4 resultados para VARIABLE SAMPLING INTERVAL
em Brock University, Canada
Resumo:
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.
Resumo:
A new approach to treating large Z systems by quantum Monte Carlo has been developed. It naturally leads to notion of the 'valence energy'. Possibilities of the new approach has been explored by optimizing the wave function for CuH and Cu and computing dissociation energy and dipole moment of CuH using variational Monte Carlo. The dissociation energy obtained is about 40% smaller than the experimental value; the method is comparable with SCF and simple pseudopotential calculations. The dipole moment differs from the best theoretical estimate by about 50% what is again comparable with other methods (Complete Active Space SCF and pseudopotential methods).
Resumo:
The purpose of this cross sectional survey design was to examine self-reported health status and lifestyle behaviours of the residents of the Town of Fort Erie, Ontario, as related to the Canadian Community Health Survey. Using a mail-out survey, entitled the Fort Erie Survey of Health (FESH), a probability cluster sampling technique was used to measure self-reported health status (present health, health conditions, health challenges, functional health limitations) and lifestyle behaviour (smoking, alcohol use, drug use, physical activity, fruit and vegetable consumption, body weight, and gaming). Each variable was described and analyzed in relation to socio-economic variables, age and gender. The findings from this study were compared to the Canadian Community Health Survey 2000/2001. Overall, 640 surveys were completed. The majority of Fort Erie residents rated their present health as good and were satisfied with their overall health and quality of life. The main chronic conditions reported were arthritis, back pain and heart disease. Other main health problems reported were vision, sleeping and chronic pain. Overall, 14.6% smoke; 58.8% engaged in physical activity either occasionally or never as opposed to regularly engaging in physical activity; 52.1% did not eat the required daily fruits and vegetables; and 40.0% were in the overweight category. Persons who practiced one healthy lifestyle behaviour were more likely to practice other healthy promoting behaviours. Therefore, health promotion programs are best designed to address multiple risk factors simultaneously. The ffiSH was generally consistent with the Canadian Community Health Survey in the overall findings. A small number of inconsistencies were identified that require further exploration to determine if they are unique to this community.
Resumo:
The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.