Soil biological communities are among the most diversified on Earth, comprising as much as a quarter of currently known global biodiversity [START_REF] Decaëns | Macroecological patterns in soil communities[END_REF]. They are involved in the regulation of a large number of ecological processes and in the provision of critical ecosystem services for human well-being. Paradoxically, belowground biota suffers from a conspicuous deficit of research when compared to aboveground organisms, and soils are still considered to be the third remaining biotic frontier after oceanic abysses and tropical forest canopies. To date, only a very small fraction of soil species diversity has been formally documented, and only a few studies have considered spatial ecology of soil communities. The paucity of our taxonomic and ecological knowledge for soil biota has historically limited its integration into the development of theoretical ecology, which has remained below what it should be given the quantitative and functional importance of these organisms [START_REF] Thakur | Towards an integrative understanding of soil biodiversity[END_REF].

DNA-based approaches, such as DNA barcoding and metabarcoding, now offer the opportunity to remove these impediments and improve our capacity to describe soil biota patterns [START_REF] Rougerie | DNA barcodes for soil animal taxonomy[END_REF]. In soil invertebrates, DNA barcodes are used in support of morphological diagnoses to increase our ability to detect and describe new species. They allow automated taxonomic assignments, including for cryptic species or for individuals not presenting the necessary diagnostic characters for morphological identifications (e.g. immature individuals). They can also be used to delineate operational taxonomic units (OTUs), which represent species surrogates to describe diversity patterns for taxonomically unresolved groups, or in poorly studied regions.

Finally, high-throughput sequencing approaches such as DNA and eDNA metabarcoding (sensu [START_REF] Taberlet | Environmental DNA[END_REF]) are now revolutionizing soil fauna community ecology. eDNA metabarcoding has been applied to soil environmental samples to describe community patterns for single taxonomic groups (e.g. earthworms in [START_REF] Pansu | Landscape-scale distribution patterns of earthworms inferred from soil DNA[END_REF] or for whole communities (e.g. Zinger et al., 2019). However, these studies generally use specific markers, rather than universally recognized barcodes, thus limiting the completion of taxonomic assignments and the possibilities of comparisons between studies. Conversely, DNA metabarcoding approaches analyse invertebrate bulk samples (Yu et al., 2012), and typically use these standard barcodes, allowing them to rely on the growing taxonomic information contained in global databases [START_REF] Andujar | Why the COI barcode should be the community DNA metabarcode for the metazoa[END_REF][START_REF] Porter | Over 2.5 million COI sequences in GenBank and growing[END_REF].

The study by [START_REF] Arribas | The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding[END_REF] is a perfect example of the added value that DNA metabarcoding can represent for soil invertebrate community ecology. The use of whole community metabarcoding (WCM) first allowed the authors to bypass the difficulties of taxonomic assignments in three highly diverse groups of soil arthropods (i.e. springtails, mites and beetles). In their study, they were able to consider tens of thousands of specimens belonging to >1000 species, thus covering a broader taxonomic range than what would have been possible through a classical approach. A key point of their study is that it exemplifies the importance of using COI in metabarcoding approaches, as this locus provides intraspecific (genetic) variation that can be used for subsequent analyses [START_REF] Andujar | Why the COI barcode should be the community DNA metabarcode for the metazoa[END_REF]. This enabled the authors to analyse the variation of beta-diversity with distance among communities at different nested phylogenetic levels, from unique haplotypes to lineages delimited with decreasing identity thresholds (here from 99% to 92 %). Their results nicely demonstrate how niche and neutral processes combine to explain the assemblage of soil arthropod communities. While community composition was primarily explained by habitat (i.e. pasture versus forest), they also found a distance-decay in community similarity, which was parallel among hierarchical levels and consistent among habitats and regions. This last pattern clearly underpins limited dispersal as an important driver of local community assembly. Finally, they described a high rate of microendemicity, reinforcing the hypothesis of short dispersal distances driving community composition, and suggesting that species richness of soil arthropods at broader scales could be higher than expected.

