A lithotrophic ammonia-oxidizing bacterium of the Nitrosomonas type was isolated from the lower River Elbe. Enrichment was attained from suspended particulate matter (SPM) of a water sample. At its natural environment, this species almost exclusively occurred attached to flocs, as demonstrated with the immunofluorescence technique. On the species level, the isolate was not related to any of the described Nitrosomonas species. The strain was characterized by strong production of exopolymeric substances (EPS) and was observed to occur self-flocculating in pure cultures. Low ammonia concentrations stimulated EPS production. The EPS revealed an extensive capacity for binding particulate and dissolved materials, as well as cells of other bacterial species. This capacity was affected by changing pH values or salt concentrations of the medium. The EPS appeared to function as a buffer against toxic compounds and against changing environmental conditions. Another Nitrosomonas strain isolated from the Elbe estuary, but lacking recognizable EPS production, was used for comparison.

As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p=0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p=0.0008) and robot perception for anthropomorphism (p=0.007) and animacy (p=0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.

Each of the trunk segments of the polychaete Eusyllis blomstrandi is equipped with paired epidermal luminescent domains. They luminesce upon mechanical or electrical stimulation. Light emission can be rapidly turned on and oV, appears intracellular and is highly coordinated among the trunk segments. Luminescent light is typically emitted in series of Xashes. Light emission in a Xash starts locally in a group of segments and recruits adjacent segments at a rate as fast as ·1 ms/segment. The collapse of light emission at the end of a Xash is almost simultaneous in all of the segments involved. In the intact worm, the luminescent reaction usually involves only a posterior group of segments. Facilitation becomes manifest as the consecutive Xashes in a series increase in brightness and duration and recruit additional anterior segments that were not active in earlier Xashes. The Xash series stops abruptly instead of decreasing asymptotically in brightness. In posterior fragments, all the segments participate in Xashing luminescence, indicating the loss of an inhibitory eVect exerted by the anterior end in the case of whole animals. Posterior fragments survive and are still capable of luminescence weeks after fragmentation although they do not regenerate a head. Immediately upon fragmentation of the worm, the posterior fragment luminesces continuously for some seconds while the anterior part quickly stops light emission.This suggests a decoy and/or a predator-alerting function of prolonged, strong luminescence by the moribund posterior fragment to the beneWt of the survival of the anterior fragment.

As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilise two Neuro-Inspired Companion (NICO)-robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of nonverbal communication. We observe a correlation of 0.43 (p = 0.02) between self-assessed trust and trust measured from the game and a positive impact of non-verbal communication on trust (p = 0.0008) and robot perception for anthropomorphism (p = 0.007) and animacy (p = 0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human's trust in robots.

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