Exploring the experiences of parents with children who have communication delays, as a population at risk for the development of behavioural concerns

Existing research identifies preschoolers with communication delays as a population at risk for the development of behavioural concerns. This risk increases when additional environmental factors such as parental stress and family conflict are also present. Research has also shown that behavioural concerns can be stable over time when they develop early. However, early intervention has been shown to be effective in addressing these concerns. The effectiveness of early intervention in addressing both child and family outcomes increases when interventions are delivered in a family-centred approach. This research project made use of data related to child behaviour and parenting, gathered through the Family Resource Project which explored the parenting experiences and resource access and allocation decisions of families who have preschool children with and without communication delays. Cluster analysis was used to explore whether there were identifiable clusters of children and families within each sample. Interview data fi"om each identified family cluster was then explored further, to identify how parents described their child's behaviour and their experience of parenting. Results show that, within this sample, parents of preschoolers with communication delays described their child's behaviour and their experience of parenting differently than did parents of children without communication delays. Results also showed that within this sample parents experiencing parental stress and/or family conflict described their child's behaviour and their experience of parenting differently than did parents from other clusters. Results suggest support for early intervention and the use of family-centred intervention, particularly for families of children with communication delays.

Gypsy moths (Lymantria dispar) in the Niagara Region : population density variation, introduction of an entomopathogenic fungus (Entomophaga maimaiga) and occurrence of nuclear polyhedrosis virus

The gypsy moth, Lymantria dispar, a major defoliator of broad leaf trees, was accidentally introduced into North America in 1869. Much interest has been generated regarding the potential of using natural pathogens for biological control of this insect. One of these pathogens, a highly specific fungus, Entomophaga maimaiga, was accredited with causing major epizootics in populations of gypsy moth across the north-eastern United States in 1989 and 1990 and is thought to be spreading northwards into Canada. This study examined gypsy moth population densities in the Niagara Region. The fungus, .E.. maimaiga, was artificially introduced into one site and the resulting mortality in host populations was noted over two years. The relationship between fungal mortality, host population density and occurrence of another pathogen, the nuclear polyhedrosis virus (NPV), was assessed. Gypsy moth population density was assessed by counting egg masses in 0.01 hectare (ha) study plots in six areas, namely Louth, Queenston, Niagara-on-the-Lake, Shorthills Provincial Park, Chippawa Creek and Willoughby Marsh. High variability in density was seen among sites. Willoughby Marsh and Chippawa Creek, the sites with the greatest variability, were selected for more intensive study. The pathogenicity of E. maimaiga was established in laboratory trials. Fungal-infected gypsy moth larvae were then released into experimental plots of varying host density in Willoughby Marsh in 1992. These larvae served as the inoculum to infect field larvae. Other larvae were injected with culture medium only and released into control plots also of varying host density. Later, field larvae were collected and assessed for the presence of .E.. maimaiga and NPV. A greater proportion of larvae were infected from experimental plots than from control plots indicating that the experimental augmentation had been successful. There was no relationship between host density and the proportion of infected larvae in either experimental or control plots. In 1992, 86% of larvae were positive for NPV. Presence and intensity of NPV infection was independent of fungal presence, plot type or interaction of these two factors. Sampling was carried out in the summer of 1993, the year after the introduction, to evaluate the persistence of the pathogen in the environment. Almost 50% of all larvae were infected with the fungus. There was no difference between control and experimental plots. Data collected from Willoughby Marsh indicated that there was no correlation between the proportion of larvae infected with the fungus and host population density in either experimental or control plots. About 10% of larvae collected from a nearby site, Chippawa Creek, were also positive for .E.. maimaiga suggesting that low levels of .E.. maimaiga probably occurred naturally in the area. In 1993, 9.6% of larvae were positive for NPV. Again, presence or absence of NPV infection was independent of fungal presence plot type or interaction of these two factors. In conclusion, gypsy moth population densities were highly variable between and within sites in the Niagara Region. The introduction of the pathogenic fungus, .E.. maimaiga, into Willoughby Marsh in 1992 was successful and the fungus was again evident in 1993. There was no evidence for existence of a relationship between fungal mortality and gypsy moth density or occurrence of NPV. The results from this study are discussed with respect to the use of .E.. maimaiga in gypsy moth management programs.

