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The aim of this study was to determine the effects of silver nanoparticles (AgNPs; speciation: NM-300 K) in the lab on the behavior of larvae in European Whitefish (Coregonus lavaretus), a relevant model species for temperate aquatic environments during alternating light and darkness phases. The behavioral parameters measured included activity, turning rate, and distance moved. C. lavaretus were exposed to AgNP at nominal concentrations of 0, 5, 15, 45, 135, or 405 µg/L (n = 33, each) and behavior was recorded using a custom-built tracking system equipped with light sources that reliably simulate light and darkness. The observed behavior was analyzed using generalized linear mixed models, which enabled reliable detection of AgNP-related movement patterns at 10-fold higher sensitivity compared to recently reported standard toxicological studies. Exposure to 45 µg/L AgNPs significantly resulted in hyperactive response patterns for both activity and turning rates after an illumination change from light to darkness suggesting that exposure to this compound triggered escape mechanisms and disorientation-like behaviors in C. lavaretus fish larvae. Even at 5 µg/L AgNPs some behavioral effects were detected, but further tests are required to assess their ecological relevance. Further, the behavior of fish larvae exposed to 135 µg/L AgNPs was comparable to the control for all test parameters, suggesting a triphasic dose response pattern. Data demonstrated the potential of combining generalized linear mixed models with behavioral investigations to detect adverse effects on aquatic species that might be overlooked using standard toxicological tests. [ABSTRACT FROM AUTHOR]

In the last decades, the focus has shifted towards mobile robots to link predictions, imagination, and expectations to human life in different aspects. A tremendous amount of research on mobile robots indicates their importance in various industrial and non-industrial fields such as production, medicine and agriculture. Despite all of these innovations in the field of robotics, intelligent mobile robots are facing challenges in processing the vast amount of sensory data from their sensory inputs. Due to the increasing amount of sensory data, a new demand is to process sensory inputs in an understandable form for both humans and robots. One approach to processing sensory data in a way that is understandable for both robots and humans is through the use of semantic technology, which is a major technology for building semantic knowledge bases in a machine-readable form. The success of semantic technology is highly reliant on ontologies which are considered the semantic knowledge representation. The huge amount of research in this field proves the undeniable impact of ontologies in the field of robotics. Yet, the work concerning the conversion of the sensory inputs from a mobile robot into semantic information in real-time are scarce. This transformation becomes more challenging when converting the sensory input of multiple sensors to a single semantic statement. The collection of semantic information for real-time ontology population is another challenge. In this regard, there is also a lack of work in transferring and using this information for natural language communication between humans and robots. This work addresses these challenges and employs semantic technology in the field of robotics to enable a mobile robot to create semantic information during exploration. In addition, the resulted semantic information is used for communicating information as well as facilitating communication between other robots and humans in a natural language. [ABSTRACT FROM AUTHOR]

An artificial compound eye (ACE) is a bio-inspired vision sensor which mimics a natural compound eye (typical of insects). This artificial eye is able to visualize large fields of the outside world through multi-aperture. Due to its functioning, the ACE is subject to optical flow, that is an apparent motion of the object visualized by the eye. This paper proposes a method to estimate the optical flow based on capturing multiple images (multi-aperture). In this method, based on descriptors-based initial optical flows, a unified global energy function is presented to incorporate the information of multi-aperture and simultaneously recover the optical flows of multi-aperture. The energy function imposes a compound flow fields consistency assumption along with the brightness constancy and piecewise smoothness assumptions. This formula efficiently binds the flow field in time and space, and further enables view-consistent optical flow estimation. Experimental results on real and synthetic data demonstrate that the proposed method recovers view-consistent optical flows crossed multi-aperture and performs better than other optical flow methods on the multi-aperture images. [ABSTRACT FROM AUTHOR]

Zebrafish larvae (Danio rerio) are among the most used model species to test biological effects of different substances in biomedical research, neuroscience and ecotoxicology. Most tests are based on changes in swimming activity of zebrafish larvae by using commercially available high-throughput screening systems. These systems record and analyse behaviour patterns using visible (VIS) and near-infrared (NIR) light sources, to simulate day (VIS) and night (NIR) phases, which allow continuous recording of the behaviour using a NIR sensitive camera. So far, however, the sensitivity of zebrafish larvae to NIR has never been tested experimentally, although being a critical piece of information for interpreting their behaviour under experimental conditions. Here, we investigated the swimming activity of 96 hpf (hours post fertilization) and 120 hpf zebrafish larvae under light sources of NIR at 860 nm and at 960 nm wavelength and under VIS light. A thermal source was simultaneously presented opposite to one of the light sources as control. We found that zebrafish larvae of both larval stages showed a clear negative phototactic response towards 860 nm NIR light and to VIS light, but not to 960 nm NIR light. Our results demonstrated that zebrafish larvae are able to perceive NIR at 860 nm, which is almost identical to the most commonly used light source in commercial screening systems (NIR at 850 nm) to create a dark environment. These tests, however, are not performed in the dark from the zebrafish´s point of view. We recommend testing sensitivity of the used test organism before assuming no interaction with the applied light source of commonly used biosensor test systems. Previous studies on biological effects of substances to zebrafish larvae should be interpreted with caution. [ABSTRACT FROM AUTHOR]

