Gaze Behavior, Believability, Likability and the iCat

The iCat is a user-interface robot with the ability to express a range of emotions through its facial features. This paper summarizes our research whether we can increase the believability and likability of the iCat for its human partners through the application of gaze behaviour. Gaze behaviour serves several functions during social interaction such as mediating conversation flow, communicating emotional information and avoiding distraction by restricting visual input. There are several types of eye and head movements that are necessary for realizing these functions. We designed and evaluated a gaze behaviour system for the iCat robot that implements realistic models of the major types of eye and head movements found in living beings: vergence, vestibulo ocular reflexive, smooth pursuit movements and gaze shifts. We discuss how these models are integrated into the software environment of the iCat and can be used to create complex interaction scenarios. We report about some user tests and draw conclusions for future evaluation scenarios

Analysis of cranial neural crest migratory pathways in axolotl using cell markers and transplantation

We have examined the ability of normal and heterotopically transplanted neural crest cells to migrate along cranial neural crest pathways in the axolotl using focal DiI injections and in situ hybridization with the neural crest marker, AP-2. DiI labeling demonstrates that cranial neural crest cells migrate as distinct streams along prescribed pathways to populate the maxillary and mandibular processes of the first branchial arch, the hyoid arch and gill arches 1-4, following migratory pathways similar to those observed in other vertebrates. Another neural crest marker, the transcription factor AP-2, is expressed by premigratory neural crest cells within the neural folds and migrating neural crest cells en route to and within the branchial arches. Rotations of the cranial neural folds suggest that premigratory neural crest cells are not committed to a specific branchial arch fate, but can compensate when displaced short distances from their targets by migrating to a new target arch. In contrast, when cells are displaced far from their original location, they appear unable to respond appropriately to their new milieu such that they fail to migrate or appear to migrate randomly. When trunk neural folds are grafted heterotopically into the head, trunk neural crest cells migrate in a highly disorganized fashion and fail to follow normal cranial neural crest pathways. Importantly, we find incorporation of some trunk cells into branchial arch cartilage despite the random nature of their migration. This is the first demonstration that trunk neural crest cells can form cartilage when transplanted to the head. Our results indicate that, although cranial and trunk neural crest cells have inherent differences in ability to recognize migratory pathways, trunk neural crest can differentiate into cranial cartilage when given proper instructive cues

Exploring curved schematization

Hand-drawn schematized maps traditionally make extensive use of curves. However, there are few automated approaches for curved schematization most previous work focuses on straight lines. We present a new algorithm for area-preserving curved schematization of geographic outlines. Our algorithm converts a simple polygon into a schematic crossing-free representation using circular arcs. We use two basic operations to iteratively replace consecutive arcs until the desired complexity is reached. Our results are not restricted to arcs ending at input vertices. The method can be steered towards different degrees of 'curviness': we can encourage or discourage the use of arcs with a large central angle via a single parameter. Our method creates visually pleasing results even for very low output complexities. We conducted an online user study investigating the effectiveness of the curved schematizations compared to straight-line schematizations of equivalent complexity. While the visual complexity of the curved shapes was judged higher than those using straight lines, users generally preferred curved schematizations. We observed that curves significantly improved the ability of users to match schematized shapes of moderate complexity to their unschematized equivalents

Small Multiples with Gaps

Small multiples enable comparison by providing different views of a single data set in a dense and aligned manner. A common frame defines each view, which varies based upon values of a conditioning variable. An increasingly popular use of this technique is to project two-dimensional locations into a gridded space (e.g. grid maps), using the underlying distribution both as the conditioning variable and to determine the grid layout. Using whitespace in this layout has the potential to carry information, especially in a geographic context. Yet, the effects of doing so on the spatial properties of the original units are not understood. We explore the design space offered by such small multiples with gaps. We do so by constructing a comprehensive suite of metrics that capture properties of the layout used to arrange the small multiples for comparison (e.g. compactness and alignment) and the preservation of the original data (e.g. distance, topology and shape). We study these metrics in geographic data sets with varying properties and numbers of gaps. We use simulated annealing to optimize for each metric and measure the effects on the others. To explore these effects systematically, we take a new approach, developing a system to visualize this design space using a set of interactive matrices. We find that adding small amounts of whitespace to small multiple arrays improves some of the characteristics of 2D layouts, such as shape, distance and direction. This comes at the cost of other metrics, such as the retention of topology. Effects vary according to the input maps, with degree of variation in size of input regions found to be a factor. Optima exist for particular metrics in many cases, but at different amounts of whitespace for different maps. We suggest multiple metrics be used in optimized layouts, finding topology to be a primary factor in existing manually-crafted solutions, followed by a trade-off between shape and displacement. But the rich range of possible optimized layouts leads us to challenge single-solution thinking; we suggest to consider alternative optimized layouts for small multiples with gaps. Key to our work is the systematic, quantified and visual approach to exploring design spaces when facing a trade-off between many competing criteria—an approach likely to be of value to the analysis of other design spaces

(4aS,5R,7R,8S,8aR)-8-(1,3-Dioxolan-2-yl)-7,8-dimethyl-5-(1-methyl­ethen­yl)perhydro­naphthalen-2-one

In the chiral title compound, C18H28O3, the two six-membered rings of the perhydronaphthalenone adopt a rigid chair–chair conformation and the five-membered dioxolanyl ring adopts an envelope conformation. The crystal structure is stabilized only by weak inter­actions

Topologically safe curved schematization

Traditionally schematized maps make extensive use of curves. However, automated methods for schematization are mostly restricted to straight lines. We present a generic framework for topology-preserving curved schematization that allows a choice of quality measures and curve types. Our fully-automated approach does not need critical points or salient features. We illustrate our framework with Bézier curves and circular arcs

Map LineUps: effects of spatial structure on graphical inference

Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.’s ‘Visual Line-up’ method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n = 361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran’s I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people’s abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference