Yannick Bleu

Florent Bourquard

Valentin Gartiser

Anne-Sophie Loir

B Caja-Munoz

J Avila

Vincent Barnier

Florence Garrelie

Christophe Donnet

Graphene synthesis on SiO 2 using pulsed laser deposition with bilayer predominance

Keywords: Bilayer graphene, Pulsed laser deposition, Raman mapping

Here we report the low-defect synthesis of bilayer graphene film on SiO 2 with a nickel catalyst using pulsed laser deposition combined with rapid thermal annealing. A parametric study was performed with various initial amorphous carbon (a-C) film thicknesses and annealing temperatures and a fixed nickel catalyst film thickness. Raman spectra and mapping over large areas of up to 100 × 100 μm² were used to investigate the structure and the defects of graphene films. Optimal conditions for graphene growth were an initial a-C film thickness of 2 nm and an annealing temperature of 900°C. Results showed that 76% of the optimized film contained graphene bilayers, and 18% of the optimized film contained graphene monolayers. A transmittance of 87% at 550 nm is observed without any transfer process from the SiO 2 substrate. This paper presents experimental guidelines for optimal synthesis conditions to control graphene growth by pulsed laser deposition.

Introduction

Research on graphene has received considerable attention due to its outstanding physical and chemical properties, and its potential for a wide range of applications [START_REF] Geim | The rise of graphene[END_REF][START_REF] Novoselov | Electric Field Effect in Atomically Thin Carbon Films[END_REF][START_REF] Nair | Fine Structure Constant Defines Visual Transparency of Graphene[END_REF][START_REF] Kim | Focused-Laser-Enabled p-n Junctions in Graphene Field-Effect Transistors[END_REF][START_REF] Bonaccorso | Graphene photonics and optoelectronics[END_REF]. Several methods including mechanical exfoliation, annealing of SiC under ultrahigh vacuum, chemical vapor deposition (CVD), reduction of graphene oxide, and pulsed laser deposition (PLD) have been used to make graphene films [START_REF] Emtsev | Towards wafer-size graphene layers by atmospheric pressure graphitization of silicon carbide[END_REF][START_REF] Li | Graphene Films with Large Domain Size by a Two-Step Chemical Vapor Deposition Process[END_REF][START_REF] Hawaldar | Large-area high-throughput synthesis of monolayer graphene sheet by Hot Filament Thermal Chemical Vapor Deposition[END_REF][START_REF] Bleu | Review of Graphene Growth From a Solid Carbon Source by Pulsed Laser Deposition (PLD)[END_REF][START_REF] Pei | The reduction of graphene oxide[END_REF]. Among these methods, PLD is one of the alternative physical routes to the commonly used CVD process. Originally, PLD was mainly used to deposit thin films with high crystallinity, accurate stoichiometry, and thickness controlled up to the atomic monolayer [START_REF] Krebs | Pulsed Laser Deposition (PLD) --A Versatile Thin Film Technique[END_REF]. PLD has also been widely used for amorphous diamond-like carbon (DLC) synthesis, with different Csp 2 /Csp 3 ratios [START_REF] Sikora | Structure of diamondlike carbon films deposited by femtosecond and nanosecond pulsed laser ablation[END_REF]. In the present study, graphene films were synthesized using an amorphous solid carbon (DLC, or a-C) precursor with precisely controlled thickness. In the present study, graphene films were synthesized using an amorphous solid carbon (DLC, or a-C) precursor with precisely controlled thickness. From our best of knowledge, the presence of a metal catalyst is necessary for graphene synthesis from a solid carbon source. The absence of catalyst was previously investigated with CVD processes, in particular by Liu et al [START_REF] Liu | Metal-catalyst-free and controllable growth of high-quality monolayer and AB-stacked bilayer graphene on silicon dioxide[END_REF] and Barbosa et al. [START_REF] Barbosa | Direct synthesis of bilayer graphene on silicon dioxide substrates[END_REF]. However, such a route appears to favor a significant density of defects, compared to synthesis routes using a metal catalyst.

So, in the present study, we use a metal catalyst to obtain graphene layers with a low defect concentration. Several catalysts including nickel, copper, cobalt, copper-nickel alloy catalyst [START_REF] Reina | Growth of large-area single-and Bi-layer graphene by controlled carbon precipitation on polycrystalline Ni surfaces[END_REF][START_REF] Delamoreanu | Wafer scale catalytic growth of graphene on nickel by solid carbon source[END_REF][START_REF] Abd Elhamid | Study of graphene growth on copper foil by pulsed laser deposition at reduced temperature[END_REF][START_REF] Narula | Copper induced synthesis of graphene using amorphous carbon[END_REF][START_REF] Tyagi | Characterization of graphene films grown on CuNi foil substrates[END_REF][START_REF] Orofeo | Synthesis of large area, homogeneous, single layer graphene films by annealing amorphous carbon on Co and Ni[END_REF] have been used to obtain graphene from the carbon film precursor. Several studies have reported the growth of graphene by PLD using nickel catalyst [START_REF] Tite | Graphene-based textured surface by pulsed laser deposition as a robust platform for surface enhanced Raman scattering applications[END_REF][START_REF] Fortgang | Robust Electrografting on Self-Organized 3D Graphene Electrodes[END_REF][START_REF] Maddi | Nano-Architecture of nitrogen-doped graphene films synthesized from a solid CN source[END_REF][START_REF] Koh | Comparison of the mechanism of low defect few-layer graphene fabricated on different metals by pulsed laser deposition[END_REF][START_REF] Zhang | Fabrication and characterization of few-layer graphene[END_REF][START_REF] Bourquard | Electroanalytical Performance of Nitrogen-Doped Graphene Films Processed in One Step by Pulsed Laser Deposition Directly Coupled with Thermal Annealing[END_REF]. In fact, graphene synthesis with nickel is due to segregation of carbon at high temperatures. Due to the high solubility of carbon in nickel, the carbon atoms diffuse through the nickel catalyst and precipitate on the surface during cooling [START_REF] Seah | Mechanisms of graphene growth by chemical vapour deposition on transition metals[END_REF][START_REF] Zhang | Review of Chemical Vapor Deposition of Graphene and Related Applications[END_REF]. As precipitation is a non-equilibrium process, controlling the thickness of the graphene is challenging [START_REF] Li | Evolution of Graphene Growth on Ni and Cu by Carbon Isotope Labeling[END_REF][START_REF] Pang | Graphene as Transparent Electrode Material for Organic Electronics[END_REF][START_REF] Weatherup | On the Mechanisms of Ni-Catalysed Graphene Chemical Vapour Deposition[END_REF]. In addition, most of the graphene films made by PLD using a nickel catalyst have turned out to be heterogeneous with a mixture of single and multilayered graphene sheets. There is thus a need to optimize the PLD process for graphene growth to obtain a uniform large-area monolayer or bilayer graphene. In the present work, we studied the influence of two process parameters, initial amorphous carbon (a-C) thickness and the annealing temperature, on the growth of graphene using PLD and rapid thermal annealing. Our parametric study identified the optimal conditions for growing predominantly bilayer graphene. The structure and defects of the graphene films were characterized using a micro-Raman spectroscopic technique. Raman mapping was used for large areas of up to 100 × 100 μm² which has rarely been investigated but is indispensable to check lateral homogeneity, and statistical analysis to determine the number of layers and overall distribution of the graphene films on the substrate.

Experimental details

The different steps of sample preparation are shown in Figure 1. SiO 2 substrates were ultrasonically cleaned first in acetone, and then in ethanol and finally in deionized water baths. Nickel film (50 nm thick) was deposited by thermal evaporation on the top of the cleaned SiO 2 substrates in a vacuum chamber pumped at a base pressure of 10 -6 mbar. High purity (99.99%) Ni was molten thermally in a tungsten nacelle and evaporated towards the substrate. The Ni/SiO 2 substrates were then placed in a vacuum PLD chamber pumped at a base pressure of 10 -7 mbar for amorphous carbon (a-C) deposition. Carbon was ablated from high purity graphite (99.9995%) target using an excimer KrF laser (248 nm wavelength, 20 ns pulse duration, 10 Hz repetition rate) at room temperature. The fluence of the laser beam was kept constant at 5 J.cm -2 . The ablation time was adjusted to vary the thickness of the amorphous (a-C) film to 1, 2, 4, 5, 10 and 20 nm. Assuming a density of 3 g.cm -3 for the deposited a-C films, this corresponds to a carbon flux of 3.8x10 15 C.cm -2 .s -1 . The Ni/SiO 2 substrates were mounted on a sample holder placed at a distance of 40 mm from the graphite target. The final step consisted in heating the a-C/Ni/SiO 2 samples at temperatures ranging from 800 to 1000 °C for 420 s in a vacuum pressure of 10 -2 mbar using a RTA oven, with a heating rate of +15 °C/s and a cooling rate of about -0.5°C/s. Table 1 summarizes the processing conditions of the samples. Raman spectroscopy was used to characterize the synthesized material with an Aramis Jobin Yvon spectrometer (Horiba Jobin Yvon, Gières, France), with 442 nm (2.81 eV) excitation laser focused through an x100 objective with a high aperture, guaranteeing the micrometric resolution of the analysis, and providing precise Raman maps of the samples. The laser power was kept below 3 mW to avoid damaging the surface of the film and the diameter of the laser beam was estimated to be near 1 micrometer, near the diffraction limit at this wavelength. To examine the uniformity of the synthesized graphene, mapping of probed surfaces 20 × 20 micrometers in size, was performed for all samples at 442 nm, totaling 400 Raman spectra per map with a 1 m spot collected on each sample. For the sample with the optimal conditions, mapping was done in two different regions over areas of 20 x 20 µm² and 100 x100 µm². The Raman signals were acquired with a spectrometer equipped with a charge-coupled device (CCD) camera. Atomic Force microscopy measurements were performed using AGILENT 5500 microscope operating in tapping mode in the ambient environment at room temperature.

All the images were obtained at 1 Hz, 512 x 512 pixels (image definition). The AFM image treatment and root mean square roughness (RMS) were determined with Gwyddion software.

