Busseola fusca is an indigenous lepidopteran pest species in tropical Africa, attacking several grain crops. Crop loss caused by this pest can be as high as 100 % depending on conditions. Despite it being a major pest in Africa, occurring in contrasting climatic zones, only a few studies have been published on its developmental biology. The effect of temperature on the development of B. fusca was studied at five different temperature regimes namely 15, 18, 20, 26 and 30 ± 1 °C and 70 ± 30 % relative humidity (RH) with 14L: 10D photoperiod. The number of instars for B. fusca was also determined. The most favourable temperature as well as the upper threshold temperature for larval development was found to be between 26 and 30 °C. Total development period was 152.6 to 52.6 days, respectively, at 15 °C, and 26 - 30 °C. The thermal constants for B. fusca was 99.50, 536.48, 246.25 and 893.66 °D and lower temperature threshold was 10.36, 8.14, 8.99 and 8.84 °C, for completion of the egg, larval, pupal, and egg-to-adult stages, respectively. The number of larval instars was determined by using head capsule widths that ranged from 0.31 - 2.68 mm. Clear distinctions of head capsule widths could be made from instar 1 to 3, yet overlapping occurred from instar 4 to 6. No distinction could be made between instars 7 and 8 in terms of head capsule width. All successive instars, except for instar eight, increased in size according to Dyar’s ratio. The effect of temperature on reproduction of B. fusca was studied at 15, 20, 26 and 30 ± 1 °C, 70 ± 30 % RH with 14L: 10D photoperiod. Oviposition occurred at all the temperatures evaluated, but no fertility was recorded at 30 °C. The total number of eggs laid by B. fusca females was 300 - 400 eggs and the optimum temperature for oviposition and fertility was determined to be between 20 and 26 °C. Results from this study on the thermal constants and lower and upper threshold temperatures of B. fusca can be used to predict the impact of climate change on the distribution and population growth of this pest. / MSc (Environmental Sciences), North-West University, Potchefstroom Campus, 2015

John Brown Gordon was committed to the mission of national reconciliation. He knew that the South would have to embrace the North to repair the devastation of the Civil War. Driven by dedication to public service after the war, he worked through his positions in governmental offices to help the South. As his public life slowed he began work on a lecture aimed at making him a peacemaker, a missionary for reconciliation. His purpose was to provide a broad, nationalistic perspective which created a common vantage point that would allow both Northerners and Southerners to derive pride and honor from their participation in the Civil War. The lecture, "The Last Days of the Confederacy," became very popular in a short period of time, and made Gordon one of the most requested speakers of the Southern Lyceum Program and Slayton Lyceum Program. The purpose of this critical interpretation of Gordon's lecture is to account for the effectiveness of the rhetorical elements and strategies in the work. The analysis will be based on Walter Fisher's narrative paradigm. Narratives dominate the content and structure of speech; narratives provide a way of ordering and presenting a view of the world through descriptions of a situation - -the act of storytellingthe format Gordon chose in creating the lecture. After drawing conclusions from application of the narrative paradigm I will focus on identifying and evaluating Gordon's rhetorical vision, which is based in Ernest Bormann's fantasy-theme theory. Finally, due to the synecdochal nature of the narratives I will use Kenneth Burke's four master tropes literature to fully interpret the various aspects of the narrative, which complements the initial mission of narrative criticism. In "The Last Days of the Confederacy," Gordon masterfully uses anecdotes from his experiences in the Civil War to create narrative sequences, which construct a strategy of transformative discourse. A typical sequence would start with an ingratiary tactic in which Gordon, in his eloquent manner, would describe a Northern character, scene, or theme and juxtapose it to another story from the South. The purpose of this sequence is to generate irony, creating a dialectic between the two stories, which, at the surface, seem to be opposed. His third step, then, was to use that dialectic to point to the commonalities between the North and the South. This he would do by illustrating an American trait, skill, or value. The result would be a major theme demonstrating a national value or belief to add strength to his existing compendium of themes, such as unity, fraternity, and brotherhood - -all tools to salve the process of reconciliation of conflict with face-saving for both. / Graduation date: 1994

