Palynology of late-glacial and postglacial sediments in Georgian Bay, Ontario, Canada, as related to the Great Lakes history /

This investigation comprises three parts: (1) the source, mechanism of transport, and distribution of pollen, spores and other palynomorphs in Georgian Bay bottom sediments and a comparison of these data with the contemporary vegetation, (2) the relative significance of fluvial transportation of pollen and spores, and (3) the late- and postglacial history of vegetational and climatic changes in the Georgicin Bay region. Modem pollen and spore assemblages in Georgian Bay do reflect the surrovinding vegetation when preservation and pollen production by the different species are considered and accounted for. Relative pollen percentage and concentration isopoll patterns indicate that rivers contribute large quantities of pollen and spores to Georgian Bay. This is further substantiated by large amounts of pollen and spores which were caught in traps in the Moon, Muskoka, and Nottawasaga Rivers which flow into Georgian Bay. The majority of pollen and spores caught in these traps were washed into the rivers by surface water runoff and so reflect the vegetation of the watershed in a regional sense. In a 12.9 metre long sediment core from northeastern Georgian Bay the relative percentage and absolute pollen concentrations allow correlation of Georgian Bay Lake phases with climatic and forest history. Four distinct pollen zones are distinguished: zone GB IV which is the oldest, reflects the succession from open spruce woodland to boreal forest; zone GB III represents a period of pine-mixed hardwoods forests from about 10,000 to 7,500 years ago. A pine-maplehemlock association dominated in zone GB II, although during the culmination of postglacial warming about 4,000 to 5,000 years ago the Georgian Bay forests had a more deciduous character. Zone GB I clearly shows European man's disturbance of the forest by logging activities.

Extracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /

Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.