Anthony Herrel
email: anthony.herrel@mnhn.fr

Camille Bonneaud

Temperature dependence of locomotor performance in the tropical clawed frog, Xenopus tropicalis

Keywords: temperature, endurance, swimming, jumping, frog, climate change, Silurana, Anura

Temperature dependence of locomotor performance in the tropical clawed frog, Xenopus tropicalis

INTRODUCTION

Amphibians are pertinent model taxa with which to investigate the effects of climate change as their physiological performance is highly thermally dependent [START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF][START_REF] Wilson | Inability of adult Limnodynastes peronii (Amphibia: Anura) to thermally acclimate locomotor performance[END_REF]Wilson et al., 2000). Moreover, amphibians are among the most endangered vertebrate taxa [START_REF] Blaustein | Direct and indirect effects of climate change on amphibian populations[END_REF]. Seventy percent of the world's 6300 described amphibian species are experiencing significant species declines and 32% of amphibians have been classified as threatened or extinct [START_REF] Wake | Colloquium paper: are we in the midst of the sixth mass extinction? A view from the world of amphibians[END_REF]. Vertebrate ectotherms such as amphibians and reptiles are likely sensitive to future climactic change as they have evolved temperature optima that closely match environmental temperatures [START_REF] Van Berkum | Evolutionary Patterns of the thermal sensitivity of sprint speed in Anolis lizards[END_REF][START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF]Angilletta et al., 2010a). Moreover, adult amphibians may show a limited capacity for acclimation, especially if confronted with low seasonal fluctuations in temperature (Wilson et al., 2000). Their permeable skin, limited dispersal capacity and dependence on threatened aquatic habitats for reproduction and development additionally contribute to a high sensitivity to global environmental change [START_REF] Blaustein | Direct and indirect effects of climate change on amphibian populations[END_REF][START_REF] Lawler | Projected climate impacts for the amphibians of the Western Hemisphere[END_REF].

As global surface temperatures are predicted to change by 1.8-4.0°C in the next century, with the most extreme changes predicted in the world's biologically most diverse regions, it is important to understand how temperature may affect ecologically relevant performance traits [START_REF] Beaumont | Impacts of climate change on the world's most exceptional ecoregions[END_REF]. Indeed, performance is often highly temperature dependent and many species have evolved narrow performance breadths (the temperature range for which they can still perform at, for example, 80 or 95% of their maximal performance) [START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF]Pörtner and Farrel, 2008;[START_REF] Angilletta | Estimating and comparing thermal performance curves[END_REF]Angilletta et al., 2010a;Angilletta et al., 2010b). Indeed, as a result of the need to produce multiple enzymes that function at different temperatures for each reaction, the biochemical constraints of a wide performance breadth make thermal generalization costly [START_REF] Pörtner | Physiology and climate change[END_REF]Angilletta et al., 2010b). Moreover, thermal optima may be different for different performance traits (e.g. [START_REF] Van Damme | The thermal dependence of feeding behaviour, food consumption and gut passage time in the lizard Lacerta vivipara Jacquin[END_REF], which may limit the ability of a given species to respond to rapid changes in environmental temperature. Indeed, if a species were to adapt to changes in temperature through changes in function of one performance trait, then this could negatively affect other performance traits.

Here we use the tropical clawed frog, Xenopus tropicalis, to explore effects of temperature on locomotor performance. Xenopus tropicalis is distributed throughout the West African rainforest belt [START_REF] Rödel | Amphibians of the Western Savannah[END_REF] and is fully aquatic, spending the rainy season in pools and puddles of gallery forests and the dry season under rocks and roots of riverbanks. However, during periods of heavy rain, overland dispersal from the forests to nearby savannah ponds has been observed [START_REF] Rödel | Amphibians of the Western Savannah[END_REF]. The mature tropical rainforest habitat of X. tropicalis represents a highly stable system with little seasonal temperature fluctuation. Species in such stable environments are predicted to exhibit narrow performance breadths and low acclimation capacity [START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF]Wilson et al., 2000), likely increasing their vulnerability to climate change. At the same time, these habitats, which are among the most diverse on our planet, are predicted to experience extreme climatic stress with average monthly temperatures rising to more than two standard deviations above the 1961-1990 baseline by 2070 [START_REF] Beaumont | Impacts of climate change on the world's most exceptional ecoregions[END_REF][START_REF] Zelazowski | Changes in the potential distribution of humid tropical forests on a warmer planet[END_REF]. These changes are likely to affect the distribution and abundance of tropical organisms globally, and thus a better understanding of these effects on the potential of animals to cope which such changes is paramount [START_REF] Beaumont | Impacts of climate change on the world's most exceptional ecoregions[END_REF]. In this context, understanding the temperature sensitivity of locomotor performance traits in a frog such as X. tropicalis may help us understand whether this species might be able to respond to predicted changes in climate. Locomotor performance is likely particularly relevant in this context as it will affect the ability of an organism to escape from predators, catch prey or disperse into novel habitats. Thus, we decided to focus on both aquatic burst performance capacity, which is likely relevant to predator escape and prey capture, and endurance capacity, relevant to the ability of animals to disperse and colonize novel habitats.

MATERIALS AND METHODS Animals

Xenopus tropicalis (Wagler 1827) were caught in the wild in December 2009 in Cameroon, brought back to France and housed at the Station d'Ecologie Experimentale du CNRS at Moulis. Animals were housed in groups of eight to 10 individuals in aquaria of 60ϫ30ϫ30cm and kept at a temperature of 24°C. This temperature is similar to temperatures measured in the field and close to the optimal and preferred body temperature in Xenopus frogs [START_REF] Miller | Effect of temperature on sprint performance in the frog Xenopus laevis and the salamander Necturus maculosus[END_REF]. Animals were fed every other day with beef heart, earthworms or mosquito larvae. All individuals were pittagged (Nonatec, Rodange, Luxembourg) before the onset of the experiments, allowing unambiguous identification of each individual. Animals were kept in the laboratory for 3months before the onset of the performance trials. Performance capacity at 24°C did not decline with time spent in captivity, as frogs measured 9months later did not differ in their maximal exertion or burst performance capacity. Moreover, burst performance traits measured in the laboratory did not differ from measurements on animals in the field.