Beyond these significant results, [START_REF] Arribas | The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding[END_REF] lay the methodological foundations of a general analytical workflow to streamline soil invertebrate community studies (Fig. 1). As exemplified in their study, WCM using COI gene first generate sets of sequences that can be used as such or after aggregating them into OTUs. To go further, taxonomic assignments of these OTUs, when made possible by the choice of standard barcodes and the availability of existing libraries, can enable to link species names to ecological information, e.g. through queries in functional trait databases. Therefore, the proposed workflow has the potential to produce dataset triplets combining phylogenetic, taxonomic and functional descriptors of communities. Hereafter, I propose some examples of how such datasets could be analysed, in complementary way to the study of [START_REF] Arribas | The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding[END_REF], to provide insights into our understanding of the ecology and evolutionary biology of soil invertebrates.

Even if DNA barcodes only capture a small fraction of phylogenetic signal, barcode trees are relevant to predict metrics of phylogenetic community structure obtained from multi-gene phylogenies [START_REF] Boyle | Community Phylogenetics: Assessing Tree Reconstruction Methods and the Utility of DNA Barcodes[END_REF]. When available, backbone phylogenies can further be used to improve the phylogenetic context of the massive community level datasets generated by WCM. Thus, WCM datasets can be analysed through combining in a complementary way trait-based and phylogenetic approaches, which has been emphasised as a powerful strategy to dissect multi-scales biodiversity patterns [START_REF] Mouquet | Ecophylogenetics: Advances and perspectives[END_REF]. Indeed, non-random patterns in functional and phylogenetic community structure can be tracked to disentangle the relative importance of niche and neutral processes, and how they interact with species evolutionary history, in the processes of community assembly. DNA barcodes obtained from WCM can also be used in phylogeographic and population genetic analyses, which, when performed comparatively for large numbers of species across ecological guilds, can reveal general patterns of differentiation and allow testing hypotheses regarding the origin and maintenance of community diversity [START_REF] Craft | Population genetics of ecological communities with DNA barcodes: An example from New Guinea Lepidoptera[END_REF][START_REF] Turon | From metabarcoding to metaphylogeography: Separating the wheat from the chaff[END_REF].

Analysing the turnover component of beta diversity among WCM datasets obtained from large-scale sampling designs, is expected to reveal macroecological patterns in the taxonomic, functional and phylogenetic components of soil biodiversity, and to allow reassessing global species numbers as suggested by [START_REF] Arribas | The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding[END_REF].

Finally, analysing WCM datasets through diversity partitioning approaches, can reveal the relative contributions of alpha and beta components to the overall diversity [START_REF] Crist | Partitioning species diversity across landscapes and regions: A hierarchical analysis of alpha, beta, and gamma diversity[END_REF]. The use of Hill's equivalent numbers of species offers the possibility of jointly analysing the taxonomic, phylogenetic and functional components of diversity through a nested hierarchy of multiple scales, in order to identify the spatial scales that most contribute to the diversity of species, genes and functional traits [START_REF] Alberdi | A guide to the application of Hill numbers to DNAbased diversity analyses[END_REF][START_REF] Pavoine | Equivalent numbers" for species, phylogenetic or functional diversity in a nested hierarchy of multiple scales[END_REF]. The scope of such an approach applied to whole communities of soil invertebrates would be considerable, as it would result in a comprehensive understanding of the mechanisms soup: Metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods in Ecology and Evolution, 3(4), 613-623. doi: 10.1111/j.2041-210X.2012.00198.x Zinger, L., Taberlet, P., Schimann, H., Bonin, A., Boyer, F., De Barba, M., … Chave, J. (2019).

