S Schneider

J.-W Lackmann

F Narberhaus

J E Bandow

B Denis

J Benedikt

Separation of VUV/UV photons and reactive particles in the effluent of a He/O 2 atmospheric pressure plasma jet

Cold atmospheric pressure plasmas can be used for treatment of living tissues or for inactivation of bacteria or biological macromolecules. The treatment is usually characterized by a combined effect of UV and VUV radiation, reactive species, and ions. This combination is usually beneficial for the effectiveness of the treatment but it makes the study of fundamental interaction mechanisms very difficult. Here we report on an effective separation of VUV/UV photons and heavy reactive species in the effluent of a micro scale atmospheric pressure plasma jet (µ-APPJ). The separation is realized by an additional flow of helium gas under well-defined flow conditions, which deflects heavy particles in the effluent without affecting the VUV and UV photons. Both components of the effluent, the photons and the reactive species, can be used separately or in combination for sample treatment. The results of treatment of a model plasma polymer film and vegetative Bacillus subtilis and Escherichia coli cells are shown and discussed. A simple model of the He gas flow and reaction kinetics of oxygen atoms in the gas phase and at the surface is used to provide a better understanding of the processes in the plasma effluent. The new jet modification, called X-Jet for its appearance, will simplify the investigation of interaction mechanisms of atmospheric pressure plasmas with biological samples.

Introduction

Cold atmospheric pressure plasmas (CAP) are increasingly in the focus of researchers investigating their possible applications in medicine or the food packaging industry [1,2]. CAP jets are able to inactivate bacteria [3], fungi [4], or bio-macromolecules [5] and offer an alternative to standard sterilization methods, where thermo-labile and vacuum-sensitive objects (plastics or living tissues) have to be treated. In addition, several studies indicate that CAP treatment can accelerate wound healing or influence cancer cells [6,7]. These plasmas can be filamentary or glow dielectric barrier discharges (DBD) with few kV voltages, usually pulsed at kHz frequencies [8,9], DBD based jets with so called plasma bullets [10,11,12], or homogeneous glow discharges generated in RF-MW frequencies in form of plasma jets [13,2,14]. The term "cold" refers to temperatures in the plasma effluent close to room temperature allowing direct treatment for instance of skin or thermolabile polymers. These plasmas are operated in air or air-containing gas mixtures. Alternatively they use only He with or without admixture of some molecular gas (usually O 2 ). These plasmas produce positive and negative ions, (V)UV radiation, and reactive radical species, which interact with the treated surface. The effects of different plasma-generated species on the treated systems are a topic of current scientific discussions [1]. The role of reactive oxygen species (ROS) has been stressed by several authors as a key factor influencing vegetative prokaryotic and eukaryotic cells [15,16]. More recently, the combination of ions and ROS has also been discussed [8,2].

Atmospheric pressure plasma jet (APPJ) sources operated with He with some addition of O 2 (≤ 1%) are known to be efficient sources of ROS, particularly oxygen atoms, ozone molecules (O 3 ), or singlet delta oxygen metastables O 2 (a 1 ∆ g ). Measurements and modelling have been reported for a coaxial jet with 1 cm diameter inner electrode and 1 mm electrode gap [17], parallel plate jet with 1 mm electrode separation and 1 mm electrode width [13], or for sources with electrode width larger than 1 mm [13,18]. The plasma dynamics and plasma chemistry in these discharges have also been modelled by several authors [19,20]. These works show that densities of above mentioned ROS are around 10 15 cm -3 in the effluent of these jets and can be tuned by adjusting O 2 concentration, applied power, gas flow, and jet-substrate distance. This kind of plasma is a promising tool for treatment of living tissues or for antibacterial treatment of surfaces at atmospheric pressure. The knowledge of ROS densities and, therefore, also the fluxes could be used to evaluate quantitatively the effects of ROS for example on vegetative bacteria. An unknown factor in these studies is the amount of VUV and UV photons, which are produced next to ROS in the plasma. These photons propagate unabsorbed through He atmosphere, irradiate the treated surface and can induce uncontrolled radiation damage. We report in this article a method, in which plasma generated VUV and UV photons and heavy reactive particles are effectively separated from each other and can be used separately for the surface treatment.

The manuscript is organized as follows. First, the microplasma jet used for the plasma generation is described and its modification allowing the separation is introduced. Second, the fluid dynamic model for the simulation of the gas flow and reaction kinetics of O atoms and ozone is described and discussed. Third, the performance of the X-Jet is tested by measuring the light emission in the 115-875 nm wavelength region and by analyzing the etching profiles of a model polymer film. Finally, the study of the interaction of plasma effluent with bacteria is presented.

Experimental Setup

Two different jets are used in this work. The first plasma source is a parallel plate microscale atmospheric pressure plasma jet (µ-APPJ) and the second source is its modification with two gas channels at the jet nozzle. The µ-APPJ is a capacitively coupled microplasma jet consisting of two stainless steel electrodes (length 30 mm, thickness 1 mm) with a separation of 1 mm, and two glass plates, which confine the inter electrode volume on the sides (cf. Fig. 1). One electrode is connected to a power supply (13.56MHz, applied root-mean-square voltage 200-230V, absorbed power < 1 W) through a matching network and the other one is grounded. The volume of the plasma is 1 x 1 x 30 mm 3 . The µ-APPJ used here equals the µ-APPJ described elsewhere [21,22]. The He gas flow through the jet is 1.4 slm with a small admixture of molecular oxygen (8.4 sccm, 0.6%). It has been shown that this microplasma jet is a typical α-mode discharge [13] and quantitative measurement of O and O 3 densities as function of O 2 concentration, applied power, and distance to the jet are available [21,22]. For example, the densities (concentrations) of O and O 3 measured by molecular beam mass spectrometry at 4 mm distance from the jet under conditions used in this work are 7×10 14 cm -3 (∼28 ppm) and 5×10 14 cm -3 (∼20 ppm) respectively [22]. The concentration of ozone increases with the distance and reaches ∼56 ppm at 50 mm. The substrate to be treated is placed perpendicular to the jet axis at a distance of 4 mm.

The gas temperature can be an issue for treatment of bacteria. The gas temperature in the effluent has been measured for 1% of O 2 admixture and it was below 34 • C under these conditions [13]. The temperature is slightly higher at lower O 2 concentrations. It is around 44 • C at 4 mm distance from the jet nozzle in the free flowing effluent when 0.6% of O 2 are admixed. The gas temperature at the surface placed at 4 mm distance from the nozzle is smaller then this value as verified by the treatment of skin, which does not cause any pain or discomfort.

The transport of atoms and molecules (heavy particles) in the plasma jets with substantial gas flows of several liters/min under atmospheric pressure conditions is mainly controlled by convection. The typical diffusion times from a ∼1 mm diameter gas stream are comparable or longer than the transport time due to convection, which is typically few hundred microseconds. On the other hand, the plasma generated photons propagate in the direction of line-of-sight regardless of the gas flow in the plasma effluent. This difference can be used to separate spatially the VUV and UV photons generated in the plasma from heavy particles in the effluent. An additional flow of helium gas crossing the plasma effluent with comparable or larger flow rate will divert plasma effluent in another direction, while the photons will propagate undisturbed. However, care has to be taken to prevent formation of turbulent flow and to avoid admixture of ambient atmosphere (air) into the flow. This admixture could result in uncontrolled absorption of VUV and UV photons as well as in the change of ROS densities due to reactions of radicals or metastables with O 2 , N 2 , or H 2 O molecules from air. To prevent this admixture we have extended the nozzle of the µ-APPJ from Fig. 1 by two crossed channels as shown in a photograph in Fig. 2(a). We call this jet modification an X-Jet and the two channels direct channel and side channel. The plasma channel is extended as the direct channel beyond the electrodes and is crossed under a 45 degree angle by the side channel with the same 1x1 mm 2 cross section. Additional He flow is applied to the side channel to divert the plasma effluent from the direct channel into the side channel. VUV and UV emission, on the other hand, propagates further through the direct channel (also filled with He) and can be used for surface treatment. This emission contains all wavelengths emitted by the plasma including for example the He excimer continuum emission at 58-100 nm range [23]. This excimer emission is blocked, when a MgF 2 filter (cutting wavelength 115 nm) is used to separate the VUV photons from heavy particles. The role of VUV radiation is often neglected in the discussion of the results obtained by atmospheric pressure plasmas. Alternatively, the treatment by the emission passed through a quartz window (cutting wavelength around 180 nm) is tested or only emission measured in the 200-1000 nm wavelength range was taken into account [24]. The above mentioned He * 2 excimer continuum or strong atomic oxygen lines at 98 and 115 nm are neglected in these cases.

Substrate preparation

A plasma polymer film has been used in etching experiments as a model layer of the organic material. We have used a hydrogenated amorphous carbon (a-C:H) film, which was deposited on a glass substrate in an inductively coupled plasma reactor [25] from 2 Pa of CH 4 gas at power of 200 W pulsed at 500 Hz with a duty cycle of 10%. The a-C:H film had 45 atomic percent of hydrogen, density of 1 g/cm 3 and the carbon was mainly sp 3 bonded. The film thickness was 300 nm with root mean square surface roughness of 3.8 nm. The etched profile was recorded by a profilometer (Dek Tak Stylus Profiler 6M) by measuring a line across the center of the etched area. The same line was measured before etching (baseline measurement) to determine the curvature of the surface due to bending of the glass substrate. This baseline is subtracted from the measured etched profile.