Critical temperatures

Critical thermal maximal and minimal temperatures were measured on 18 adult individuals (10 females, eight males) derived from a single population. Animals were placed individually in plastic containers with water in an incubator of which the temperature was changed gradually (1°C10min -1 ). Animals were checked every 10min for a lack of righting response and their body temperatures were measured. Below 15°C and above 30°C animals were checked every minute. Temperatures were considered to be critical if animals were no longer able to right themselves after having been placed on their back. After the experiments, animals were returned to their aquaria, fed, and allowed to rest for at least 1week.

Performance

Performance traits (burst performance and maximal exertion capacity) were measured for the same 18 individuals at six different temperatures (15, 20, 24, 27, 30 and 32°C). Before the onset of performance measurements, animals were placed for 1h in individual containers with water in an incubator set at the target temperature. All performance measurements were repeated three times for each individual with an inter-trial interval of at least 1h during which animals were returned to the incubator and allowed to rest. Immediately after the trials we checked body temperature of the animals to make sure it did not deviate more than 1°C from the test temperature. At the end of the performance trials, animals were weighed, their pit tag numbers were recorded and they were returned to their home aquaria and fed ad libitum. Animals were given at least 1week to rest between measurement of different performance parameters (burst performance capacity versus endurance) and at least 1day between trials at different temperatures.

The order of the trial temperatures was assigned using a random table.

Maximal exertion capacity was measured by chasing each individual down a 3m long circular track until exhaustion.

The Journal of Experimental Biology 215 ( 14 Animals were considered exhausted if they were no longer able to right themselves after having been placed on their back. The floor of the endurance track was covered with cork to improve traction. For each individual, we recorded both the total distance covered and the time spent moving until exhaustion. Note that we were unable to record exertion capacity at 15°C because we were unable to cool down the room enough, causing the animals to heat up during the trials. Consequently, results at 15°C were discarded from the analysis.

Burst performance capacity was quantified by measuring maximal instantaneous swimming speed and acceleration. Animals were filmed in dorsal view using a Redlake MotionPro high-speed camera (Tallahassee, FL, USA) set at 500Hz (Fig. 1). Illumination was provided by two custom-made arrays of eight ultra bright red LEDs. A scale was filmed at the onset of each trial and used to scale measurements in pixels to metric units. Only video clips of good contrast and where the frog swam continuously and in a straight line were retained. Next, video clips were saved, cropped to include at least two locomotor cycles and analyzed using ProAnalyst software (Xcitex, Cambridge, MA, USA). For each frame, the snout tip was digitized either manually or using the auto-tracking routine implemented in ProAnalyst. Raw coordinates were exported to Excel (Microsoft, Redmond, WA, USA) and the displacement of the individual along its path was calculated. Next, the raw displacement profile was smoothed using a zero phase shift low-pass Butterworth filter [START_REF] Winter | Biomechanics and Motor Control of Human Movement[END_REF]) with the cutoff frequency set at 30Hz (Fig. 1). Velocities and accelerations were calculated by numerical differentiation of the smoothed displacement profiles. For each individual, we extracted the single highest instantaneous velocity and acceleration across all swimming sequences recorded (i.e. the fastest velocity and acceleration may thus come from different sequences).

Analyses

All data were log 10 -transformed before analyses. A repeatedmeasures ANOVA was used to test the effect of temperature and the interaction between temperature and sex on each of the four performance traits. Next, thermal performance curves were plotted for each individual using the minimum convex polygon method [START_REF] Van Berkum | Evolutionary Patterns of the thermal sensitivity of sprint speed in Anolis lizards[END_REF]. Relative performance (the percent of maximal performance achieved at a given temperature) was plotted against temperature and adjacent points were connected using a minimum convex polygon. This approach assumes that the relationship between performance and temperature is gradual and continuous. Note, however, that other methods including Gaussian curve fitting may provide improved estimates of thermal performance curves [START_REF] Angilletta | Estimating and comparing thermal performance curves[END_REF]. Here we decided to use the minimum convex polygon method as most previously published data have used this method and we wanted to compare results from our study with these data. The use of relative performance measures normalizes differences in absolute performance differences across individuals. From the performance curves, temperature optima and performance breadths for 80% (T pb80 ) and 95% (T pb95 ) of maximal performance capacity were calculated for each individual. A multivariate ANOVA (MANOVA) was used to test whether temperature optima and performance breadths differed for each performance trait. Subsequent ANOVAs were used to explore how each measure of thermal sensitivity differed for the four performance traits. Bonferroni post hoc multiple comparisons tests were used to examine how temperature dependence differed among performance traits. All analyses were performed using SPSS v. 15.0 (IBM, Armonk, NY, USA).

RESULTS

The critical thermal minimum (i.e. the temperature at which animals were no longer able to right themselves after being placed on their back) was 12°C; the critical thermal maximum was 34°C. A repeated-measures MANOVA indicated that temperature had a significant effect on three of the four performance traits measured (Figs2, 3, Table1). Temperature significantly affected the time jumped until exhaustion (Wilks' lambda0.14, F 4,11 16.40, P<0.001). Moreover, although no interaction was found between temperature and sex (Wilks' lambda0.68, F 4,11 1.30, P0.33), a significant sex difference in the time jumped until exhaustion was observed, with males displaying a greater time until exhaustion than females (F 1,14 5.27, P0.04). Temperature did not, however, have a significant effect on the distance jumped until exhaustion (Wilks' lambda0.48, F 4,11 3.00, P0.07), nor on the interaction between temperature and sex (Wilks' lambda0.69, F 4,11 1.21, P0.36). However, the distance jumped until exhaustion differed significantly between sexes, with males again outperforming females (F 1,14 10.80, P0.01). Although temperature significantly affected maximal velocity (Wilks' lambda0.12, F 5,12 18.18, P<0.001), no significant interaction between temperature and sex was detected (Wilks' lambda0.78, F 5,12 0.67, P0.65). Sexes also did not differ in maximal swimming velocity (F 1,16 0.70, P0.42). Temperature significantly affected maximal acceleration capacity (Wilks' lambda0.21, F 5,12 8.84, P0.001); however, no significant interaction was detected between temperature and sex (Wilks' lambda0.87, F 5,12 0.36, P0.87), nor was there a significant difference in maximal acceleration capacity between the two sexes (F 1,16 1.25, P0.28).