Traffic crashes tend to occur at relatively greater frequencies at particular locations, at particular time periods, and for particular subsets of drivers and vehicles. It is well recognized among the road safety community that crash-risk is highly elevated when inclement weather conditions occur in the winter. To present, most of the road safety studies focus on event-based analysis or seasonal analysis and give little attention to explore high-risk conditions at the daily temporal scale. The purpose of the study is to advance our understanding of high-risk crash conditions at the daily level and their occurrences in Southern Ontario, Canada. The study explores different definitions of high-crash days, and quantifies the influences of weather conditions, risk exposure, months and timing of precipitation on the likelihood of a high-crash day occurring using binary logistic regression model. Additionally, an approach for estimating the relative risk exposure using available traffic count data has also been developed. The results of the study show a small proportion of high-crash days are responsible for a considerable amount of traffic crashes during the winter. The risk of traffic crash is twice as high on high-crash days in comparison to non-high-crash days. The modeling approach well-fits the data and shows that winter weather conditions have significant influence on high-crash days with results being mostly consistent across the four study areas, Toronto, the Area Surrounding Toronto, London and the Area Surrounding London. Low temperature, heavy snowfalls, high wind speeds, high traffic volumes, early winter months, occurrence of precipitation in both morning and evening increase the odds of high-crash days to a large extent. The results of study could help to pre-schedule traffic operation and enforcement, to effectively distribute road safety resources and personnel, and to create situational awareness among road users and other stakeholders.

The use of statistics has been common practice within the petroleum industry for over a decade. With such a mature subject that includes specialized software and numerous articles, the challenge of this project was to introduce a duplicable method to perform deterministic regression while confirming the mathematical and actual validation of the resulting model. A five-step procedure was introduced using Statistical Analysis Software (SAS) for necessary computations to obtain a model that describes an event by analyzing the environmental variables. Since SAS may not be readily available, the code to perform the five-step methodology in R has been provided. The deterministic five-step procedure methodology may be applied to new fields with a limited amount of data. As an example case, 17 wells drilled in north central Texas were used to illustrate how to apply the methodology to obtain a deterministic model. The objective was to predict the number of days required to drill a well using environmental conditions and technical variables. Ideally, the predicted number of days would be within +/- 10% of the observed time of the drilled wells. The database created contained 58 observations from 17 wells with the descriptive variables, technical limit (referred to as estimated days), depth, bottomhole temperature (BHT), inclination (inc), mud weight (MW), fracture pressure (FP), pore pressure (PP), and the average, maximum, and minimum difference between fracture pressure minus mud weight and mud weight minus pore pressure. Step 1 created a database. Step 2 performed initial statistical regression on the original dataset. Step 3 ensured that the models were valid by performing univariate analysis. Step 4 history matched the models-response to actual observed data. Step 5 repeated the procedure until the best model had been found. Four main regression techniques were used: stepwise regression, forward selection, backward elimination, and least squares regression. Using these four regression techniques and best engineering judgment, a model was found that improved time prediction accuracy, but did not constantly result in values that were +/- 10% of the observed times. The five-step methodology to determine a model using deterministic statistics has applications in many different areas within the petroleum field. Unlike examples found in literature, emphasis has been given to the validation of the model by analysis of the model error. By focusing on the five-step procedure, the methodology may be applied within different software programs, allowing for greater usage. These two key parameters allow companies to obtain their time prediction models without the need to outsource the work and test the certainty of any chosen model.

Traffic crashes tend to occur at relatively greater frequencies at particular locations, at particular time periods, and for particular subsets of drivers and vehicles. It is well recognized among the road safety community that crash-risk is highly elevated when inclement weather conditions occur in the winter. To present, most of the road safety studies focus on event-based analysis or seasonal analysis and give little attention to explore high-risk conditions at the daily temporal scale. The purpose of the study is to advance our understanding of high-risk crash conditions at the daily level and their occurrences in Southern Ontario, Canada. The study explores different definitions of high-crash days, and quantifies the influences of weather conditions, risk exposure, months and timing of precipitation on the likelihood of a high-crash day occurring using binary logistic regression model. Additionally, an approach for estimating the relative risk exposure using available traffic count data has also been developed. The results of the study show a small proportion of high-crash days are responsible for a considerable amount of traffic crashes during the winter. The risk of traffic crash is twice as high on high-crash days in comparison to non-high-crash days. The modeling approach well-fits the data and shows that winter weather conditions have significant influence on high-crash days with results being mostly consistent across the four study areas, Toronto, the Area Surrounding Toronto, London and the Area Surrounding London. Low temperature, heavy snowfalls, high wind speeds, high traffic volumes, early winter months, occurrence of precipitation in both morning and evening increase the odds of high-crash days to a large extent. The results of study could help to pre-schedule traffic operation and enforcement, to effectively distribute road safety resources and personnel, and to create situational awareness among road users and other stakeholders.