Body size determines soil community assembly in a tropical forest. Molecular Ecology, 28(3), 528-543. doi: 10.1111/mec.14919 FIGURE 1 General workflow for a comprehensive analysis of soil faunal communities through the use of whole community DNA metabarcoding (WCM). Soil invertebrates are sampled through spatially explicit design and standardised sampling protocols, before being processed through WCM as described in [START_REF] Arribas | The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding[END_REF]. Sequences are aggregated into operational taxonomic units (OTUs), which are further identified to species by comparison with available DNA barcode libraries (e.g. Barcode of Life Data systems -BOLD). Species names are further used to query functional trait databases, or alternatively traits are described from voucher samples. The complete workflow results in the production of dataset triplets combining taxonomic, phylogenetic and functional descriptors of soil invertebrate communities, which can be used to further explore fundamental aspects of community ecology, evolutionary biology and conservation of soil invertebrates (see text for details). Envir = environement; Geogr = geographic; TPF = taxonomic / phylogenetic / functional; PD = phylogenetic dispersion; FD = functional dispersion; SES = standardised effect size.

  Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France. Email : Thibaud.Decaens@cefe.cnrs.fr Identifying the determinants of the distribution of soil organism communities at different spatial scales is essential to our understanding of the functioning of terrestrial ecosystems. Indeed, spatial patterns of soil biota, and the factors that determine them, influence spatial patterns of many ecological processes such as the decomposition of organic detritus, the release of nutrients and, ultimately, the spatial structure of plant communities (Ettema & Wardle, 2002). However, our ability to describe and understand the spatial distribution of soil communities is severely hampered by taxonomic and methodological limitations, significantly reducing our ability to infer ecological and evolutionary mechanisms from observed patterns. In a From the Cover article in this issue of Molecular Ecology, Arribas, Andujar, Salces-Castellano, Emerson, & Vogler (2020) used a high-throughput-sequencing approach, i.e. haplotype-level-COI metabarcoding, to bypass these roadblocks and analyse the spatial arrangements of soil arthropods communities at different phylogenetic levels, from haplotypes to nested operational units. They found that local assemblage composition was primarily explained by habitat, and that community similarity decreased with distance in a similar way in all habitats and geographical regions, and at all hierarchical levels. This highlights that both habitat filtering and dispersal limitation are major drivers of local-scale assembly process in soil arthropod communities. Beyond these significant results, their study also highlights how DNA-based approaches, by producing combined description of genetic and taxonomic diversity, opens up new perspectives to soil spatial ecology and macroecology.

supporting soil biological diversity within and between communities, and would help to reach a better integration of these functionally important organisms in the definition of conservation strategies.

Sampling


Aleksandra Markovic
email: amarkovic@laas.fr

Gaël Pillonnet
email: gael.pillonnet@cea.fr

Bernard Legrand
email: bernard.legrand@laas.fr

INNOVATION FOR RADIO AND PHOTONIC

Keywords: Ultra-low power digital circuits, adiabatic logic, silicon MEMS, comb-drive Mots clés : Circuits à ultra-basse consommation, logique adiabatique, MEMS sur silicium, peignes interdigités

We introduce an architecture of logic gates based on capacitive MEMS devices in a differential architecture, operated in the adiabatic regime and aiming at reaching ultra-low power operation. The tunable capacitances, which are the fundamental component of our MEMS devices are realized using comb-drive actuators. Their design was a result of an extensive FEM analysis and had to satisfy criteria for sufficient logic differentiation and cascadability of individual gates. Microfabrication tests were performed on silicon wafers as optimization of the fabrication process for the realization of full logic gates on SOI wafers.

Introduction

Logic gates are devices that act as building blocks for digital circuits. Based on the combination of digital signals coming from their inputs, logic gates perform logical functions based on Boolean algebra that are fundamental to digital circuits. In modern practice, most gates, e.g. in microprocessors, are made from MOSFETs (metal-oxidesemiconductor field-effect transistors) [START_REF] Fanet | Ultra Low Power Electronics and Adiabatic Solutions[END_REF]. In current technology, the combinatorial logic is based on abrupt charging and discharging of the capacitors for moving from one logic state to the other. The logic state is determined by the quantity of the charge stored in a capacitor. Abrupt charging and discharging of these capacitors (changing of the logic state) is realized with MOSFETs that act as switches.