Endurance performance measures had relatively lower temperature optima and narrower performance breadths than measures of burst speed (Table2, Figs2, 3). A MANOVA showed that the overall temperature effect was significant (Wilks' lambda0.39, F 9,160 8.50, P<0.001). Subsequent univariate analyses showed that optimal temperature, 80% performance breadth and 95% performance breadth were each significantly different for the four performance traits (T opt : F 3,68 11.76, P<0.001; T pb80 : F 3,68 13.90, P<0.001; T pb95 : F 3,68 5.00, P0.003). Post hoc tests showed that the optimal temperature for the time until exhaustion was significantly different from that for maximal velocity (P<0.001) and maximal acceleration (P<0.001). Moreover, the optimal temperature for the distance jumped until exhaustion was significantly different from that for maximal velocity (P0.01). The performance breadth at 80% of maximal capacity was significantly different between the time jumped until exhaustion and all other performance traits (P<0.001 for all comparisons). The performance breadth at 95% of maximal capacity was significantly different between the time jumped until exhaustion and maximal swimming acceleration (P0.004) and between the time and distance jumped until exhaustion (P0.02).

DISCUSSION

Our analyses show that locomotion is thermally sensitive in X. tropicalis, as illustrated by significant effects of temperature on one measure of maximal exertion capacity (time jumped until exhaustion) and two measures of burst speed (maximal swimming velocity and maximal swimming acceleration). The absence of a temperature effect on the distance jumped until exhaustion may be an artifact of the limited number of temperatures that were tested (we were unable to obtain data for exertion capacity at 15°C) and the resulting narrow peak in performance measures. Indeed, similar to the other performance traits investigated, this measure showed a trend towards a decrease in performance at high and low temperatures (Fig. 3). No evidence of a significant interaction between temperature and sex was found, indicating that the effect of temperature was sex independent for all locomotor traits. Yet males showed greater maximal exertion capacity than females for the subset of animals included in this study. However, an analysis of a larger number of animals tested at a single temperature (24°C) showed that, overall, no absolute differences in performance between the sexes exist. Yet, males do show greater relative performance, which may be related to their relatively longer hindlimbs [START_REF] Herrel | Inter-sexual differences in body shape and locomotor performance in the aquatic frog, Xenopus tropicalis[END_REF]. The optimal temperature for performance and performance breadths for 80 and 95% of maximal capacity were different for each performance trait. Exertion performance measures had relatively lower temperature optima (21.8-24.1°C) than measures of burst performance capacity (26.6-27.6°C; Tables1, 2). Note, however, that these results may potentially be biased by the absence of data at 15°C, thus artificially skewing the optimum to the left. However, even raw data suggest an optimum for measures of exertion capacity that is lower than that for burst performance measures (Table1).

Interestingly, an analysis of the effects of temperature on burst performance and sustained activity at the muscular level indicated that for both types of measures, hotter was better, with performance increasing with temperature up to 32°C [START_REF] James | Warmer is better: thermal sensitivity of both maximal and sustained power output in the iliotibialis muscle isolated from adult Xenopus tropicalis[END_REF]. The discrepancy between the effects of temperature on muscle contraction (hotter is better) versus the whole-organismal performance (lower optimum for exertion compared with burst performance) illustrates the importance of measuring whole- organism performance traits when trying to understand the responses of organisms to variation in temperature. Moreover, the difference between the effects observed at these two levels suggests that exertion capacity at the organismal level is limited by the circulatory system rather than by the muscle contractile elements. Finally, optimal temperatures for maximal exertion capacity are close to the operative temperatures measured in the field (approximately 24°C), suggesting that an increase in environmental temperature as a result of global change or local deforestation may significantly affect the overland dispersal capacity of animals such as X. tropicalis.

Performance traits related to endurance capacity also had narrower performance breadths than burst performance. Interestingly, thermal performance breadths for X. tropicalis are narrower than those reported for hylid tree frogs, which span a wide spectrum of geographic ranges [START_REF] John-Alder | Thermal physiology, phenology, and distribution of tree frogs[END_REF]. Moreover, the optimum for swim speed in X. tropicalis as measured here was lower than that measured for the subtropical X. laevis [27°C [START_REF] Miller | Effect of temperature on sprint performance in the frog Xenopus laevis and the salamander Necturus maculosus[END_REF]]. Yet X. tropicalis does follow the general trend among amphibians, with tropical species having narrower performance breadths than temperate species [START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF][START_REF] John-Alder | Thermal physiology, phenology, and distribution of tree frogs[END_REF]. Ectotherm performance is highly temperature dependent and several studies have found evidence of direct selection on thermal physiology and significant thermal specialization [START_REF] Van Berkum | Evolutionary Patterns of the thermal sensitivity of sprint speed in Anolis lizards[END_REF][START_REF] Marvin | Effects of acute temperature and thermal acclimation on aquatic and terrestrial locomotor performance of the three-lined salamander, Eurycea guttolineata[END_REF]. For example, jumping performance in the frog Limnodynastes peronii is optimized over its geographic range: populations from cooler climates outperformed those from warmer climatic zones at cooler experimental temperatures, and vice versa [START_REF] Wilson | Geographic variation in thermal sensitivity of jumping performance in the frog Limnodynastes peronii[END_REF].

Characterizing the thermal sensitivity of locomotor performance, and thus understanding how physiological traits may limit distributions and ranges of species, may help identify species at the greatest risk when faced with rapid human-induced climate changes [START_REF] Pörtner | Physiology and climate change[END_REF][START_REF] Chown | Adapting to climate change: a perspective from evolutionary physiology[END_REF]. Amphibians and reptiles are generally considered to have a conservative thermal ecology, making adaptive shifts in thermal preference potentially difficult [START_REF] Sinervo | Erosion of lizard diversity by climate change and altered thermal niches[END_REF]. Additionally, aquatic frogs do not have the ability to thermoregulate to the extent that lizards do. Coupled with their lack in physiological plasticity, adult amphibians are likely more sensitive to variation and changes in environmental temperature [START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF]. Among ectotherms, those from environments with large daily temperature variation are characterized by a reduced thermal sensitivity. In contrast, ectotherms from highly stable environments (such as tropical regions with little seasonal variation, or aquatic environments in which temperature fluctuations are suppressed by the high thermal conductance of water) are generally more sensitive to changes in temperature [START_REF] Wilson | Inability of adult Limnodynastes peronii (Amphibia: Anura) to thermally acclimate locomotor performance[END_REF][START_REF] Navas | Thermal relationships and exercise physiology in anuran amphibians: integration and evolutionary implications[END_REF], as demonstrated here for X. tropicalis.

