Let’s animate: Reflections on a Scholarship of Teaching and Learning funded project

This paper describes and reflects on a project that introduced animation into assessment for undergraduate students

Diffusion of Point Defects in Two-Dimensional Colloidal Crystals

We report the first study of the dynamics of point defects, mono and di-vacancies, in a confined 2-D colloidal crystal in real space and time using digital video microscopy. The defects are introduced by manipulating individual particles with optical tweezers. The diffusion rates are measured to be $D_{mono}/a^{2}\cong3.27\pm0.03$Hz for mono-vacancies and $D_{di}/a^{2}\cong3.71\pm0.03$Hz for di-vacancies. The elementary diffusion processes are identified and it is found that the diffusion of di-vacancies is enhanced by a \textit{dislocation dissociation-recombination} mechanism. Furthermore, the defects do not follow a simple random walk but their hopping exhibits memory effects, due to the reduced symmetry (compared to the triangular lattice) of their stable configurations, and the slow relaxation rates of the lattice modes.Comment: 6 pages (REVTEX), 5 figures (PS

The experience of enchantment in human-computer interaction

Improving user experience is becoming something of a rallying call in human–computer interaction but experience is not a unitary thing. There are varieties of experiences, good and bad, and we need to characterise these varieties if we are to improve user experience. In this paper we argue that enchantment is a useful concept to facilitate closer relationships between people and technology. But enchantment is a complex concept in need of some clarification. So we explore how enchantment has been used in the discussions of technology and examine experiences of film and cell phones to see how enchantment with technology is possible. Based on these cases, we identify the sensibilities that help designers design for enchantment, including the specific sensuousness of a thing, senses of play, paradox and openness, and the potential for transformation. We use these to analyse digital jewellery in order to suggest how it can be made more enchanting. We conclude by relating enchantment to varieties of experience.</p

The performance of permutations and exponential random graph models when analyzing animal networks

This is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.The R code used to simulate and analyze the networks are available as supplemental files. Simulation R code, and necessary summary data and R code to reproduce the analyses reported in this article are provided by (Evans et al. 2020).Social network analysis is a suite of approaches for exploring relational data. Two approaches commonly used to analyze animal social network data are permutation-based tests of significance and exponential random graph models. However, the performance of these approaches when analyzing different types of network data has not been simultaneously evaluated. Here we test both approaches to determine their performance when analyzing a range of biologically realistic simulated animal social networks. We examined the false positive and false negative error rate of an effect of a two-level explanatory variable (e.g., sex) on the number and combined strength of an individual’s network connections. We measured error rates for two types of simulated data collection methods in a range of network structures, and with/without a confounding effect and missing observations. Both methods performed consistently well in networks of dyadic interactions, and worse on networks constructed using observations of individuals in groups. Exponential random graph models had a marginally lower rate of false positives than permutations in most cases. Phenotypic assortativity had a large influence on the false positive rate, and a smaller effect on the false negative rate for both methods in all network types. Aspects of within- and between-group network structure influenced error rates, but not to the same extent. In "grouping event-based" networks, increased sampling effort marginally decreased rates of false negatives, but increased rates of false positives for both analysis methods. These results provide guidelines for biologists analyzing and interpreting their own network data using these methods

Protecting eyewitness evidence: Examining the efficacy of a self-administered interview tool

Given the crucial role of eyewitness evidence, statements should be obtained as soon as possible after an incident. This is not always achieved due to demands on police resources. Two studies trace the development of a new tool, the Self-Administered Interview (SAI), designed to elicit a comprehensive initial statement. In Study 1, SAI participants reported more correct details than participants who provided a free recall account, and performed at the same level as participants given a Cognitive Interview. In Study 2, participants viewed a simulated crime and half recorded their statement using the SAI. After a delay of 1 week, all participants completed a free recall test. SAI participants recalled more correct details in the delayed recall task than control participants

Molecular evolution: sex accelerates adaptation

An analysis confirms the long-standing theory that sex increases the rate of adaptive evolution by accelerating the speed at which beneficial mutations sweep through sexual, as opposed to asexual, populations

Ward's Hierarchical Clustering Method: Clustering Criterion and Agglomerative Algorithm

The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. However there are different interpretations in the literature and there are different implementations of the Ward agglomerative algorithm in commonly used software systems, including differing expressions of the agglomerative criterion. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward's hierarchical clustering method.Comment: 20 pages, 21 citations, 4 figure