In the sixties in the last century Rolf Landauer has proposed the principle describing the smallest amount of energy that is used to switch between two logic states -"0" and "1", that is, to erase one bit of information. This principle is now known as the Landauer's limit and claims that the energy requirement, at room temperature for one operation, should be of the order of magnitude of zepto (10 -21 ) joules. However, this limit is still far from being reached. The state-of-the-art MOSFET transistors dissipate ~1000 kBT (~10 -18 joules) even in advanced CMOS nodes during a single logic operation and remain therefore orders of magnitude above Landauer's limit [START_REF] Fanet | Ultra Low Power Electronics and Adiabatic Solutions[END_REF] [START_REF] Landauer | Irreversibility and heat generation in the computing process[END_REF]. The energy dissipation of digital circuits has been widely studied and can be explained by three different aspects:

1. Dynamic losses which occur during abrupt switching between two logic states, 2. Static losses which are due to the non-zero leakage currents when the switch is "off" 3. In order to be able to distinguish two different states their energetic difference has to be well above the thermal noise level (kBT), which in turn increases the dynamic losses.

In our work, we aim to eliminate static and dynamic losses from logic circuits and therefore approach zero power dissipation during the logic operations. Overcoming such a challenge requires hardware-and system-level shifts in the paradigm used for logic circuits. Lower dynamic losses however come at a cost of lower processing speed as this approach requires operating at low frequencies (speed limit comes from the device's time constant). At lower frequencies static losses become dominant. Their elimination requires devices with zero-leakage.

Some previous works in the field have made use of nano/micro-electro-mechanical system (N/MEMS) relays to pursue this goal [START_REF] Samaali | MEMS four-terminal variable capacitor for low power capacitive adiabatic logic with high logic state differentiation[END_REF][START_REF] Ye | Demonstration of 50-mV digital integrated circuits with microelectromechanical relays[END_REF][START_REF] Pillonnet | Adiabatic capacitive logic: A paradigm for low-power logic[END_REF][START_REF] Perrin | Contact-Free MEMS Devices for Reliable and Low-Power Logic Operations[END_REF]. However, their limited mechanical reliability, relatively high operating voltages and low operating frequencies have already been discussed and elaborated [7][8]. Here, we propose capacitive MEMS devices based on comb-drive actuators for storing and transmission of the logic information in a differential architecture. Such capacitive devices are contactless, which strongly limits leakage current and therefore static losses which are usually met by ohmic M/NEMS relays.

Contactless capacitive MEMS device -Principle of operation

The architecture of our device basically relies on a four-terminal MEMS device forming a mechanically-variable capacitor whose terminals are electrically isolated and which is moved by an actuator. The variation of the capacitor, here an interdigitated comb, could be realized with several actuation technologies like e.g. magnetic or piezoelectric. However, our choice of electrostatic MEMS actuation has been driven by their better scaling properties and ease of fabrication. The four-terminal MEMS capacitors are thereby realized with pairs of interdigitated combs -one input comb actuating the second one and varying its capacitance value. The proposed electromechanical logic gate consists of the moving mass combined with two moveable, grounded electrodes and two fixed electrodes. The voltage across the gate-input allows us to control the capacitance of the gate-output.

The capacitance between the interdigitated combs is governed by their physical position and controlled by the electrostatic forces that act between two electrically conductive combs. In our approach, by using a capacitive divider instead of a resistance divider to define the logic level like in CMOS logic (Figure 1a and 1b), the electrical connection between the power and the ground is omittedtherefore avoiding leakage currents through a direct resistive connection. Furthermore, using the AC power supply -acting as the power-clock (VPC), allows for recovery of the electrical charges invested in the encoding of the logic state. Such adiabatic operation is described in references [START_REF] Fanet | Ultra Low Power Electronics and Adiabatic Solutions[END_REF] and [START_REF] Teichmann | Adiabatic Logic: Future Trend and System Level Perspective[END_REF]. The cascade between gates and the propagation of logic states are not covered in the scope of this article, but are clearly described in reference [START_REF] Galisultanov | Contactless four-terminal MEMS variable capacitor for capacitive adiabatic logic[END_REF].