Vegetative B. subtilis and E. coli cells have been treated by both types of the microplasma jets. The following procedure has been used to prepare and evaluate them. B. subtilis 168 and E. coli K12 liquid cultures were incubated for 18 hours over night at 37 • C in LB medium [26]. The cultures were diluted to an optical density of 0.1 at 500 nm (B. subtilis) or 580 nm (E. coli) and were sprayed for 1 second onto LB agar plates. A monolayer surface coverage with ∼4×10 6 cm -2 cell density is achieved in this case. The plates were grown for 2 hours at 37 • C before plasma treatment. After plasma treatment, the sample plates were incubated over night for 18 hours at 37 • C to allow survivors to growth. Zone of inhibitions were observed where treatment was lethal. The diameter of the zone of inhibition is used as a simple measure of the effect of plasma on the bacteria. The shape of the zone of inhibition varies from circular to elliptic and the diameter is reported as an average of its major and minor diameters. Additionally, we have checked that treating of the agar plates with plasma before the application of cells had no effect on bacterial growth. Furthermore, no pH change of the medium occurred during plasma treatment.

Fluid model of plasma effluent

A fluid model of the gas flow combined with the basic kinetic model of the reaction of O atoms with O 2 molecules has been created and solved (using commercial COMSOL 3.5 software) to get better insight into processes in the plasma effluent and to estimate the flux of atomic oxygen to the surface. Two geometries have been simulated. First, the crossing of the channels in the X-Jet has been modelled in a 2D geometry assuming for simplicity infinite thickness of electrodes. Second, the 2D axially symmetric geometry has been used to simulate the oxygen chemistry in the effluent and the flux of oxygen atoms to the surface at the jet surface distance of 4 mm. Governing equations and boundary conditions, which have been used in both models, will be discussed now.

The flow of He is described by incompressible momentum conservation and continuity equations:

ρ ∂u ∂t -∇ • η(∇u + (∇u) T ) + ρu + ∇p = 0 (1) ∇ • u = 0 (2)
with ρ being He gas density (0.164 kg/m 3 at 101325 Pa and 300 K), u gas flow velocity, η dynamic viscosity of He (2×10 -5 Pa/s), and p the pressure (101325 Pa). No volume force is assumed to work on the gas. As boundary conditions no slip has been selected for walls, the average velocity calculated from the gas flow and cross section of the channel has been applied to the gas inlets (∼25.6 m/s for 1.4 slm He flow through 1 mm 2 ) and a constant pressure condition (p = 101325 Pa) has been chosen for any outlet boundary. 300 K gas temperature is assumed in the model.

The transport of O and O 3 species has been simulated as a diffusion-convection transport with diffusion coefficients of 1.29×10 -4 m 2 s -1 and 0.713×10 -4 m 2 s -1 for O and O 3 , respectively (taken from ref. [19]) and with velocities taken from the He flow simulation. The governing equation for species i (i = O, O 3 ) is:

∂n i ∂t + ∇ • (-D i ∇n i ) = R i -u∇n i (3)
The R i is the production or loss of particles due to gas phase reactions. The volume in both geometries is divided into two parts. A plasma region, where steady state conditions with constant densities of all species are assumed, and effluent, where the reactive species recombine. For simplicity, no reactions are assumed in the plasma region (the densities of O and O 3 are taken from the literature and introduced into the model via boundary condition) and only three body reaction of atomic oxygen, O 2 , and He is considered in the effluent.

O + O 2 + He → O 3 + He (4)
This is the dominant gas phase reaction in the plasma effluent, where negligible densities of ions or electrons can be assumed [19]. Reaction rate constant of this reaction is k = 3.4 × 10 -46 (300/T g ) 1.2 m 6 s -1 [27]. For simplicity, constant values of 2.48 × 10 25 m -3 (101325 Pa) and 1.49 × 10 23 m -3 (0.6% of 101325 Pa) are taken for the helium and molecular oxygen, respectively. The following boundary conditions have been used: the densities of O and O 3 are set to 8 × 10 20 m -3 and 3 × 10 20 m -3 , respectively, at the gas inlet of the plasma channel. These values are extrapolated values from the experimental measurements in the effluent [22]. The convection flow is assumed for the outlet boundaries. The boundary conditions at any wall are different for O 3 and O. Ozone is assumed to be unreactive at the wall with insulation/symmetry boundary condition at any solid surface. Oxygen can on the contrary recombine or react at the surface, which has to be considered in the model. The Neumann's boundary condition is therefore used at any solid surface with normal flux of O atoms being lost at that boundary defined as [28]:

F O,surf ace = -n O • 1 2 • β (2 -β) • v (5)
where the minus sign indicates the loss process, β is the surface reaction probability of O atoms at a given surface, and v is the gas thermal velocity given by (8k B T/πm i ) 0.5 . The surface reaction probability β depends on the surface. It can be very low for example for glass (10 -5 to 10 -3 , [29]) and could be close to unity for very reactive surfaces. We take β glass = 10 -3 for glass surface of the channels and β a-C:H = 0.03 for the a-C:H surface. The variation of the former one in the above mentioned range does not modify significantly the results of the simulation and the choice of the latter one will be explained later in the text. The results of the simulation for the crossing of channels in the X-Jet are shown in Fig. 2(b). The gas flow direction and velocity magnitude is indicated by the white arrows (maximum gas velocity on the axis of a single channel is around 33.8 m/s) and the color map represents the simulated density of atomic oxygen. It can be seen that majority of oxygen atoms are diverted into the side channel of the X-Jet. Only small amounts diffuse into the direct channel. This diffusion can be prevented by using higher He flow through the side channel. But we will demonstrate later that even with both He flows being the same the flux of any heavy reactive particle from the plasma to the surface under the direct channel is negligible.

The flux of atomic oxygen towards the surface can be modelled better with the 2D axially symmetric geometry. This model does not allow to model both channels at the same time. However, it describes more correctly the gas flow in a single channel (gas flow is surrounded by walls at each side) and after the channel nozzle. The square 1×1 mm 2 channel is approximated by a cylinder with the radius of 0.564 mm giving the same cross section area. Fig. 3 shows the geometry selected for the simulation. First, a 10 mm long cylinder represents the last 3 mm of plasma channel (no gas phase reaction simulating the plasma steady state) followed by 7 mm of gas flow in a channel without a plasma (taking into account the O recombination reaction (4)). These 7 mm represent the transport in one of the channels of the X-Jet. The effluent outside the channel is simulated as a 4 mm high cylinder with radius of 15 mm. Both top and bottom boundaries are assumed to be walls for simplicity. The top one is assumed to have properties of glass and the bottom one is assumed to be an a-C:H film with different O atom surface reaction probability. The outer wall of this cylinder serves as an outlet boundary in this case. The atomic oxygen and ozone densities in the volume and the flux of atomic oxygen to the surface can be estimated with this model.

The color map in Fig. 3 shows the atomic oxygen density in the gas channel and in the region near the surface. The inset in Fig. 3 shows the velocity field in the region where the gas stream hits the a-C:H surface. Additionally, three streamlines, along which the gas flow moves, are also shown in the inset. The prediction of the model can be validated by comparison with the experimental data. The densities of O and O 3 have been measured as function of the distance from the jet nozzle for the experimental conditions simulated here. The MBMS and TALIF measurements show that O density decreases to 50% at the distance of 11 mm from the nozzle [22]. The simulation predicts a decrease to 65% after transport through the 7 mm tube and 4 mm gap. The simulated decrease is smaller than the measured one. However, it has to be taken into account that measurements were done with the free-standing effluent, without confining glass tube around it. The flow velocity drops without the glass tube confining the gas flow. Additionally, losses of O atoms due to the radial diffusion (which is hindered by the glass surface of the tube) will also cause the faster decrease of O density in the effluent. We performed the same simulation with "free-standing" effluent without confining glass tube and the O density decreases to 55% of its original value, in a very good agreement with the measured data. It corroborates that reaction (4) is the dominant reaction in the plasma effluent. The simulation also predicts that the majority of O atoms reacts with O 2 and is transformed into O 3 molecules. This result is also in agreement with the experimental observations, where the drop of O density is accompanied by a similar increase of O 3 density [22].

The model can help us now to understand the processes governing the spacial distribution of O densities in the effluent and to determine the O flux towards the surface. The O density is highest on the jet axis, where the gas velocity is the largest and the transport time from the plasma is the shortest. That is why the O density drops only to 65% of its original value in plasma. The larger the distance from the axis, the slower is the gas flow and the faster is the drop of the O density due to the three body gas phase reaction with O 2 and He. The gas flow is redirected at the surface from the axial movement into the radial movement. The streamlines in Fig. 3 show that mainly the gas from the axis and near axis region, where the O density is the highest, comes close to the substrate surface. That is why the surface reactions at the glass wall inside the jet or some impurities entering the gas channel near the wall, as it is the case in the direct channel of the X-Jet with additional He gas flow, do not play any significant role in the surface processes at the treated substrate. No significant change of the O flux to the surface is observed even if the surface reaction probability of O at the glass wall is set to 1. The O density in the gap between the jet and the substrate is high only at those places, where also the gas velocity is large (cf the distribution of the O density and the velocity field in Fig. 3). It is again the consequence of fast gas phase reaction of O with O 2 . The O density is large only in those regions, where the transport time from the plasma is shorter or comparable with the reaction time of reaction (4). The surface loss of O atoms at the substrate only has a marginal effect on the bulk O density here because the diffusion is slow compared to gas phase reactions. Only a thin boundary layer just near the substrate is depleted if the surface reaction probability of O at a-C:H film surface is very large. The reaction probability will then influence the profile of the O flux to the substrate, as it is shown later in this article.