Our results for X. tropicalis confirm predictions that animals from stable environments should show a high thermal sensitivity. The narrow performance breadths, combined with the divergent temperature optima for endurance and burst speed, which may result in a trade-off when adapting to changes in temperature (i.e. adaptation to a temperature that improves burst performance may negatively affect exertion capacity), underscore the vulnerability of X. tropicalis. Indeed, temperature changes of even a few degrees could potentially push this species outside its 80% performance breadth, thus significantly affecting its locomotor capacity and survival. Despite the fact that aquatic frog larvae from fluctuating environments may be able to acclimate to changes in temperature [START_REF] Wilson | Thermal acclimation of locomotor performance in tadpoles of the frog Limnodynastes peronii[END_REF], aquatic adult frogs with narrow performance breadths such as Xenopus may also be limited in their ability to acclimate, as has been shown for X. laevis [START_REF] Miller | Effect of temperature on sprint performance in the frog Xenopus laevis and the salamander Necturus maculosus[END_REF]. The ability of X. tropicalis to thermally acclimate was not tested in the present study, but will provide an important next step in understanding the ability of this species to respond to changes in temperature that are due to global change or local deforestation. Although our results are limited in the number of traits measured, they add to the growing body of literature documenting how temperature affects locomotor performance. Given the importance of locomotion to survival and overall fitness, our data suggest that changes in temperature may have strong affects on the survival of tropical aquatic amphibians. Yet similar data for other species are needed to test the generality of these observations. T opt is the temperature at which performance is optimal. T pb80 and T pb95 represent the temperature breadths at which frogs can still achieve 80 and 95% of their maximal performance, respectively. Data are means ± s.d.

  Fig.1. Analysis of videos used to quantify burst performance. (A)Displacement of the snout in Xenopus tropicalis. A period of two complete swim strokes was tracked on digitized videos. Images were taken from the sequence illustrated. (B)Instantaneous velocity calculated based on the smoothed displacement profile. (C)Instantaneous acceleration calculated based on the velocity profile. The single highest instantaneous velocity and acceleration values were extracted for each individual for further analysis.

B

  Fig.2. Mean (±s.e.m.; N16 individuals) percentage of maximum performance for the burst speed measures (A) peak velocity and (B) peak acceleration. The horizontal dotted line represents the 80% performance breadth, a measure of the temperature range for which frogs can still achieve 80% of their maximal performance. Note that temperature-performance curves are bound by the critical thermal minimum and maximum temperatures (vertical dotted lines) as determined experimentally.

  Fig.3. Mean (±s.e.m.; N18 individuals) percentage of maximum performance achieved for the endurance capacity measures (A) time jumped until exhaustion and (B) distance jumped until exhaustion. The horizontal dotted line represents the 80% performance breadth, a measure of the temperature range for which frogs can still achieve 80% of their maximal performance. Note that temperature-performance curves are bound by the critical thermal minimum and maximum temperatures (vertical dotted lines) as determined experimentally.

  TheJournal of Experimental Biology 215 (14) Table1. Raw mean performance data across all individual Xenopus tropicalis at different temperatures

	Temperature	Max. velocity (ms -1 )	Max. acceleration ( m s -2 )	Max. time jumped until exhaustion (min)	Max. distance jumped until exhaustion (m)
	15°C	0.85±0.05	28.70±2.15	n/a	n/a
	20°C	1.19±0.04	40.98±2.18	3.32±0.76	17.44±2.87
	24°C	1.34±0.07	51.94±2.54	2.95±0.75	19.04±5.13
	27°C	1.36±0.06	42.79±2.44	1.37±0.09	14.57±1.20
	30°C	1.20±0.05	40.16±2.61	1.19±0.11	13.24±1.08
	32°C	1.28±0.07	42.16±3.26	1.05±0.06	12.69±0.75
	Note that we were unable to record exertion capacity at 15°C.

Data are means ± s.e.m. (N18 for exertion capacity, N=16 for burst performance capacity).

  Table2. Temperature optima and performance breadths for locomotor performance in X. tropicalis

		Max. velocity	Max. acceleration	Max. time	Max. distance
	T opt (°C)	27.56±3.43	26.56±3.65	21.78±2.05	24.11±3.83
	T pb80 (°C)	11.47±2.39	10.97±2.67	6.94±1.94	10.53±2.85
	T pb95 (°C)	4.19±2.02	5.53±3.12	2.58±1.56	5.28±3.62

ACKNOWLEDGEMENTS

We would like to thank Legrand Nono Gonwouo and Erik Fokam for their valuable help in the field, N. Bonneaud, P. Provini, O. Calvez and J. Rodriguez for helping to take care of the frogs, M. Antoine for logistical help, and K. Walter for help with the digitizing of swimming sequences and discussions on the paper.

FUNDING

This research was supported by l'Agence Nationale de la Recherche (ANR) MOBIGEN [ANR-09-PEXT-003 to A.H. and C.B.], a Muséum National d'Histoire Naturelle Action transversale du Muséum (MNHN ATM) grant of the programme ʻBiodiversité actuelle et fossile' [to A.H.], and a Marie Curie reintegration grant [FP7-PEOPLE-IRG-2008 no. 239257 to C.B.].


Signe Seidelin
email: signe.seidelin@neel.cnrs.fr

Yann Le Coq

Klaus Mølmer

Rapid cooling of a strain-coupled oscillator by optical phaseshift measurement

We consider an optical probe that interacts with an ensemble of rare earth ions doping a material in the shape of a cantilever. By optical spectral hole burning, the inhomogeneously broadened transition in the ions is prepared to transmit the probe field within a narrow window, but bending of the cantilever causes strain in the material which shifts the ion resonances. The motion of the cantilever may thus be registered by the phase shift of the probe. By continuously measuring the optical field we induce a rapid reduction of the position and momentum uncertainty of the cantilever. Doing so, the probing extracts entropy and thus effectively cools the thermal state of motion towards a known, conditional oscillatory motion with strongly reduced thermal fluctuations. Moreover, as the optical probe provides a force on the resonator proportional to its intensity, it is possible to exploit the phase shift measurements in order to create an active feedback loop, which eliminates the thermal fluctuations of the resonator. We describe this system theoretically, and provide numerical simulations which demonstrate the rapid reduction in resonator position and momentum uncertainty, as well as the implementation of the active cooling protocol.

