An analysis of decoupling procedures in generating thermal Green's functions of O([lambda]â ´) by the Zubarev equation of motion method

The Zubarev equation of motion method has been applied to an anharmonic crystal of O( ,,4). All possible decoupling schemes have been interpreted in order to determine finite temperature expressions for the one phonon Green's function (and self energy) to 0()\4) for a crystal in which every atom is on a site of inversion symmetry. In order to provide a check of these results, the Helmholtz free energy expressions derived from the self energy expressions, have been shown to agree in the high temperature limit with the results obtained from the diagrammatic method. Expressions for the correlation functions that are related to the mean square displacement have been derived to 0(1\4) in the high temperature limit.

Individual differences in risk-taking and associated characteristics : a test of specificity in executive functions /

Multiple measures have been devised by clinicians and theorists from many different backgrounds for the purpose of assessing the influence of the frontal lobes on behaviour. Some utilize self-report measures to investigate behavioural characteristics such as risktaking, sensation seeking, impulsivity, and sensitivity to reward and punishment in an attempt to understand complex human decision making. Others rely more on neuroimaging and electrophysiological investigation involving experimental tasks thought to demonstrate executive functions in action, while other researchers prefer to study clinical populations with selective damage. Neuropsychological models of frontal lobe functioning have led to a greater appreciation of the dissociations among various aspects of prefrontal cortex function. This thesis involves (1) an examination of various psychometric and experimental indices of executive functions for coherence as one would predict on the basis of highly developed neurophysiological models of prefrontal function, particularly those aspects of executive function that involve predominantly cognitive abilities versus processes characterized by affect regulation; and (2) investigation of the relations between risk-taking, attentional abilties and their associated characteristics using a neurophysiological model of prefrontal functions addressed in (1). Late adolescence is a stage in which the prefrontal cortices undergo intensive structural and functional maturational changes; this period also involves increases in levels of risky and sensation driven behaviours, as well as a hypersensitivity to reward and a reduction in inhibition. Consequently, late adolescence spears to represent an ideal developmental period in which to examine these decision-making behaviours due to the maximum variability of behavioural characteristics of interest. Participants were 45 male undergraduate 18- to 19-year olds, who completed a battery of measures that included self-report, experimental and behavioural measures designed to assess particular aspects of prefrontal and executive functioning. As predicted, factor analysis supported the grouping of executive process by type (either primarily cognitive or affective), conforming to the orbitofrontal versus dorsolateral typology; risk-taking and associated characteristics were associated more with the orbitofrontal than the dorsolateral factor, whereas attentional and planning abilities tended to correlate more strongly with the dorsolateral factor. Results are discussed in light of future assessment, investigation and understanding of complex human decision-making and executive functions. Implications, applications and suggestions for future research are also proposed.

Moderating effects of gender and general self-efficacy on the relationship between sensation-seeking and adolescent substance use /

This study performed a aecondvy dau analysis of information collected during the Youth Leisure Study (YLS). The purpose of this study was to examine the potential moderating influences of gender and general self-efTicacy on the relationships aoKXig sensation-seeking and various forms of substance use in adolescents. Specifically, the predictive ability of sensation seeking on five adolescents substance use outcomes (alcohol, tobacco, and marijuana use; binge drinking; and number of times drunk) was examined. Moderated hierarchical multiple regression (MHMR) analyses were used to examine the relationships among study variables. The results for this study indicate that the relationships among sensation-seeking and forms of adolescent substance use are more complex than literature suggests. Main effect relationships were found consistently for sensation-seeking and general self-efficacy with each of the outcome variables. Results for gender were not consistent across the substance use outcomes. Gender was a significant predictor for marijuana use only. The moderating effects of general self-efficacy (GSE) on the sensation-seekingsubstance use relationship were inconsistent. While no significant interactions were found for tobacco or alcohol use outcomes, GSE was found to moderate the relationship between sensation-seeking and marijuana use indicating that feelings of high general selfefficacy act as a buffer or guard against marijuana use. A consistent pattern was found among the alcohol use variables (alcohol use. binge drinking, and number of times drunk). Gender was found to moderate each of these variables indicating that higher levels of sensation seeking are more predictive of higher levels of adolescent alcohol use in males only. Implications of this study on the field of education, are discussed further, and suggestions for future research are presented.

Prime Rational Functions and Integral Polynomials

Let f(x) be a complex rational function. In this work, we study conditions under which f(x) cannot be written as the composition of two rational functions which are not units under the operation of function composition. In this case, we say that f(x) is prime. We give sufficient conditions for complex rational functions to be prime in terms of their degrees and their critical values, and we derive some conditions for the case of complex polynomials. We consider also the divisibility of integral polynomials, and we present a generalization of a theorem of Nieto. We show that if f(x) and g(x) are integral polynomials such that the content of g divides the content of f and g(n) divides f(n) for an integer n whose absolute value is larger than a certain bound, then g(x) divides f(x) in Z[x]. In addition, given an integral polynomial f(x), we provide a method to determine if f is irreducible over Z, and if not, find one of its divisors in Z[x].

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.