Experimental results and discussion

The big advantage of the X-Jet is that it allows us to separate the effect of plasma generated VUV and UV photons from the effects induced by ROS (O 3 , O, impurities,...). The effects of VUV and UV photons only, ROS only, and photons and ROS together on a given sample (for example vegetative bacterial cells on agar plates) can be studied in the following ways: 1) radiation and ROS together: An X-Jet without additional He flow in the side channel will result in the transport of both ROS and (V)UV through the direct channel. 2) ROS only: The same He flow is used in both channels. The additional flow through the side channel will push the heavy particles from the plasma effluent into the side channel as demonstrated in Fig. 2(b).

The flow rates through both channels after the crossing will be the same due to the symmetry of this geometry. The flux of ROS at the exit of the side channel should be similar to the ROS flux at the direct channel in case 1). Some differences will occur due to a missing photo-dissociation and excitation of ROS and O 2 after the crossing of both channels (see also discussion of E. coli treatment later) and due to a slightly asymmetric velocity field across the side channel. The plasma generated VUV and UV photons cannot enter directly into side channel due to geometry constrains, which was corroborated by measurements presented later in this article. 3) VUV and UV only: With additional He flow, only VUV and UV photons without ROS are at the exit of the direct channel. Higher He flow in the side channel can be used to make sure that no ROS from the plasma diffuse into the direct channel.

We report in the following results of several tests, which were carried out to demonstrate the performance of the X-Jet. Afterwards, results of treating bacteria with the unmodified µ-APPJ source in air followed by results of treating E. coli with the X-Jet in controlled He atmosphere will be presented and discussed.

Effectiveness of separation of heavy particles and photons

Measurements of emission intensity: The light emission from the side channel was compared to the emission emitted through the direct channel. First, the emission spectrum in the 200-875 nm wavelength range was measured (Ocean Optics USB4000 spectrometer, data not shown). The atomic oxygen lines at 777.4 and 844.7 nm dominated the spectrum, the third most intens line was the He line at 706.6 nm. Additionally, other He emission lines and emission band of OH around 309 nm were observed in the direct channel. Only the most intens 777.4 line was observed on axis of the side channel with intensity at 0.3% of the value observed in the direct channel. Slightly higher intensity (around 0.7%) is observed slightly off axis of the side channel under the angle of ∼45 degree to the channel axis. This measurements show that the light emission through the side channel is reduced to less than 1% of the value in the direct channel and that reflections inside the channel structure are probably responsible for the residual emission. However, there is still a possibility that the VUV photons with wavelength below 200 nm will be emitted by some longliving excited species, or that VUV photons from the plasma will be reabsorbed and reemitted in the direction of the side channel. Therefore, the solar blind VUV and UV detector (PMT-142, effective in 115 -450 nm wavelength range with maximum relative efficiency at around 220 nm [30]) in the evacuated housing with MgF 2 window has been used to measure the intensity of VUV and UV emission from both channels of the X-Jet and also from the µ-APPJ directly. A 1 mm diameter diaphragm was placed on the MgF 2 window and the jet was always at 4 mm distance from the window to maintain the same acceptance angle for each measurement. The same experimental conditions with 0.6% of O 2 were used again. Again, the emission from the side channel was significantly reduced, now to 0.7% on axis and to 1.5% off axis of the side channel.

No equipment for measuring the complete emission spectrum including wavelengths below 115 nm is currently available in our lab so we cannot exclude that some emission at short wavelength range is emitted through the side channel. However, the fact that the emission above 115 nm was reduced below at least 1.5% and the observation, which will be shown and discussed later, that VUV and UV radiation from the direct channel has only a very small effect on bacteria, strongly indicate that VUV and UV radiation through the side channel is negligible. Additionally, the signal intensity of µ-APPJ and that of the direct channel of the X-Jet could be compared. The installation of the channel structure to the µ-APPJ reduced the emission intensity at 4 mm distance from the jet to approximately 17 percent.

Treatment of a model a-C:H film: A model polymer film, the plasma deposited a-C:H layer, was treated with different components of the plasma effluent separated in the X-Jet. Fig. 4 shows the etching profiles induced by the treatment with the side channel and with additional He flow (further on called ROS-only treatment) and by the direct channel without additional He flow (further on called combined treatment). The gas channel used for the treatment was positioned perpendicular to the treated surface with the channel exit-substrate distance of 4 mm. These experiments were performed in He atmosphere to suppress possible admixture of surrounding air. The treatment time was 4 min with 0.6% of O 2 in the gas mixture and RMS voltage of 230 V.

The etching profile after the ROS-only treatment was bell shaped with a maximum etch depth of 120 nm and a full width at half maximum of around 2 mm. It extended up to ∼4 mm from its symmetry axis (diameter ∼8 mm). This is an expected etching profile caused by reactive species like atomic oxygen, who's density in the gas flow decreases with time (and therefore also with the distance from the jet axis) due to gas phase reactions and surface recombination. The flux of atomic oxygen to the substrate was also simulated by the 2D axially symmetric simulation as described above. The resulting normal flux of this reactive particles for two surface reaction probabilities of O at the a-C:H surface, β a-C:H = 1 and β a-C:H = 0.03, are compared to the etched profiles in Fig. 4. It can be seen that the shape of the etched profile in the ROS-only treatment case matches perfectly the simulated flux of atomic oxygen to the surface when β a-C:H = 0.03 is used, which is a reasonable value between β glass and 1. However, the profile simulated with β a-C:H = 1 is also very similar, just with a little bit smaller width. The small effect of β a-C:H on the profile is due to the fact that the fast gas phase reaction (4) determines the O density near the surface. Higher β a-C:H makes therefore only a small difference in the O depletion in the boundary layer close to the a-C:H surface. Additionally, the predicted absolute flux of 8×10 16 of O atoms/cm 2 /s is higher than the measured etching rate of carbon atoms of 2.8×10 15 of C atoms/cm 2 /s (calculated based on a-C:H film density of 1 kg/m 3 and 45 atomic percent of hydrogen in the film). It can therefore explain the observed etch rate very well even assuming that two O atoms are needed per C to form CO 2 and that some O atoms recombine with each other or react with hydrogen at the surface. We conclude therefore that most probably the atomic oxygen is responsible for the etching of the model a-C:H film and that the area reached by atomic oxygen has a diameter of no more than 10 mm.

The etching profile looked different after 4 minutes of the combined treatment (direct channel, X-Jet without additional He flow). The etched profile was similar only at a distance greater than 1 mm from the jet axis. However, the etching just underneath the jet, where the a-C:H film was in direct line-of-sight to plasma, was significantly slower than in the previous case. This difference in the etching profiles could be explained by hardening of the model a-C:H film by VUV and UV photons. The quanta of VUV and UV radiation have enough energy to break C-H and C-C bonds in the a-C:H film resulting in enhanced cross-linking and densification of the material, which makes it more difficult for atomic oxygen to etch it. The data presented in Fig. 4 nicely demonstrates how important it is to consider VUV and UV radiation generated by the plasma in these experiments. The change of the surface profile of a-C:H film after the treatment with VUV and UV photons only (direct channel, X-Jet with additional He flow) has been checked as well and no etching has been observed after 4 or 20 minutes. This observation corroborates that O atoms do not reach the treated surface in this case even if the same fluxes of He are used in both channels, the case in which some ROS and O 2 diffuse into the direct channel at the channel crossing. However, these species will not diffuse up to the axis of the direct channel and will, therefore, not be transported to the vicinity of the treated substrate (see the discussion of the 2D axially symmetric model and streamlines in Fig. 3).

Treatment of bacteria with µ-APPJ

The bacteria on agar plates were treated with the effluent of the µ-APPJ source in ambient atmosphere. The jet was at 4 mm distance with He/O 2 gas mixture (0.6% O 2 in He) and RMS voltage of 230 V. The densities of the most dominant ROS species, atomic oxygen, and ozone, are around 6×10 14 cm -3 at 4 mm distance under these conditions [22]. The plasma emission is localized between the electrodes and there is no direct contact of this active plasma region with the substrate. Fig. 5 shows the diameter of the zone of inhibition as a function of treatment time. Additionally, the photograph shows the zone of inhibition for B. subtilis after 600 s of the treatment.