The proposed geometry (architecture) of the device is shown in Figure 1c. This differential architecture consists of two pairs of comb-drive actuatorsinput and output pair. Each pair consists of a fixed (active) and a movable (passive) electrode while the movable electrodes are connected by a mechanical spring of a stiffness k. Active and passive electrodes are connected to the power-clock VPC and to the ground, respectively. They are electrostatically coupled by n interdigitated fingers separated by an air gap g. The architecture being differential, the input and output are driven by complementary voltages 𝑉 𝑖𝑛 and 𝑉 ̅ 𝑖𝑛 and 𝑉 𝑜𝑢𝑡 and 𝑉 ̅ 𝑜𝑢𝑡 , respectively (Figure 1b and1c), defining a so-called dual-rail logic. The input voltage that is set on the fixed comb in the input pair (blue in Figure 1c) causes the movement of the "input"-movable comb and therefore the "output" movable comb as well. The consequential movement of the output comb, coding the logic state, results in a changed capacitance between the combs of the output actuator (green in Figure 1c) which can then be read through a capacitive divider formed with the fixed capacitor (Cf in Figure 1b and1c) and the load C (from the interconnection and the next gate). The output voltages 𝑉 𝑜𝑢𝑡 and 𝑉 ̅ 𝑜𝑢𝑡 serve as the input voltages for the control of the next device.

a) b) c)

Our proposed system follows the adiabatic logic style [START_REF] Fanet | Ultra Low Power Electronics and Adiabatic Solutions[END_REF][9]. The information encoding and reading is done in four phases governed by the power clock VPC which has a trapezoidal waveform for the sake of energy efficiency and recovery of the electrical charges. Dissipation in the adiabatic logic is governed by the ramping time T of the power clock signal. Figure 2 shows the waveform of the main signals needed to drive a single logic gate as well as the corresponding position of the device during the information encoding and reading. As an example, the four phases of the transportation of the logic state "1" (high state) are shown. In phase 1 (known as set) the signals A and Ab of respective amplitudes VH and VL are applied, corresponding to a logic signal in the high state and in the low state, respectively. Two electrostatic forces act on the beam. The beam undergoes a greater force by the electrode A because VH>VL. At the end of phase 1 (at t=T), the beam has moved to the left.

In phase 2 (known as evaluate), the VPC signal is applied via the capacitive bridge formed by the fixed capacitance and the equivalent capacitance of the nodes S and Sb. The beam continues to move. The output voltage S is established at a value VH corresponding to a high logic state (t=2T).

In phase 3 (called maintenance or hold), the input signals A and Ab are gradually lowered to ground (t=3T). The maintenance of the position is due to the output electrodes that are still polarized via VPC which is maintained.

In phase 4 (known as recovery) the VPC signal is gradually reduced, leading the position of the beam towards the center -the "resting" position (t=4T).

FEM analysis of capacitive behaviour of the combs with low overlap

Our device is based on electrostatic actuation of the comb-drives and requires fine knowledge and control of the capacitance between the opposing combs. The variation of the capacitance is realized through the change of the finger overlap. Deep understanding of the comb-drive behavior and the impact of their geometry and displacement is required for the design of a logic gate that can provide sufficient logic differentiation between "0" and "1" states at the output stage (Vout in Figure 1c). Furthermore, the logic state should be preserved during propagation through a cascade of several gates and ultimately a complex logical circuit where multiple inputs are being driven by a single output should be feasible. System level modeling and optimization showed us that some critical phases of the device operation require controlling of the combs in an arrangement where the finger overlap is close to a zero. Such a model is neither covered by the usual analytical modeling of electrostatic comb-drives nor in the literature.