Scanning electron microscopy (SEM) images were recorded using a FEI Novanano SEM 200 operated at 15kV. XPS analysis was performed at Synchrotron SOLEIL (Saclay, France), ANTARES beam line. The ring operating conditions were 2.5 GeV electron energy, with injection currents of 500 mA and "Top-up" mode. Radiation was monochromatized using a plane-grating monochromator (PGM), which is characterized by a slitless entrance and the use of two varied linear spacing (VLS) gratings with variable groove depth (VGD) along the grating lines. The diameter of the X-ray spot impinging the surface is 140 µm and the X-ray energy was fixed at 700 eV for analysis of the graphene film. The photoemission spectra were taken with incident photon energies of 700 eV (see details in each figure 9

Results

The initial a-C thickness and growth temperature play a major role in determining the number of layers and the quality of graphene grown on SiO 2 with a nickel catalyst. In order to investigate their effect on graphene film architecture, we considered 18 sets of graphene growth conditions, crossing 6 initial a-C thicknesses with 3 annealing temperatures. All samples were characterized by Raman spectroscopy and mapping, the most widely used technique to investigate the structure, defects, and the number of layers in graphene materials [START_REF] Ferrari | Raman Spectrum of Graphene and Graphene Layers[END_REF][START_REF] Graf | Raman mapping of a single-layer to double-layer graphene transition[END_REF][START_REF] Malard | Raman spectroscopy in graphene[END_REF]. In graphene films, the D, G, and 2D bands are the most significant features observed in Raman spectroscopy. The G band appears near 1 580 cm -1 and is associated with These maps clearly show that the as-grown film is heterogeneous, containing single to multilayer graphene sheets. The difference in the number of graphene layers is remarkable, as detailed in the Discussion section below. With an initial a-C film thickness as low as 1 nm, the I 2D /I G ratio remains low (< 0.6), whatever the annealing temperature within the range 800-1 000 °C, compared to thicker a-C films. This may be because the initial carbon thickness is too thin to induce the formation of graphene layers over a large area in this temperature range, with domains exhibiting very low I 2D /I G ratios. Among all growth conditions, the highest average value of I 2D /I G ratio was 0.862, as can be seen on the map of the sample with an initial a-C film with a thickness of 2 nm at an annealing temperature of 900 °C. This suggests the formation of bilayer graphene. The samples a-C (4 nm -900 °C) and a-C (5 nm -900 °C) also had high I 2D /I G ratios of 0.809 and 0.822, respectively. However, their maps look more heterogeneous than that of sample a-C (2 nm -900 °C). Figure 3 shows the plot of average values of I 2D /I G as a function of initial a-C thicknesses and synthesis temperatures. At an annealing temperature of 900 °C, we observed a progressive decrease in the I 2D /I G ratio with an increase of from 2 to 20 nm in the thickness of the a-C film. This observation is consistent with that reported by Xiong et al. (Fig. 4d in [START_REF] Xiong | Single-Step Formation of Graphene on Dielectric Surfaces[END_REF]). At 1 000 °C, the I 2D /I G ratio exhibited little dependence on the initial a-C film thickness in the 2-20 nm range, whereas at 800 °C, the I 2D /I G ratios were systematically lower than those at higher temperatures. Considering the same growth temperatures for each initial thickness of the a-C, 900 °C was the temperature at which the average I 2D /I G ratio was higher for all initial a-C thicknesses except 20 nm. We, therefore, conclude that, in our growth conditions, the optimal temperature for high I 2D /I G ratios is 900 °C. The defect density was rather homogeneous except in samples with an initial a-C thickness of 1 nm, and the homogeneity was higher at both 900 °C and 1 000 °C than at 800 °C whatever the thickness of the a-C film. The lowest average I D /I G ratio of 0.069 was observed for the a-C (20 nm -1 000 °C) sample. Figure 5b shows the plot of average values of the I D /I G ratio deduced from Figure 5a, as a function of initial a-C thickness at different synthesis temperatures. The samples grown at 900 °C and 1 000 °C had a lower defect density, with I D /I G ratios ranging from 0.069 to 0.163 for a-C of 2 to 20 nm. In the sample synthesized at 800 °C, the defect density was much higher, with the I D /I G in between 0.136 and 0.460. From these results, we conclude that a temperature of 800 °C is too low as it produces a rather high defect density in graphene films, whereas at 900 and 1 000 °C, the graphene is formed with a significantly lower defect density. This defect density is comparable with that reported with CVD synthesis [START_REF] Umair | Controlled synthesis of bilayer graphene on nickel[END_REF].

Discussion

In this section, we discuss Raman mapping statistics in order to quantify the percentage graphene layer number distribution as a function of the initial a-C film thickness and annealing temperature. In our mapping procedure, areas with an I 2D /I G ratio >1.4 are considered to be representative of graphene monolayers, areas with I 2D /I G ratios between 0.75 and 1.4 are considered to be representative of graphene bilayers, and areas with I 2D /I G ratios below 0.75 are considered to be representative of graphene with three and more layers, as reported in the literature cited above.

Figure 6a shows the 3D plot of percentage graphene layer number distribution as a function of the initial a-C thickness at 800 °C. We observed that, at this annealing temperature, the asgrown graphene mostly had three or more layers. At a growth temperature of 900 °C (Figure 6b), graphene films contained a higher proportion of mono-and bilayers. In particular, sample a-C (2 nm) contained 89% of bilayers. At a growth temperature of 1 000 °C (Figure 6c), the heterogeneity of the synthesized graphene was much more pronounced, mostly bilayer, and three and more layers. Therefore, we conclude that our best sample for bilayer formation is the one with an initial a-C thickness of 2 nm and the growth temperature of 900 °C when the thickness of the nickel catalyst film is fixed at 50 nm. Such an optimum low thickness of a-C to form a dominant graphene bilayer is explained on the basis of previous works related to graphene synthesis from solid carbon films in the presence of a metal catalyst. It has been already shown [START_REF] Koh | Comparison of the mechanism of low defect few-layer graphene fabricated on different metals by pulsed laser deposition[END_REF][START_REF] Weatherup | Introducing Carbon Diffusion Barriers for Uniform, High-Quality Graphene Growth from Solid Sources[END_REF] that graphene growth mainly occurs during the thermal cycle by carbon dissolution and diffusion through the metal catalyst. A lower a-C film thickness of 1 nm probably does not provide enough carbon to form a homogeneous graphene layers when carbon precipitated on the Ni surface upon cooling after its dissolution during the steady-state high temperature range. Indeed, we observe that the different annealing temperatures have quite no effect on the graphene quality with such a low a-C film thickness. On the other side, an excessive initial a-C film thickness provides more carbon, but the rather high diffusion of carbon in nickel with temperature probably leads to the diffusion of carbon deep into the metal catalyst, and most of this carbon remains trapped upon cooling, limiting the quality of the graphene grown upon cooling. This may be a possible explanation of the optimum a-C film thickness of 2 nm observed with our protocol. To go further in the investigation of the bilayer homogeneity related to the sample a-C (2 nm -900 °C), we performed Raman mapping over a large area (100 x 100 µm²) with the step of 1 µm totaling 10 000 spectra. Such wide Raman mapping is rarely performed but makes it possible to obtain a more representative probed area of the graphene film. Figures 7a and7b show Raman mapping of I 2D /I G and I D /I G ratios with their average values of 1.06 and 0.12, respectively, indicating the predominant growth of bilayer and low defect density. The distribution of the number of layers was obtained by statistical analysis. We found that 18% of the 100 ×100 μm² probed area is covered by graphene monolayers, 76% by graphene bilayers and only 6% by more than three graphene layers (Figures 7c and7d). This result is consistent with the results of a study by Peng et al. [START_REF] Peng | Direct Growth of Bilayer Graphene on SiO2 Substrates by Carbon Diffusion through Nickel[END_REF] related to bilayer graphene growth using a polymer as a solid carbon source. Through Raman mapping, these authors observed 70% of bilayer coverage in an area of 100 x 100 µm². Figures 7e and7f show the shape and Lorentzian fitting of the 2D band of the bilayer spectrum and the other Raman parameters extracted from this spectrum. The 2D band shows an asymmetric band with an FWHM around 61 cm -1 and can be decomposed with four Lorentzian peaks, each one with a FWHM of 30 cm -1 , corresponding to the AB stacking of the bilayer [START_REF] Gong | Layer-Controlled and Wafer-Scale Synthesis of Uniform and High-Quality Graphene Films on a Polycrystalline Nickel Catalyst[END_REF][START_REF] Madito | Raman analysis of bilayer graphene film prepared on commercial Cu(0.5 at% Ni) foil[END_REF][START_REF] Yang | Layer-selective synthesis of bilayer graphene via chemical vapor deposition[END_REF][START_REF] Fang | Rapid Identification of Stacking Orientation in Isotopically Labeled Chemical-Vapor Grown Bilayer Graphene by Raman Spectroscopy[END_REF]. Our results demonstrate the possibility of synthesizing predominantly bilayer graphene with AB stacking mode from a solid carbon source using pulsed laser deposition and rapid thermal annealing, as observed by Raman over a rather large area. In addition to Raman characterization, atomic force microscopy (AFM) and scanning electron microscopy (SEM) were performed to get the topological information about our best sample a-C (2 nm -900 °C). Further XPS characterization were done in order to get the chemical composition. Additionally, since the sample was transparent after graphene synthesis, transmittance measurement was carried out for this sample.

"Figure 8a shows the surface morphology with an RMS of 182 nm observed using AFM.