I. INTRODUCTION

Mechanical resonators have multiple applications in science and technology and their operation in the quantum regime enable effective coupling to weak perturbations and to a variety of other quantum systems for precision sensing and quantum information processing purposes. The preparation of mechanical oscillators in well-defined quantum states have thus been the target of many efforts, and both thermalization with a low temperature environment [START_REF] O'connell | Quantum groundstate and singlephonon control of a mechanical resonator[END_REF], sideband microwave cooling [START_REF] Teufel | Sideband Cooling Micromechanical Motion to the Quantum Groundstate[END_REF], and more elaborate heralding schemes [START_REF] Vanner | Cooling-by-measurement and mechanical state tomography via pulsed optomechanics[END_REF][START_REF] Rossi | Measurement-based quantum control of mechanical motion[END_REF] have been employed or theoretically proposed. In this article, we propose and analyze a novel scheme for cooling of a cantilever, which makes use of a rare earth ion ensemble, doped into the cantilever material. In ref. [START_REF] Mølmer | Dispersive coupling between light and a rare-earth-ion-doped mechanical resonator[END_REF] we suggested to prepare such an ensemble by optical hole burning techniques such that light strongly detuned from all the ions can be transmitted through a spectral hole, while bending of the material causes strain and shifts the optical transition frequencies of the ions modifying their dispersive interaction with the light probe. Using realistic parameters, we argued in ref. [START_REF] Mølmer | Dispersive coupling between light and a rare-earth-ion-doped mechanical resonator[END_REF] that it would be possible to resolve the thermal bending motion of the cantilever in much shorter time than the life time of the spectral hole. Here, we take the analysis further and derive the conditional state of the system subject to continuous homodyne monitoring of the transmitted field.

In Sec. II, we introduce our system and motivate a Gaussian ansatz for the state of motion of a vibrational mode of the cantilever and of the quantized probe field. In Sec. III, we derive and solve the equations of motion for the first and second moments of the Gaussian phase space distribution of the cantilever motion subject to optical probing. We obtain numerical and approximate analytical expressions for the position and momentum variances and we show sample trajectories for the mean displacement of the cantilever motion, conditioned on realistic measurement records. We argue that the reduced position and momentum uncertainty is equivalent to a cooling of the mechanical motion, and permits definition of an effective temperature of the cantilever far below the surrounding environment. By adding an active feed back mechanism, we show that this low effective temperature can also be translated into an effective "freezing" of the resonator where its mean position and momentum are not only precisely known but also constant. Finally, Sec. V provides a brief conclusion and outlook.

II. THE PHYSICAL SYSTEM

We consider the physical system depicted in fig. 1, consisting of a transparent cantilever which is probed by a coherent laser beam. The interferometric set-up allows measurement of the quadrature of the transmitted beam which contains information about the bending motion of the cantilever: the cantilever material is doped with rare earth ions featuring a narrow optical transition which is shifted in frequency due to crystal strain. The inhomogeneously broadened absorption profile of the ion dopants is prepared by spectral hole burning to allow transmission of the probe laser field, but when the cantilever is bent, the spectral hole is distorted, and the dispersive interaction with ions causes an optical phase shift. For details, the full protocol of this strain-coupling is outlined in ref. [START_REF] Mølmer | Dispersive coupling between light and a rare-earth-ion-doped mechanical resonator[END_REF].

Cryostat Cantilever

The coherent beam of light with flux Φ can be thought of as a product state of segments of duration τ , each containing a coherent state with average photon number n = Φτ . We assume that, prior to interaction with the cantilever, the coherent states have null phase and real argument α = √ n = √ Φτ . In our previous work [START_REF] Mølmer | Dispersive coupling between light and a rare-earth-ion-doped mechanical resonator[END_REF] we have shown that, by interacting with a bent cantilever with appropriately prepared spectral hole structure, the light beam experiences a phase shift proportional to the resonator displacement X m , namely ∆φ = kX m . A Fock state |n , for its part, undergoes a quantum phase shift, |n → e -in∆φ |n , where the phase shift per photon is equal to the phase shift of the coherent field amplitude. We write â = α + δâ, such that the number operator n can be written

n = â † â = (α + δâ † )(α + δâ) α 2 + α(â -α) + α(â † -α) = α(â + â † ) -α 2 = √ 2α Xph -α 2 . ( 1
)
Utilizing our assumption that the input coherent state |α have null phase, the effect of the Fock state phase factor e -in∆φ is hence approximated by the operator e -i √ 2α Xph k Xm = e -iκτ Xph Xm , where κ 2 τ ≡ κ 2 τ ≡ 2k 2 Φτ . The exponential operator form reflects the unitary evolution of the joint state of the field and mechanical os-cillators, which is governed by a coupling Hamiltonian Ĥ = κ τ Xph Xm /τ .

III. GAUSSIAN STATE FORMALISM

We consider the joint quantum state of the mechanical oscillator bending mode and a single incident segment of the probe photon beam. The oscillator Hamiltonian and the interaction between the two systems are second order in their respective position and momentum quadrature operators ( Xm , Pm , Xph , Pph ), and their time evolution for a short time interval τ is given by a linear mapping,

    Xm Pm Xph Pph     →    1 ωτ 0 0 -ωτ 1 κ τ 0 0 0 1 0 κ τ 0 0 1        Xm Pm Xph Pph     . ( 2
)
The operators are expressed in dimensionless units, such that the variables defining the mechanical resonator are given by X m = x m /x 0 with x 0 = /mω and P m = p m /p 0 with p 0 = √ mω. If we assume an initial thermal state of the cantilever, both systems occupy Gaussian states and while they become correlated, the combined system maintains its Gaussian character due to the interaction. Gaussian states are fully characterized by their first and second order moments, and we shall hence identify the changes in these quantities for the cantilever observables due to the continuous interaction with the field and its subsequent homodyne detection.

For this purpose, we introduce the covariance matrix Γ with elements Γ ij = 2Re( (q i -q i )(q j -q j ) , where qi denotes the four quadrature observables and q i their expectation values. Reserving the first two components for the mechanical degrees of freedom and the last two for the field, the covariance matrix separates in blocks,

Γ = A C C T B (3)
where

A = a 11 a 12 a 21 a 22 , (4)
represents the oscillator position and momentum variances and covariances, while the matrix B describes the similar quantities for the field and C represents correlations between the two systems. Prior to the application of each novel segment of the optical field, which is incident on the mechanical system in a coherent state, B and C take the initial values

B 0 = 1 0 0 1 , C 0 = 0 0 0 0 . ( 5
)
After the interaction of the two systems, the oscillator and the light segment are correlated as described by Eq.( 2), which transforms the covariance matrix as

Γ → SΓS T , (6)
where S denotes the 4x4 matrix in Eq. ( 2). If the transmitted light segment is discarded after the interaction, we merely retain the upper left block of Γ as our new mechanical covariance matrix A, while replacing B and C by B 0 and C 0 in Γ in Eq. ( 3) to accommodate for the interaction with the subsequent coherent segment of the beam. However, rather than discarding the transmitted field, we perform a measurement of the phase rotation of the optical field segment, right after its interaction with the cantilever. This is done by homodyne measurement of the quadrature P ph . This measurement yields information about X m , and for Gaussian states, the gain in information is represented by the following transformation [START_REF] Fiurasek | Gaussian Transformations and Distillation of Entangled Gaussian States[END_REF][START_REF] Giedke | Characterization of Gaussian operations and distillation of Gaussian states[END_REF][START_REF] Eisert | Introduction to the basics of entanglement theory in continuous-variable systems[END_REF] of the cantilever part of the covariance matrix

A → A -ηC 0 0 0 1 C T , (7)
where C, C T are extracted from Γ after the update rule Eq.( 6) and η is the detector efficiency.

