Supporting parent-child conversations in a history museum

BACKGROUND: Museums can serve as rich resources for families to learn about the social world through engagement with exhibits and parent-child conversation about exhibits. AIMS: This study examined ways of engaging parents and child about two related exhibits at a cultural and history museum. Sample participants consisted of families visiting the Animal Antics and the Gone Potty exhibits at the British Museum. METHODS: Whilst visiting two exhibits at the British Museum, 30 families were assigned to use a backpack of activities, 13 were assigned to a booklet of activities, and 15 were assigned to visit the exhibits without props (control condition). RESULTS: Compared to the families in the control condition, the interventions increased the amount of time parents and children engaged together with the exhibit. Additionally, recordings of the conversations revealed that adults asked more questions related to the exhibits when assigned to the two intervention conditions compared to the control group. Children engaged in more historical talk when using the booklets than in the other two conditions. CONCLUSIONS: The findings suggest that providing support with either booklets or activities for children at exhibits may prove beneficial to parent-child conversations and engagement with museum exhibits

Few-Shot Bayesian Imitation Learning with Logical Program Policies

Humans can learn many novel tasks from a very small number (1--5) of demonstrations, in stark contrast to the data requirements of nearly tabula rasa deep learning methods. We propose an expressive class of policies, a strong but general prior, and a learning algorithm that, together, can learn interesting policies from very few examples. We represent policies as logical combinations of programs drawn from a domain-specific language (DSL), define a prior over policies with a probabilistic grammar, and derive an approximate Bayesian inference algorithm to learn policies from demonstrations. In experiments, we study five strategy games played on a 2D grid with one shared DSL. After a few demonstrations of each game, the inferred policies generalize to new game instances that differ substantially from the demonstrations. Our policy learning is 20--1,000x more data efficient than convolutional and fully convolutional policy learning and many orders of magnitude more computationally efficient than vanilla program induction. We argue that the proposed method is an apt choice for tasks that have scarce training data and feature significant, structured variation between task instances.Comment: AAAI 202

Generalization of the effective Wiener-Ikehara theorem

International audienceWe consider the classical Wiener–Ikehara Tauberian theorem, with a generalized condition of slow decrease and some additional poles on the boundary of convergence of the Laplace transform. In this generality, we prove the otherwise known asymptotic evaluation of the transformed function, when the usual conditions of the Wiener-Ikehara theorem hold. However, our version also provides an effective error term, not known thus far in this generality. The crux of the proof is a proper asymptotic variation of the lemmas of Ganelius and Tenenbaum, also constructed for the sake of an effective version of the Wiener–Ikehara theorem

Gender comparisons in mother-child emotion talk: A meta-analysis

Mother-child emotion talk is one of the main ways through which children learn about emotions. Some previous research studies have suggested that mother-child emotion talk is a gendered process, influencing how girls and boys talk about emotions. Despite inconsistent findings in establishing if mothers use different amounts of emotion talk with their daughters and sons, there is no known meta-analysis of the literature examining gender differences in the frequency of mother-child emotion talk. The aim of this comprehensive meta-analysis is to explore gender comparisons in the frequency of mother-child emotion talk as well as the moderators of these differences. Based on 34 independent group samples (samples of unique individuals) consisting of 3649 participants, no gender differences in the frequency of emotion talk between mothers of daughters and mothers of sons were found. Using a random-effects model, the meta-analysis had a mean weighted effect size of Cohen’s d = .04 (95% CI = [−.05, .13], p = .36). It was not heterogeneous, Qw (33) = 39.36, p = .21. Thus, findings of the present meta-analysis suggest that mother-child emotion talk has not been shown to be gendered, which has implications for children’s socialization of emotions

Cylindrical gravitational waves in expanding universes: Models for waves from compact sources

New boundary conditions are imposed on the familiar cylindrical gravitational wave vacuum spacetimes. The new spacetime family represents cylindrical waves in a flat expanding (Kasner) universe. Space sections are flat and nonconical where the waves have not reached and wave amplitudes fall off more rapidly than they do in Einstein-Rosen solutions, permitting a more regular null inifinity.Comment: Minor corrections to references. A note added in proo

Bi-stochastic kernels via asymmetric affinity functions

In this short letter we present the construction of a bi-stochastic kernel p for an arbitrary data set X that is derived from an asymmetric affinity function {\alpha}. The affinity function {\alpha} measures the similarity between points in X and some reference set Y. Unlike other methods that construct bi-stochastic kernels via some convergent iteration process or through solving an optimization problem, the construction presented here is quite simple. Furthermore, it can be viewed through the lens of out of sample extensions, making it useful for massive data sets.Comment: 5 pages. v2: Expanded upon the first paragraph of subsection 2.1. v3: Minor changes and edits. v4: Edited comments and added DO

Cohesion, team mental models, and collective efficacy: Towards an integrated framework of team dynamics in sport

A nomological network on team dynamics in sports consisting of a multi-framework perspective is introduced and tested. The aim was to explore the interrelationship among cohesion, team mental models (TMM), collective-efficacy (CE), and perceived performance potential (PPP). Three hundred and forty college-aged soccer players representing 17 different teams (8 female and 9 male) participated in the study. They responded to surveys on team cohesion, TMM, CE and PPP. Results are congruent with the theoretical conceptualization of a parsimonious view of team dynamics in sports. Specifically, cohesion was found to be an exogenous variable predicting both TMM and CE beliefs. TMM and CE were correlated and predicted PPP, which in turn accounted for 59% of the variance of objective performance scores as measured by teams’ season record. From a theoretical standpoint, findings resulted in a parsimonious view of team dynamics, which may represent an initial step towards clarifying the epistemological roots and nomological network of various team-level properties. From an applied standpoint, results suggest that team expertise starts with the establishment of team cohesion. Following the establishment of cohesiveness, teammates are able to advance team-related schemas and a collective sense of confidence. Limitations and key directions for future research are outlined

Aligning Manifolds of Double Pendulum Dynamics Under the Influence of Noise

This study presents the results of a series of simulation experiments that evaluate and compare four different manifold alignment methods under the influence of noise. The data was created by simulating the dynamics of two slightly different double pendulums in three-dimensional space. The method of semi-supervised feature-level manifold alignment using global distance resulted in the most convincing visualisations. However, the semi-supervised feature-level local alignment methods resulted in smaller alignment errors. These local alignment methods were also more robust to noise and faster than the other methods.Comment: The final version will appear in ICONIP 2018. A DOI identifier to the final version will be added to the preprint, as soon as it is availabl

Modulated Floquet Topological Insulators

Floquet topological insulators are topological phases of matter generated by the application of time-periodic perturbations on otherwise conventional insulators. We demonstrate that spatial variations in the time-periodic potential lead to localized quasi-stationary states in two-dimensional systems. These states include one-dimensional interface modes at the nodes of the external potential, and fractionalized excitations at vortices of the external potential. We also propose a setup by which light can induce currents in these systems. We explain these results by showing a close analogy to px+ipy superconductors