This image suggests a relatively rough surface with the presence of nickel clusters. The SEM image in Figure 8b confirms this surface morphology showing the island-shaped metallic nickel nodules. These Ni nodules have been also previously reported by others [START_REF] Xiong | Single-Step Formation of Graphene on Dielectric Surfaces[END_REF][START_REF] Banno | Transfer-free graphene synthesis on insulating substrates via agglomeration phenomena of catalytic nickel films[END_REF] with graphene grown in the presence of Ni catalyst, using rapid thermal annealing in the temperature range 900-1100 °C. However, we cannot exclude the presence of a residual very thin film of Ni on the rather flat areas surrounding the Ni clusters. EDX probing in such regions (not shown) confirms the presence of residual nickel. In such a way, any AFM quantification of the surface to extract the number of graphene layers should be carried out with extreme caution. Indeed, even though theoretically it is possible to measure the number of layers in AFM using the height from line profile, in practice in our case, it is hard to achieve the necessary vertical resolution with a rough surface probably covered by residual nickel. The selected lines labelled 1-2-3-4 on Figure 8a are typical of the surface morphology between the Ni nodules, with height quantification depicted in Figures 8c-f. The profile 1 gives height values between 0.56 and 2.18 nm suggesting the presence of mono and bilayer graphene, as reported in references [START_REF] Yao | Histogram method for reliable thickness measurements of graphene films using atomic force microscopy (AFM)[END_REF][START_REF] Obraztsova | Statistical analysis of atomic force microscopy and Raman spectroscopy data for estimation of graphene layer numbers[END_REF]. The profile 2 gives height values from 1.82 to 7.04 nm suggesting the presence of bilayer to multilayer graphene. The profiles 3 and 4 give the height values rather high from 2.59 to 69.18 nm, again consistent with multilayer graphene.

However, these values should take with very much care, because of the presence of nickel catalyst residual and surface roughness that may affect the thickness estimation. As mentioned before, those graphene layers certainly cover some residual Ni in the form of a very thin film on the SiO 2 substrate, thus consistent with a roughness higher than the roughness of graphene layers covering SiO 2 . This is one experimental limit of the protocol used at hand, which requires in the future further investigations to obtain graphene layers without any traces of residual Ni if such a catalyst is required for the graphene growth."

In Figure 9a Since we observed nickel residual on our sample, we performed the nickel etching using 4M of FeCl 3 solution before the transmittance measurement. We measured the transmittance (T) of both bilayer graphene after Ni etching and the starting material before annealing (a-C (2nm)/ Ni (50)) on glass substrates for comparison (Figure 10). The transmittance values of the starting material at 550 nm is about 1.47 % (mainly due to the Ni thin film), whereas the one for our bilayer graphene is about 87.21%. Theoretically, each graphene layer absorbs 2-3% [START_REF] Nair | Fine Structure Constant Defines Visual Transparency of Graphene[END_REF] of the incident light at 550 nm, which means that the bilayer graphene transmittance value should be around 94% as reported in previous works [START_REF] Sun | Growth of graphene from solid carbon sources[END_REF][START_REF] Liu | Synchronous growth of AB-stacked bilayer graphene on Cu by simply controlling hydrogen pressure in CVD process[END_REF]. Nevertheless, there is an offset between our transmittance value and the the theoretical value. However, our result is consistent with what was observed by Lee et al. [START_REF] Lee | Homogeneous bilayer graphene film based flexible transparent conductor[END_REF]. They reported that the decreasing of the transmittance value can be due to the transfer method. We believe that it might a similar effect here in our case, the deviation is likely due to the remaining residual nickel nodules observed by SEM.

Conclusion

Here, we have reported a parametric study in which we adjusted the initial thickness and growth temperature of amorphous carbon, using pulsed laser deposition and rapid thermal annealing with nickel catalyst films on a SiO 2 substrate. From the experimental findings, we deduced that the optimized process parameters to obtain a high proportion of graphene bilayers were an initial a-C thickness of 2 nm and an annealing temperature of 900°C. A transmittance of 87% at 550 nm is observed without any transfer process from the SiO 2 substrate. Under these synthesis conditions, bilayer graphene was formed on 76% of the 100 x100 µm² probed surface, monolayer graphene on 18%, and three and more layer graphene on 6%, with a low defect density. The investigated synthesis route allows to synthetize predominantly bilayer graphene films, with a significant lower density of defect than graphene film architectures obtained by CVD without any metal catalyst. However, the residual nickel catalyst in the form of micrometer-size nodules remains a limitation to ensure a homogeneous distribution of bilayer graphene over a wide surface exempt of catalyst residues. This finding demonstrates the possibility of obtaining graphene bilayers over a large area using an alternative less frequently investigated synthesis route (compared to CVD), pulsed laser deposition combined with rapid thermal annealing. However, more work is required to investigate the synthesis of low-defect graphene films from a solid carbon source, without any use of metal catalyst.

Figure 1 :

 1 Figure 1: Synthesis route for graphene films obtained by pulsed laser deposition and rapid thermal annealing on SiO 2 .

  panel), with 190 meV energy resolution. UV-Visible spectroscopy in transmission mode was performed by a spectrophotometer Cary50 Probe (Varian) within the spectral range 200-800 nm.

  Figures 2 and 3 show the Raman maps and the average values of the I 2D /I G ratio of all the samples over an area of 20 x 20 µm².

Figure 2 :

 2 Figure 2: Raman spectroscopy maps of I 2D /I G of all samples.

Figure 3 : 3 . 2 .

 332 Figure 3: (a) Summary of the mean values of each I 2D /I G map; (b) plot of the effect of initial a-C thickness on mean I 2D /I G values as a function of growth temperature.

Figure 4 :

 4 Figure 4: Raman spectroscopy maps of I D /I G of all the samples.

Figure 5 :

 5 Figure 5: (a) Table summarizing the mean values of each I D /I G map; (b) plot of the effect of initial a-C thickness on mean I D /I G values as a function of growth temperature.

Figure 6 :

 6 Figure 6: Raman mapping statistics: (a) 3D plot of percentage graphene layer number distribution as a function of the initial a-C thickness (left) and the coverage percentage values (right) at 800 °C; (b) 3D plot of percentage graphene layer number distribution as a function of the initial a-C thickness (left) and the percentage distribution values (right) at 900 °C; (c) 3D plot of percentage graphene layer number distribution as a function of the initial a-C thickness (left) and the percentage distribution values (right) at 1 000 °C.

Figure 7 :

 7 Figure 7: Raman mapping of a large 100 ×100 μm² region, of sample a-C (2 nm -900 °C): (a) Raman mapping of I 2D /I G ratio with an average value of 1.06; (b) Raman mapping of I D /I G ratio in a 100 ×100 μm² region with the average value of 0.12; (c) spectra of the graphene with different numbers of layers in Raman mapping of graphene on a SiO 2 substrate; (d) Statistical histogram of the Raman mapping of I 2D /I G ratio showing the predominance of bilayers; (e) Fitting of the 2D band in the Raman spectrum of bilayer graphene showing an asymmetric shape and four Lorentzian peaks corresponding to AB stacking; (f) table showing the other Raman parameters of the bilayer graphene spectrum.

Figure 8 :

 8 Figure 8: AFM and SEM images of sample a-C (2 nm -900 °C): (a) AFM image showing the surface morphology with a RMS value of 182 nm; (b) SEM image showing different contrast and the nickel residual nodules; (c) AFM line profile 1 spectrum; (d) AFM line profile 2 spectrum; (e) AFM line profile 3 spectrum; (f) AFM line profile 4 spectrum. The height of all the peaks in the spectra corresponds to the thickness of the probed area.

  , the XPS survey spectrum of our best sample a-C (2 nm -900 °C) shows carbon located near 284 eV, oxygen located near 533 eV and some residual of nickel. The presence of the oxygen might be due to top-surface oxidation and contamination after the a-C film synthesis and/or during thermal annealing at 10 -2 mbar. The nickel traces confirm what was observed by SEM and AFM. Figure9bshows the C1s deconvolution into two components.The first one is centered at 284.4 eV and assigned to sp 2 hybridized C atoms in graphene. This component is the most intense and prominent in graphitic carbon indicating that most of the amorphous carbon has been transformed to graphene or graphitic carbon[START_REF] Blume | Characterizing Graphitic Carbon with X-ray Photoelectron Spectroscopy: A Step-by-Step Approach[END_REF]. The other less intense component is located at 285.2 eV, corresponding to C-O bonds. Figure 9c shows the O1s decomposed in two components. The first component, located at 533.4 eV, and corresponds to O-C bonds. The second component, located at 531.7 eV, corresponds to O-C=O oxygen group[47-49].

Figure 9 :

 9 Figure 9: XPS spectra of sample a-C (2 nm -900 °C): (a) XPS survey spectrum; (b) XPS C 1s spectrum; (c) XPS O 1s spectrum.

Figure 10 :

 10 Figure 10: Transmittance curve as a function of wavelength for both: as-deposited sample (bottom) and the synthesized bilayer graphene after thermal annealing and FeCl 3 etching (top). The inset at the top figure shows the bilayer graphene after Ni etching.

Table 1 :

 1 Summary of the growth conditions.

Acknowledgments

This work was conducted with the financial support of the Future Program Lyon Saint-Etienne (PALSE) in the framework of the LABEX MANUTECH-SISE (ANR-10-LABX-0075) from the University of Lyon (ANR-11-IDEX-0007), under the Investissements d'Avenir program managed by the French National Research Agency (French acronym ANR).


Penelope Troude

Laurence Foix-L'hélias

Anne-Marie Raison-Boulley

Christine Castel

Jean Bouyer

Elise De La

Pénélope Troude

Laurence Foix L'hélias

Elise De

Apgar Scores Reported in Personal Child Health Records: Validity for Epidemiological Studies?