The diameter is measured up to the region with the homogeneous density of bacteria. For both bacteria, the diameter of the zone of inhibition reached a final value of 30 mm (Fig. 5). It indicates that the maximal distance on the surface from the jet axis, which the reactive species responsible for inactivation can reach (in the ambient air atmosphere) is 15 mm. We have already shown that the effective distance the atomic oxygen can reach was less than 5 mm. The flux of VUV and UV photons is the most intense just underneath the jet but will be absorbed by air at any radial distance from the jet axis larger than a few millimeters. Therefore, some long-living reactive species have to be responsible for bacterial inactivation at 15 mm distance. We propose that ozone is this reactive species. It is known for its bactericidal effects. Just 5 min treatment with 0.2 ppm of ozone in water is lethal for E. coli, B. cereus, or B. megaterium [31]. Moreover, experiments in air with ozone have shown that it is also effective in killing bacteria laying on the agar plates. Ozone concentrations below 1 ppm and treatment times less than 100 min have been reported to be effective in killing Staphylococcus albus, Streptococcus salivarius, and B. prodigiosus [32]. Ozone is produced effectively in the jet with concentrations at the surface higher than 20 ppm, well above the lethal limits reported in the literature. However, this does not explain why the zone of inhibition is limited to 30 mm diameter only. Moreover, the experiments performed in helium atmosphere, which are discussed in the next paragraph, do not exhibit this behavior. For example, the whole Petri dish with 80 mm diameter was affected after 3 minutes of combined treatment.

These observations can be explained as follows. Ozone is responsible for the inactivation at large distances from the jet. It is lethal in the concentrations generated in the jet and it is stable enough to survive the transport. The difference between the treatment in air and in He atmosphere is the buoyancy force acting on the He/O 2 /O 3 gas mixture in the surrounding air. The O 2 and O 3 concentrations are so small that the average density of the mixture is very close to He density and the diffusion is slow preventing fast depletion of O 2 and O 3 densities from He and fast mixing with air. The buoyancy force lifts up the He/O 2 /O 3 flow from the probe surface at some distance from the jet axis. Ozone is lifted up with the He flow and can therefore not reach the surface at a distance larger than 15 mm from the jet axis. The experimental evidence for this hypothesis is shown in Fig. 6, which presents a schlieren image of the µ-APPJ with 1.4 slm He gas flow pointing downwards to the plane at 4 mm distance. The brighter and darker regions mark the presence of density gradients revealing in this case the boundary between He and air. It can be seen, that this boundary is around 12 mm from the jet axis. It corroborates that the He flow is indeed lifted from the surface. Moreover, this boundary moves a few millimeters over time indicating that turbulent or unstable flow takes place in this region. These observations can very well explain the maximum diameter of the zone of inhibition in the treatment with air as ambient atmosphere.

The buoyancy force is not present when He is used as the surrounding atmosphere and the flow of plasma effluent can spread undisturbed along the substrate surface. Ozone can therefore reach and inactivate the whole area of the Petri dish in this case.

Fig. 5 also shows that the increase of diameter with the treatment time is 4 to 5 times faster for E. coli than for B. subtilis. The reason probably is that B. subtilis, as a Gram-positive bacterium, has a thicker cell wall and is protected better against the plasma treatment. B. subtilis is well known for its resistance against environmental stresses.

Treatment of bacteria with X-Jet

E. coli cells were exposed to the same treatment as a-C:H films. Fig. 7 shows the resulting zone of inhibitions after 0.5, 1, 3, and 6 minutes of combined, ROS-only and radiation only treatments of E. coli. Again, the treatments were performed in a closed reactor filled with He. Because the O 2 gas injected into the jet is depleted only up to several percent, the reactor is filled with a He/O 2 gas mixture. We used an additional He gas flow into the reactor to further reduce the O 2 concentration in the background atmosphere to below 0.2 %. The second constituent of the background atmosphere with larger concentration was O 3 , which is produced in the jet.

The VUV and UV only experiment (direct channel, X-Jet with additional He flow) showed that these photons induce only a very small effect. No inactivation was observed up to 3 min of the treatment and two small zones of inhibition appeared after 6 min of treatment. One was located directly on the jet axis (diameter <1.5 mm) and was probably caused directly by VUV and UV photons. The other one was donut-shaped with a diameter of about 6 mm. This latter one was probably caused by admixture of O 2 or O 3 from the background gas into the effluent, their photo dissociation and reaction at the surface.

The combined treatment and ROS-only treatment showed typical dose-effect relationships. Elongated treatment times resulted in larger zones of inhibition and lower numbers of colony forming units. Contrary to the experiments in ambient air, where the maximum size of the zone of inhibition was limited to 30 mm, the whole area of the Petri dish is affected after 3 and 6 min of combined treatment and after 6 min of ROS-only treatment. The 40 by 40 mm areas (marked by asterisk in Fig. 7) are representative for the whole area of the Petri dishes (diameter 80 mm) in these three cases. As already discussed above, ozone is the most probable candidate for the inactivation at large distance from the jet axis. VUV and UV photons generated in the plasma reach only a very small area (∼2 mm diameter) directly under the plasma jet and reactive atomic oxygen is depleted quickly from the gas phase as it was shown by the etching experiments and by the 2D axially symmetric simulation.

Surprisingly, the effect of the combined treatment was approximately twice as fast as the effect of the ROS-only treatment (cf Fig. 7). We expected to see a synergistic effect between ROS and photons directly under the jet, where cells are exposed to both simultaneously. The diameter of this area is ∼2 mm only. We also expected that the effect outside of this area will be similar for both the combined and ROS-only treatments, in a similar way to that observed for the etching of a-C:H films. This, however, was not the case. The zone of inhibition of the combined treatment had a diameter of 5 mm after 30 s and the density of cells was decreased up to 20 mm from the jet axis after 1 min of treatment. The ROS-only treatment showed no zone of inhibition after 30 s and the visibly affected area only had a 5 mm diameter after a 1 min treatment. Additionally, the combined treatment at 3 min looks similar to the ROS-only treatment at 6 min. These observations indicate that the plasma effluent is changed by the presence of VUV and UV photons, some photochemistry takes place, and more reactive or excited species reach the substrate. Further investigations are planned to better understand this effect.

Conclusions

The modification of the microscale atmospheric pressure plasma jet (µ-APPJ) operated in He/O 2 , so called X-Jet, has been used to test the possibility of separating VUV and UV photons emitted by plasma from reactive particles transported by the gas flow in the plasma effluent. This separation provides the opportunity to study separately the effects of these components on living organisms, biological macromolecules or model films. We have shown that emission intensity of photons in the 115-875 nm wavelength region is reduced to less than 1.5% in the gas channel transporting the reactive oxygen species and we have demonstrated the performance of the X-Jet in etching experiments using a model a-C:H film as a substrate. Similar etching profiles were observed for both combined treatment and for ROS-only treatment. However, in the case of the combined treatment, the VUV and UV photons cause hardening of the model film on the area in line-of-sight to the plasma, which results into slower etch rates directly under the jet nozzle. The fluid model simulation of the gas flows and O reaction kinetics indicate that O atoms are responsible for the etching of the polymer film and that they can reach an area with maximum diameter of 10 mm.

The plasma effluent has been used for the treatment of bacteria. First, we have verified that the µ-APPJ can inactivate B. subtilis and E. coli. Treatment of several minutes leads to zones of inhibition with a diameter of 30 mm with faster inactivation of E. coli. Second, E. coli monolayers on agar plates were treated by the X-Jet in a controlled helium atmosphere. Under the conditions tested, the VUV and UV photons alone had only a small effect on the bacteria. In the ROS-only and combined treatments, the cells were most probably inactivated by ozone at larger distances from the jet and by combined effect of ozone, atomic oxygen, and some other possible impurities in the region close to the jet axis. We could show that the size of zone of inactivation is limited by the buoyancy force when working in ambient air. Furthermore, the results indicate that the VUV and UV photons can produce effectively reactive species in the gas phase, which leads to faster inactivation of E. coli.

We believe that the X-Jet is a powerful tool for the fundamental study of inactivation mechanisms by atmospheric pressure plasmas. Furthermore, this jet can also be used for any surface processing, which requires high fluxes of ROS without VUV and UV radiation, such as treatment of polymers or living tissues.

Figure 1 .

 1 Figure 1. Schematics of a µ-APPJ source and its photograph during the operation with He/O 2 gas mixture.

Figure 2 .

 2 Figure 2. The modification of the source geometry. Additional helium flow diverts the plasma effluent in a side channel. VUV and UV photons propagate in line-of-sight with the plasma through the direct channel. (a) Photograph of the X-Jet operated with He/O 2 plasma. (b) Results of 2D fluid simulation of gas flow and O atom reaction kinetics; arrows correspond to gas velocity field, the color map represents the simulated density of O atoms.

Figure 3 .

 3 Figure 3. The results of the 2D axially symmetric fluid model. The large color map represents the simulated O density in the gas channel (region from -10 to 0 mm on the y-axis with first 3 mm being simulated without reaction (4)) and in the gap between the jet and substrate (0 to 4 mm on the y-axis). Y-axis is the symmetry axis of the model and boundary conditions (glass wall, a-C:H surface, gas inlet and gas outlet) are indicated. The small inset shows the velocity field and streamlines in the zoomed region near the substrate.

1 β

 1 a-C : H = 0. 03 si m ul at ed f l ux ofO radi cal s t o t he surf ace: norm al i zed f l ux ofat om i c oxygen di st ance f rom t he channelaxi s [ m m ]

Figure 4 .