As a consequence, behavioral modeling and extensive FEM analysis (using COMSOL Multiphysics) of the device, including the comb-drive actuators, have been done in order to better understand this regime. The analysis provided the information about capacitance and generated force -necessary for the design of the comb-pairs and for enabling the operation of logic functions in cascaded gates. In particular, geometrical parameters as the length of the fingers, their width d and thickness h, gap between consecutive fingers g, their overlap xr and number N were investigated.

The influence of these parameters on the variable, fixed and parasitic capacitances of the actuator, including fringe effects, and the induced force between the combs were analyzed in detail. As an example, Figure 3 shows the FEM modeling of an electrostatic comb and the simulation of the electric field between fingers of the corresponding combs.

Microfabrication process flow

The extensive FEM analysis provided sufficient data for the design of a full logic gate that could be fabricated using standard microfabrication technologies. As the devices include moveable parts, they require fabrication on silicon-on-insulator (SOI) wafers, the buried oxide layer being used as the sacrificial layer during the releasing step.

Figure 4 illustrates the main steps of the fabrication process. We use 4-inch (100 mm) (1-0-0) SOI wafers with the device layer of 5 µm and buried oxide of 2 µm thickness. Device layer has resistivity of 0.001-0.005 Ohm•cm, it is n-doped with As with concentration 10 19 -10 20 cm -3 .

Before the beginning of the fabrication wafers are cleaned in the standard RCA procedure. This step ensures removal of all the organic and ionic contaminants from the wafer surfaces. Cleaned wafers are first coated with bottom anti reflective coating (BARC) and baked at 200°C for 60s. On top of the cooled-down BARC a positive ECI (MicroChemicals) photoresist is applied and soft-baked for 90s using EVG120 (EVG Group) automatic resist processing system. Exposure is done on Canon FPA 3000i4/i5 Stepper (Figure 4b), which allows photoresist exposure at 365 nm (i-line), followed by a development in MF-CD-26 (Microposit) developer with EVG120 system (Figure 4c). Pattern transfer into silicon is performed with Alcatel AMS4200, a high-density plasma reactor (Figure 4d). The reactor is ICP-RIE (Inductively Coupled Plasma) and is used for treatment of 4-inch wafers. The top silicon layer is etched in a DRIE procedure (Bosch process) with cycle 2.2s/2s (SF6/CH2F2). Backside etching is performed bellow unfixed device parts in order to reduce the parasitic capacitance (Figure 4e). Moveable parts are finally released in the hydrofluoric acid that etches the buried oxide beneath the structures (Figure 4f). The preliminary tests for the determination of optimal photolithography and etching parameters were performed on pure silicon wafers. The fabricated test-patterns included sets of identical parallel lines. The sets were varying in line widths and gaps between them. These test structures were used to determine the smallest line width that could be used as the width of the fingers in comb-drive structures. The narrower the fingers are in the comb-drive, the smaller is the footprint of the entire gate. Exposure dose 1.1 µm thick ECI photoresist was varied from 700 mJ cm 2 to 1600 mJ cm 2 in 100 mJ cm 2 steps, whereas the focus was varied from -1 µm to 0.3 µm in 0.1 µm steps. The etching was performed for 65 s using Bosch procedure. The combination of exposure dose and focus that yielded the structures closest in size to the ones on the mask. Underetching was measured to be about 20 nm. This can be compensated at the design level or considered in our modeling in order to ensure a proper operation of the devices.