The field measurement outcome is governed by a Gaussian distribution with mean value Pph = κ τ Xm and variance 1/2. Denoting the outcome as Pph + χ, the mean value of the Gaussian distribution of cantilever observables is, indeed, shifted conditioned on the field measurement,

Xm Pm → Xm Pm + √ ηC 0 χ . (8)
In addition to the deterministic and stochastic evolution of the oscillator covariance matrix and mean values due the field probing and free evolution, we include the equilibration of the oscillator with its thermal environment at rate γ. This is done by adding the following terms to the rate equations in the continuous limit, da ii /dt| γ = -γa ii + γ(2n + 1) for i = 1, 2, da ij /dt| γ = -γa ij for i = j, and d Xm /dt| γ = -γ 2 Xm , and d Pm /dt| γ = -γ 2 Pm . In the absence of any other terms, these rate equations would lead to a steady state with a 11 = a 22 = 2Var(X m ) = 2Var(P m ) = 2n + 1, representing the familiar mean energy

1 2 X2 m + P 2 m = (n + 1
2 ) of the thermalized oscillator.

To summarize, the mechanical resonator is described by the 2×2 covariance matrix A (Eq. 4) that evolves in a deterministic manner, and by mean values ( Xm , Pm ) that follow from the combination of free evolution and the accumulated stochastic measurement record. This evolution is equivalent to the general quantum trajectory treatment of continuously monitored quantum systems by a stochastic master equation, but it is considerably simplified by the restriction to Gaussian states.

A. Continuous limit

Our division of the probe beam into segments of duration τ allows us to take the continuum limit, assuming the derivative to be given by dx/dt = (x(t + τ ) -x(t))/τ . It is a special property of the Gaussian states, that the covariance matrix of the mechanical system evolves in a deterministic manner, independent of the measurement outcome. Putting all terms together, we thus get for the components of the oscillator part of the covariance matrix the following explicit equations:

da 11 dt = -
The first, non-linear term in the equation for a 11 shows that the variance of X m is reduced, and the proportionality with the measurement efficiency η emphasizes that this squeezing of the oscillator position is conditional on the probing. The first term in the equation for a 22 shows that the unobserved P m undergoes an increasing variance due to the interaction with the probe field -a diffusive heating due to the spread in X ph of the incident state.

Setting η = 0 corresponds to no detection, and hence absence of the cooling/squeezing effect on X m , while P m always heats up due to the interaction with the probe field.

The effective anti-squeezing of P m ensures the Heisenberg uncertainty relation remains fulfilled even if there were no free rotation (at ω), no heating and if X m were probed at unit efficiency. Due to the rotation, however, a mixing of the degrees of freedom subject to squeezing and antisqueezing and heating leads, ideally, to reduction of both variances.

Together with the deterministic change of the covariance matrix and mean values of the mechanical position and momentum, the mean values of Xm and Pm experience stochastic changes (Eq. 8) associated with the measurement outcomes. In the limit of infinitesimal time steps dt, the difference dW between the measured value and the expected mean value is stochastic with variance dW 2 = dt, corresponding to detector shot noise, and its explicit variation leads to the update equation for the mean values:

Xm → Xm + √ ηa 11 κdW Pm → Pm + √ ηa 21 κdW. (10)

B. Steady-state solutions

The nonlinear Eqs. 9 can be solved analytically in the steady state limit. For γ ω (which is readily ful-filled for realistic parameters, see IV), the rapidly oscillating system is effectively subject to equal strength probing of X m and P m , and the equations for a 11 and a 22 can be replaced by the average of the corresponding equations in Eq. ( 9). The steady state variances, Var(X m ) = Var(P m ) = a 11 /2 are then determined from the roots of a single quadratic equation, and we obtain

a 11 = -γ + {γ 2 + ηκ 2 κ 2 + 2γ(2n + 1) } 1/2 ηκ 2 . ( 11
)
For the realistic system explored in IV, we furthermore have γ κ, and Eq. ( 11) further reduces to

a 11 = 1 √ η 1 + 2γ κ 2 (2n + 1). (12)
This result explicitly reflects the competition between the cooling induced by the measurements with efficiency η and probe interaction strength κ 2 and the heating with rate γ. For the physical parameter range of interest, we obtain a significant reduction and favorable square root scaling of the position and momentum variances compared to their values in thermal equilibrium with the environment. We recall, however, that the reduction of these variances does not represent extraction of energy from the oscillator, as the mean position and momentum have finite random values. But since these values are known from the measurement record through Eq. ( 6), we can either reduce them deterministically by application of a force to the system as demonstrated in Sec. IV, or we can merely retain our knowledge about their values and subtract them "in software" in applications of the system, e.g., for sensing purposes.

We observe that the Eqs. (9,10) have the same formal structure as the Kalman filter equations [START_REF] Maybeck | Stochastic models, estimation, and control[END_REF] for the estimated state and the variance of the estimate of a linear dynamical system. This is no coincidence: For a quadratic Hamiltonian with linear evolution of the position and momentum observables, quantum measurement theory assigns a conditional Gaussian quantum state, which fully characterizes the probability distribution for the observables by mean values and a covariance matrix. The evolution of these objects is equivalent to the classical Kalman filter, while the derivation based on quantum theory ensures, e.g., fulfillment of Heisenberg's uncertainty relation.

