such as Kelvin-Helmholtz's, at least for academic conditions is shown in  Fortin et al. (2018).
History of the calculation cases The generation and propagation of four unidirectional waves have been simulated in 2D by CADYF and FSID for five density ratios (20 cases for each code). These wave cases have been first proposed in  Guilcher et al. (2013)  and  Guilcher et al. (2014)  with water and air. They lead to a flip-through impact (denoted FTI) and three gas-pocket impacts with entrapped gas-pockets of different sizes (the impact with the largest gas pocket is denoted LGPI). For the sake of brevity, only the results corresponding to the waves leading to the FTI and to the LGPI are presented here with only three DRs (6 cases for each code). They are sufficient to illustrate the general conclusions. In  Guilcher et al. (2013)  and  Guilcher et al. (2014) , the focus was made on the impact simulation by a SPH code solving the compressible Euler equations for both the liquid and the gas.
3. and Fig. 4. looks very much constant for both waves. This can be checked more carefully by looking at ∆ ̃ in Fig. 5. and Fig. 8. For the FTI, ∆ ̃ remains lower than 10 -5 whatever the code and whatever the DR. For the LGPI, Fig. 8. shows a quick drop of ∆ ̃ with CADYF around t=2 s whatever the DR. ∆ ̃ remains lower than 10 -5 until the sudden growth of kinetic energy into the gas around this time, whatever the DR. The energy dissipation observed here is mainly a numerical artefact: numerical energy dissipation is cumulated at each remeshing operation mainly due to a too simple linear interpolation scheme used in CADYF. The drop of mechanical energy observed on the figure corresponds to the sudden increase of the number of remeshing operations when the curvature of the interface becomes very high at some locations due to the development of free surface instabilities.
Comparison between CADYF and FSID results We can observe in Fig. 7. and Fig. 10. that the differences on the global wave shape before impact as obtained by CADYF and FSID simulations are hardly visible and much smaller than the differences generated by the influence of DR that we wanted to capture. FSID ensures the continuity of normal velocity (and pressure) but there is a discontinuity of tangential velocity at the interface that is calculated. The program stops the simulation as soon as this discontinuity becomes too large and perturbations at the interface start to grow. It would be possible to delay the time when the program stops by artificially reducing the resolution at the interface (smaller number of Lagrangian markers). This would inhibit the development of large jumps of the tangential velocity at the interface but would be paid by worse energy/mass conservation.
To test our hypothesis, we partitioned the region of interest in several subregions, for each of which we built a gaze direction distribution polling together the gaze direction data of the whole population. The number of subregions was determined by a sliding window of size 0. 5m and step 0. 05m. Such a representation allowed us to assess and to compare the evolution in time, from start to FDP, of the gaze direction distribution of each population. To be able to incorporate eye movements during re-planning of an alternative route in the model, we analysed eye movements statistics for each individual observer during test trials. In particular, we counted the proportion of fixations made straight ahead November 28, 2018 7 towards the central corridor, towards the right and towards the left arm while the observer moved from start to FDP.
e. who chose more often the right path). While still considering young and old data categories separately, we analyzed two datasets of gaze directions, pooling together B trials repetitions: 'All' and 'Correct' data. 'All' data refers to the use of gaze directions drawn from all subjects in the considered category, disregarding whether they succeed or not the trial, whereas 'Correct' data refers to the selection of successfully completed trials. In order to evaluate the onset of the gaze anticipatory effect in the two populations, we evaluated the location within the region of interest (DM * Y,O ) at which the gaze direction distribution significantly departed from unimodality (Hartigan test). As a matter of fact, as soon as subjects got closer to the FDP, their gaze direction was no longer peaked at 0 • , i.
e. the location at which the eyes anticipated the direction of motion. On the right plot, the gaze direction distribution obtained in the last bin, i. e. closest to the F DP , is represented on a semi-polar plot; the superimposed line labels the median of the distribution. Note how the gaze distribution of Y observers is much more biased towards the right direction. B. To estimate the variability associated to the decision making point DM * Y,O , we applied for each of the four datasets Young correct (YC)/old correct (OC), Young All data (YAD) / old All data (OAD) the following procedure. For each sliding window, we generated a kernel probability density estimate for the current gaze direction distribution, using a normal kernel smoothing function. We then randomly sampled 20 synthetic datasets from the pdf of the kernel distribution.