Keywords: Apgar score, infant, newborn, medical records health record, CI confidence interval

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In studies on child health and development, neonatal factors have to be considered since it has been clearly demonstrated that pregnancy, delivery and events during the first days of life are correlated with future child or even adult health [START_REF] Gissler | Can children's health be predicted by perinatal health?[END_REF][START_REF] Frontini | Low birth weight and longitudinal trends of cardiovascular risk factor variables from childhood to adolescence: the bogalusa heart study[END_REF][START_REF] Bergvall | A Study Among Swedish Twins[END_REF] . Among child health indicators at birth, the Apgar score has been shown to predict neonatal mortality and neurological development [START_REF] Apgar | A proposal for a new method of evaluation of the newborn infant[END_REF][START_REF] Casey | The continuing value of the Apgar score for the assessment of newborn infants[END_REF][START_REF] Moster | Joint association of Apgar scores and early neonatal symptoms with minor disabilities at school age[END_REF][START_REF] Moster | The association of Apgar score with subsequent death and cerebral palsy: A population-based study in term infants[END_REF][START_REF] Thorngren-Jerneck | Perinatal factors associated with cerebral palsy in children born in Sweden[END_REF] . This score evaluates newborns at 1 and 5 minutes after birth on the basis of 5 vital signs (heart rate, respiratory effort, color, muscle tone and responsiveness to stimuli). In most countries, no national neonatal registries exist, and neonatal information must be retrieved from the medical records of the maternity departments. However, data collection from obstetric records is problematic because medical records are dispersed in various hospitals, making data collection very timeconsuming, expensive and sometimes impossible.

The personal child health record (PCHR) could be a promising alternative approach to obtain the neonatal data required for epidemiological studies, since PCHRs containing information on the health of newborns exist in most European countries [START_REF] Rollet | Le carnet de santé pour les enfants en Europe[END_REF] . In France, the newborn's PCHR is systematically given to his/her family on the day of discharge from the maternity department and is kept by the family at home. It contains information on health status at birth, the child's diseases, vaccinations and growth curves, and also advice for parents and health education pages. Several studies have found a 90 to 100 percent completion rate for birthweight in PCHRs [START_REF] Jeffs | Retention and use of personal health records: a population-based study[END_REF][START_REF] Lakhani | Evaluation of a home based health record booklet[END_REF][START_REF] Chalumeau | Information recorded by maternity ward staff in permanent pediatric health records[END_REF] . Studying their use for epidemiological purposes, the Millennium Cohort study found that the child's last weight was recorded in 97 percent of PCHRs consulted [START_REF] Walton | Use of personal child health records in the UK: findings from the millennium cohort study[END_REF] . Hampshire et al found in the UK that child health surveillance reviews were well recorded in PCHRs [START_REF] Hampshire | Are child health surveillance reviews just routine examinations of normal children?[END_REF] . The satisfactory completion suggested by these studies indicates that PCHRs are potentially useful for epidemiological studies.

However, this completion rate may be lower for some categories of information. For instance, a British review of 140 PCHRs found that information related to delivery was recorded in only 84 percent [START_REF] Lakhani | Evaluation of a home based health record booklet[END_REF] and an Australian study of retention and use of PCHRs found Apgar scores recorded in 86 percent of those examined [START_REF] Jeffs | Retention and use of personal health records: a population-based study[END_REF] . Furthermore, a French study has suggested that missing information in PCHRs might not be random: socially sensitive information could be voluntarily omitted [START_REF] Dommergues | Personal child health record: informativity and confidentiality[END_REF] . The authors suggested such possible bias with regard to immunodeficiency virus status, genetic diseases, psychological disorders and Apgar scores. Because the PCHR is kept by the family and is often passed on to other persons, particularly in school, it raises the problem of confidentiality. In consequence, accuracy of reporting may be voluntarily compromised by physicians when recording information considered as potentially socially detrimental to the child if disclosed. Such a hypothesis could be termed "intentional data alteration" and requires testing. In particular, it would be of great interest to investigate this hypothesis with regard to Apgar scores, which are an important long-term health predictor [START_REF] Casey | The continuing value of the Apgar score for the assessment of newborn infants[END_REF] and could be considered as potentially sensitive information since they may be seen as a "label" and are thought to be predictive of the child's development [START_REF] Casey | The continuing value of the Apgar score for the assessment of newborn infants[END_REF][START_REF] Moster | The association of Apgar score with subsequent death and cerebral palsy: A population-based study in term infants[END_REF] .

The aim of this study was to test the "intentional data alteration" hypothesis on Apgar scores in the PCHR in individual children, using maternity medical records as the gold standard.

Methods

The study was carried out between January 1 and February 4, 2006, in two hospitals in the Paris region (France). Foch hospital has a level II maternity department (with a neonatal department) and Béclère hospital a level III maternity department (with a neonatal intensive care unit). The study received approval from the French Data Protection Authority (CNIL) in September 2005 (authorization number 05-1335).

During the inclusion period, 484 women delivered and within 24 to 48 hours following delivery the majority (n = 473, 98%) were asked by pediatricians to participate in the study. Eleven mothers were not asked to participate because they were discharged before they could be seen by the pediatricians. Others (n = 38) were excluded because of adverse pregnancy outcome (fetal death in utero or pregnancy termination) or poor condition of the newborn (n = 12), mother's transfer to an intensive care unit for more than 48 hours (n = 4), age under legal majority (n = 2), difficulties with the French language (n = 16), or major psychological disorders (n = 4). Of the 435 remaining women, 422 agreed to take part (participation rate 97%). We first collected from medical records information on maternal health, pregnancy and the child's health during the first days of life at the maternity hospital.

Six weeks after delivery, mothers were asked to fill in a postal questionnaire. A total of 392 mothers responded to the questionnaire (response rate 93%), which included items on parents' sociodemographic characteristics, antenatal and obstetric complications, delivery, child's health at birth and conditions of return home. Mothers were asked to copy data from the PCHR concerning gestational age, birthweight, birth size, cranial circumference at birth and Apgar scores at 1 and 5 minutes. The relevant pages of the PCHR were indicated in the postal questionnaire to help mothers find the information.

In order to investigate specifically the "intentional data alteration" hypothesis on Apgar scores, we controlled for possible general altered data in PCHRs by selecting mothers who had accurately reported, in the questionnaire, neonatal information that was not socially sensitive (birthweight, birth size and cranial circumference at birth).

Reporting of this neonatal information was considered as accurate if the mother's reports of birthweight, birth size and cranial circumference at birth were within 2 percent of the values noted in medical records (which represents a maximum variation of 50 g for birthweight, 5 mm for birth size and 2 mm for cranial circumference at birth). In multiple pregnancies we included only the firstborn of the twins or triplets.

We excluded 5 mothers because the 1-min or 5-min Apgar score was missing in the medical records. Finally, analyses were conducted among 331 mother-child dyads.

To assess the validity of Apgar scores, information from medical records was considered as the gold standard. Sensitivity and specificity of PCHR-reported Apgar scores were calculated using a cut-off of 7 (< 7 or ≥ 7) since a score from 7 to 10 indicates a child in good condition [START_REF] Letko | Understanding the Apgar score[END_REF][START_REF] Montgomery | Apgar Scores: Examining the Long-term Significance[END_REF] . Percentages were compared using the chisquare test or Fisher's exact test. All statistical analyses were performed using Stata/SE 9.0 (Stata Press, College Station, TX, USA).

Results

The characteristics of the study population are described in Table 1. The first part of the table summarizes the child's characteristics at birth. Of these 331 children, 7.6 percent were preterm and 12.7 percent were transferred to a neonatology unit. The second part of Table 1 describes the sociodemographic characteristics of mothers. Most of the mothers were French (others were mainly natives of Africa or Europe) and lived as a couple, their mean age was 32 years and 77 percent had an educational level higher than the baccalaureat (high school diploma).

The 1-min Apgar score was missing in 7.9 percent (n=26) of PCHRs and the 5-min score in 6.0 percent (n=20). When the 1-min Apgar score noted in the medical records was ≥ 7, 5.0 percent (n=15) of 1-min Apgar scores were missing in the PCHR versus 37.9 percent (n=11) when the Apgar score in the medical records was < 7 (p <0.001). Similar results were observed for 5-min Apgar scores, which were missing in 5.5 percent (n=18) of PCHRs when the score noted in the medical records was ≥ 7 and in 66.7 percent (n=2) of PCHRs when the score was < 7 in the medical records (p = 0.01).

Table 2 shows the agreement between medical records and PCHRs for the 1-min Apgar score when this score was noted in the PCHR (n=305). Using medical records as the gold standard, specificity for PHCR-reported 1-min Apgar score < 7 was 100% (95% CI [98.7%, 100%]) and sensitivity 33.3% [13.3%, 59.1%]. When comparing the exact value of the Apgar score (and not only by classes <7 / ≥ 7), the 1-min Apgar scores were wrongly reported in 81 PCHRs: they were all higher in the PCHR than in medical records (on average, 1.9 point higher in the PHCR).

Finally, when considering all the 1-min Apgar scores noted in the medical records < 7 (n=29), we observed that 37.9% were missing, 41.4% were reported as ≥ 7 in the min Apgar scores noted in the medical records ≥ 7 (n=302), we observed that 5.0% were missing, 0.0% were reported as < 7 in the PCHR and 95.0% were reported as ≥ 7 in the PCHR.

Of the 28 wrongly reported 5-min scores in PCHRs, the same tendency to overestimation as for 1-min scores was observed: only one 5-min Apgar score was higher than in medical records. Sample size for low 5-min Apgar scores was too small to estimate sensitivity and specificity analyses with a cut-off of 7, but with a 5-min score cutoff of 9 (< 9 or ≥ 9), results were similar to those for 1-min Apgar scores: specificity was 100% [98.8%, 100%] and sensitivity 27.3% [6.0%, 61.0%].

Discussion

Our results supported the hypothesis that the Apgar scores reported in PCHRs may provide altered information, as low scores are more likely to be misreported. Firstly, we should not be reassured by the fairly low rate of missing scores (6-8 percent) since they were not missing at random (more missing values in PCHRs when Apgar scores were low in medical records). Secondly, Apgar scores reported in PCHRs were systematically higher than in medical records when the two sources differed. This could induce differential biases. Indeed, when the 1-min score was less than 7 in the PCHR, we could be almost certain that it was the same in medical records (positive predictive value 100%); on the contrary, only 20.7 percent of the lowest 1-min Apgar scores in the medical records (lower than 7) were correctly reported in the PCHR (because of both missing values and overestimation of the Apgar score reported in the PCHR). When the 1-min Apgar score was reported in the PCHR, it lacked the sensitivity to reflect low scores reported in medical records but its specificity was good.

