RESUMO
Artificial Intelligence (AI) methods need to be evaluated thoroughly to ensure reliable behavior. In applications like autonomous driving, a complex environment with an uncountable number of different situations and conditions needs to be handled by a method whose behavior needs to be predictable. To accomplish this, simulations can be used as a first step. However, the physical world behaves differently, as the example of autonomous driving shows. There, erroneous behavior has been found in test drives that was not noticed in simulations. Errors were caused by conditions or situations that were not covered by the simulations (e.g., specific lighting conditions or other vehicle's behavior). However, the problem with real world testing of autonomous driving features is that critical conditions or situations occur very rarely-while the test effort is high. A solution can be the combination of physical world tests and simulations-and miniature vehicles as an intermediate step between both. With model cars (in a sufficiently complex model environment) advantages of both can be combined: (1) low test effort and a repeatable variation of conditions/situations as an advantage like in simulations and (2) (limited) physical world testing with unspecified and potentially unknown properties as an advantage like in real-world tests. Additionally, such physical tests can be carried out in less stable cases like already in the early stages of AI method testing and/or in approaches using online learning. Now, we propose to use a) miniature vehicles at a small scale of 1:87 and b) use sensors and computational power only on the vehicle itself. By this limitation, a further consequence is expected: Here, autonomy methods need to be optimized drastically or even redesigned from scratch. The resulting methods are supposed to be less complex-and, thus, again less error-prone. We call this approach "Miniature Autonomy" and apply it to the road, water, and aerial vehicles. In this article, we briefly describe a small test area we built (3 sqm.), a large test area used alternatively (1,545 sqm.), two last generation autonomous miniature vehicles (one road, one aerial vehicle), and an autonomous driving demo case demonstrating the application.
RESUMO
BACKGROUND: Small mammals are crucial for the life history of ixodid ticks, but their role and importance in the transmission cycle of tick-borne pathogens is mostly unknown. Candidatus Neoehrlichia mikurensis (CNM) and Anaplasma phagocytophilum are both tick-borne pathogens, and rodents are discussed to serve as main reservoir hosts for CNM but not for the latter especially in Germany. Analysing the prevalence of both pathogens in small mammals and their ticks in endemic regions may help to elucidate possible transmission paths in small mammal populations and between small mammals and ticks. METHODS: In 2012 and 2013, small mammals were trapped at three different sites in Germany. DNA was extracted from different small mammal tissues, from rodent neonates, foetuses and from questing and attached ticks. DNA samples were tested for CNM and A. phagocytophilum by real-time PCR. Samples positive for A. phagocytophilum were further characterized at the 16S rRNA gene locus. RESULTS: CNM was detected in 28.6% of small mammals and in 2.2% of questing and 3.8% of attached ticks. Altogether 33 positive ticks were attached to 17 different hosts, while positive ticks per host ranged between one and seven. The prevalences for this pathogen differed significantly within small mammal populations comparing sites (χ(2): 13.3987; p: 0.0004) and between sexes. Male rodents had an approximately two times higher chance of infection than females (OR: 1.9652; 95% CI: 1.32-2.92). The prevalence for CNM was 31.8% (95% CI: 22-44) in rodent foetuses and neonates (23 of 67) from positive dams, and 60% (95% CI: 35.7-80.25) of positive gravid or recently parturient rodents (9 out of 15) had at least one positive foetus or neonate. Anaplasma phagocytophilum was detected at a low percentage in rodents (0-5.6%) and host-attached ticks (0.5-2.9%) with no significant differences between rodent species. However, attached nymphs were significantly more often infected than attached larvae (χ(2): 25.091; p: <0.0001). CONCLUSION: This study suggests that CNM is mainly a rodent-associated pathogen and provides evidence for a potential transplacental transmission in rodents. In contrast, most of the rodent species captured likely represent only accidental hosts for A. phagocytophilum at the investigated sites.