IV. NUMERICAL INVESTIGATION AND ACTIVE FEEDBACK

In order to investigate numerically the outcome of the model in a realistic experimental example, we refer to our previous publication [START_REF] Mølmer | Dispersive coupling between light and a rare-earth-ion-doped mechanical resonator[END_REF]. We consider the example of a 100 × 10 × 10 µm 3 cantilever with a bending mode frequency of ω = 2π × 1 MHz mode and an effective mass m = 1.1 • 10 -11 kg, corresponding to the cantilever depicted in fig. 1. The cantilever material consists of Y 2 SiO 5 containing a 0.1 % doping of Eu 3+ ions, with a 7 F 0 → 5 D 0 transition centered at 580 nm and a single ion natural linewidth of 2π × 122 Hz and a measured linewidth of typically 2π × 1 kHz at a temperature of 3 K or lower. When using a spectral hole width of 6 MHz, we previously determined the phase shift ∆φ = kX m to be 0.65 µrad for a bending of x 0 = /mω = 1.3 fm, corresponding to the width of the quantum ground state of the cantilever. Thus, if X m is measured in units of x 0 , k = 0.65 µrad. Moreover, assuming a laser intensity of 1 mW (i.e. a photon flux of Φ = 2.92 × 10 -15 ), we have κ 2 = 2k 2 Φ = 2π × 197 Hz. Furthermore, we assume η = 1, the initial temperature T=400 mK (corresponding to a bath excitation n = 9360), and the bath coupling γ = 2π × 10 Hz.

A first consequence of the application of the probe laser is the shifting of the classical rest position of the resonator. This comes from the action on the mechanical oscillator of the same unitary time evolution operator e -ik Xm n that yields the phase shift of the field, and it occurs independently of the measurement back-action. When the probe laser is turned on abruptly from a situation at thermal equilibrium where the resonator position and momentum are centered at zero ( X m = P m = 0), this leads to a large swing, and the resonator mean values will oscillate for a long time (of the order of 2π/γ) before thermalization brings it to the new rest position. It is, however, possible to suppress this swing by applying the laser in a feed-forward procedure as the swing is governed by perfectly deterministic classical equations of motions. In our case, this simply consists in first applying the laser at half power for half a period π/ω of the resonator oscillation, before applying the laser at full power. Indeed, after the first half period of oscillation, the classical motion arrives at its apex with zero average momentum, and this is the equilibrium phase space position for the oscillator subject to the full laser power.

Second, when the probe laser is on and its phase is detected, the continuous monitoring leads to a rapid decrease in the uncertainty in position and momentum of the oscillator. This translates into a rapid decrease in the corresponding variances, and a concomitant localization of the Gaussian state which exhibits oscillations at angular frequency ω with a random phase and a random amplitude, determined stochastically from the measurement record. Note that because of the constant coupling with the thermal bath, the phase and amplitude will vary in time, but with a very slow rate governed by the coupling coefficient γ.

Third, from the outcome of the continuous measurement, and the corresponding knowledge of Xm and Pm , if the intended application of the system requires so, one can apply a feed-back mechanism which will maintain the resonator position as close as possible to the rest position in phase-space. Owing to the continuous measurement process, the resonator will then rapidly acquire a fixed position with an uncertainty substantially smaller than the one governed by the thermal bath. Because the coupling to the thermal bath is relatively weak, the random fluctuations of the phase and amplitude of the resonator oscillation are relatively slow, and the feed-back mechanism is therefore robust against experimentally unavoidable time delay in the feed-back loop. As a demonstration, we have included time delays up to 1 µs in this process, without impacting the stability of the servo loop.

Figure 2 represents the application of this sequence of operation for a resonator with an initial temperature of 400 mK. Initially, no probe laser is applied and the uncertainty in resonator position is given by its temperature imposed by the thermal bath. When switching on the laser (without detecting its phase), using the feedforward process described above, we displace the equilibrium position without modifying the effective temperature of the resonator. When the probe laser is applied and its phase after interaction with the cantilever is detected, the oscillator becomes localized in a sine-wave oscillation. After 10 µs, we apply the active feedback modulation of the probe power to keep the resonator as close as possible to the rest place, and the amplitude of the oscillations rapidly decrease to zero. The feed-back mechanism used here is based on the continuous evaluation of the amplitude and phase of the oscillation at angular frequency ω and the application of a small modulation of the probe laser intensity at frequency ω, with an amplitude and phase continuously adapted to counter-balance the resonator oscillation, see bottom panel in Fig. 2. In our numerical example, we have limited the gain of the feedback loop to keep the relative modulation of the probe laser power lower than 10 %, which implies a negligible impact on the measurement back-action process, in order to simplify numerical integration. Note that the successive application of the above steps is only chosen for clarity. In practice, it is certainly possible to apply the feed-forward ramping of the laser power and implement the phase detection and the feed-back mechanism all together and immediately, so as to accelerate the progress towards the final steady state, should it be desirable for practical applications.

The steady state given in Eq.( 12) leads to an uncertainty in the position of the resonator that corresponds to an effective temperature < 0.7 mK (or, equivalently < 15 quanta). This more than 600 fold reduction in effective temperature is a striking demonstration of how effectively the continuous monitoring extracts knowledge of the resonator state. Moreover, a large part of the decrease in a 11 and a 22 occurs at the beginning of the process (see fig. 2): only 4 µs after application of the continuous measurement, the effective temperature is already decreased to 100 quanta i.e. 4 mK, a 100-fold reduction of the effective temperature. After 50 µs, the effective temperature is already within less than 1% of that of the steady state. Figure 2: Mechanical resonator subject to optical probing. The physical properties are described in the text (ω = 2π × 1 MHz, γ = 2π × 10 Hz, laser full power 1 mW, initial temperature 400 mK). The sequence used here is the following: 1) we start at thermal equilibrium with no probing laser; 2) after 1 µs, we apply the probe laser at half power (feed-forward); 3) at 1.5 µs we apply the probe laser at full power; 4) at 2.5 µs we detect the probe laser phase continuously, which progressively localizes the resonator on a sine-wave oscillation with random amplitude and phase; 5) after 10 µs, we apply an active feed-back process (which includes a 1 µs delay time) that keeps the resonator near its rest position by acting on the probe laser power. Top panel: mean position of the resonator (the thickness of the curve indicates the uncertainty); middle panel: two times the standard deviation (root-mean-square) of the position and momentum variables; bottom panel: variation in the probe laser power normalized to its final constant value, showing the excitation at half power and the oscillatory feedback modulation, conditioned on the measurement outcome.