In our study population, the mothers' educational level was higher than in the general French population [START_REF] Blondel | Enquête périnatale 2003: situation en 2003 et évolution depuis 1998[END_REF] . This was mainly due to the recruitment of the participating maternity hospitals. Thus, we cannot rule out an overestimation of the validity of Apgar scores reported from PCHRs by the mothers of higher educational level in our study. However, since our objective was to investigate how Apgar scores were recorded in PCHRs, we did not seek to obtain a representative population of women giving birth.

On the contrary, we sought to minimize misreporting by mothers in order to attribute, as far as possible, low validity of Apgar scores to reporting in PCHRs instead of to mothers' copying errors. For the same reason, analysis was restricted to women who accurately reported information other than Apgar scores.

Previous analysis of PCHRs mostly focused on their use and acceptability and rarely

on the validity of the information they contain [START_REF] Jeffs | Retention and use of personal health records: a population-based study[END_REF][START_REF] Lakhani | Evaluation of a home based health record booklet[END_REF][START_REF] Walton | Use of personal child health records in the UK: findings from the millennium cohort study[END_REF][START_REF] Hampshire | Are child health surveillance reviews just routine examinations of normal children?[END_REF][START_REF] O'flaherty | Personal health records: an evaluation[END_REF][START_REF] Saffin | How well are parent held records kept and completed?[END_REF][START_REF] Emon | Reliability of parent-held child health records[END_REF] . Some studies, showing relatively good completion of PCHRs, suggested that they are potentially useful in epidemiological studies [START_REF] Jeffs | Retention and use of personal health records: a population-based study[END_REF][START_REF] Lakhani | Evaluation of a home based health record booklet[END_REF][START_REF] Chalumeau | Information recorded by maternity ward staff in permanent pediatric health records[END_REF][START_REF] Saffin | How well are parent held records kept and completed?[END_REF] . However, these studies did not specifically assess reliability of neonatal information reported in PCHRs in comparison with other sources, and almost none addressed the issue of the Apgar score. When comparing distribution of PCHR Apgar scores with that of scores collected in the French Department for Mother and Infant Welfare, Vincelet et al suggested that Apgar scores could be underreported in PCHRs [START_REF] Vincelet | How are personal child health records completed? A evaluation study[END_REF] . However, the implication of these results was limited because the PCHR data was only globally compared with another source, without checking the validity of the PCHR at the individual level. In our study, we were able to compare individual PCHR information to that in the child's medical record, and we found that low Apgar scores were both more often missing and more often wrongly reported in PCHRs when they were low in medical records. This observation supported the hypothesis of "intentional data alteration" of Apgar scores, leading not only to missing values when the information is socially sensitive but also to misreporting (by noting a higher Apgar score than the true score).

Misreporting of low Apgar scores in PCHRs may be explained by the fact that both physicians and parents overestimate the importance of this score as a predictor of a child's health and development. In an American study among 172 health care professionals, Paneth and Fox showed a 10-fold overestimate of the impact of a low 5min Apgar score on handicap risk and concluded that the score's predictive value is largely overestimated by professionals, who in their study were mainly obstetricians, pediatricians and nurses [START_REF] Paneth | The relationship of Apgar score to neurologic handicap: a survey of clinicians[END_REF] . Other studies found that parents did not properly understand the purpose or value of the score, thinking that their child had somehow failed if he or she did not receive a score of 10, whereas a score higher than 7 is considered as normal 16, 17 . It would be interesting to investigate more thoroughly the reasons for misreporting of low Apgar scores in PCHRs, in particular possible overestimation of its predictive value by physicians as well as misrepresentation by parents, in order to increase the quality of this information in the PCHR by better informing physicians and parents as to the purpose of the Apgar score. Moreover, similar research on validity of Apgar scores reported in PCHRs in other hospitals and other countries would be useful to confirm our results.

Our results show that Apgar scores recorded in PCHRs are a biased source of information for epidemiological purposes. So although the Apgar score may be pertinent for assessing the neonatal period [START_REF] Casey | The continuing value of the Apgar score for the assessment of newborn infants[END_REF][START_REF] Montgomery | Apgar Scores: Examining the Long-term Significance[END_REF][START_REF] Jepson | The Apgar score: evolution, limitations, and scoring guidelines[END_REF][START_REF] Bharti | A review of the Apgar score indicated that contextualization was required within the contemporary perinatal and neonatal care framework in different settings[END_REF][START_REF]The Apgar score[END_REF] , we suggest that the Apgar scores reported in the PCHR should not be used in epidemiological studies on children's longterm outcome. Instead, they should be replaced by a composite indicator compiled from more accurate information that is less socially sensitive, such as birthweight, gestational age and transfer of the newborn to a neonatology unit, that has been shown to be relevant also for predicting future child health 1 .

Table 1. Characteristics of the Study Population (n = 331)

Children's characteristics (a) n

Table 2 . Agreement of 1-min Apgar Score between Medical Records and Personal Child Health Records (PCHR) when Score was Recorded in the PCHR (n = 305)

 2

			1-min Apgar score in medical records	Total
			< 7 n (%)	≥ 7 n (%)	n (%)
	Reported	< 7	6 (33.3)	0 (0)	6 (2.0)
	in PCHR	≥ 7	12 (66.7)	287 (100)	299 (98.0)
	Total		18 (100)	287 (100)	305 (100)
			Sensitivity 33.3% [13.3%, 59.1%]
			Specificity 100% [98.7%, 100%]


Thomas Vuillaume
email: vuillaume@lapp.in2p3.fr

Mikaël Jacquemont
email: jacquemont@lapp.in2p3.fr

Luca Antiga

Alexandre Benoit

Patrick Lambert

Gilles Maurin

Giorgia Silvestri

Mikael Jacquemont

GammaLearn -first steps to apply Deep Learning to the Cherenkov Telescope Array data

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

The Cherenkov Telescope Array

The Cherenkov Telescope Array (CTA) is the next generation of Imaging Atmospheric Cherenkov Telescopes (IACT) used for gamma-ray astronomy. CTA aims at studying the very-high-energy universe, such as cosmic ray origins, astrophysical phenomena, fundamental physics and cosmology [1].

CTA will be composed of two arrays of IACTs in two different observing locations (one in each hemisphere) in order to be able to observe the full sky and achieve different science goals. Today in pre-production phase, CTA is planned to acquire its first observational data in the coming years.

IACT data reconstruction

The high sensitivity of CTA will lead to the acquisition of unmatched volumes of raw data in gamma-ray astronomy with several PB per year. Such volumes of data require complex systems to handle, transfer and archive the data, but also efficient analysis methods without sacrificing the instrunment's performances.

Typical IACTs are composed of an array of telescopes operating as a single instrument to observe atmospheric showers generated by high-energy particles or photons entering the atmosphere. For gamma-ray astronomy, the showers initiated by charged particles represent a background that must be classified as such and eliminated to retrieve the gamma-ray light emitted by astronomical sources.

By combining the information from several telescopes, one can use stereoscopic reconstruction to derive the physical parameters (arrival direction, energy, particle type) of the original particle. This reconstruction is a complex but central process of the instrument. Recent advances in machine learning led to believe the stereoscopic reconstruction could be handled using convolutional neural networks (CNN) and some work has been done in this regard, in CTA [START_REF] Nieto | Cherenkov Telescope Array[END_REF][START_REF] Mangano | Extracting Gamma-Ray Information from Images with Convolutional Neural Network Methods on Simulated Cherenkov Telescope Array Data[END_REF], or in other IACT [START_REF] Shilon | [END_REF].

These CNN have presented great performance improvements in many domains, including astronomy [START_REF] Feng | The analysis of VERITAS muon images using convolutional neural networks[END_REF][START_REF] Schawinski | [END_REF], being able to extract more information from raw data than traditional methods based on human selected features. Moreover, they present the advantages to learn directly from data and therefore to replace complex processing pipelines and to be very fast during the prediction (a.k.a inference) step, thus making them usable at speeds comparable to data acquisition ones.

Deep learning for CTA

Training deep networks for regression and classification requires large amounts of annotated data. To do so in the case of CTA, we will use simulated monte-carlo data produced to understand the instrument's response function. Two main issues arise when trying to apply Deep Learning techniques to these data however:

• CTA will be composed of cameras of different types, some with unconventional images in the sense that they do not present cartesian grids of pixels and are therefore not adapted to standard Deep Learning frameworks

• CTA, alike other IACT, takes advantage of the stereoscopic information to reconstruct the primary particle parameters. A way to combine several images coming from different telescopes and presenting different characteristics (shapes, sizes...) needs to be found.

In order to tackle these issues, the GammaLearn project, born from a collaboration of the Laboratory of Annecy of Particle Physics (LAPP), the Laboratoire d'Informatique, Systèmes, Traitement de l'Information et de la Connaissance (LISTIC) and an industrial partner specialized in Deep Learning solutions for manufacturers, Orobix, has been funded. We present here the preliminary stages of two solutions in development, to process unconventional images and take advantage of the stereoscopic information with Deep Learning.

Convolution and pooling for unconventional images

Convolution and pooling operations, which are core components of Deep Learning, as well as image processing tools in general have been developed to process rectangular and regular pixel grid images. However, some imaging sensors, including CTA LSTCam [7] and NectarCam [8], produce unconventional images. A common approach, allowing to use traditional image processing frameworks and in particular convolutional neural network ones, is to re-sample these unconventional images into ones with a rectangular and regular grid and a rectangular shape. Another approach, for unconventional images with regular grid, for example hexagonal grid images, is to shift them into a Cartesian grid via a geometrical transformation. However, such approaches needs additional image processing, generally performed on the CPU, slowing down both the training and inference phases of Deep Learning. Moreover, these approaches may result in image shape and size changing, and may introduce distortions that can potentially affect the performance of the method for its dedicated task.

