A dose-response investigation of the attentional blink during sleep restriction /

Recent dose-response sleep restriction studies, in which nightly sleep is curtailed to varying degrees (e.g., 3-, 5-, 7-hours), have found cumulative, dose-dependent changes in sleepiness, mood, and reaction time. However, brain activity has typically not been measured, and attentionbased tests employed tend to be simple (e.g., reaction time). One task addressing the behavioural and electrophysiological aspects of a specific attention mechanism is the Attentional Blink (AB), which shows that the report accuracy of a second target (T2) is impaired when it is presented soon after a first target (Tl). The aim of the present study was to examine behavioural and electrophysioiogical responses to the AB task to elucidate how sleep restriction impacts attentional capacity. Thirty-six young-adults spent four consecutive days and nights in a sleep laboratory where sleep, food, and activity were controlled. Nightly sleep began with a baseline sleep (8 hours), followed by two nights of sleep restriction (3,5 or 8 hours of sleep), and a recovery sleep (8 hours). An AB task was administered each day at 11 am. Results from a basic battery oftests (e.g., sleepiness, mood, reaction time) confirmed the effectiveness of the sleep restriction manipulation. In terms of the AB, baseline performance was typical (Le., T2 accuracy impaired when presented soon after Tl); however, no changes in any AB behavioural measures were observed following sleep restriction for the 3- or 5-hour groups. The only statistically significant electrophysiological result was a decrease in P300 amplitude (for Tl) from baseline to the second sleep restriction night for the 3-hour group. Therefore, following a brief, two night sleep restriction paradigm, brain functioning was impaired for the TI of the AB in the absence of behavioural deficit. Study limitations and future directions are discussed.

Study of the application of the high performance liquid chromatography-particle beam interface-mass spectrometry technique on some pesiticides and the reduction phenomena in the system

This work includes two major parts. The first part of the work concentrated on the studies of the application of the highperfonnance liquid chromatography-particle beam interface-mass spectrometry system of some pesticides. Factors that have effects on the detection sensitivity were studied. The linearity ranges and detection limits of ten pesticides are also given in this work. The second part of the work concentrated on the studies of the reduction phenomena of nitro compounds in the HPLC-PB-MS system. Direct probe mass spectrometry and gas chromatography-mass spectrometry techniques were also used in the work. Factors that have effects on the reduction of the nitro compounds were studied, and the possible explanation is proposed. The final part of this work included the studies of reduction behavior of some other compounds in the HPLC-PB-MS system, included in them are: quinones, sulfoxides, and sulfones.

Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.