The impact of tobacco control policies on university students' smoking in Ontario

Objective. Despite steady declines in the prevalence of tobacco use among Canadians, young adult tobacco use has remained stubbornly high over the past two decades (CTUMS, 2005a). Currently in Ontario, young adults have the highest proportion of smokers of all age cohorts at 26%. A growing body of evidence shows that smoking restrictions and other tobacco control policies can reduce tobacco use and consumption among adults and deter initiation among youth; whether young adult university students' smoking participation is influenced by community smoking restrictions, campus tobacco control policies or both remains an empirical question. The purpose of this study is to examine the relationship among current smoking status of students on university campuses across Ontario and various tobacco control policies, 3including clean air bylaws of students' home towns, clean air by-laws of the community where the university is situated, and campus policies. Methods. Two data sets were used. The 200512006 Tobacco Use in a Representative Sample of Post-Secondary Students data set provides information about the tobacco use of 10,600 students from 23 universities and colleges across Ontario. Data screening for this study reduced the sample to 5,114 17-to-24 year old undergraduate students from nine universities. The second data set is researcher-generated and includes information about strength and duration of, and students' exposure to home town, local and campus tobacco control policies. Municipal by-laws (of students' home towns and university towns) were categorized as weak, moderate or strong based on criteria set out in the Ontario Municipal By-law Report; campus policies were categorized in a roughly parallel fashion. Durations of municipal and campus policies were calculated; and length of students' exposure to the policies was estimated (all in months). Multinomial logistic regression analyses were used to examine the relationship between students' current smoking status (daily, less-than-daily, never-smokers) and the following policy measures: strength of, duration of, and students' exposure to campus policy; strength of, duration of, and students' exposure to the by-law in the university town; and, strength of, duration of, and students' exposure to the by-law in the home town they grew up in. Sociodemographic variables were controlled for. Results. Among the Ontario university students surveyed, 7.0% currently use tobacco daily and 15.4% use tobacco less-than-daily. The proportions of students experiencing strong tobacco control policies in their home town, the community in which their university is located and at their current university were 33.9%,64.1 %, and 31.3% respectively. However, 13.7% of students attended a university that had a weak campus policy. Multinomial logistic regressions suggested current smoking status was associated with university town by-law strength, home town by-law strength and the strength of the campus tobacco control policy. In the fmal model, after controlling for sociodemographic factors, a strong by-law in the university town and a strong by-law in students' home town were associated with reduced odds of being both a less-than-daily (OR = 0.64, 95%CI: 0.48-0.86; OR = 0.80, 95%CI: 0.66-0.95) and daily smoker (OR = 0.59, 95%CI: 0.39-0.89; OR = 0.76, 95%CI: 0.58-0.99), while a weak campus tobacco control policy was associated with higher odds of being a daily smoker (OR = 2.08, 95%CI: 1.31-3.30) (but unrelated to less-than-daily smoking). Longer exposure to the municipal by-law (OR = 0.93; 95%CI: 0.90-0.96) was also related to smoking status. Conclusions. Students' smoking prevalence was associated with the strength of the restrictions in university, and with campus-specific tobacco control policies. Lessthan- daily smoking was not as strongly associated with policy measures as daily smoking was. University campuses may wish to adopt more progressive campus policies and support clean air restrictions in the broader community. More research is needed to determine the direction of influence between tobacco control policies and students' smoking.

Decoding algorithms using side-effect machines

Bioinformatics applies computers to problems in molecular biology. Previous research has not addressed edit metric decoders. Decoders for quaternary edit metric codes are finding use in bioinformatics problems with applications to DNA. By using side effect machines we hope to be able to provide efficient decoding algorithms for this open problem. Two ideas for decoding algorithms are presented and examined. Both decoders use Side Effect Machines(SEMs) which are generalizations of finite state automata. Single Classifier Machines(SCMs) use a single side effect machine to classify all words within a code. Locking Side Effect Machines(LSEMs) use multiple side effect machines to create a tree structure of subclassification. The goal is to examine these techniques and provide new decoders for existing codes. Presented are ideas for best practices for the creation of these two types of new edit metric decoders.

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

Improving Short DNA Sequence Alignment with Parallel Computing

Variations in different types of genomes have been found to be responsible for a large degree of physical diversity such as appearance and susceptibility to disease. Identification of genomic variations is difficult and can be facilitated through computational analysis of DNA sequences. Newly available technologies are able to sequence billions of DNA base pairs relatively quickly. These sequences can be used to identify variations within their specific genome but must be mapped to a reference sequence first. In order to align these sequences to a reference sequence, we require mapping algorithms that make use of approximate string matching and string indexing methods. To date, few mapping algorithms have been tailored to handle the massive amounts of output generated by newly available sequencing technologies. In otrder to handle this large amount of data, we modified the popular mapping software BWA to run in parallel using OpenMPI. Parallel BWA matches the efficiency of multithreaded BWA functions while providing efficient parallelism for BWA functions that do not currently support multithreading. Parallel BWA shows significant wall time speedup in comparison to multithreaded BWA on high-performance computing clusters, and will thus facilitate the analysis of genome sequencing data.

Article - "Those darling young women in their flying machines", 1977

A retrospective article written by Dorothy Rungeling as she recalls the the International Air Races that often began or ended in Welland-Port Colborne Airport. The article was published in the Welland Evening Tribune, 9 September 1977.