Vulnerability to adverse consequences of drinking and problem drinker status as predicted by risky drinking behaviours, drug use, sex differences and affect : a test of multiple models /

Although alcohol problems and alcohol consumption are related, consumption does not fully account for differences in vulnerability to alcohol problems. Therefore, other factors should account for these differences. Based on previous research, it was hypothesized that risky drinking behaviours, illicit and prescription drug use, affect and sex differences would account for differences in vulnerability to alcohol problems while statistically controlling for overall alcohol consumption. Four models were developed that were intended to test the predictive ability of these factors, three of which tested the predictor sets separately and a fourth which tested them in a combined model. In addition, two distinct criterion variables were regressed on the predictors. One was a measure of the frequency that participants experienced negative consequences that they attributed to their drinking and the other was a measure of the extent to which participants perceived themselves to be problem drinkers. Each of the models was tested on four samples from different populations, including fIrst year university students, university students in their graduating year, a clinical sample of people in treatment for addiction, and a community sample of young adults randomly selected from the general population. Overall, support was found for each of the models and each of the predictors in accounting for differences in vulnerability to alcohol problems. In particular, the frequency with which people become intoxicated, frequency of illicit drug use and high levels of negative affect were strong and consistent predictors of vulnerability to alcohol problems across samples and criterion variables. With the exception of the clinical sample, the combined models predicted vulnerability to negative consequences better than vulnerability to problem drinker status. Among the clinical and community samples the combined model predicted problem drinker status better than in the student samples.

The kinetics and induced decomposition on the thermal decomposition of hydroperoxides /

This project is focussed on the thermsLl decomposition of t-butyl hydroperoxide and sec-butyl hydroperoxide at 120°C to 160°C in three alcohol solvents. These are methanol, ethajiol and isopropyl alcohol. The aim of the project was to examine the process of induced decomposition. Thermal decomposition of t-hutyl hydroperoxide and sec-butyl hydroperoxide indicate that these reactions have first-order kinetics with activation energies on the order of 20 to 28 K cal/mole, Styrene was used as a free radical trap to inhibit the induced decomposition. The results permitted calculation of how much induced decomposition occurred in its absence. The experimental resvilts indicate that the induced decomposition is important for t-butyl hydroperoxide in alcohol solvents, as shown by both the reaction rate suid product studies. But sec-butyl hydroperoxide results show that the concerted mechanism for the interaction of two sec-butylperoxy radicals occurs in addition to the induced decomposition. Di-sodium E.D,T.A. was added to reduce possible effects of trace transition metal ion .impurities. The result of this experiment were not as expected. The rate of hydroperoxide decomposition was about the same but was zero-order in hydroperoxide concentration.

A study of the thermal decomposition of allyl t-butyl peroxide and 3-hydroperoxy-1-propene (allyl hydroperoxide) in toluene /|nby Krishnankutty Nair V. G. -- 260 St. Catharines [Ont. : s. n.],

Kinetics and product studies of the decompositions of allyl-t-butyl peroxide and 3-hydroperoxy- l-propene (allyl hydroperoxide ) in tolune were investigated. Decompositions of allyl-t-butyl peroxide in toluene at 130-1600 followed first order kinetics with an activation energy of 32.8 K.cals/mol and a log A factor of 13.65. The rates of decomposition were lowered in presence of the radical trap~methyl styrene. By the radical trap method, the induced decomposition at 1300 is shown to be 12.5%. From the yield of 4-phenyl-l,2- epoxy butane the major path of induced decomposition is shown to be via an addition mechanism. On the other hand, di-t-butYl peroxyoxalate induced decomposition of this peroxide at 600 proceeded by an abstraction mechanism. Induced decomposition of peroxides and hydroperoxides containing the allyl system is proposed to occur mainly through an addition mechanism at these higher temperatures. Allyl hydroperoxide in toluene at 165-1850 decomposes following 3/2 order kinetics with an Ea of 30.2 K.cals per mole and log A of 10.6. Enormous production of radicals through chain branching may explain these relatively low values of E and log A. The complexity of the reaction is indicated a by the formation of various products of the decomposition. A study of the radical attack of the hydro peroxide at lower temperatures is suggested as a further work to throw more light on the nature of decomposition of this hydroperoxide.

The kinetics and mechanism of the thermal decomposition of sec-Butyl peroxide in liquid phase /|nby Sandor Szilagyi. -- 260 St. Catharines, Ont. : [s. n.],

