Early school-based parent involvement, children’s self-regulated learning and academic achievement: An Australian longitudinal study

Parent involvement is widely accepted as being associated with children’s improved educational outcomes. However, the role of early school-based parent involvement is still being established. This study investigated the mediating role of self-regulated learning behaviors in the relationship between early school-based parent involvement and children’s academic achievement, using data from the Longitudinal Study of Australian Children (N = 2616). Family socioeconomic position, Aboriginal and Torres Strait Islander status, language background, child gender and cognitive competence, were controlled, as well home and community based parent involvement activity in order to derive a more confident interpretation of the results. Structural equation modeling analyses showed that children’s self-regulated learning behaviors fully mediated the relationships between school-based parent involvement at Grade 1 and children’s reading achievement at Grade 3. Importantly, these relationships were evident for children across all socio-economic backgrounds. Although there was no direct relationship between parent involvement at Grade 1 and numeracy achievement at Grade 3, parent involvement was indirectly associated with higher children’s numeracy achievement through children’s self-regulation of learning behaviors, though this relationship was stronger for children from middle and higher socio-economic backgrounds. Implications for policy and practice are discussed, and further research recommended.

Nash equilibrium based semantic cache in mobile sensor grid database systems

Mobile applications are being increasingly deployed on a massive scale in various mobile sensor grid database systems. With limited resources from the mobile devices, how to process the huge number of queries from mobile users with distributed sensor grid databases becomes a critical problem for such mobile systems. While the fundamental semantic cache technique has been investigated for query optimization in sensor grid database systems, the problem is still difficult due to the fact that more realistic multi-dimensional constraints have not been considered in existing methods. To solve the problem, a new semantic cache scheme is presented in this paper for location-dependent data queries in distributed sensor grid database systems. It considers multi-dimensional constraints or factors in a unified cost model architecture, determines the parameters of the cost model in the scheme by using the concept of Nash equilibrium from game theory, and makes semantic cache decisions from the established cost model. The scenarios of three factors of semantic, time and locations are investigated as special cases, which improve existing methods. Experiments are conducted to demonstrate the semantic cache scheme presented in this paper for distributed sensor grid database systems.

Involvement of Ca2+-dependent hyperpolarization in sleep duration in mammals

The detailed molecular mechanisms underlying the regulation of sleep duration in mammals are still elusive. To address this challenge, we constructed a simple computational model, which recapitulates the electrophysiological characteristics of the slow-wave sleep and awake states. Comprehensive bifurcation analysis predicted that a Ca2+-dependent hyperpolarization pathway may play a role in slow-wave sleep and hence in the regulation of sleep duration. To experimentally validate the prediction, we generate and analyze 21 KO mice. Here we found that impaired Ca2+-dependent K+ channels (Kcnn2 and Kcnn3), voltage-gated Ca2+ channels (Cacna1g and Cacna1h), or Ca2+/calmodulin-dependent kinases (Camk2a and Camk2b) decrease sleep duration, while impaired plasma membrane Ca2+ ATPase (Atp2b3) increases sleep duration. Pharmacological intervention and whole-brain imaging validated that impaired NMDA receptors reduce sleep duration and directly increase the excitability of cells. Based on these results, we propose a hypothesis that a Ca2+-dependent hyperpolarization pathway underlies the regulation of sleep duration in mammals.

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.