Side View

The view of the alumni greenhouse from the west side.

Aquatic Centre Walls

Construction of the concrete walls and pillars for the Aquatic Centre progress.

The effect of age on the structure and compostition of the cell walls of Choanephora cucurbitarum

The effect of age on the structure and composition of isolated and purified cell walls from cultures of Choanephora cucurbitarum was investigated by microchemical analyses, visible and infrared spectrophotometry, x-ray diffractometry and electron microscopy. Qualitative evaluation revealed the presence of lipids, proteins, neutral sugars, strong alkali soluble sugars, chitin, chitosan and uronic acids in the cell walls of both the 1 and 7 day old cultures. As the mycelium aged, there was a slight but statistically significant increase in the protein content, and a pronounced rise in the chitin and neutral sugar constituents of the cell walls. Conversely, the decrease in the chitosan content during this period had the net effect of altering the chitin: chitosan ratio from near unity in the younger cultures, to a 2:1 ratio in the 7 day old cell wall samples. Glutaraldehyde-osmium fixed thin sections of the 1 day old vegetative hyphae of £. curbitarum revealed the presence of a monolayered cell wall, which upon aging became bilayered. Replicas of acid hydrolysed cell walls demonstrated that both the 1 and 7 day old samples possessed an outer layer which was composed of finely granular amorphous material and randomly distributed microfibrils. The deposition of an inner secondary layer composed of parallel oriented microfibrils in the older hypha was correlated with an increase in the chitin content in the cell wall. The significance of these results with respect to the intimate relationship between composition and structure is discussed.

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.

Bio-inspired optimization & sampling technique for side-chain packing in MCCE

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.

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.

Photograph - Julia Cleveland Woodruff, Side angle Pose

Black and white photograph, mounted on board, 7 cm x 4 cm, of Julia in a side angle face pose. This photo was taken by Fred Pfaff of Peach Street, Erie, Pennsylvania.

Photograph - Margaret Julia Woodruff Band, Side Angle Lace Dress

Black and white photograph, 23 cm x 17 cm, of Margaret Julia Woodruff Band in a seated position, taken from a side angle. She is wearing a lace dress. The photo was taken by Dudley Hoyt of New York.

American Falls from Canadian side, Niagara, U.S.A.

The description reads "(12) American Falls from the Canadian side, Niagara, U.S.A."

Whirlpool and River View from Canadian side, Niagara

The description of the image reads "(18) Looking over the 'Whirlpool' and down the River - from Canadian side - Niagara, U.S.A."

Horseshoe Falls, Canada Side

The description of the image reads "29 Horseshoe Fall - Canada Side".