For each dataset, we performed the Hartigan test. Parametric t-tests showed that 'All' Y and 'All' O data exhibited a significant (p < 0. 001) difference between onsets of the multimodal gaze direction pattern. Within each of these groups, changes in onset value when considering 'All' or only 'Correct' trials were not significant. November 28, 2018 14  7C. , left panel). The model free version of HRL was the slowest and less accurate (Fig. 7C. , central panel). Importantly, the way in which we defined options in HRL algorithms impedes the agent to repeatedly go back and forth in small subregions of the maze, i. e. to get jammed in unrealistic loops, which we never observed in the subjects behaviour. Those unrealistic loops are hardly avoidable in standard MB algorithms, which use primitive actions.
During conceptual design phase, system architects pre-validate architectures following different constrains. This paper proposes a new pre-designing method applied to a flexible multibody system to characterize its vibrational behavior analytically with Dymola/Modelica language. We study the vibration interaction between perturbations sources (motors) and receivers (electronic cards) through a flexible beam with arbitrary boundary conditions. In fact, a lot of mechatronic systems may have their natural frequencies and mode shapes dependent on their spatial configuration, which affect the dynamic response of the system. This methodology shows that using Modelica, we can implement different boundary conditions, making the element suitable for any multibody simulation. This model can help system architects to study the influence of the boundary conditions on the system response.
The dynamic response of the beam is expressed as follows: Y ðx; tÞ ¼ wðx; tÞ ¼ X N k¼1 F k X ∞ i¼1 W i ðxÞW i ðx k Þ v 2 i À V k 2 sinV k t À V k v i sinv i t : ð19Þ For two motors, the beam displacement can be written as: Y ðx; tÞ ¼ wðx; tÞ ¼ F 1 X ∞ i¼1 W i ðxÞW i ðx 1 Þ v 2 i À V 1 2 sinV 1 t À V 1 v i sinv i t þ F 2 X ∞ i¼1 W i ðxÞW i ðx 2 Þ v 2 i À V 2 2 sinV 2 t À V 2 v i sinv i t : ð20Þ 3 Modelica system modeling In this paper, the object-oriented simulation software Dymola/Modelica has been used to develop and simulate this system (Fig. 3 ). According to the theoretical analysis presented in Section 2, two motors and an electronic card located on the beam are considered in this study. In order to study the physical interaction and to define the components location, a mechatronic system must be divided into its components.
As Modelica is an object oriented modeling language, it allows the realization of a complex system by simple gathering components  [22]. The proposed model has been implemented in Dymola/ Modelica. Figure  4  is a graphic representation of the model designed in Dymola. From a structural view point, the setup of the system is decomposed into a set of connected components. It includes elements developed specifically for this application and parts that belong to standard Modelica library. The beam is modeled by the behaviour characteristic equations presented in Section 2. Two selected boundary conditions are considered in this study: clamped at both ends (C-C) beam and simply supported at both ends (S-S) beam. The user has the ability to choose particular boundary conditions for simulating the flexural deformation and he can also compare the behavior response of a system for the two types of boundary conditions in the same time.
Conclusions In this paper, a new conceptual design methodology to help system architects to define concepts and solutions has been carried out. The object-oriented technology is utilized to create a reusable component-based architecture. In fact, the developed model uses standard connector to guaranty the compatibility with Modelica Standard library components. In order to obtain quick resolutions, an analytical approach is adapted using Modelica language. This methodology enables designers to characterize the vibration behaviour of the overall system and to investigate the influence of selected boundary conditions on the dynamic response. This modeling process will help system architects to quickly build up system models, the analysis, and the characterisation of complex multibody systems.
Natural Constraints The pan-European CCM catchment database v2. 1  (Vogt et al. , 2007;  http://ccm. jrc. ec. europa. eu) was used to define elementary catchments (5,793 units) for the Seine basin and basic morphological information for characterizing the drainage network. The light followed an annual cycle dependent on the latitude of the catchment, and water temperature was set by Strahler order (adapted from  Billen et al. , 1994).
Anthropogenic Constraints Domestic point sources were set from the European UWWTD waterbase (EEA, 2012) using data reported for the year 2010. Fluxes of N, P, C and suspended solids discharged to the drainage network were calculated on the basis of a spatially explicit census of wastewater treatment plants. For each release point, raw emissions were provided (in inhabitant equivalents), associated with a wastewater treatment type (including discharge without any treatment). The corresponding water and nutrient fluxes were considered constant over the year. Diffuse sources were estimated for surface runoff and base flow as nutrient concentrations characterizing each land use class of the watershed. Data were retrieved from European databases and regionalized for each land use class  (Bossard et al.