Conclusion

In this paper we introduce an architecture of logic gates and circuits aiming to reach ultra-low power operation, with lower energy dissipation than any CMOS circuit. The paradigm is based on capacitive MEMS devices in a differential architecture, operated in the adiabatic regime. Several design considerations and trade-offs have to be considered to reach the goal, in particular to ensure that a logic differentiation of the output voltage is high enough to enable complex circuits cascading multiple gates. In the current state of research, the devices are realized with MEMS-based tunable capacitors using comb drive actuators and foremost a very fine knowledge of their behavior is necessary. The FEM analyses provided the fundamental information that was necessary for the design of the

Figure 1 :

 1 Figure 1: a) Resistor-based (CMOS) logic with VDD being the DC supply voltage, Vin and Vout being the input and output voltages, respectively, and C being the input load of the next gate; b) Adiabatic contactless logic based on variable capacitors with VPC being the power clocka variable power supply capable of energy recovery and Cf being the fixed capacitance; c) Implementation of variable capacitors with comb-drive actuators in a differential configuration. Vout can then be read through a capacitive divider formed with the fixed capacitor Cf and the input load C.

Figure 2 :

 2 Figure 2: The applied signals and the position of the device during the information transportation (the example of logic state "1") from the input to the output stage of the logic gate. The operation is performed in four stages: phase 1(set)application of signals A and Ab and movement of the beam towards electrode experiencing greater force (here A); phase 2 (evaluate)application of VPC signal, establishment of the output signals S and Sb; phase 3 (hold)lowering of the signals A and Ab to the ground, maintenance of the states through VPC; phase 4 (recovery) reduction of VPC signal, return of the moveable part to the initial position.

Figure 3 :

 3 Figure 3: FEM modeling of an electrostatic comb-pair: a) 3D model, b) simulated electrical field between the combs.

Figure 4 :

 4 Figure 4: Process flow for the microfabrication of the contactless capacitive MEMS device: a) SOI wafer; b) coating with the ECI photoresist and mask exposure; c) pattern development in MF-CD-26; d) Bosch processpattern transfer in the top silicon layer; e) backside etching of bulk silicon; f) releasing of the moveable structures in hydrofluoric acid -wet etching of buried oxide.

Figure 5 :

 5 Figure 5: SEM images of the test structures consisting of sets of parallel 0.5µm wide lines separated by 0.5 µm gaps. The structures were exposed with the dose of 700 𝑚𝐽 𝑐𝑚 2 and with the focus of -0.3 µm.

logic gate and the subsequent floor planning for the device fabrication on SOI wafers. From the microfabrication tests performed in the cleanroom we managed to identify the most optimal fabrication conditions. The next steps in the project would be realization of the devices, i.e. single logic gates and more complex digital circuits, in LAAS followed by their electrical and electromechanical characterizations. This work was supported by the French National Research Agency (ANR) under the research project ZerÔuate (grant ANR-19-CE24-013) involving 4 laboratories: CEA-LETI, LAAS, ESYCOM and G2ELAB, and by the RENATECH French national technological network.


The objective of this assessment is to quantify the confidence in an assurance case or a safety case as it was studied at LAAS [START_REF] Idmessaoud | Belief functions for safety arguments confidence estimation: A comparative study[END_REF][START_REF] Idmessaoud | Quantifying confidence of safety cases with belief functions[END_REF][START_REF] Idmessaoud | Calculation of aggregation formulas for GSN argument types using belief functions[END_REF] . In this questionnaire, we ask an expert to provide her/his judgment regarding some specific situations. Her/his answers will be then integrated in a quantitative framework which is not presented here.

How to play

In order to assess confidence in an assurance case, an assessor needs to evaluate all goal that leads to the overall claim. We adopt an evaluation matrix (figure 1) to assess each goal by two criteria:

• Decision: In a scale of 5 equidistant items, it describes which side the expert leans towards, from the rejection of the claimed goal to its acceptance.

• Confidence: It reflects the amount of information an assessor possesses that can justify her/his decision.

There are 6 equidistant levels of the confidence scale. From "Lack of confidence" to "For sure".