In order to prevent these drawbacks, we propose to re-implement the convolution and pooling operators (thereafter denoted indexed operations) in the following way. Given that the neighbors of each pixel of interest is known and provided, we first build a matrix of neighbors indices for each pixel of interest (including itself). Then, we re-arrange the data according to this indices matrix and apply the classical general matrix multiply operation GEMM [START_REF] Van De Geijn | BLAS (Basic Linear Algebra Subprograms[END_REF] for convolution or any suitable function (max, average, softmax) for pooling.

In Fig. 1 we exhibit an example of how to build the indices matrix for hexagonal grid images. After a pooling operation, the index matrix needs to be rebuild, as shown in Fig. 2. This work will also be presented in more details in a paper, that has been accepted for publication for VISAPP 2019 conference.

Stereoscopy

Stereoscopy is an essential part of the IACT reconstruction methods. Indeed, single images only give a limited quantitiy of information compared to the association of images from several telescopes combined with the position of these telescopes. However, traditional Deep Learning networks have been developed to deal with single images. An adaptation of these networks and establishment of new methods based on CNN is therefore required. [START_REF] Shilon | [END_REF] has shown that LSTM networks could be used to combine the images from several telescopes. In this preliminary work, we have considered a simpler solution consisting in duplicating the convolution part of the network (that learns a representation of the input) as many times as the number of telescopes, and then concatenating the obtained representations to feed the dense part of the network, leading to the architecture presented Fig. 3. This implies to feed the branches of telescopes that didn't trigger with inputs of zeros. The main disadvantage of this method is the number of telescope branches increasing dramatically when taking into account the whole CTA, leading to feeding the model with sparse inputs (as only several telescopes trigger for the same event). As we focus for this work on the four LSTs of CTA, this is not an issue. Each entry is fed to the same convolution block (e.g. the convolutional part of VGG or a ResNet, in this case four convolutional layers with maxpooling and batchnorm). The feature vectors thus created are concatenated and the result is fed to the multitasking block (a fully connected network) inferring at the same time the energy, the arrival direction and the virtual (as the shower doesn't reach the ground) impact point of the shower event.

GammaLearner framework

The aim of the GammaLearn project is to find the best possible neural networks for gamma / cosmic rays separation and gamma parameters reconstruction. As the Deep Learning is a very empirical process, many hyperparameters and parameters initialization combinations will be explored and hopefully fine tuned. This represents a lot of learning cycles, and highlights the need of a tool to ease this process. The GammaLearner framework has been designed to address this issue, automatically dealing with bookkeeping all the experiments information. Moreover, it enables the use of the indexed operations and stereoscopy introduced before and developed especially for CTA in a more friendly manner.

GammaLearner components

As shown on Fig. 4, GammaLearner relies on PyTorch [START_REF] Paszke | Automatic differentiation in PyTorch[END_REF] for the Deep Learning fundamental components (tensor objects, automatic differentiation) augmented by the indexed convolution, described in 2.1, to handle unconventional images. It uses Ignite [START_REF]Ignite[END_REF] for the organization of the training process itself, Tensorboard [START_REF] Googleinc | Tensorboard[END_REF] (via TensorboardX [START_REF] Tensorboardx | [END_REF]) and Gammaboard as visualization tools. GammaLearner consists of an experiment runner tool, the engine of the framework, and a collection of functions and classes needed for the Deep Learning process to:

• load datasets,

• pre-process data (filter, augment, transform),

• train, validate and test networks,

• monitor the training process,

• visualize training results (Gammaboard).

Experiment work-flow

To launch an experiment, i.e. train and test a neural network, one fills an experiment settings file (a python script) describing the conditions of the experiment : location of the data and data pre-processing, loss function, optimizer, network parameters (related to the network) etc.. If specific functions or classes are needed for this experiment and are not yet in the collection of files provided in the framework (i.e. criterions.py, optimizers.py, steps.py and plots.py), one can simply write them in these files. One also defines the network to train, as a Python class inheriting from PyTorch nn.Module class to benefit from automatic differentiation. Then one starts the experiment runner, the settings and the network are saved for reproducibility, and the process runs to the end by its own. During the training process, various metrics can be monitored via a log file and Tensorboard:

• loss,

• accuracy (in case of a classification task),

• features and convolution kernels,

• weights and gradients of the network,

• hardware usage.

Once the network is trained, the raw data of the test phase and the network are saved (network checkpoints can also be saved during the training). The test results can then be analyzed with the Gammaboard tool, that plots end result curves (energy and angular resolution, migration matrices) and allows an easy comparison between experiments and CTA requirements/performances.

Preliminary results

The architecture described Fig. 3 has been trained on CTA simulation data (90k gamma diffuse events from La Palma Prod3b1 , with the four LSTs of the chosen layout triggered) exhibiting an ability to learn, as shown in Fig. 5. The same architecture has then been used to compare the performances of the square kernels (3 × 3 pixels) and hexagonal kernels (nearest neighbors) for the convolution and the pooling layers on the hexagonal grid images of the LSTs. As shown in Fig. 6, the global loss (cumulative loss of every task, i.e. energy, direction and virtual impact point) is lower for hexagonal kernels, as expected as they match the pixel organization of the images. Indeed, the neighbors defined by the hexagonal kernel on a hexagonal grid image are the real neighbors of the pixel of interest, all with the same distance to it.

Conclusion

Machine learning is likely to gain more and more momentum in the coming years as it enables to deal with huge amount of data in an performant and efficient way. The impressive results obtained in other domains lead us to believe IACT reconstruction performances can be improved thanks to Deep Learning techniques such as deep convolutional neural networks.

We have presented in this work the issues specific to applying Deep Learning to CTA data (images shapes and pixels organisation and stereoscopy) and have proposed some approaches to solve these issues and applied them to show preliminary results on the regression of particles direction (altitude, azimuth) and energy.

This work needs to be developed and compared to state-of-the-art methods to show a potential advantage of Deep Learning. Many other challenges will likely need to be overcome (such as transfer learning from simulation to real data, robustness to real life noise) to apply these techniques to CTA real data.

Figure 1 .

 1 Figure1. Building the indices matrix for hexagonal grid images. Assuming that the image is stored as a vector and that we know the position of each pixel in the axial addressing system, we can build an index matrix. With the appropriate kernel, in blue, we can identify the neighbours of each pixel of interest, in red, and fill the indices matrix.

Figure 2 .

 2 Figure 2. Rebuilding the index matrix after pooling (with hexagonal kernel).

Figure 3 .

 3 Figure 3. Preliminary architecture developed for the stereoscopic analysis of CTA data. For this preliminary work we focused on the four LSTs of the CTA North site leading to 4 entries to the network.Each entry is fed to the same convolution block (e.g. the convolutional part of VGG or a ResNet, in this case four convolutional layers with maxpooling and batchnorm). The feature vectors thus created are concatenated and the result is fed to the multitasking block (a fully connected network) inferring at the same time the energy, the arrival direction and the virtual (as the shower doesn't reach the ground) impact point of the shower event.

Figure 4 .

 4 Figure 4. Description of the GammaLearner framework.

Figure 5 .

 5 Figure 5. Migration matrices of the stereoscopic architecture described in 2.2 when trained on CTA gamma diffuse simulations (LST only). The Y-axis is the prediction of the network while the X-axis is the ground truth. The closer to the red line are the points, the better.

Figure 6 .

 6 Figure 6. Global loss comparison between square kernels and hexagonal kernel during training. The X-axis represents the epochs of the training process, the Y-axis the loss value.

The Prod3b corresponds to a batch of simulated events in order to choose the final layout of the different telescopes on both sites.

Acknowledgement

This work has been done thanks to the facilities offered by the Univ. Savoie Mont Blanc -CNRS/IN2P3 MUST computing center and support from the H2020-Astronomy ESFRI and Research Infrastructure Cluster (Grant Agreement number: 653477).


Matthieu Allon
email: matthieu.allon@etudiant.univ-lille1.fr

Gilles Vanwormhoudt
email: gilles.vanwormhoudt@univ-lille1.fr

Bernard Carré
email: bernard.carre@univ-lille1.fr

Olivier Caron
email: olivier.caron@univ-lille1.fr

Isolating and Reusing Template Instances in UML

Keywords:

In MBE, design of systems can be improved and accelerated thanks to reusable models which are made available in model repositories or libraries. One answer for designing reusable models is parameterization as offered by UML templates and their binding relationship. The standard aims at embracing under the same constructs two distinct kinds of template usages, namely template instantiation and aspectual binding. Template instantiation is concerned with the capacity of UML templates to model generic components (like C++ templates or Java generics) and produce new models from their binding. Aspectual binding is much more concerned with the capacity of UML templates to specify functionalities to inject into models of systems (contexts) which must conform to a required parameter model. In this paper, we focus on the generative interpretation of UML template binding. On the basis of a deep analysis of the standard, it will be shown that template binding consists in template instantiation plus context merging. This allows to isolate the capacity of instantiating templates (under their generative view) to get reusable models coming from applicative contexts. Then the possibility of partial instantiation inspired by partial binding as promoted by the standard is studied. At a practical level, related functionalities are offered within Eclipse.

Introduction

In Model-based Engineering, model reuse is a big challenge that aims to facilitate the capitalization of technology independent design efforts and logics ("off-theshelves" model components libraries [START_REF] Herrmannsdörfer | Library concepts for model reuse[END_REF]) then to accelerate system design and improve their quality via early checking, by the reuse of proved models. Besides the composition of model pieces [START_REF] Whittle | MATA: A unified approach for composing UML aspect models based on graph transformation[END_REF][START_REF] Melnik | A semantics for model management operators[END_REF], another way to face this challenge is model parameterization [START_REF] Bottoni | A language-independent and formal approach to pattern-based modelling with support for composition and analysis[END_REF][START_REF] Klein | Reusable aspect models[END_REF], that is the capacity for a model to expose some of its elements as parameters, then produce other models through parameter substitution. This allows to capitalize models of a higher kind which capture recurrent structure, so that they can be applied (reused) in multiple modeling contexts.