An artificial compound eye system is the bionic system of natural compound eyes with much wider field-of-view, better capacity to detect moving objects and higher sensitivity to light intensity than ordinary single-aperture eyes. In recent years, renewed attention has been paid to the artificial compound eyes, due to their better characteristics inheriting from insect compound eyes than ordinary optical imaging systems. This paper provides a comprehensive survey of the state-of-the-art work on artificial compound eyes. This review starts from natural compound eyes to artificial compound eyes including their system design, theoretical development and applications. The survey of artificial compound eyes is developed in terms of two main types: planar and curved artificial compound eyes. Finally, the most promising future research developments are highlighted. [ABSTRACT FROM AUTHOR]

The use of computer animation in behavioral research is a state-of-the-art method for designing and presenting animated animals to live test animals. The major advantages of computer animations are: (1) the creation of animated animal stimuli with high variability of morphology and even behavior; (2) animated stimuli provide highly standardized, controlled and repeatable testing procedures; and (3) they allow a reduction in the number of live test animals regarding the 3Rs principle. But the use of animated animals should be attended by a thorough validation for each test species to verify that behavior measured with live animals toward virtual animals can also be expected with natural stimuli. Here we present results on the validation of a custom-made simulation for animated 3D sailfin mollies Poecilia latipinna and show that responses of live test females were as strong to an animated fish as to a video or a live male fish. Movement of an animated stimulus was important but female response was stronger toward a swimming 3D fish stimulus than to a "swimming" box. Moreover, male test fish were able to discriminate between animated male and female stimuli; hence, rendering the animated 3D fish a useful tool inmate-choice experiments with sailfin mollies. [ABSTRACT FROM AUTHOR]

Animal behavior researchers often face problems regarding standardization and reproducibility of their experiments. This has led to the partial substitution of live animals with artificial virtual stimuli. In addition to standardization and reproducibility, virtual stimuli open new options for researchers since they are easily changeable in morphology and appearance, and their behavior can be defined. In this article, a novel toolchain to conduct behavior experiments with fish is presented by a case study in sailfin mollies Poecilia latipinna. As the toolchain holds many different and novel features, it offers new possibilities for studies in behavioral animal research and promotes the standardization of experiments. The presented method includes options to design, animate, and present virtual stimuli to live fish. The designing tool offers an easy and user-friendly way to define size, coloration, and morphology of stimuli and moreover it is able to configure virtual stimuli randomly without any user influence. Furthermore, the toolchain brings a novel method to animate stimuli in a semiautomatic way with the help of a game controller. These created swimming paths can be applied to different stimuli in real time. A presentation tool combines models and swimming paths regarding formerly defined playlists, and presents the stimuli onto 2 screens. Experiments with live sailfin mollies validated the usage of the created virtual 3D fish models in mate-choice experiments. [ABSTRACT FROM AUTHOR]

In many computer vision problems, the essential information can be most easily interpreted in the form of structural models. However, the computation of distances between structural models can be difficult, since small changes in the underlying image data often cause significant differences in the graph layout. The other way around, changes in the link structure of a graph often mean complex changes in feature attributes or do not correspond to any valid visual data at all. In contrast, structural models can often be used conveniently for the classification of a pattern. Based on this observation, we propose to shift the graph matching problem to the easier problem of matching classifiers and patterns. The similarity between two models is detected if a model serving as a pattern can be recognised by another model serving as classifier. To extend this measure beyond single binary digits, models are compared to whole sets of other models. Single models are described by the vector of similarities to the set. Further comparisons between models can be done using appropriate distance functions on the vector representation. The use of the method is demonstrated in a graph clustering task. We also discuss the numerical stability of the method with respect to the dimensionality of the descriptors. [ABSTRACT FROM AUTHOR]

This article presents an overview over the whole process of generating a precise and rich 3D representation of the local environment of a moving mobile outdoor robot. The resulting model of this process is a camera image textured triangle mesh which is triangulated from a motion-corrected laser scanned 3D point cloud. The demanding requirements of autonomous off-road environment model acquisition are handled by applying a multi-sensor fusion approach. Additionally to the model creation process a novel way of detecting and describing feature points on a piece-wise linear 3D surfaces is presented. The set of feature points generated by the proposed method is a valuable abstraction of a whole outdoor scene that can be used in several following processing steps like mesh simplification or segmentation and robotics-specific tasks like obstacle detection or classification. All described methods are implemented and successfully used on the award-winning robot AMOR. [ABSTRACT FROM AUTHOR]

This article gives an overview of the current state of research in the field of off-road robotics. It focuses on techniques used in the areas of perception, environment representation, as well as navigation, and introduces different types of robot control systems. A presentation of different applications is given along with an outlook on future developments. [ABSTRACT FROM AUTHOR]