Abstract. There is an increasing demand for entertainment applications developed for pets, in particular for dogs and cats. However, play interaction between animals and technological devices still remains an uncharted territory both for animal behavior and entertainment computing scientific communities. While there is a lot of anecdotal evidence of pets playing digital games, the nature of animal-computer play interactions is still not understood. In this paper we report on empirical findings based on observing and analyzing dog-tablet game interactions. Using categories emerging from our data analysis, we construct an ethogram, a "catalogue" of behavioral patterns typical of dog-tablet interactions. Based on our data analysis, we hypothesize that the nature of the observed interactions is that of predatory behavior, in response to stimuli in the form of "prey-like" virtual objects displayed on the screen. Based on our hypothesis, we further propose some questions for future investigation, and raise some issues that need to be addressed by game developers when targeting dogs as their users.
With the advance of modern technologies, computerbased systems for animals are gaining popularity. In particular, there is an explosion of products and gadgets for pets: wellness monitoring applications (e.g., FitBark and PetPace), automatic food dispensers, cognitive enrichment apps, and many more. Furthermore, the discipline of Animal-Computer Interaction has emerged, focusing on a user-centric development of technologies for animals, making them stakeholders in the development process. Animal-centric technologies have already been developed to support activities of rescue and assistance dogs, to provide environmental and cognitive enrichment for animals in captivity, and to support conservation and animal behavior research. Going beyond human stakeholders poses new exciting challenges for requirement engineering and can be used to significantly expand its boundaries under broader theoretical and methodological frameworks. This paper highlights these challenges and proposes a research agenda for developing methodologies for requirement elicitation and analysis for a user-centric development of computerized systems for non-human users.
This is a report of three ZooJams that have taken place at the annual Animal-Computer Interaction conference. The ZooJam is a type of workshop whose aim is to extend the reach of UX design beyond human experience in order to become inclusive of other species and their interactions with technology. As organisers, our attempts have knitted together colleagues from a range of disciplines, all focused on developing practical solutions to different environmental enrichment challenges. We describe the format of the event, explaining the rationale for this approach, and showcase some of the crafted design outcomes.
This workshop will allow participants to work together to devise novel forms of technically enhanced enrichment for farm animals. It will take the format of a gamejam, whereby teams will be given clear briefs, they will brainstorm concepts and present their ideas to the group for feedback and analysis.
Repetitive elements (RE) and transposons (TE) can comprise up to 80% of some plant genomes and may be essential for regulating their evolution and adaptation. The “repeatome” information is often unavailable in assembled genomes because genomic areas of repeats are challenging to assemble and are often missing from final assembly. However, raw genomic sequencing data contain rich information about RE/TEs. Here, raw genomic NGS reads of 10 gymnosperm species were studied for the content and abundance patterns of their “repeatome”. We utilized a combination of alignment on databases of repetitive elements and de novo assembly of highly repetitive sequences from genomic sequencing reads to characterize and calculate the abundance of known and putative repetitive elements in the genomes of 10 conifer plants: Pinus taeda, Pinus sylvestris, Pinus sibirica, Picea glauca, Picea abies, Abies sibirica, Larix sibirica, Juniperus communis, Taxus baccata, and Gnetum gnemon. We found that genome abundances of known and newly discovered putative repeats are specific to phylogenetically close groups of species and match biological taxa. The grouping of species based on abundances of known repeats closely matches the grouping based on abundances of newly discovered putative repeats (kChains) and matches the known taxonomic relations.
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