Characterization of complex quantum dynamics with a scalable NMR information processor

We present experimental results on the measurement of fidelity decay under contrasting system dynamics using a nuclear magnetic resonance quantum information processor. The measurements were performed by implementing a scalable circuit in the model of deterministic quantum computation with only one quantum bit. The results show measurable differences between regular and complex behavior and for complex dynamics are faithful to the expected theoretical decay rate. Moreover, we illustrate how the experimental method can be seen as an efficient way for either extracting coarse-grained information about the dynamics of a large system or measuring the decoherence rate from engineered environments.

Perceptual speed does not cause intelligence, and intelligence does not cause perceptual speed

There is ongoing debate whether the efficiency of local cognitive processes leads to global cognitive ability or whether global ability feeds the efficiency of basic processes. A prominent example is the well-replicated association between inspection time (IT), a measure of perceptual discrimination speed, and intelligence (IQ), where it is not known whether increased speed is a cause or consequence of high IQ. We investigated the direction of causation between IT and IQ in 2012 genetically related subjects from Australia and The Netherlands. Models in which the reliable variance of each observed variable was specified as a latent trait showed IT correlations of -0.44 and -0.33 with respective Performance and Verbal IQ; heritabilities were 57% (IT), 83% (PIQ) and 77% (VIQ). Directional causation models provided poor fits to the data, with covariation best explained by pleiotropic genes (influencing variation in both IT and IQ). This finding of a common genetic factor provides a better target for identifying genes involved in cognition than genes which are unique to specific traits.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

Training emotional intelligence: Presenting the results of an experimental study

This presentation outlines the results of an eighteen month study examining the effect of an emotions focused training intervention on the emotional intelligence of employees from a large public sector organisation. Utilising an experimental methodology, 280 staff attended a two-day program focused on training emotional intelligence skills and abilities. These interventions were created around Mayer and Salovey’s four-branch model of emotional intelligence (awareness, understanding, facilitation and management of emotions). The experimental group’s emotional intelligence was tested pre and post training using the Workgroup Emotional Intelligence Profile (WEIP). In addition, a control group from the same organisation also completed the same measure at three points during the same eighteen month period. Analysis of the control and experimental group data were conducted, and whilst no changes were found in the control group, the experimental group’s overall emotional intelligence significantly improved post training. To further strengthen these findings, a measure of effect size using Cohen’s d was also conducted to assess the magnitude of the training intervention’s overall effect. Full results will be presented during the presentation, with feedback on the study and methods utilised encouraged from participants.