 4 Figure 4. Etched profiles generated in the model a-C:H film after 4 min of the combined treatment (direct channel ) and ROS-only treatment (side channel ) with He/O 2 plasma (0.6% O 2 in He). Applied RMS voltage was 230 V. The profiles were measured across the middle of the treated region. Additionally, a simulated normal flux of atomic oxygen to the surface is shown for two surface reaction probabilities of O at the a-C:H surface, β a-C:H = 1 and β a-C:H = 0.03. Dashed lines indicate, which part of the surface is exposed to the VUV and UV photons in the case of the combined treatment.

Figure 5 .

 5 Figure 5. Diameter of zone of inhibition for B. subtilis and E. coli as function of the treatment time as induced by the µ-APPJ. Plasma parameters: 1.4 slm He with 8.4 sccm O 2 (concentration 0.6%), U RM S =230 V, jet-substrate distance 4 mm, ambient atmosphere. Photograph shows the size of a zone of inhibition for B. subtilis after 600 s of the treatment.

Figure 6 .

 6 Figure 6. Schlieren image of the µ-APPJ with 1.4 slm of He (no O 2 added, plasma off) pointing downwards perpendicularly to the plane at 4 mm distance.

Figure 7 .

 7 Figure 7. 40 by 40 mm details of photographs of Petri dishes with zones of inhibition after 30 s and 1, 3, and 6 min of combined, ROS-only, and VUV and UV photons only treatments of E. coli monolayers. Details marked by * : the entire plate (80 mm diameter) was affected.

Acknowledgement

The authors thank Volker Schultz-von der Gathen for fruitful discussions about the operation of the µ-APPJ source and Henrik Böttner and Nick Knake for the help with Schlieren imaging of the jet. This work has been performed with the support of the research group FOR1123 approved by the German Research Foundation (DFG). This work has also been supported by the Research Department Plasmas with Complex Interactions of the Ruhr-Universität Bochum.


When students give biased responses to researchers

Keywords: Data collection, online surveys, paper-and-pencil surveys, response bias, social desirability, demand artifact

This article investigates the impact of two data collection modes (online surveys and paper-and-pencil surveys) and the perceived attractiveness of the experimenter on two types of response biases: social desirability and demand artifacts. Its results highlight the combined effect of the data collection mode and the perceived attractiveness of the experimenter on social desirability and show that signs sensitivity and signs interpretation (two types of demand artifacts) are stronger in the context of online surveys than in the context of paper-and-pencil surveys.

Researchers in social sciences often use student samples for their investigations, because such respondents are easily accessible. Since the 60's, 80% of the empirical studies published in some of the most prestigious journals in social psychology [START_REF] Sears | College sophomores in the laboratory: influences of a narrow data base on social psychology's view of human nature[END_REF] and consumer behavior, especially in Journal of Consumer Research or Journal of Consumer Psychology [START_REF] Peterson | On the use of college students in social science research: Insights from a second-order meta-analysis[END_REF], have used self-administered questionnaires on student samples. Yet, the use of students is controversial. On the one hand, students' homogeneity enables a better control of the noise created by exogenous variables, which increases the internal validity of the results [START_REF] Calder | Designing research for application[END_REF][START_REF] Greenberg | The college sophomore as guinea pig: Setting the record straight[END_REF]. But on the other hand, some of their characteristics might alter the quality of their responses. Specifically, their self-concept and attitudes are less precisely defined than those of adults [START_REF] Sears | College sophomores in the laboratory: influences of a narrow data base on social psychology's view of human nature[END_REF], which may increase socially desirable responding. In addition, their higher cognitive abilities [START_REF] Orne | On the social psychology of the psychological experiment: With particular reference to demand characteristics and their implications[END_REF]) may increase demand artifacts, i.e. "the biases that result from the adoption of a specific role by the subject who believes that he or she has discerned the objective of the study, or provoked by a reaction to the decoding of an experimental manipulation" [START_REF] Herbert | Comportement de réponse de l'individu en situation de questionnement : le biais du répondant en comportement du consommateur[END_REF]. The existence of these biases could explain why the effects observed on student populations differ in intensity and sometimes in direction from the effects observed on nonstudents [START_REF] Peterson | On the use of college students in social science research: Insights from a second-order meta-analysis[END_REF].

In this article, we study these biases in the light of the opportunities provided by the diffusion of the Internet. Whereas many researchers have highlighted that online surveys enabled to save time and effort in quantitative data collection [START_REF] Couper | Web surveys: A review of issues and approaches[END_REF][START_REF] Cobanoglu | A comparison of mail, fax, and Web-based survey methods[END_REF][START_REF] Mcdonald | A comparison of online and postal data collection methods in marketing research[END_REF], their ability to reduce social desirability bias and demand artifacts has yet to be studied. Our first objective is to compare the impact of two self-administered data collection modespaper-and-pencil surveys and online surveyson these biases. Since both administration modes imply the physical (paper-and-pencil) or virtual (online) presence of an experimenter, our second objective is to explore the role of the perceived attractiveness of the experimenter on the two biases.

Theoretical Foundations and Hypotheses

Many studies have already compared online surveys to face-to-face interviews [START_REF] Heerwegh | Face-to-face versus Web surveying in a high-Internetcoverage population: differences in Response Quality[END_REF] or phone interviews [START_REF] Dillman | Response rate and measurement differences in mixed mode survey using mail, telephone, interactive voice response and the Internet[END_REF][START_REF] Fricker | An experimental comparison of web and telephone surveys[END_REF][START_REF] Kreuter | Social desirability bias in CATI, IVR, and Web surveys: the effects of mode and question sensitivity[END_REF]. These studies have reached the following conclusions. Interviewer-administered questionnaires (face-to-face and phone interviews) enable to collect higher quality responses than online questionnaires: a lower rate of "don't know" responses and non-responses and a higher variance in the responses [START_REF] Heerwegh | Face-to-face versus Web surveying in a high-Internetcoverage population: differences in Response Quality[END_REF]. As Holbrook and his colleagues (2003) explain, the presence of an interviewer gives rise to non-verbal communication, enables the interviewer to ease the comprehension of the questions, and reduces respondents' distraction. However, intervieweradministered questionnaires generate more social desirability than online questionnaires. Though interesting, these studies do not compare online surveys to self-administered paperand-pencil surveys. To make up for this gap, we propose and test an explicative framework.

The impact of data collection mode on social desirability

The concept of social desirability rests on the notions that there are social norms governing some behaviors and attitudes and that people may misrepresent themselves to appear to comply with these norms [START_REF] Kreuter | Social desirability bias in CATI, IVR, and Web surveys: the effects of mode and question sensitivity[END_REF]. In social science research, Naas, Moon, and Carney (1999) explain that social desirability is triggered by two factors: the nature of the questions (sensible or related to personal topics) and the presence of an interviewer, who activates the existence of social norms.

As previously mentioned, there is no consensus on the impact of the collection mode (online vs. paper-and-pencil) on social desirability. Whereas some authors suggest that the interaction with a computer creates a feeling of intimacy and anonymity that reduces socially desirable responding (e.g., [START_REF] Martin | Some effects of computerized interviewing on job applicant responses[END_REF], others find contradicting results (e.g., [START_REF] Lautenschlager | Computer administration of questions: More desirable or more social desirability[END_REF]. According to them, respondents to a computerized survey anticipate the fact that their answers will be identified, verified and stored in a database, which increases socially desirable responding. A meta-analysis conducted by [START_REF] Richman | A meta-analytic study of social desirability distortion in computer-administered questionnaires, traditional questionnaires, and interviews[END_REF] on more than 61 studies published between 1967 and 1997 reached the conclusion that it is not so much the medium (computer vs. paper) as the existence of moderating variables that triggers social desirability. Among these moderating variables is the presence or absence of an experimenter. Since paper-and-pencil surveys require the presence of an experimenter and online surveys do not, we propose the following hypothesis:

H 1a : Social desirability bias is stronger in paper-and-pencil surveys than in online surveys.

In the case of an online survey, the researcher is not physically present when respondents answer the questionnaire. However, he or she can signal his or her presence with the use of graphic elements. Several studies in electronic commerce (e.g., [START_REF] Hassanein | The impact of infusing social presence in the web interface: An investigation across product types[END_REF] have shown that the use of design elements such as pictures were indeed able to create an online social presence that leads to more favorable consumer attitudes. In this study, we hypothesize that this online social presence activates the existence of social norms, which increases social desirability.

H 1b : In online surveys, social desirability bias is stronger when the experimenter is visually identified (i.e. in the presence of a picture of the experimenter) than when it is not identified (i.e. in the absence of a picture of the experimenter).

The impact of data collection mode on demand artifacts

Demand artifacts consist of three biases: a signs sensitivity bias (the respondent pays attention to the connections that exist between the questions and tries to guess the objective of the study), a signs interpretation bias (the respondent actually figures out the objective of the study) and a motivation bias (the respondent modifies his or her responses to go either in the direction or in the opposite direction of the study's perceived objective). These three biases represent the three steps of an ordered sequence [START_REF] Schwartz | Answering questions: methodology of determining cognition and communication processes in survey research[END_REF][START_REF] Herbert | Comportement de réponse de l'individu en situation de questionnement : le biais du répondant en comportement du consommateur[END_REF]. In this study, we hypothesize that two elements have an impact on these biases: 1) the data collection mode and 2) the interviewer attractiveness. More precisely, the data collection mode furthers (or not) an information processing that increases signs sensitivity and signs interpretation. Then, the interviewer attractiveness leads (or not) to a distortion of the responses according to the perceived objective of the study.