Background: Marijuana is the most widely used illicit substance in the United States. Public approval of marijuana has driven its legalization in twenty states and the District of Columbia for medical use; and, this year alone (2013), two states have legalized recreational use of the drug. Despite the nation’s growing trend towards marijuana acceptance, the evidence regarding the health effects of its use remains vague. This study was designed to evaluate the health profile of marijuana users by determining the association of marijuana use with quality of life, defined in terms of perceived overall health and as self-reported medical conditions. Methods: The 2007-2010 National Health and Nutrition Examination Survey data was used to evaluate the health profile and quality of life of marijuana smokers. Chi-square and one-way ANOVA analyses were respectively used to compare prevalence and mean differences of select characteristics across different categories grouped by marijuana use. Logistic regression analyses were then performed to determine the association between the reported number of unhealthy days or medical conditions and marijuana use in the past month. All analyses were performed with SAS 9.2 software using weighted data, while 95% confidence intervals were used to determine statistical significance. Results: In total, 7716 cases were included in the study analysis. The prevalence of lifetime marijuana use was 59% (N = 3632), while the prevalence of current (past month) marijuana use was 12.6% (N = 861). Current marijuana users differed significantly from never users with respect to age, gender, income-to-poverty ratio, cigarette smoking, and alcohol and drug use. Current marijuana users also reported more unhealthy days per month, but less frequently reported diagnosis of a medical condition. Results of logistic regression analysis demonstrated that after controlling for confounders, there was no significant association between unhealthy days and current marijuana use, but there was an inverse association with reporting 3+ medical conditions and current marijuana use. Conclusions: This study shows that marijuana users are more likely to engage in health risk behaviors, and report lower quality of life when compared to individuals who have never used marijuana. However, after controlling for confounders, marijuana use was not found to be associated with poor health outcomes.

Thesis (M.T.S.)--Catholic Theological Union at Chicago, 1994. / Vita. Includes bibliographical references (leaf [62]).

