The battle over deficits : the struggle to maintain Canada's social welfare state : a thesis /

Abstract This thesis seeks to answer a number of questions concerning the deficit and debt in Canada. It focuses pri.arily on the federal level of government but with SOBe discussion of provincial governaent policy as well. In ~997, Canada's federal debt caae close ro six hundred billion dollars - $594 billion or 74.4 % of Gross Do.estic Product (GDP) to be exact. The purpose of this theses is threefold: To find out why Canada accu.ulated such a debt, to discover if there is a so-called debt crisis; and to discover if it is possible to preserve Canada's national welfare state given the financial restraints that have been adopted by both federal and provincial governments. Politicians are torn between economist' two contrasting views regarding deficits: Neo-Keynesian and neo-conservative. The neoKeynesian school focuses al1llOst exclusively on the short term stability of the economy and tends to dismiss concerns regarding the level of debt. Neo conservatives focus almost exclusively on the perceived costs of growth in the national debt and are willing to forego any stabilization benefits to ensure that the debt is controlled. These polar view do have one thing in coa.on; both confix-. that deficits influence govermaent policies. Both of these econoBic theories will have far-reaching influences on the federal gover1lJlJent's decision-making process. These economic theories will be discussed throughout this thesis.

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.