The impact of data collection mode on signs sensitivity and signs interpretation

To understand the impact of the data collection mode on signs sensitivity and signs interpretation, we refer to the satisficing theory [START_REF] Krosnick | Response strategies for coping with the cognitive demands of attitude measures in surveys[END_REF]. According to this theory, optional question-answering takes a considerable amount of cognitive work: a respondent must interpret the meaning and intent of each question, retrieve relevant information from his or her memory, integrate that information into a summary judgment, and then report that judgment taking into account the provided response alternatives. Whereas many respondents may perform these steps, other respondents might take cognitive shortcuts to reduce the required effort (and exhibit satisficing behavior). The motivation and ability of the respondent reduce the probability to use a heuristic whereas the perceived difficulty of the task increases this probability.

When answering an online survey, respondents can be distracted by the simultaneous use of other applications, as well as by the execution elements (colors, buttons to click etc.) that build up online questionnaires. Online surveys also require respondents to understand how to use the data collection software and its peripheral tools, which complicates the answering procedure and decreases respondents' motivation to thoroughly process the questions. In the light of the satisficing theory [START_REF] Krosnick | Response strategies for coping with the cognitive demands of attitude measures in surveys[END_REF], the probability to use a heuristic will therefore be higher in the case of an online survey than in the case of a paper-and pencil survey. Alternatively, the probability of elaboration will be higher in the case of a paper-and-pencil survey than in the case of an online survey. We hypothesize that this higher elaboration translates into a higher signs sensitivity, which in turn translates into a higher signs interpretation.

H 2 : Signs sensitivity bias is stronger in paper-and-pencil surveys than in online surveys.

H 3 : Signs interpretation bias is stronger in paper-and-pencil surveys than in online surveys.



The impact of the experimenter attractiveness on the motivation bias

Subjects who are sensitive to the signs of a questionnaire and who have been able to discern the objective of the research may (or not) be motivated to answer in the direction of the survey. According to the source-attractiveness model [START_REF] Mcguire | Attitude and Attitude Change[END_REF], a message depends for its effectiveness chiefly on the familiarity, likeability and similarity of the source with the receiver of the message. We hypothesize that the relationship between the signs interpretation bias and the motivation bias too is moderated by the attractiveness of the experimenter, that is, by its perceived familiarity, similarity and likeability.

H 4 : The motivation bias is stronger in the presence of an attractive experimenter than in the presence of an unattractive experimenter.

Methodology

Three variables were manipulated: the data collection mode (online survey vs. paper-andpencil survey), the presence of an experimenter (presence vs. absence) and his attractiveness (attractive vs. unattractive). Since paper-and-pencil surveys require the presence of an experimenter, five experimental conditions (i.e. five versions of the same questionnaire) were created: 1) an online questionnaire with the picture of an attractive experimenter, 2) an online questionnaire with the picture of an unattractive experimenter, 3) an online questionnaire without any picture of the experimenter, 4) a paper-and-pencil questionnaire distributed by an attractive experimenter and 5) a paper-and-pencil questionnaire distributed by an unattractive experimenter.

To test our hypotheses, we needed a theme that triggers social desirability. We chose that of consumer's ecological sensitivity. At the beginning of the questionnaire, respondents therefore had to answer general questions about their ecological sensitivity and knowledge in terms of ecology. Then, they were asked to look at an extract of an internet site that promoted the launching of a new ecological car. Two series of questions followed. The first one evaluated the respondents' attitude toward the internet site as well as their attitude toward the car; the second one evaluated their memorization abilities (e.g., respondents were asked specific questions about the informative elements that appeared on the site, and they also had to make the list of all the elements they remembered from the site). These memorization questions were asked to provide an indirect measure of the information processing mode (elaborated or not). Finally, Herbert (2005)'s demand effects scales were inserted, as well as general questions about the survey (perceived boredom and seriousness with which the respondents answered the questionnaire) and the experimenter. The latter enabled to do a manipulation check.

In total, 232 students participated in the study. They were distributed within the five versions of the questionnaire.

Results

Social desirability can be measured directly, with the use of a scale (one of the most wellknown scales was developed by [START_REF] Crowne | A new scale of social desirability independent of psychopathology[END_REF]), or indirectly, through an examination of the means and variances obtained on sensitive questions [START_REF] Holbrook | Telephone vs. face-to-face interviewing of national probability samples with long questionnaires: comparisons of respondent satisficing and social desirability response bias[END_REF][START_REF] Nass | Are respondents polite to computers? Social desirability and direct responses to computers[END_REF]. Since most of the social desirability scales are long to administer (e.g., 33 items for the Marlowe-Crowne scale), we chose the indirect method. More precisely, we assessed social desirability by running t-tests on two variables: the declared ecological sensitivity of the respondents (3 items) and the difference between their declared expertise in terms of ecology (2 items) and their actual expertise (6 items).

No direct effect of the administration mode (online vs. paper-and-pencil, H 1a ) and the presence of an experimenter (H 1b ) was identified, which supports the meta-analyses conducted on the topic. Interestingly, complementary analyses showed that in the context of an online survey, respondents were significantly more inclined to define themselves as sensitive to ecological matters when the experimenter was attractive than when the experimenter was unattractive. Though interpretable with caution (the comparison of the mean ecological sensitivity scores is only an indirect way to measure social desirability bias), this result suggests that the experimenter's attractiveness may have an impact on social desirability in the context of online surveys.

To test H 2 , we performed a t-test with sign sensitivity as the dependent variable. The results indicate that contrary to predictions, respondents are significantly more sensitive to the signs of the questionnaire when they answer an online survey than when they answer a paper-andpencil survey (M onliune = 5.13 vs. M paper-and-pencil = 4.44 ; t = 3.75 ; p<0.001). However, this does not mean that they process information in a more extensive manner. Indeed, respondents to the paper-and-pencil survey were better at memorizing the slogan of the brand and the gas emission rate of the car (34.8% and 87.0% of correct answers for the respondents to the paper-and-pencil version of the questionnaire vs. 27.0% and 67.5% for the respondents to its online version) and the number of informative elements they remembered was significantly higher than the respondents to the online version of the questionnaire (M online = 2.25 vs. M paper- and-pencil = 3.35 ; t = 4.39 ; p<0.001). This suggests that when students answer a paper-andpencil survey, they focus more on the content of the questions than on what the questionnaire tries to show. In other words, they take care of providing responses that truly correspond to what they think and they more extensively process each piece of information. This could be because the administration context (a class or lecture room) is similar to the context in which students are evaluated. Students are therefore put in a situation that furthers an elaborate information processing.

Since respondents are more sensitive to the signs of the questionnaire in the context of an online survey than in the context of a paper-and-pencil survey, we logically find that they are also more inclined to interpret these signs (M online = 4.76 vs. M paper-and-pencil = 4.37 ; t = 1.81 ; p=0.07). Similar to H 2 , H 3 is not supported.

Finally, no direct or indirect effect of the perceived attractiveness of the experimenter was identified on the motivation bias. H 4 is not supported

Discussion

This research aimed at studying the impact of two data collection modes (online surveys vs. paper-and-pencil surveys) and the perceived attractiveness of the experimenter on two types of response biases: social desirability and demand artifacts. Though not expected, its results hold important implications for researchers. First of all, they highlighted the combined effect of the data collection mode and the perceived attractiveness of the experimenter on social desirability. Second of all, they showed that signs sensitivity and signs interpretation (two types of demand artifacts) were stronger in the context of online surveys than in the context of paper-and-pencil surveys.

Despite the increasing use of online surveys, and despite all their advantages (when conducted on students, online surveys enable to save time and effort in data collection, and they give access to a wider sample than paper-and-pencil surveys), researchers therefore have to be aware of the specific biases they trigger.

Figure 1

 1 Figure 1 displays the conceptual framework of the study and summarizes the hypothesis tested.

Figure

  Figure 1. Conceptual framework


Ludovick Lepauloux
email: ludovick.lepauloux@intel.com

Pascal Scalart
email: pascal.scalart@enssat.fr

HIGHLIGHTING THE INFLUENCE OF ARTIFACT SIGNALS ON THE EQUILIBRIUM STATE OF THE FEEDBACK STRUCTURE

In this paper, we address the problem of the determination of the equilibrium point of the feedback structure initially used for twochannel adaptive noise cancellation in the presence of crosstalk. We concentrate on an important characteristic of an adaptive filter, i.e. the steady-state mean-square error observed once the algorithm has converged. Our approach relies on the analysis of the relationships between the useful signals and their artifacts (distortion, residual noise, crosstalk) at the system outputs. The obtained equilibrium point essentially comes from experimental observations, nevertheless, we propose in the first part a theoretical framework that enables to highlight the links between the different signals in the feedback structure and also used to define the equilibrium point. Then, we give experimental results that show that the equilibrium state is obtained when the energy of the artifacts on the output signals is the same on each channel.

