The development, assessment, and implementation of an evaluation of the EMPOWER Program at shelters for abused women /

The development, assessment, and implementation of a program evaluation instrument was carried out to evaluate the impact and efficacy of the EMPOWER Program. This intervention was created to educate residents at a shelter for abused women with an anticipated outcome of prevention. Participants included the staff and residents at 2 shelters in Southern Ontario. Client pre, post and follow-up measures were obtained and analyzed statistically and using keyword content analysis. A single staff measure was obtained and summarized using keyword content analysis. Qualitative results were suggestive of important change in participants. All women in the post and follow-up measures believed their participation in the EMPOWER Program provided them with the knowledge, skills, and confidence to avoid abusive relationships in the fliture. This transformational impact was repeatedly expressed in both resident and staff feedback. Limitations of this research, as well as suggestions for future study were discussed.

The nesting biology of Ceratina (Hymenoptera: Apidae) in the Niagara Region : new species, nest site selection and parasitism

One of the most common bee genera in the Niagara Region, the genus Ceratina (Hymenoptera: Apidae) is composed of four species, C. dupla, C. calcarata, the very rare C. strenua, and a previously unknown species provisionally named C. near dupla. The primary goal of this thesis was to investigate how these closely related species coexist with one another in the Niagara ~ee community. The first necessary step was to describe and compare the nesting biologies and life histories of the three most common species, C. dupla, C. calcarata and the new C. near dupla, which was conducted in 2008 via nest collections and pan trapping. Ceratina dupla and C. calcarata were common, each comprising 49% of the population, while C. near dupla was rare, comprising only 2% of the population. Ceratina dupla and C. near dupla both nested more commonly in teasel (Dipsacus sp.) in the sun, occasionally in raspberry (Rubus sp.) in the shade, and never in shady sumac (Rhus sp.), while C. calcarata nested most commonly in raspberry and sumac (shaded) and occasionally in teasel (sunny). Ceratina near dupla differed from both C. dupla and C. calcarata in that it appeared to be partially bivoltine, with some females founding nests very early and then again very late in the season. To examine the interactions and possible competition for nests that may be taking place between C. dupla and C. calcarata, a nest choice experiment was conducted in 2009. This experiment allowed both species to choose among twigs from all three substrates in the sun and in the shade. I then compared the results from 2008 (where bees chose from what was available), to where they nested when given all options (2009 experiment). Both C. dupla and C. calcarata had the same preferences for microhabitat and nest substrate in 2009, that being raspberry and sumac twigs in the sun. As that microhabitat and nest substrate combination is extremely rare in nature, both species must make a choice. In nature Ceratina dupla nests more often in the preferred microhabitat (sun), while C. calcarata nests in the preferred substrate (raspberry). Nesting in the shade also leads to smaller clutch sizes, higher parasitism and lower numbers of live brood in C. calcarata, suggesting that C. dupla may be outcompeting C. calcarata for the sunny nesting sites. The development and host preferences of Ceratina parasitoids were also examined. Ceratina species in Niagara were parasitized by no less than eight species of arthropod. Six of these were wasps from the superfamily Chalcidoidea (Hymenoptera), one was a wasp from the family Ichneumonidae (Hymenoptera) and one was a physogastric mite from the family Pyemotidae (Acari). Parasites shared a wide range of developmental strategies, from ichneumonid larvae that needed to consume multiple Ceratina immatures to complete development, to the species from the Eulophidae (Baryscapus) and Encyrtidae (Coelopencyrtus), in which multiple individuals completed development inside a single Ceratina host. Biological data on parasitoids is scarce in the scientific literature, and this Chapter documents these interactions for future research.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

A DFT Guided/Experimental Approach to Asymmetric Allylation and Phase-Transfer Catalysis

The Dudding group is interested in the application of Density Functional Theory (DFT) in developing asymmetric methodologies, and thus the focus of this dissertation will be on the integration of these approaches. Several interrelated subsets of computer aided design and implementation in catalysis have been addressed during the course of these studies. The first of the aims rested upon the advancement of methodologies for the synthesis of biological active C(1)-chiral 3-methylene-indan-1-ols, which in practice lead to the use of a sequential asymmetric Yamamoto-Sakurai-Hosomi allylation/Mizoroki Heck reaction sequence. An important aspect of this work was the utilization of ortho-substituted arylaldehyde reagents which are known to be a problematic class of substrates for existing asymmetric allylation approaches. The second phase of my research program lead to the further development of asymmetric allylation methods using o-arylaldehyde substrates for synthesis of chiral C(3)-substituted phthalides. Apart from the de novo design of these chemistries in silico, which notably utilized water-tolerant, inexpensive, and relatively environmental benign indium metal, this work represented the first computational study of a stereoselective indium-mediated process. Following from these discoveries was the advent of a related, yet catalytic, Ag(I)-catalyzed approach for preparing C(3)-substituted phthalides that from a practical standpoint was complementary in many ways. Not only did this new methodology build upon my earlier work with the integrated (experimental/computational) use of the Ag(I)-catalyzed asymmetric methods in synthesis, it provided fundamental insight arrived at through DFT calculations, regarding the Yamamoto-Sakurai-Hosomi allylation. The development of ligands for unprecedented asymmetric Lewis base catalysis, especially asymmetric allylations using silver and indium metals, followed as a natural extension from these earlier discoveries. To this end, forthcoming as well was the advancement of a family of disubstituted (N-cyclopropenium guanidine/N-imidazoliumyl substituted cyclopropenylimine) nitrogen adducts that has provided fundamental insight into chemical bonding and offered an unprecedented class of phase transfer catalysts (PTC) having far-reaching potential. Salient features of these disubstituted nitrogen species is unprecedented finding of a cyclopropenium based C-H•••πaryl interaction, as well, the presence of a highly dissociated anion projected them to serve as a catalyst promoting fluorination reactions. Attracted by the timely development of these disubstituted nitrogen adducts my last studies as a PhD scholar has addressed the utility of one of the synthesized disubstituted nitrogen adducts as a valuable catalyst for benzylation of the Schiff base N-diphenyl methylene glycine ethyl ester. Additionally, the catalyst was applied for benzylic fluorination, emerging from this exploration was successful fluorination of benzyl bromide and its derivatives in high yields. A notable feature of this protocol is column-free purification of the product and recovery of the catalyst to use in a further reaction sequence.