V. CONCLUSION

We have in this article presented a Gaussian state formalism that accounts for the evolution of a mechanical oscillator subject to continuous homodyne probing. The measurement outcome is stochastic, and the measurement back action entails a displacement of the oscillator, which one must know to benefit from the significantly reduced variance of the inferred position and momentum of the cantilever. The increased purity of the quantum state accompanies a reduced entropy, and we refer to the process as measurement induced cooling (a term also used in ref. [START_REF] Vanner | Cooling-by-measurement and mechanical state tomography via pulsed optomechanics[END_REF]), as the residual energy of the system is mainly due to a precisely known oscillatory motion in phase space. We also show that this motion that can be arrested by application of a force. In particular, we can use a force which arises from interaction with the probe itself and perform a feedback according to the measurement of the resonator position by varying the intensity of the probe. Future work may incorporate separate studies of the so-called retrodicted state [START_REF] Gammelmark | Past Quantum States of a Monitored System[END_REF][START_REF] Rossi | Observing and Verifying the Quantum Trajectory of a Mechanical Resonator[END_REF][START_REF] Zhang | Prediction and retrodiction with continuously monitored Gaussian states[END_REF][START_REF] Kiarn | Quantum State Smoothing for Linear Gaussian Systems[END_REF] of the system, in particular, what do we know at time T about the oscillator's position at the earlier time t, due to the measurements performed both until t and after t, and how this can benefit application of the probed cantilever for force and motional sensing [START_REF] Tsang | Quantum theory of optical temporal phase and instantaneous frequency. II. Continuous-time limit and state-variable approach to phase-locked loop design[END_REF].

Figure 1 :

 1 Figure 1: A schematics of the set-up allowing to detect the vibrations of a cantilever using homodyne detection. The dimensions of the cantilever are × 10 × 10 µm 3 , for more details, see Sec. IV.

  ηκ 2 a 2 11 + ω(a 21 + a 12 ) -γ(a 11 -(2n + 1)) da 12 dt = -ηκ 2 a 11 a 12 -ω(a 11 -a 22 ) -γa 12 da 21 dt = -ηκ 2 a 11 a 21 -ω(a 11 -a 22 ) -γa 21 da 22 dt = κ 2 -ηκ 2 a 12 a 21 -ω(a 21 + a 12 )

-γ(a 22 -(2n + 1)).

ACKNOWLEDGEMENTS KM acknowledges support from the Villum Foundation and YLC from the Ville de Paris Emergence Program and from the LABEX Cluster of Excellence FIRST-TF (ANR-10-LABX-48-01), within the Program "Investissements d'Avenir" operated by the French National Research Agency (ANR). The project has also received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 712721 (NanOQTech).


Many important decisions are based on the results of laboratory analysis. Thus, it is important to have some indica2ons on the quality of the results, i.e. how much your clients can trust your result to make a decision.

Context

Many important decisions are based on the results of laboratory analysis. Thus, it is important to have some indica2ons on the quality of the results, i.e. how much your clients can trust your result to make a decision.

With globalisa3on, the lab managers are coming under an increasing pressure: (i) to demonstrate the quality of their results and (ii) to demonstrate their results can be compared to results obtained by other laboratories.

the concepts of 'error' and of 'good data'

Introduc2on:

When you cook food, you like to do it corrctly, to have good food that everybody like it and enjoy.

Secondly, let's speak about MEASURES in the laboratory…

To describe the quality of analyses:

First

  soil analysis they are no drama3c consequence but my objec3ve was to demonstrate that even in case of high risk, human do not like to follow SOP… And because in Soil science there is no drama3c consequence, there is a high probability not to follow the SOP.... you cannot change it, you must DETECT IT....

  decide the SOP for your lab or you have to follo the SOP of a network if you are involved in a larger network. DALAM can decide to do what it wants But now they are intran3onal accreditaiton and custommer want to know you fit with interna3onal rules. For example Chinese, Thai, australian copany, etc… want to be sure your data fit with whzt they know.... A good exemple is Carbone and ORGANIC MATTER If you work for chicken food, you have to do like the indistry of chicken food is used

	The objec2ves of a SOP is to do all the important
	opera2ons:
	(i) correctly,
	(ii) always in the same way.
	Thus, a SOP is a mandatory instruc2on!
	You have to strictly follow a SOP, not to adapt it.
	A SOP should be available at the place where the work is
	done".
	SOPs should be kept as simple as possible, par2cularly in
	the beginning.

you

Systema2c or 'predictable', regular devia2on from the "true" value.

Systema2c or 'predictable', regular devia2on from

Thanks for your alen3on

First Mee3ng of the GLOSOLAN, FAO Headquarters, Rome, 1-2 Nov 2017


Marie-Stéphanie Bracq

Estelle Michinov

Bruno Arnaldi

Alexandre Audinot

Benoît Caillaud

Bernard Gibaud

Valérie Gouranton

Pierre-Louis Henaux

Aurélien Lamercerie

Béatrice Nogues

Modeling, Simulation and Training Procedural Skills: User experience and acceptability of a virtual reality simulator for scrub nurses in neurosurgery

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

  V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly. 2012;36(1):157-178. 2. Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In: Advances in Psychology [Internet]. Elsevier; 1988. 3. Slater M, Usoh M, Steed A. Depth of presence in virtual environments. Presence: Teleoperators & Virtual Environments. 1994;3(2):130-44. 4. Kennedy RS, Lane NE, Berbaum KS, Lilienthal MG. Simulator sickness questionnaire: An enhanced method for quantifying simulator sickness. The international journal of aviation psychology. 1993;3(3):203-20. M.S. Bracq, E. Michinov, B. Arnaldi, A. Audinot, B. Caillaud, B. Gibaud, V. Gouranton, P.L. Henaux, A. Lamercerie, B. Nogues, P. Jannin Instrumentation table scenario Assess acceptability and user experience of a VR simulation to train procedural skills for scrub nurses with dedicated models and validated tools • Acceptability the VR simulator was demonstrated for all participants • No statistical significant differences regarding age, gender and expertise • Most participants stressed its pedagogical interest, fun and realism • VR simulator was validated for initial and vocational training Limits • small sample size • experts from only one specialty and department Following steps • Measure transfer of skills to the OR • Development of Non-Technical Skills (NTS) scenarios • Intercultural studies presence) and SSQ 4 (simulator sickness )  Qualitative data from post test interviews and logs

SunSET Project Pre-test questionnaire Debriefing Post-test questionnaire VR Instrumentation table scenario VR pre-training scenario 2 nd session VR pre-training scenario 1 sr session Instruction video