Emotional climate and behavioral management during sleep time in early childhood education settings

The majority of children cease napping between 3 and 5 years of age yet, internationally, the allocation of a sleep time during the day for children of this age remains a practice in many early childhood education (ECE) settings. These dual circumstances present a disjuncture between children's sleep needs and center practices, that may cause conflict for staff, increase stress for children and escalate negative emotional climate in the room. Testing this hypothesis requires observation of both the emotional climate and behavioral management used in ECE rooms that extends into the sleep time. This study was the first to apply the Classroom Assessment and Scoring System (CLASS) Pre-K (Pianta, La Paro, & Hamre, 2008) to observe the emotional climate and behavioral management during sleep time. Pilot results indicated that the CLASS Pre-K functioned reliably to measure emotional climate and behavioral management in sleep time. However, new sleep-specific examples of the dimensions used were developed, to help orient fieldworkers to the CLASS Pre-K rating system in the sleep time context. The CLASS was then used to assess emotional climate and behavior management between the non-sleep and sleep time sessions, in 113 ECE rooms in Queensland, Australia. In these rooms 2.114 children were observed. Of these children, 71% did not sleep at any point during the allotted sleep times. There was a significant drop in emotional climate and behavioral management between the non-sleep and sleep-time sessions. Furthermore, the duration of mandated sleep time (a period of time where no activities are provided to non-sleeping children) accounted for significant independent variance in the observed emotional climate during sleep-time. The CLASS Pre-K presents a valuable tool to assess the emotional climate and behavior management during sleep-time and draws attention to the need for further studies of sleep time in ECE settings.

Real-time decision making for autonomous city vehicles

This paper addresses the topic of real-time decision making by autonomous city vehicles. Beginning with an overview of the state of research, the paper presents the vehicle decision making & control systemarchitecture, explains the subcomponents which are relevant for decision making (World Model and Driving Maneuver subsystem), and presents the decision making process. Experimental test results confirmthe suitability of the developed approach to deal with the complex real-world urban traffic.

Multiple criteria-based real-time decision making by autonomous city vehicles

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

Real-time decision making by driverless city vehicles : a discrete event driven approach

This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

A contextual analysis of secondary home economic teachers' agency in a time of mandatory curriculum change

This qualitative research explored secondary Home Economics teachers' perceptions of their teacher agency to influence classroom, department and school level curriculum decision making. Teachers responded to curriculum change with proactive, reactive and/or passive agency. Findings indicated that teachers' perceptions of their classroom agency remained high. However, agency decreased at department and school levels. Recent changes in schools as a result of the Australian Curriculum; NAPLAN and Queensland Studies Authority have resulted in changes that have been detrimental to teacher agency. Agency was enacted differently depending on whether change was teacher initiated or mandated by authority.

Genetic bottlenecks in time and space: reconstructing invasions from contemporary and historical collections

Herbarium accession data offer a useful historical botanical perspective and have been used to track the spread of plant invasions through time and space. Nevertheless, few studies have utilised this resource for genetic analysis to reconstruct a more complete picture of historical invasion dynamics, including the occurrence of separate introduction events. In this study, we combined nuclear and chloroplast microsatellite analyses of contemporary and historical collections of Senecio madagascariensis, a globally invasive weed first introduced to Australia c. 1918 from its native South Africa. Analysis of nuclear microsatellites, together with temporal spread data and simulations of herbarium voucher sampling, revealed distinct introductions to south-eastern Australia and mid-eastern Australia. Genetic diversity of the south-eastern invasive population was lower than in the native range, but higher than in the mid-eastern invasion. In the invasive range, despite its low resolution, our chloroplast microsatellite data revealed the occurrence of new haplotypes over time, probably as the result of subsequent introduction(s) to Australia from the native range during the latter half of the 20th century. Our work demonstrates how molecular studies of contemporary and historical field collections can be combined to reconstruct a more complete picture of the invasion history of introduced taxa. Further, our study indicates that a survey of contemporary samples only (as undertaken for the majority of invasive species studies) would be insufficient to identify potential source populations and occurrence of multiple introductions.

Facial emotion modulates the neural mechanisms responsible for short interval time perception

Emotionally arousing events can distort our sense of time. We used mixed block/event-related fMRI design to establish the neural basis for this effect. Nineteen participants were asked to judge whether angry, happy and neutral facial expressions that varied in duration (from 400 to 1,600 ms) were closer in duration to either a short or long duration they learnt previously. Time was overestimated for both angry and happy expressions compared to neutral expressions. For faces presented for 700 ms, facial emotion modulated activity in regions of the timing network Wiener et al. (NeuroImage 49(2):1728–1740, 2010) namely the right supplementary motor area (SMA) and the junction of the right inferior frontal gyrus and anterior insula (IFG/AI). Reaction times were slowest when faces were displayed for 700 ms indicating increased decision making difficulty. Taken together with existing electrophysiological evidence Ng et al. (Neuroscience, doi: 10.3389/fnint.2011.00077, 2011), the effects are consistent with the idea that facial emotion moderates temporal decision making and that the right SMA and right IFG/AI are key neural structures responsible for this effect.