INTRODUCTION

Identifying an unknown system has been a central issue in various applications areas such as control, equalization, echo cancellation in commmunication networks and many others. In this work, we focus on a particular type of system, namely the symmetric adaptive filter structure, that has been proposed by different authors to solve noise cancellation problems with signal leakage, also called crosstalked problems or cross-coupled interference problems. We concentrate our analysis on the convergence properties and asymptotic behaviour of the feedback separation structure which is represented in Figure 1 in the two-channel case. Such properties have been first studied in very simple cases. Most of the time, stationary input signals and/or single tap mixing filters (instantaneous mixture) were assumed [START_REF] Van Gerven | Signal separation by symmetric adaptive decorrelation : stability, convergence and uniqueness[END_REF][START_REF] Weinstein | Multi-channel signal separation by decorrelation[END_REF] as a consequence of the mathematical complexity of the required analyses [START_REF] Lepauloux | An efficient lowcomplexity algorithm for crosstalk-resistant adaptive noise canceller[END_REF][START_REF] Mirchandani | A new adaptive noise cancellation scheme in the presence of crosstalk[END_REF]. Indeed, the inherent cross-coupling Figure 1: Mixing model (left) and separation structure (right). The introduced delay arbitrarily fixed in the separation structure is justified by implementation considerations. of this structure introduces an infinite impulse response filter which can lead to potential instability. Thus, the convergence analysis is a critical issue but addressing this problem is more difficult than in classical adaptive FIR filtering because the Hessian matrix associated with the considered structure is time-varying even when the input signals are stationary. Usually, analysis of adaptive filtering algorithms requires simplifying assumptions, such as the small step-size assumption or the well-known independence assumption between successive regressors, in order to derive expressions that describe the performance of the algorithm. As an example, we can refer to the fixed point theory [START_REF] Mandic | Machine learning and signal processing applications of fixed point theory[END_REF] that is an elegant manner to derive convergence properties of adaptive systems. Although these assumptions are rarely satisfied by real-life data, they render the convergence analysis tractable. Furthermore, when analyzing the feedback structure of Figure 1, we can easily derive an equivalent adaptive identification problem [START_REF] Eweda | A new approach for analyzing the limiting behavior of the normalized lms algorithm under weak assumptions[END_REF] for the adaptive filter w 21 (illustrated in Figure 2) where (i) the input sequence s 2 (n) and the noise b(n) are mutually dependent, (ii) the noise sequence b(n) is not stationary and (iii) the noise sequence depends on w 21 . The same analysis holds for the dual filter w 12 . The above properties are not usual in the context of adaptive filtering and, to our knowledge, no theoretical results have so far been established in such conditions. As a consequence, no useful design guidelines are avalaible to control the convergence of the adaptive feedback system of Figure 1. Nevertheless, some major contributions were produced in Figure 2: Equivalent adaptive plant identification of h 21 . On this scheme, Δs 2 (n) denotes the vector composed of artifact signals and defined by Δs

2 (n) = s 2 (n) -s 2 (n).
the literature. In [START_REF] Charkani | Self-adaptive separation of convolutively mixed signals with a recursive structure. part i: stability analysis and optimization of asymptotic behaviour[END_REF][START_REF] Charkani | Self-adaptive separation of convolutively mixed signals with a recursive structure. part ii: theoretical extensions and application to synthetic and real signals[END_REF] Charkani and Deville give a complete analysis of the recursive structure for self-adaptive (blind) separation of convolutively mixed signals. On account of ordinary differential equation technique (ODE), equilibrium and stability conditions can be analyzed for a large class of separating functions that are restricted in order to ensure the separating point is an equilibrium state. Indeed, due to the heavy complexity of the obtained mathematical expressions, this study was carried out only around the desired solution (w 21 = h 21 and w 12 = h 12 ) that is assumed to be the equilibrium point corresponding to the separating solutions. In contrast with the common approaches which consist in first defining the adaptive algorithm and then analyzing the behavior of this one according to a given structure, in this paper, we first define analytically useful relations between the different signals. Then, based on energy conservation arguments and under weak assumptions, we define the observed equilibrium point of the separation structure of Figure 1. In that sense, our approach is close to the energy conservation principle developed by Yousef and Sayed [START_REF] Yousef | A unified approach to the steadystate and tracking analyses of adaptive filter[END_REF]. Finally, extensive simulations illustrate the derived results and show the validity of this equilibrium state.

PROBLEM STATEMENT

Let us consider the mixing model described in Figure 1. The two observations can be expressed in the Z-domain as:

Y 1 (z) Y 2 (z) = M(z) S 1 (z) S 2 (z) , M(z)= 1 H 12 (z) H 21 (z)
1 .

Where M(z) denotes the mixing matrix. In order to cancel the existing coupling effect between the observations and to recover the original sources, the separating filters w ij of the recursive structure shown in the same figure (right side) just have to 'mimic' the filter h ij of the mixing model, i.e. to converge towards them. Then, inversion of M(z) is actually performed by the recurrent connection. This is the main advantage of the feedback structure in contrast with the feedforward one that needs to estimate the inverse of the mixing matrix M(z).

EQUILIBRIUM STATE

In the following, uppercase symbols in boldface font denote matrix quantity whereas lowercase symbols in boldface font indicate a vector quantity. Normal font is used for scalar quantity. The diag operator denotes diagonal elements of matrix and * the convolution operator. As stated in Figure 1, {s 1 , s 2 } and {y 1 , y 2 } are respectively the source and the observation signals. We use { s 1 , s 2 } to represent the estimated signals. The following assumptions are used throughout the paper.

• Assumption A1. The filter coefficients are slowly varying in time.

• Assumption A2. To ensure stability, we impose that h 12 is strictly causal. • Assumption A3. The equilibrium state of the feedback structure is obtained when the energy of the artifacts on the output signal is equal on each channel. • Assumption A4. The source signals s 1 and s 2 are assumed to be stationary random variables with zero mean and variance σ 2 s 1 and σ 2 s 2 respectively.

Artifact analysis on each estimated signal

According to the mixing and separation models, the artifact signals

Δs 1 (n) = s 1 (n) -s 1 (n) on s 1 (n) can be formulated as Δs 1 (n) = y 1 (n) -w 21 T (n) s 2 (n) -s 1 (n) = h 21 T s 2 (n) -w 21 T (n)y 2 (n) + w 21 T (n)diag W 12 T (n) S 1 (n -1) (1)
with

h 21 = [h 0 21 h 1 21 ...h L-1 21 ] T , w 21 (n) = [w 0 21 (n) w 1 21 (n) ...w L-1 21 (n)] T , y 2 (n) = [y 2 (n) y 2 (n -1) ...y 2 (n -L + 1)] T , s 2 (n) = [s 2 (n) s 2 (n -1) ...s 2 (n -L + 1)] T , s 2 (n) = [ s 2 (n) s 2 (n -1) ... s 2 (n -L + 1)] T , S 1 (n -1) = [ s 1 (n -1) s 1 (n -2) ... s 1 (n -L)], W 12 (n) = [w 12 (n) w 12 (n -1) ...w 12 (n -L + 1)].
Assuming that the filter coefficients are slowly time varying [START_REF] Lepauloux | An efficient lowcomplexity algorithm for crosstalk-resistant adaptive noise canceller[END_REF] (A1), i.e. w 12 (nj) = w 12 (n) ∀ j = 0,...,L -1, which is equivalent to fix a low step-size (asymptotic behaviour) and noting

that y 2 (n) = s 2 (n) + S 1 T (n)h 12 , relation (1) could be reformu- lated as Δs 1 (n) = Δh 21 T (n)s 2 (n)- w 21 T (n) S 1 T (n)h 12 -S T 1 (n -1)w 12 (n) . ( 2
)
Where Δh 21 (n) = h 21 -w 21 (n) is the weight deviation vector.

Let us introduce the matrix

ΔS 1 (n) = S 1 (n) -S 1 (n), (3)
and causality constraint (A2) on h 12 such that h 12 (0) = 0, the expression in the bracket reduces, and (2) yields to

Δs 1 (n) = Δh 21 T (n)s 2 (n)- w 21 T (n) S 1 (n -1)Δ h 12 (n) + ΔS 1 T (n -1)w 12 (n) (4)
where

S 1 (n -1) is a truncated version of S 1 (n -1) of size L × (L -1). Similarly, h 12 = h 12 (i) | i=1,...,
Δs 2 (n) = Δ h T 12 (n) s 1 (n -1)- w 12 T (n)S 2 T (n -1)Δh 21 (n -1) - w 12 T (n)ΔS 2 T (n -1)w 21 (n -1). (5)
Equations ( 4) and ( 5) define the artifact signals on the outputs and associated with the feedback structure. The global network corresponding to these two relations is shown in Figure 3. Based on this network, the equilibrium point will be discussed in the next paragraph.