Made available in DSpace on 2014-06-11T19:24:39Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-07-05Bitstream added on 2014-06-13T19:31:24Z : No. of bitstreams: 1 isler_pr_me_botfca.pdf: 418245 bytes, checksum: 17cd225e9fb840990eb59cc92588bcb5 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / O Brasil é um grande produtor agrícola. Os dados do Levantamento Sistemático da Produção Agrícola (LSPA), divulgados pelo Instituto Brasileiro de Geografia e Estatística (IBGE), mostram uma previsão de 158,7 milhões de toneladas para a safra brasileira em 2011, um volume 6% maior que o recorde de 149,7 milhões de toneladas colhidas em 2010. Nos últimos anos a produção tem crescido e a área apta para plantio ainda não foi totalmente utilizada e estima-se que está sendo usada metade da área adequada para a agricultura. Esta grande produção se deve, em grande parte, ao clima do país, pois apesar das variações atuais de temperatura, o Brasil ainda possui um clima adequado para o cultivo de um grande número de espécies. Outro fator que tem sido relevante para o crescimento da agricultura é a evolução na forma de produção, pois a utilização de tecnologia de ponta e de novas variedades tem participação fundamental no desenvolvimento agrário. Mas, as grandes dimensões do país, a rapidez no desenvolvimento e as intensas modificações climáticas, têm trazido grandes problemas técnicos, econômicos e administrativos. Assim, os gestores deste setor têm buscado o auxílio de técnicas matemáticas e computacionais na obtenção de estimativas e nas tomadas de decisões. A modelagem matemática pode ser utilizada como ferramenta para auxiliar a melhoria na precisão e conseqüentemente na rentabilidade agrícola. Este trabalho propõe o uso de técnicas para modelagem matemática da temperatura diária, visando determinar equações matemáticas que descrevam as temperaturas diárias de um modo satisfatório, de tal forma que as curvas descritas pelas equações, auxiliem no cálculo de Graus Dia, que é uma importante medida na área de produção agrícola. Uma aplicação deste procedimento é feito para a cultura da cana de açúcar / Brazil is a large agricultural producer. The data in the Systematic Survey of Agricultural Production (LSPA), released by the Brazilian Institute of Geography and Statistics (IBGE), show a forecast of 158.7 million tonnes for the brazilian harvest in 2011, a volume 6% higher than the record of 149.7 million tons harvested in 2010. In recent years the production has grown and the area suitable for planting has not yet been fully used and it is estimated that is being used half the area suitable for agriculture. This large production is, in large part, to the climate of the country, because in spite of the variations of current temperature, Brazil still has a suitable climate for the cultivation of a large number of species. Another factor that has been important for the growth of agriculture is the evolution in the form of production, because the use of high technology and new varieties are also fundamental in agricultural development. But, the big dimensions of the country, the speed in the development and the intense climate changes, has brought a great many technical problems, economic and administrative. Thus, the managers of this sector has sought the aid of mathematical techniques and computational to obtain estimates and in making decisions. The mathematical modeling can be used as a tool to help the improvement in accuracy and consequently in agricultural profitability. This paper proposes the use of techniques for mathematical modeling of daily temperatures, in order to determine how mathematical equations to describe the daily temperatures in a satisfactory manner, so that the curves as described by the equations, help in the calculation of Degree-Day, which is a significant extent in the area of agricultural production. An application of this procedure is done for the culture of sugar cane

The dissertation concerning a given topic {\clqq}Customs, festivities and way of life in Bavaria`` focuses on one federal country in Germany and the process of its festivals and traditions. The work is divided into 3 parts, where there is gradually explained the wide range of traditions. In the introduction there are mentioned and described the particular terms used in the work. At the beginning the reader is informed about the typical local traditions in individual regions of Bavaria. The separation of this federal country gives the possibility to compare traditions and festivals. In the following parts there are chapters where the seasons of the year are defined. There are mentioned the festivals and traditions according to their occurrence in actual season of the year {--} the religion festivals, the agricultural traditions and other celebrations. In some examples there is briefly described the gastronomy of the festival. In the last part of the work there is compared some Bavor´s festivals to Czech ones. The choice is limited on the main religion festivals, which are held in both countries. There is mainly described the process and variety of Christmas and Easter celebrations. The all three parts of the work are completed with the enclosed maps and pictures. These enclosures can help the reader to make the complete conception of the mentioned traditions and festivals. The aim of this work is first of all the introduction of different celebrations in Bavaria and giving such kind of the formation that can push out the frontiers of culture knowledge.

This thesis examines the impacts of inclement weather days on AP exam scores in public schools, specifically low socioeconomic districts, and the assessment of their current closure procedures. By investigating the potential disruption in scores by inclement weather days, I can create a new dataset in analyzing a field that has yet to be studied through this lens, in addition to advising future policy for district superintendents and state government officials. The areas studied include Massachusetts and Georgia, representing states that are properly prepared for inclement weather closures and are under-prepared for inclement weather, respectively. I use two research methods to fully understand the quantitative and qualitative effects of inclement weather closures. The first is a quantitative analysis of district-level data on inclement weather days and AP exam scores over the past five years. To accomplish this, I contacted public-school districts in the two states involved in the case study to get raw data on school closures and combine this with already available datasets on AP exam score performance. The second is a qualitative account of inclement weather days from teachers and superintendents from districts across both states to establish their opinions regarding school closures and investigate the decision-making process in canceling school. In this qualitative assessment, I observe the roles that socioeconomic status and public transportation, among other factors, play in cancelations. This thesis seeks to challenge the argument proposed by previous research that snow days have no effect on test performance. Previously, this was measured by looking at state-wide exams. By using AP exams as a performance measure instead, a more direct impact on exam scores is expected due to the immovable testing dates and content- specific nature of the exams. Policy recommendations are given to accommodate the negative relationship between closures and test scores, given socioeconomic status.