, 2000; EEA, 2007;  Corine Land Cover database) inside each statistical NUTS region (NUTS level 3). Particulate sources were estimated from the PESERA model  (Kirkby et al. , 2004 ) combined with land-based estimates of phosphorus and organic carbon (LUCAS survey;  Tóth et al. , 2013). Dissolved silica concentrations were determined according to litho-morphological properties, distinguishing crystalline and sedimentary rocks. Nitrogen (nitrate) leaching flux was calculated based on a comprehensive analysis of the agricultural EUROSTAT databases and N surplus  (Anglade et al. , 2015)  established with the GRAFS (generalized representation of agro-food systems) approach  (Billen et al. , 2014). Given that the objective of this work was to evaluate the impact of climate-induced changes, human practices (i.
The rates of MEs, vMEs and mEs depend on a number of factors: (i) presence and width of an intermediate zone; (ii) position of a population relative to the CBP; and (iii) methodological variation. The latter parameter includes both the methodological imprecision (inoculum size, agar composition, incubation time, disc content, inter-and intra-person variability in the reading) and the biological variation. 5 ere we report on Antibiotrust, a software that visualizes the antibiogram and the reliability of the categorization. Antibiotrust was developed with the aim of conveying a graphic report displaying AST data from Kirby-Bauer disc diffusion testing. However, this approach can also be used for data based on MIC determination. As shown in Figure  1 , Antibiotrust reports display the inhibition zone diameters of antibiotic panels used for the various bacterial groups (e.
Acknowledgements G. K. gratefully acknowledge the financial support from the  SERB, Department of Science and Technology, India  ( SB/FTP/PS-051/2014 ). DRC gratefully acknowledge the financial support from the  SERB, Department of Science and Technology, India  ( EMR/2015/001339 ). SJM Rao would like to acknowledge the financial support from the  Ministry of Human Resource Development, Government of India  for a research fellowship.
Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships.
THE GROWING WEIGHT OF STATISTICS IN LINGUISTICS Different reasons can be put forward for why data-driven approaches are gaining more prominence in the whole linguistic field. First, large digital datasets such as WALS  (Dryer and Haspelmath, 2013) , ASJP  (Wichmann et al. , 2016) , Lapsyd  (Maddieson et al. , 2013) , or D-Place  (Kirby et al. , 2016)  are freely and readily available for computational analysis. Second, personal computers now offer high computational power, along with efficient and open-source statistical software, like the R language and environment for statistical computing and graphics (R Development Core Team, 2017). In particular, advanced modeling techniques that were either still under development or computationally out of reach with affordable computers two decades ago are becoming accessible.
Both proposals have led to substantial debates (e. g. ,  Pericliev, 2004; Bybee, 2011; Donohue and Nichols, 2011; Moran et al. , 2012) , both at a theoretical and at a methodological level. Beyond that, language contact and subsequent borrowing -or lack of it -, but also inheritance from parent languages, are obvious partial answers to why a phonemic inventory may be small or large. In the next sections, we perform as series of regression analyses of phonemic inventory size, in order to illustrate the potentialities and limits of various approaches. In order to do this, we built a dataset of 1529 languages containing 681 languages from the Lapsyd database  (Maddieson et al. , 2013) , complemented by 846 languages from the Phoible database  (Moran et al. , 2014). This dataset compiles information for a number of predictors: -Linguistic families and number of speakers extracted from the WLMS dataset (Global Mapping International SIL International, 2012); -Distance from Africa computed following Atkinson's methodology with a departure point located in eastern Africa (36 • W, 8 • N) and great circle distances constrained by specific passage points (Sinai region, Bering Strait etc.
)  (Atkinson, 2011b) ; -A measure of local linguistic density, equal for each language to the number of languages spoken less than 50 km away, on the basis of the polygons delimiting the respective areas of these languages, again given by the WLMS dataset; computations were performed with QGIS (Quantum GIS Development Team, 2017). There were 139 linguistic families, including a number of families restricted to a single language in the case of isolates or creoles. Several transformations were applied to the continuous variables: (i) a natural logarithm transformation was applied to the number of speakers, (ii) a cubic root transformation was applied to the local linguistic density, since it allows to expand the range of values without the issues raised by the log transformation, especially with 0 values, (iii) a scaling without centering was applied to all continuous variables -which is to say, we divided the values of each variable by the standard deviation of this variable, in order to be able to compare their respective effect sizes in the models.
4. 3) (R Development Core Team, 2017), using various packages that are cited in the following sections. The code used to produce the results and the figures can be found in Supplementary Presentation 1. We remain in a frequentist framework, and therefore do not refer to packages offering Bayesian approaches. Our models always include Distance from Africa, Number of Speakers and Local linguistic density as fixed continuous effects, and Family as an intercept random effect for reasons given in section 3. 1. The dependent/predicted variable is always Phonemic inventory size, also called Number of phonemes. In summaries of models, p-values lower than 0. 05 are in bold, but all exact p-values are given unless very small -smaller than 0. 001.