Conservation of the artifacts energy at each output

Let us assume that the equilibrium state of the feedback structure given in Figure 1 is obtained when the energy of the artifacts on the output signal is the same on each channel (A3), i.e. E Δs 2 1 (n) = E Δs 2 2 (n) . By considering that the filters are slowly time varying, i.e. w 21 (n) * w 12 (n) = w 12 (n) * w 21 (n -1), equal output artifact energy ensure identical correlation properties of the signals present at points A and B (see Figure 3). Although it is not universally correct, we will assume that the previous statement is equivalent to the equality of the power spectral densities given hereafter:

Φ AA (e jω ) = ∞ ∑ k=-∞ r AA (k)e -jkω = ∞ ∑ k=-∞ r BB (k)e -jkω = Φ BB (e jω ) (6)
where

r AA (k) = E [A(n)A(n + k)]
is the correlation function of the signal in point A. Assuming that s 1 (n) and s 2 (n) are independent, we get from Figure 3:

Φ AA (e jω ) = Φ S 1 S 1 (e jω ) H 12 (e jω ) -W 12 (e jω ) 2 W 21 (e jω ) 2 + Φ S 2 S 2 (e jω ) H 21 (e jω ) -W 21 (e jω ) 2 . ( 7
)
The same reasoning holds in B with r BB (k). By introducing the misalignment vector, the power spectral densities can be rewritten as Inserting ( 8) and ( 9) into ( 6), we get the following equilibrium relationship for the feedback structure:

Φ AA (e jω ) = Φ S 1 S 1 (e jω ) Δ
Δ H 12 (e jω ) 2 |ΔH 21 (e jω )| 2 = Φ S 2 S 2 (e jω ) Φ S 1 S 1 (e jω ) • W 12 (e jω ) 2 -1 |W 21 (e jω )| 2 -1 . ( 10
)
By exploiting the usual spectral analysis of the time-invariant (stationary) system for some fixed W 12 (z) and W 21 (z), the obtained relation is valid whatever the coefficients of the separating filters are. And note that the originality of our approach stands in the fact we apply it to artifact signals what has never been done yet.

Signal to artifact ratio (SAR) analysis

Through the above analysis, the signal to artifact ratio on each channel could be easily defined as follow: Then, according to the stated equality principle expressed in (6), the following important relation holds

SAR 1 (e jω ) = Φ S 1 S 1 (e jω ) Φ ΔS 1 ΔS 1 (e jω ) = Φ S
SAR 1 (e jω ) SAR 2 (e jω ) = Φ S 1 S 1 (e jω ) Φ S 2 S 2 (e jω ) . ( 13
)
This relation describes the behavior of the feedback structure and is valid whatever the nature of the signals sources are and whatever the value of impulse responses of identification filters w 12 (n) and w 21 (n) are. Note that if the two sources s 1 (n) and s 2 (n) correspond to white noise, the ratio given by ( 13) is equal to the average power ratio σ 2 s 1 /σ 2 s 2 between the source signals.

EXPERIMENTAL RESULTS

Convergence: transient and steady-state analysis

In this section we present simulation results illustrating the validity of the asymptotic analysis presented previously. In these experiments, the signal s 2 (n) corresponds to a zero mean white Gaussian noise with Φ S 2 S 2 (e jω ) = σ 2 s 2 . The input signal s 1 (n) is a Gaussian first order autoregressive process (AR) with variance σ 2 s 1 and with pole α ∈ [0, 1[. To adapt the adaptive filters w 12 (n) and w 21 (n), we choose the symmetric adaptive decorrelation algorithm, [START_REF] Van Gerven | Signal separation by symmetric adaptive decorrelation : stability, convergence and uniqueness[END_REF]:

w ji (n + 1) = w ji (n) + μ s i (n) s j (n) ∀ i = j ∈ 1, 2 (14)
where s j (n) = [ s j (n) ... s j (n -L + 1)] T denotes the vector of the last L output samples of the separating filters. We assume perfect modelisation with separating filters having the same length as the mixing ones. In the experiments, coupling filters of order L = 20 are used and the separating filters are adapted from the relationship (14) with a low step-size, μ = 10 -4 . Figure 4 shows, for a signal to noise ratio of 10 dB and for colored signal s 1 (n), the convergence of the system distance over time of the two filters w 12 (n) and w 21 (n). We can observe that the behavior of the transient phase is different between the two channels, the fastest convergence being obtained in the most energetic channel.

Signal to artifact ratio on each channel

We now consider the previously established relations expressing the signal to artifact ratio at the output of each channel of the feedback structure. In this paragraph, we assume that the source signals are the ones described previously. It is possible to compute, at each time instant n, the power spectral densities ( 8) and ( 9) by observing the coefficients of the separating filters at that time instant. Once the power spectral densities Φ AA (e jω ) and Φ BB (e jω ) are known, we can then express, from relations (11) and ( 12), the value of the SAR on each spectral component of both channels. Such curves are displayed in Figure 5 (top) when the source signal s 1 (n) is an AR (1) signal with pole α = 0.8 and with an average power ratio of σ 2 s 1 /σ 2 s 2 = 10. These curves are obtained by considering mean values w 12 = lim n→∞ E [w 12 (n)] and w 21 = lim n→∞ E [w 21 (n)], which is equivalent to consider asymptotic behavior of the adaptive filters. The curve in Figure 5 (bottom) corresponds to the evalua- tion of (13) under the same experimental conditions. In noting that the theoretical power spectral density (PSD) of the AR(1) source is given by:

Φ S 1 S 1 (e jω ) = ∑ k r S 1 S 1 (k)e -jkω = (1 -α 2 )σ 2 s 1 1 + α 2 -2αcosω , ( 15
)
it is possible to also represent on Figure 5 (dashed curve) the theoretical value of this ratio, which is given by

SAR 1 (e jω ) SAR 2 (e jω ) = σ 2 s 1 σ 2 s 2 × (1 -α 2 ) 1 + α 2 -2αcosω . ( 16
)
From this figure, we note the capability of the theoretical relation given by ( 16) to closely predict the behavior of the experimental curve (we recall here that the PSD given by (15) obtained through AR parametric modeling is able to model spectral envelope maxima). Let us define the frequency average SAR noted SAR f b , obtained by integrating SAR i (e jω ) with i = {1, 2} over the whole spectral domain.

SAR f b i = π -π SAR i (e jω )dω
Consequently and according to (13), the ratio of the full-band SAR should be equal to the average power ratio of the sources. To compute these full-band SAR, we do not use the mean values of w 12 and w 21 . We compute these full-band SAR directly by using the experimental signals E (s 1 -ŝ1 ) 2 , E (s 2 -ŝ2 ) 2 , E s 2 1 and E s 2 2 , that is to say all along the convergence of the filter without limiting to the asymptotic behavior with the mean value of the filters. Consequently, we observe the validity of the obtained relations also during the convergence of the filters. Under the same experimental conditions as above, we can see that the experimental results in Figure 6 (bottom) are consistent with the theoretical analysis expressed in (13). In fact, even during the initial convergence, our theoretical analysis (and therefore the underlying assumptions), we give in Figure 7 and Figure 8 the full-band SAR values obtained during the steady-state convergence phase of the algorithms for different configurations of the input sources power ratio σ 2 s 1 /σ 2 s 2 . On Figure 7 the two input signals s 1 (n) and s 2 (n) correspond to white Gaussian noise process (α = 0) and AR(1) signals with pole α = 0.4 and α = 0.7 in Figure 8. We can see from Figure 7 (bottom) and Figure 8 (right) that, in all considered cases, the ratio between the experimental full-band SAR f b of each channel is equal to σ 2 s 1 /σ 2 s 2 , also with colored signals and as predicted by the theoretical analysis. Finally, we test the robustness of our analysis with speech signals. Consequently, we are no more compliant with assumption (A4). The input signal-to-noise ratios are computed using the ITU-T recommendation P.56 speech voltmeter (SV56). The speech signals are recorded from a male and a female speakers and shown in Figure 9. Results are given on Figure 10. As before with stationary signals, the same behavior is observed. We can see that the evaluated ratio corresponds to the average power ratio of the speech sources across all considered SNRs. Thus, the assumption (A3) seems to be consistent even with speech signals.

CONCLUSION

In this paper, the intrinsic convergence properties of the twochannel feedback structure have been discussed. Based on the analysis of the relationship between output signals and their artifacts, we have shown that the equilibrium state is obtained when the energy of the artifacts on the output is the same on each channel. Thus, this paper provides new relations for further analyzing the convergence and stability properties of the feedback structure widely used for noise cancelling problems or equally for blind source separation. However, nothing enables us to ensure that the observed equilibrium point is unique. A better theoretical description is needed to deal with this point that will be investigated in future work.

Figure 3 :

 3 Figure 3: Global network for getting the artifact signals on each channel.

Figure 4 :

 4 Figure 4: Convergence of the system distance Δh 12 (n) 2 / h 12 (n) 2 (grey) and Δh 21 (n) 2 / h 21 (n) 2 (black) for different values of the pole α = 0, 0.1, 0.2, ••• , 0.9.

  e jω ) / SAR 2 (e jω ) experimental SAR 1 (e jω ) / SAR 2 (e jω ) theoretical

Figure 5 :

 5 Figure 5: Frequency behavior of SAR 1 (e jω ) and SAR 2 (e jω ) (top) and SAR 1 (e jω )/SAR 2 (e jω ) (bottom).

Figure 7 :

 7 Figure 6: Time evolution of SAR f b 1 and SAR f b 2 (top), and SAR f b 1 /SAR f b 2 (bottom).

Figure 8 :

 8 Figure 8: Frequency average SAR (SAR f b ) obtained on channel 1 and 2 when α = 0.4 and α = 0.7 for different values of σ 2 s 1 /σ 2 s 2 .

Figure 9 :

 9 Figure 9: Time-amplitude plot showing signal mixture.

Figure 10 :

 10 Figure 10: Frequency average SAR (SAR f b ) obtained on channel 1 (black) and 2 (grey) with speech sources for different values of σ 2 s 1 /σ 2 s 2 .

ACKNOWLEDGMENT

The authors express gratitude to the anonymous reviewers for their helpful comments.