The UML standard answer to this need is the "template construct" and its binding relationship. This construct is general enough to support MBE reuse practices ranging from the representation at a model level of generic software components (such as C++ templates or Java generics) to the weaving of reusable functionalities into models, mainly the way aspect-, pattern-and view-oriented modeling do. In our prior work [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF], we contributed to this research by enhancing the semantics of UML Templates for their aspectual interpretation. This leads to so called "aspectual templates" whose parameters must form a model of systems in which to inject the functionalities. This semantics enhancement ensures the "parameters as a model" requirement and its consistency throughout substitution and composition mechanisms, notably when binding is partial. Thanks to this enhancement, UML templates can be better controlled for their aspectual usage, particularly in case of complex assembly.

In this paper, we concentrate on template instantiation which underlies MBE practices related to their generative usage, that is the creation of new models from their generic modeling structure. This calls for the isolation of template instantiation from standard binding. Given this, consequences on template parameters, particularly when they form a model, need to be examined and we do so by the proper identification of template constituents as submodels. It will be shown that instantiation can be applied on any templates being aspectual or not. Similarly to partial binding, partial instantiation is provided when not all parameters are substituted. A study of this feature is offered and its interest for producing models with pieces from multiple contexts is presented. More generally, the isolation of template instances as stated here contributes to increase UML templates reusability and to enrich template-based MDE facilities [START_REF] Allon | Template Based MDE[END_REF].

The rest of the paper is structured as follows. After providing background on UML templates, we present an analysis of template binding in Section 3. This analysis will lead to the isolation of template instantiation. Then, Section 4 examines how instantiation relates to template parameters. Partial instantiation is studied in Section 5. Section 6 describes application of the results in modeling tools. Before concluding with perspectives, Section 7 discusses template instantiation in existing works.

Background on UML Templates

In this section, a reminder on UML templates and their aspectual enhancement [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF] are presented to ground the study.

UML Template and the Binding Relationship

In UML [START_REF]OMG: Auxiliary Constructs Templates[END_REF], a template is a model which exposes some of its model elements as formal parameters using a signature (list of formal parameters). Examples are class or package templates. Graphically, the signature is contained in a small dashed rectangle on the top right-hand corner of the template symbol. Templates can be applied, and thus reused to produce other models thanks to parameter substitution, through the standard binding relationship 3 . It links a bound model to a template (from which it was obtained) via a parameter substitution set that associates formal parameters of the template to actual elements of the bound model. Constraints of the standard only impose that the type of each actual model element must be a subtype of the corresponding formal parameter. Fig. 1: UML package template example Figure 1 shows an example of UML template and its binding for extending the model of a system. It shows a package template used to model the observer pattern parameterized by the Subject and Observer classes, the value property, the T type and the observers association. The system where the pattern must be applied represents a car rental agency with its clients and cars. In the figure, the ObserverPattern template is used to introduce the observer functionality between Agency and Clients for capacity observation by clients. This design choice is specified by the binding relationship between the CarHiringSystem model and the ObserverPattern template with the specified set of substitutions. As a result of the binding, CarHiringSystem includes the model structure of the ObserverPattern with respect to substitutions.

Finally, UML allows partial binding. Partial binding occurs when not all formal template parameters are substituted. For that, the UML specification states that the unsubstituted formal template parameters are formal template parameters of the bound element, which is itself a template as a consequence. Partial binding will be specifically studied in Section 5.

Parameters as a Model

Regarding template parameters, the standard does not require any structuring between them. The only constraint imposed by UML is the inclusion of the set of parameters into the set of template elements. Although this choice is permissive, it is underspecified to capture structuring constraints expected from candidate models to correctly apply the template functionality.

Figure 2 illustrates the issue. On the left of the figure, a variant of the Observer template compliant with UML is presented. As expected, all the parameters are model elements of the template core but one can observe that they do 3 Informally specified in [START_REF]OMG: Auxiliary Constructs Templates[END_REF], page 650. value : T Subject Fig. 2: Set of parameters vs model of parameters not form a consistent model. Indeed, the value property is exposed without its owning class whereas the latter is required to enable its mapping with a property contained in a context class. Similarly, the observers association exposed as parameter is underspecified because one of its ends (the Subject class) is not declared as a parameter.

In our previous work [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF], we deeply studied the aspectual interpretation of UML templates with the requirement that parameters have to form a well formed modeling structure to which candidate models must have to conform. Following this requirement, we stated a semantical enhancement of UML templates which consists in enforcing templates to have a full model as parameter. Its aim is to improve the consistency of templates, notably for aspectual usages, but also to better specify the model of systems to which the functionalities will apply. Following this enhancement, the (partial) binding mechanism has been adapted to enable substitution of the model parameter by a conforming substructure of the base model.

Right of Figure 2 gives the enhanced version of the Observer template. One can observe that the template parameters (see the superimposed dashed box) form a full model. One can also verify that the structure of this model parameter is well preserved by the substituted elements of the binding in Figure 1.

Towards Explicit Template Instantiation

In this section, we analyze template binding. We will see that template binding underlies template instantiation. This analysis will serve to motivate our proposal which consists in isolating template instantiation separately from template binding. Constraints that template instantiation imposes on the parameters and the specific case of partial template instantiation will be studied in the next sections.

In UML, the semantics of the binding relationship is specified as follows:

"The presence of a TemplateBinding relationship implies the same semantics as if the contents of the template owning the target template signature were copied into the bound element, substituting any elements exposed as a formal template parameter by the corresponding elements specified as actual parameters in this binding."( [START_REF]OMG: Auxiliary Constructs Templates[END_REF], page 650) Following this semantics, the bound model resulting from a template binding can be seen as the merging of an applicative context with the content of the template after substitutions were made. As represented in Figure 3, the bound model (ObservableCarHiringSystem) contains all the content of the template instance plus the content of the context. This can be captured using the standard "merge" relationship from the bound model to the template instance and the context:

template binding = instantiation + context merging
Following this, once template instances have been isolated, they can be promoted as valuable artifacts of their own and then be reused. This new capacity is of interest when designers are much more concerned by the construction of new models from templates instead of enriching existing ones. This calls for giving a much more active role to template instantiation in the modeling space and its related processes.

As a consequence, we propose to isolate template instantiation from template binding. For representing template instantiation, we use a relationship named instantiate. Like the binding relationship, this requires a template, a source modeling context plus a set of parameter substitutions. Its semantics consists in copying the content of the template and replacing the parameters by corresponding copies of actual elements from the source model. 3. The result of this instantiation is the template instance (ObserverPatternInstance) presented in Figure 3. Regarding substitution specified in the instantiate relationship, substituted elements from the context model must conform to the modeling structure formed by the parameters. In Figure 4, one can verify that it is actually the case.

Finally, to isolate the instantiate relationship, we showed the treatment of template with a well formed parameter model. More generally, how instantiation relates to the structure of templates needs to be deeply examined. It is the intent of the next section.

Instantiation Regarding Kinds of Templates

To study how instantiation relates to template structure, we decompose a template into two complementary constituents: its parameter and its specific submodels. Main questions are: which constituent provides the template structure and what are the requirement on template parameters when instantiation is considered ?

Consider a template with a well formed parameter submodel. It is this submodel which provides the modeling structure of the template core. This is illustrated in Figure 5. In this situation, the lack of well-formedness for the specific model is due to the fact that classes owning the register and update methods are parameters, so are not part of the specific model.

5: Template model = parameter + specific submodels

The observation regarding the well-formedness of template constituents raises the question of alternative cases. It can be questioned whether a parameter submodel that is not well formed (respectively a specific model that is well formed) is of interest and what are the specific usages. Indeed, depending on the well-formedness or not of each template constituent, other cases can be considered in addition to the previous one, whether the parameter submodel is well formed or not. Cases when the parameter model is not well formed are shown in Figure 6.

Fig. 6: Possible forms of template constituents

Not well formed parameter model, well formed specific model: This case is shown on top of Figure 6. Here, it is the specific submodel that is well formed and therefore provides the modeling structure of the template.

Not well formed parameter model, not well formed specific model: This last case is illustrated in bottom of Figure 6. Compared to the previous case, this one has both submodels which are not well Here, the structure of the template content is in the template in its entirety. These cases being identified, they can be analyzed with regard to template instantiation. It is done in the following.

Let us consider cases 1 and 2 corresponding to a well formed parameter submodel. The situation was examined in Section 3. It leads to a resulting model where the well-formedness of its structure is brought by substituted elements of the context model. So, similarly to aspectual template binding, instantiation can be applied to any template having a well formed parameter submodel. This is an interesting result for the reuse of templates. It means that any template having this property can be applied both for aspectual and generative usages depending on the modeling needs. Fig. 7: Template instantiation with a not well formed parameter model Let us continue with the two remaining cases corresponding to the situations where the submodel parameter is not well formed (Figure 6), regardless of its specific submodel. Figure 7 shows an example of template instantiation for case 3, accompanied with the resulting model. As can be observed, the parameter submodel is not well formed contrary to the specific model. Thus, in this case, the structure is provided by the specific model. Concerning case 4, similar comments can be made regarding template instantiation. Even if both template submodels are not well formed, the template they form can be instantiated. To be convinced, it suffices to modify the status of the Subject class as parameter in Figure 7. Despite this change, such a template continues to be applicable through an instantiate relationship.

The last two cases typically occur when modeling generics (e.g. C++ or Java) but also in partial template instantiation. Thus, it is important to handle them and ensure they are treated consistently through template instantiation. The following section specifically studies partial instantiation and concludes on the comparison between aspectual binding and template instantiation.

Partial Instantiation

UML templates allow partial binding when not all parameters are substituted and unsubstituted ones remain parameters in the resulting model which is therefore a template. Partial binding is a powerful feature that allows modelers to obtain richer templates through the composition of templates. It was deeply studied in our preceding work [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF] for aspectual templates. Following UML principles concerning parameter substitution and propagation of the unsubstituted parameters, partial instantiation can be offered to benefit from additional capacities. It gives the ability to produce new templates from instantiated ones and, thus, sequences of instantiations. It also enables instantiation in multiple contexts. Figure 8 gives an example of a partial instantiation between the Observer-Pattern template and the CarHiringSystem model. In this example the Subject, value and T parameters are bound in the substitution set of the instantiate relationship while the observers and Observer parameters are unbound. This figure also shows the result of this partial instantiation which is a new template named ObservableAgency. For this template, the parameter model contains the unbound observers and Observer, following the propagation strategy of UML for unsubstituted parameters.