Transmission of West Nile virus in the Niagara Region among a population at risk for exposure

Background. West Nile Virus (WNV), a mosquito-borne flavivirus, is one of an increasing number of infectious diseases that have been emerging or re-emerging in the last two decades. Since the arrival ofWNV to Canada to present date, the Niagara Region has only reported 30 clinical cases, a small number compared to the hundreds reported in other regions of similar conditions. Moreover, the last reported human case in Niagara was in 2006. As it has been demonstrated that the majority of WNV infections are asymptomatic, the question remains whether the lack of clinical cases in Niagara truly reflects the lack of transmission to humans or if infections are still occurring but are mostly asymptomatic. Objectives. The general objective of this study was to establish whether or not active WNV transmission could be detected in a human population residing in Niagara for the 2007 transmission season. To fullfil this objective, a cross-sectional seroprevalence study was designed to investigate for the presence of anti-WNV antibodies in a sample of Mexican migrant agricultural workers employed in farms registered with the Seasonal Agricultural Workers Program (SAWP). Due to the Mexican origin of the study participants, three specific research objectives were proposed: a) determine the seroprevalence ofanti-WNV antibodies as well as anti-Dengue virus antibodies (a closely related virus prevalent in Mexico and likely to confound WNV serology); b) analyze risk factors associated with WNV and Dengue virus seropositivity; and c) assess the awareness of study participants about WNV infection as well as their understanding of the mode of transmission and clinical importance of the infection. Methodology: After obtaining ethics clearance from Brock University, farms were visited and workers invited to participate. Due to time constraints, only a small number of farms were enrolled with a resulting convenience and non-randomized study sample. Workers' demographic and epidemiological data were collected using a standardized questionnaire and blood samples were drawn to determine serum anti-WNV and anti- Dengue antibodies with a commercial ELISA. All positive samples were sent to the National Microbiology Laboratory in Winnipeg, Manitoba for confirmation with the Plaque Reduction Neutralization Test (PRNT). Data was analyzed with Stata 10.0. Antibody determinations were reported as seroprevalence proportions for both WNV and Dengue. Logistic regression was used to analyze risk factors that may be associated with seropositivity and awareness was reported as a proportion of the number of individuals possessing awareness over the total number of participants. Results and Discussion. In total 92 participants working in 5 farms completed the study. Using the commercial ELISA, seropositivity was as follows: 2.2% for WNV IgM, 20.7% for WNV IgG, and 17.1 % for Dengue IgG. Possible cross-reactivity was demonstrated in 15/20 (75.0%) samples that were positive for both WNV IgG and Dengue IgG. Confirmatory testing with the PRNT demonstrated that none of the WNV ELISA positive samples had antibodies to WNV but 13 samples tested positive for anti-Dengue antibodies (14.1 % Dengue sereoprevalence). The findings showed that the ELISA performance was very poor for assessing anti-WNV antibodies in individuals previously exposed to Dengue virus. However, the ELISA had better sensitivity and specificity for assessing anti-Dengue antibodies. Whereas statistical analysis could not be done for WNV seropositivity, as all samples were PRNT negative, logistic regression demonstrated several risk factors for Dengue exposure_ The first year coming to Canada appeared to be significantly associated with increased exposure to Dengue while lower socio-economic housing and the presence of a water basin in the yard in Mexico appeared to be significantly associated with a decreased exposure to Dengue_ These seemingly contradictory results illustrate that in mobile populations such as migrant workers, risk factors for exposure to Dengue are not easily identified and more research is needed. Assessing the awareness of WNV and its clinical importance showed that only 23% of participants had some knowledge of WNV, of which 76% knew that the infection was mosquito-borne and 47% recognized fever as a symptom. The identified lack of understanding and awareness was not surprising since WNV is not a visible disease in Mexico. Since WNV persists in an enzootic cycle in Niagara and the occurrence of future outbreaks is unpredictable, the agricultural workers remain at risk for transmission. Therefore it important they receive sufficient health education regarding WNV before leaving Mexico and during their stay in Canada. Conclusions. Human transmission of WNV could not be proven among the study participants even when due to their occupation they are at high risk for mosquito bites. The limitations of the study sample do not permit generalizable conclusions, however, the study findings are consistent with the absence of clinical cases in the Niagara Region, so it is likely that human transmission is indeed neglible or absent. As evidenced by our WNV serology results, PRNT must be utilized as a confirmatory test since false positivity occurs frequently. This is especially true when previous exposure to Dengue virus is likely.

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.