Re~tes artd pJ~oducts of tllerma]. d,ecom.position of sec-butyl peroxide at 110 - 150°C i.n four solvents h,ave been determined. The d,ecompos i tion vJas sb.o\'\Tn to be tlnlmolecl.llar wi tho energies of activation in toluene, benzene, and cyclohexane of 36 .7-+ 1.0, 33.2 +- 1..0, 33.t~) +.. 1.0 I'(:cal/mol respectively. The activation energy of thermal decomposition for the d,et.1terated peroxide was found to be 37.2 4:- 1.0 KC8:1/1TIol in toluene. A.bo1J.t 70 - 80/~ ol~ tJJ.e' pl~od.1..1CtS could, be explained by kn01rJ11 reactions of free allcoxy raclicals J and very littJ...e, i.f allY, disPl"Opox~tiol'lation of tll10 sec-butoxy radica.ls in t116 solvent cage could be detected. The oth,er 20 - 30% of the peroxide yielded H2 and metb.:'ll etb..yl 1{etol1e. Tl1.e yield. o:f H2 "'lIas unafJ:'ected by the nature or the viscosity of the solvent, but H2 was not formed when s-t1U202 lrJaS phctolyzed. in tolttene at 35°C nor 'tl!Jrl.en the peroxide 1;'JaS tl1.ermally o..ecoJnposed. in the gas p11ase. ~pC-Dideutero-~-butYlperoxide was prepared and decomposed in toluene at 110 - 150°C. The yield of D2 was about ·•e1ne same 248 the yield. of I{2 from s-Bu202, bU.t th.e rate of decomposition (at 135°C) 1iJas only 1/1.55 as fast. Ivlecl1.anisms fOl') J:1ydrogen produ.ction are discussed, but none satisfactorily explains all the evidence.

The kinetics and mechanism of the thermal decomposition of bis diphenyl methyl and related peroxides in liquid phase /|nby C. Thankachan. -- 260 St. Catharines, Ont. : [s. n.],

Rates and products have been determined for the thermal decomposition of bis diphenyl methyl peroxide and diphenyl methyl tert* butyl peroxide at 110@~145@C* The decomposition was uniformly unimolecular with activation energies for the bis diphenyl methyl peroxide in tetrachloroethylene* toluene and nitrobenzene 26,6* 28*3f and 27 Kcals/mole respectively. Diphenyl methyl tert* butyl peroxide showed an activation energy of 38*6 Kcals/mole* About 80-90% of the products in the case of diphenyl methyl peroxide could be explained by the concerted process, this coupled with the negative entropies of activation obtained is a conclusive evidence for the reaction adopting a major concerted path* All the products in the case of diphenyl methyl peroxide could be explained by known reactions of alkoxy radicals* About 80-85% of tert butanol and benzophenone formed suggested far greater cage disproportionation than diffusing apart* Rates of bis triphenyl methyl peroxide have been determined in tetrachloroethylene at 100-120@C* The activation energy was found to be 31 Kcals/mole*

The kinetics and solvent effects on the thermal decomposition of isopropyl peroxide and 1, 2-dioxane

Rates of H2 formation have been determined for the thermal decomposition of isopropyl peroxide at l30o-l50oC in toluene and methanol and at l400C in isopropyl alcohol and water. Product studies have been carried out at l400C in these solvents. The decomposition of isopropyl peroxide was shown to be unimolecular with energies of activation in toluene, and methanol of 39.1, 23.08 Kcal/mole respectively. It has been shown that the rates of H2 formation in decomposition of isopropyl peroxide are solvent dependent and that the ~ vs "'2';' values (parameters for solvent polarity) givesastraight line. Mechanisms for hydrogen production are discussed which satisfactorily explain the stabilization of the six-centered transition state by the solvent. One possibility is that of conformation stabilization by solvent and the other, a transition state with sufficient ionic character to be stabilized by a polar solvent. Rates of thermal decomposition of 1,2-dioxane in tert-butylbenzene at l40o-l70oC have been determined. The activation energy was found to be 33.4 Kcal/mole. This lower activation energy, compared to that for the decomposition of isopropyl peroxide in toluene (39.1 Kcal/mole) has been explained in terms of ring strain. Decomposition of 1,2 dioxane in MeOH does not follow a first order reaction. Several mechanisms have been suggested for the products observed for decomposition of 1;2-dioxane in toluene and methanol.

Posttraumatic stress disorder symptoms might be destroying your intimacy : a test of mediational models in a community sample of couples

The present research focused on the pathways through which the symptoms of posttraumatic stress disorder (PTSD) may negatively impact intimacy. Previous research has confirmed a link between self-reported PTSD symptoms and intimacy; however, a thorough examination of mediating paths, partner effects, and secondary traumatization has not yet been realized. With a sample of 297 heterosexual couples, intraindividual and dyadic models were developed to explain the relationships between PTSD symptoms and intimacy in the context of interdependence theory, attachment theory, and models of selfpreservation (e.g., fight-or-flight). The current study replicated the findings of others and has supported a process in which affective (alexithymia, negative affect, positive affect) and communication (demand-withdraw behaviour, self-concealment, and constructive communication) pathways mediate the intraindividual and dyadic relationships between PTSD symptoms and intimacy. Moreover, it also found that the PTSD symptoms of each partner were significantly related; however, this was only the case for those dyads in which the partners had disclosed most everything about their traumatic experiences. As such, secondary traumatization was supported. Finally, although the overall pattern of results suggest a total negative effect of PTSD symptoms on intimacy, a sex difference was evident such that the direct effect of the woman's PTSD symptoms were positively associated with both her and her partner's intimacy. I t is possible that the Tend-andBefriend model of threat response, wherein women are said to foster social bonds in the face of distress, may account for this sex difference. Overall, however, it is clear that PTSD symptoms were negatively associated with relationship quality and attention to this impact in the development of diagnostic criteria and treatment protocols is necessary.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

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.