One observation can be made concerning the propagation of unsubstituted parameters in the new template. This propagation is achieved with respect to specified substitution causing adaptation of method parameters. See for example the substitution of Observer by Resource in the register method of the Agency parameter, in the ObservableAgencyResource template instance. Depending on the substituted parameters, the resulting template may have a well formed model as parameter or not.

Templates resulting from partial instantiation can be further applied. They can help to construct other parts of the same system or serve as valuable artifacts in order to build parts of new systems. For applying a template resulting from partial instantiation to a new context, complete or partial instantiation can be used. Additionally, such a template can also be bound for aspectual usages as long as their parameter model is well formed. In our example, only instan-Fig. 8: Partial instantiation tiation is because the parameter model is not well formed. Figure 8 shows a partial instantiation of the obtained template ObservableAgency to get ObservableAgencyResource. This instantiation takes place in a new applicative context related to stock management. In this instantiation, the Observer and observers are substituted in order to produce a final model that combines ingredients from the two modeling contexts. Such a model can be useful for observing state changes between the two parts.

In this example, it is interesting to highlight that the same result could be obtained through an alternative sequence of instantiations: first, partially instantiating the ObserverPattern template in the StockManagement context and then instantiating the intermediate result in the CarHiringSystem context. Moreover, obtaining the same ObservableAgencyResource model with a complete instantiation would require merging CarHiringSystem and StockManagement models into a single model followed by a complete instantiation of ObserverPattern to this merged model. These equalities emphasize the compatibility between partial and complete instantiation and, thus, their consistency.

The preceding example also illustrates successive template instantiations from an initial template. Along a sequence of instantiations, the set of parameters decreases in intermediate templates. This may cause relaxation of structural constraints on the parameters. Such relaxation has the effect to enlarge the set of potential elements for substituting parameters in instantiation. This flexibility at the level of substitution is visible in the previous example. In the template ObservableAgency, Observer and observers parameters form a less-constrained structure than their counterpart in the initial template. This enables mapping them on a larger set of candidate elements when compared with the initial template.

Table 2 summarizes the situations studied in this paper. It characterizes applicability and results of examined relationships depending on whether the template is aspectual or not. This table should help to have a better understanding of the UML Template modeling space, particularly in case where parameters form a model.

Tool Support

A software environment dedicated to template based model engineering in Eclipse was previously implemented [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF]. This environment4 is composed of plugins which are based on the official EMF (Eclipse Modeling Framework), UML and OCL plugins. These plugins offer core functionalities to specify and verify aspectual templates well-formedness but also apply their binding in a compliant way with the UML plugin thanks to a specific profile. In addition, the plugins provide general and original facilities to support other modeling tasks targeting templates or user assistance such as automatic completion of template signature and binding inference. All the plugins functionalities are reusable in modeling tools that handle model templates.

Following the present work, this environment has been extended to include the capacity of instantiating templates. For that purpose, we added the following enhancements to existing plugins :

-An adaptation of OCL constraints for checking the consistency of template parameters and their substitutions when instantiation is applied. The constraints applied in that case are a subset of the ones for checking aspectual templates. These constraints mainly enforce that and the substituted elements involved in a template instantiation have a compatible structure. -An implementation of total and partial instantiation. The implemented algorithm proceeds by copying the core of the template into a new model and replacing copied parameters by substituted elements from the context model. Thanks to their compatibility with instantiation, this implementation is also applicable to aspectual templates. -An extension of the current profile dedicated to templates with a new stereotype related to template instantiation, i.e., InstantiationBinding. It specializes the TemplateBinding UML metaclass and provides an OCL context for applying constraints due to template instantiation.

Related Works

This study started from UML template and showed that this concept is a general construct both for aspect-oriented and generative modeling based on parameterized models. A detailed review of related works regarding aspectual templates can be found in our previous work [START_REF] Vanwormhoudt | Aspectual templates in UML[END_REF]. In these works, instantiation is sometimes mentioned as an underlying mechanism for binding aspectual templates [START_REF] Berg | System Analysis and Modeling: Theory and Practice: 7th International Workshop, SAM 2012[END_REF][START_REF] Klein | Reusable aspect models[END_REF][START_REF] Reddy | Directives for composing aspect-oriented design class models[END_REF] but it is not isolated as a full-right mechanism, as studied here. In the following, we review existing works that explicitly support template instantiation since it is the focus of this paper.

As already indicated, one motivation for template instantiation is the modeling of generic classes. [START_REF] Cuccuru | Constraining type parameters of UML 2 templates with substitutable classifiers[END_REF] is a work that studies this need in UML by means of template classifier. The authors mainly focus on mechanism offered by this construct for expressing constraints on type parameters of represented generic classes and checking their substitutability in bindings. The work presented in [START_REF] Farinha | Extending UML templates towards computability[END_REF] addresses the similar modeling need but aims to offer a stronger conformance for the binding of template classifiers. For that purpose, it proposes a set of well-formedness rules, additional to that of UML, to enforce the correctness of bound attributes and methods regarding their types, their membership and some of their meta-attributes. By offering generic classes similar to Java, Ecore (the metamodel of EMF) [START_REF] Steinberg | EMF: Eclipse Modeling Framework[END_REF] can also be cited as a work dealing with this need. Thanks to this feature, models expressed in Ecore can contain declaration of generic classes or use instantiation of generic classes for typing attributes and methods. This feature also improves the capacities delivered by EMF for code generation (i.e., generate generic code).

The Catalysis approach [START_REF] Souza | Catalysis: Objects, Components, and Frameworks with UML. Object Technology Series[END_REF] proposes model frameworks in order to design reusable packages. A model framework is a form of parameterized package containing placeholders which are names that can be substituted with actual type names when the framework is instantiated. Each instantiation of the framework provides its own substitution of the placeholders. The names of attributes and associations of placeholder types are themselves placeholders. This approach, based on string substitution, is realized in the XMF tool. studies the support of genericity in component models. This work proposes a structural pattern to extend an existing component model with concepts for genericity. With this pattern, a component model can be made generic through parametrization. Elements that can be exposed as parameters are types of input and output ports, types of component implementation and the number of nested subcomponents. This work also introduces an algorithm to instantiate a generic component model. The use of the pattern is demonstrated by extending the SCA component model.

In [START_REF] De Lara | From types to type requirements: genericity for modeldriven engineering[END_REF], the authors present a notion of model template and its instantiation mechanism in the context of the framework. In this work, a model template specifies its generic modeling structure by means of the "concept" construct which is a separate model expressing both the parameters and a set of structural requirements on these parameters. In some way, the "concept" construct is related to the notion of "parameters as a model" and has a similar purpose but it is not part of the template body. Instantiation of a model template is done by importing substituted elements from a model conforming to the concept into a new model constructed from the template body.

Compared to these works, the present contribution differs on several main points. First, only one of the existing works [START_REF] Cuccuru | Constraining type parameters of UML 2 templates with substitutable classifiers[END_REF] takes place inside the scope of standard UML but only for template classifiers. Second, all these works except [START_REF] De Lara | From types to type requirements: genericity for modeldriven engineering[END_REF] do not consider template parameters as a fully structured model. As discussed in the paper, this requirement allows us to overcome possible inconsistencies when instantiating templates. It also provides a way to better characterize and control the usages of templates during processes. A last difference between the present work and existing ones is related to partial instantiation. To our knowledge, no existing approach offers capacities comparable to this feature. As a result, interesting capacities are enabled like instantiation of template in multiple contexts or the construction of complex assembly, mixing aspectual and generative usages of templates through partial binding and instantiation.

Conclusion

Starting from UML templates and their binding relationship, this work isolated instantiation of templates with "parameters as a model". As a consequence, new capacities were offered for the reuse of templates and the construction of new models from their complete or partial instantiation. This work also provided a characterization of the resulting UML Template modeling space. More generally, it contributes to enrich template-based MDE capacities.

In future work, we plan to focus on order and equivalence of instantiation sequences, the way we did in one of our works [START_REF] Muller | On Some Properties of Parameterized Model Application[END_REF] for aspectual binding. Another interesting perspective to investigate is the study of alternative strategies for unsubstituted parameters, like no propagation or the use of default values for them. Lastly, we are working on the formalization of the template construct by exploiting our previous work on model inclusion and the notion of submodel [START_REF] Carré | From subsets of model elements to submodels, a characterization of submodels and their properties[END_REF]. We expect this formalization will help to a better theoretical understanding and generalization of template for the quest of model reuse.

Figure 3

 3 presents this construction principle on the scenario presented in Figure 1. It makes explicit (upper-right in the figure) the applicative context (car agency) to which both the template and the intermediate model apply, instance of the template (ObserverPatternInstance upper-left). It is the context that provides actual elements for the binding.

Fig. 3 :

 3 Fig. 3: Template binding = instantiation + context merging

Fig. 4 :

 4 Fig. 4: Template instantiation

Table 1

 1 gives a summary of all possible cases of template constituents.

Table 1 :

 1 Possible forms of template constituents

			Specific Model
			well formed not well formed
	Parameter	well formed	Case 1	Case 2
	Model	not well formed	Case 3	Case 4

Table 2 :

 2 Template applicability and kinds of resulting models

		Aspectual Template	Not Aspectual Template
		(Well formed Parameter Model)	(Not Well formed Parameter Model)
		Applicable ? Kind of Resulting Model Applicable ? Kind of Resulting Model
	Aspectual Binding	Yes	Model	No	No Resulting Model
	Instantiation	Yes	Model	Yes	Model
	Partial	Yes	Aspectual Template	No	No Resulting Model
	Aspectual Binding
	Partial	Yes	Template	Yes	Template
	Instantiation

Eclipse plugins and modeling tool snapshots are available at http://www.cristal. univ-lille.fr/caramel/MBE_Template/