Examples

In the first example (figure 2), the assessor accept the statement in goal (G1) with a very high level of confidence. This decision and its corresponding degree of confidence is based on the simulation report given as evidence (or reference in GSN nomination). In the second example (figure 3) the opinion about (G1) is conditioned by initial opinions on sub-goals (G2) and (G3). In this case, the assessor should give his or her decision and its corresponding level of confidence of (G1) according to the decision and confidence provided in the goals (G2) and (G3).

We can notice that the assessor is opposable to this statement with high level of confidence. This opinion could be explained by the fact that the sub-claim (G3) cannot support (G1) alone. To give a favorite opinion more information about the other sub-claim (G2) is needed. The argument structure to assess Figure 4 represent an extract of the assurance case form the paper [START_REF] Damour | Towards certification of a reduced footprint acas-xu system: A hybrid ml-based solution[END_REF], which aim to demonstrate that a Machine Learning (ML) based system meets its system and safety requirements. This extract shows through different pieces of evidence that the statement (G1) : "The real world situations where the machine learning model (MLM) is not robust are identified and mitigated " is achieved. This statement is supported by two pieces of evidence (G2) and (G3). Each of them is respectively supported by three (S1, S2 and S3) and one (S4) pieces of evidence.

Real-world situations where the MLM is not robust are identified and mitigated

(G1)

Ensure that all unsafe situations are correctly identified and mitigated

(ST)

All unsafe situations are identified

(G2) (G3)

All unsafe situations identified are mitigated

(G7)

Architecture mitigation (switch to the LUT when appropriate)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes

(G5)

Certified development process DO178

(S4)

Formal verification results

(S3)

The validation is trivial (it consists of mathematical decomposition on the whole 3D input space)

(S2)

The validation of this property is trivial (S1)

Figure 4: Assurance Case -ML subsystem robustness [START_REF] Damour | Towards certification of a reduced footprint acas-xu system: A hybrid ml-based solution[END_REF] Part 1 : Elicitation of the opinions on G2

Please read the arguments bellow and give your opinion about the claim (G1) by taking into consideration the initial opinions for sub-goals (G4), (G5) and (G6). To do so, please select the couples (decision, confidence) in the goal (G2) evaluation matrix of each case. It is forbidden to choose couples in the grey area (couples situated in the median are not included).

Figure 1 :

 1 Figure 1: Evaluation MatrixBy analogy, this is comparable to the classical conference paper reviewing where reviewers have to provide a decision (strongly reject to strongly accept) and a level of confidence associated with it (low to expert).

Figure 2 :

 2 Figure 2: Example 1

Figure 3 :

 3 Figure 3: Example 2

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5)

? (G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

All unsafe situations are identified

(G2)

The LUT property is correctly defined

(G4)

The LUT property is checked in each p-box

(G6)

The input space (ODD) is correctly decomposed to p-boxes (G5) ?

Part 2 : Elicitation of opinions on G3

The confidence in (G3) can be deduced from the sub-goal (G7). Please read the arguments bellow and give your opinion about the goal (G3) by taking into consideration the initial opinions on the sub-goal (G7). To do so, please select the couples (decision, confidence) in the goal (G3) evaluation matrix in each case. It is forbidden to choose couples in the grey area (couples situated in the median are not included).

(G3)

All unsafe situations identified are mitigated

(G7)

Architecture mitigation (switch to the LUT when appropriate)

? (G3)

All unsafe situations identified are mitigated

(G7)

Architecture mitigation (switch to the LUT when appropriate)

?

Part 3 : Elicitation of opinions on G1

The confidence in the top goal (G1) can be deduced from these premises. Please read the arguments bellow and give your opinion about the goal (G1) by taking into consideration the initial opinions for sub-goals (G2) and (G3). To do so, please select the couples (decision, confidence) in the goal (G1) evaluation matrix in each case. It is forbidden to choose couples in the grey area (couples situated in the median are not included). In this final section, you have to give your opinion about the premises directly from the evidence provided in each argument. To do so, please read the argument below and choose the appropriate couple (decision, confidence) in each case.

? ? ? ?