Daytime lidar measurements of tidal winds in the mesospheric sodium layer at Urbana, Illinois

For more than 15 years lidar systems have been used to study the chemistry and dynamics of the mesospheric sodium layer. Because the layer is an excellent tracer of atmospheric wave motions, sodium lidar has proven to be particularly useful for studying the influence of gravity waves and tides on mesospheric dynamics. These waves, which originate in the troposphere and stratosphere, propagate through the mesosphere and dissipate their energy near the mesopause making important contributions to the momentum and turbulence budget in this region of the atmosphere. Recently, the sodium lidar was modified for daytime operation so that wave phenomena and chemical effects could be monitored throughout the complete diurnal cycle. The results of continuous 24 hour lidar observations of the sodium layer structure are presented alond with measurement of the semidiurnal tidal winds

Distribution And Abundance Of Glucocorticoid And Mineralocorticoid Receptors Throughout The Brain Of The Great Tit (Parus Major)

The glucocorticoid stress response, regulated by the hypothalamic-pituitary-adrenal (HPA) axis, enables individuals to cope with stressors through transcriptional effects in cells expressing the appropriate receptors. The two receptors that bind glucocorticoids—the mineralocorticoid receptor (MR) and glucocorticoid receptor (GR)—are present in a variety of vertebrate tissues, but their expression in the brain is especially important. Neural receptor patterns have the potential to integrate multiple behavioral and physiological traits simultaneously, including self-regulation of glucocorticoid secretion through negative feedback processes. In the present work, we quantified the expression of GR and MR mRNA throughout the brain of a female great tit (Parus major), creating a distribution map encompassing 48 regions. This map, the first of its kind for P. major, demonstrated a widespread but not ubiquitous distribution of both receptor types. In the paraventricular nucleus of the hypothalamus (PVN) and the hippocampus (HP)—the two brain regions that we sampled from a total of 25 birds, we found high GR mRNA expression in the former and, unexpectedly, low MR mRNA in the latter. We examined the covariation of MR and GR levels in these two regions and found a strong, positive relationship between MR in the PVN and MR in the HP and a similar trend for GR across these two regions. This correlation supports the idea that hormone pleiotropy may constrain an individual’s behavioral and physiological phenotype. In the female song system, we found moderate GR in hyperstriatum ventrale, pars caudalis (HVC), and moderate MR in robust nucleus of the arcopallium (RA). Understanding intra- and interspecific patterns of glucocorticoid receptor expression can inform us about the behavioral processes (e.g. song learning) that may be sensitive to stress and stimulate future hypotheses concerning the relationships between receptor expression, circulating hormone concentrations and performance traits under selection, including behavior

Initial references to persons and places

This task has two parts: (i) video-taped elicitation of the range of possibilities for referring to persons and places, and (ii) observations of (first) references to persons and places in video-taped natural interaction. The goal of this task is to establish the repertoires of referential terms (and other practices) used for referring to persons and to places in particular languages and cultures, and provide examples of situated use of these kinds of referential practices in natural conversation. This data will form the basis for cross-language comparison, and for formulating hypotheses about general principles underlying the deployment of such referential terms in natural language usage

The PInSoRo dataset: supporting the data-driven study of child-child and child-robot social dynamics

The study of the fine-grained social dynamics between children is a methodological challenge, yet a good understanding of how social interaction between children unfolds is important not only to Developmental and Social Psychology, but recently has become relevant to the neighbouring field of Human-Robot Interaction (HRI). Indeed, child-robot interactions are increasingly being explored in domains which require longer-term interactions, such as healthcare and education. For a robot to behave in an appropriate manner over longer time scales, its behaviours have to be contingent and meaningful to the unfolding relationship. Recognising, interpreting and generating sustained and engaging social behaviours is as such an important—and essentially, open—research question. We believe that the recent progress of machine learning opens new opportunities in terms of both analysis and synthesis of complex social dynamics. To support these approaches, we introduce in this article a novel, open dataset of child social interactions, designed with data-driven research methodologies in mind. Our data acquisition methodology relies on an engaging, methodologically sound, but purposefully underspecified free-play interaction. By doing so, we capture a rich set of behavioural patterns occurring in natural social interactions between children. The resulting dataset, called the PInSoRo dataset, comprises 45+ hours of hand-coded recordings of social interactions between 45 child-child pairs and 30 child-robot pairs. In addition to annotations of social constructs, the dataset includes fully calibrated video recordings, 3D recordings of the faces, skeletal informations, full audio recordings, as well as game interactions