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.

A tour from the City of New-York, to Detroit, in the Michigan Territory, made between the 2d of May and the 22d of September, 1818 : the tour extends from New-York, by Albany, Schenectady, and Utica to Sacket's Harbor, and thence throught Lake Ontario, to St. Lawrence river, and down that stream to Hamilton village. Thence along both banks of the St. Lawrence, from Hamilton to the Thousand Islands; thence to Sacket's Harbor by water; from that place by the route of great Sodus, Geneva, Cananaigua and Batavia, to Buffalo; and from thence to Black Rock, Fort Erie, the Falls of Niagara, Queenston, Lewiston, and the memorable fields of Bridgewater and Chippewa after viewing the interesting place of Niagara, the author traversed the south shore of Lake Erie to the City of Detroit, and visited in the latter range, Dunkirk, Erie, Cleveland, Sandusky, and other places of less note. The tour is accompanied with a map upon which the route will be designated; a particular map of the Falls andRiver of Niagara, and the environs of the City of Detroit /

Errata slip inserted.

The Terroir of Winter Hardiness: Investigation of Winter Hardiness, Water Metrics, and Yield of Riesling and Cabernet Franc in the Niagara Region Using Geomatic Technologies

Grapevine winter hardiness is a key factor in vineyard success in many cool climate wine regions. Winter hardiness may be governed by a myriad of factors in addition to extreme weather conditions – e.g. soil factors (texture, chemical composition, moisture, drainage), vine water status, and yield– that are unique to each site. It was hypothesized that winter hardiness would be influenced by certain terroir factors , specifically that vines with low water status [more negative leaf water potential (leaf ψ)] would be more winter hardy than vines with high water status (more positive leaf ψ). Twelve different vineyard blocks (six each of Riesling and Cabernet franc) throughout the Niagara Region in Ontario, Canada were chosen. Data were collected during the growing season (soil moisture, leaf ψ), at harvest (yield components, berry composition), and during the winter (bud LT50, bud survival). Interpolation and mapping of the variables was completed using ArcGIS 10.1 (ESRI, Redlands, CA) and statistical analyses (Pearson’s correlation, principal component analysis, multilinear regression) were performed using XLSTAT. Clear spatial trends were observed in each vineyard for soil moisture, leaf ψ, yield components, berry composition, and LT50. Both leaf ψ and berry weight could predict the LT50 value, with strong positive correlations being observed between LT50 and leaf ψ values in eight of the 12 vineyard blocks. In addition, vineyards in different appellations showed many similarities (Niagara Lakeshore, Lincoln Lakeshore, Four Mile Creek, Beamsville Bench). These results suggest that there is a spatial component to winter injury, as with other aspects of terroir, in the Niagara region.

APPLICATION OF GEOMATICS TECHNOLOGIES TO CHARACTERIZE SPATIAL VARIABILITY AT STRATUS VINEYARDS

Vineyards vary over space and time, making geomatics technologies ideally suited to study terroir. This study applied geomatics technologies - GPS, remote sensing and GIS - to characterize the spatial variability at Stratus Vineyards in the Niagara Region. The concept of spatial terroir was used to visualize, monitor and analyze the spatial and temporal variability of variables that influence grape quality. Spatial interpolation and spatial autocorrelation were used to measure the pattern demonstrated by soil moisture, leaf water potential, vine vigour, soil composition and grape composition on two Cabernet Franc blocks and one Chardonnay block. All variables demonstrated some spatial variability within and between the vineyard block and over time. Soil moisture exhibited the most significant spatial clustering and was temporally stable. Geomatics technologies provided valuable spatial information related to the natural spatial variability at Stratus Vineyards and can be used to inform and influence vineyard management decisions.

Students’ Use and Perceptions of Social Networking Technologies: Connections to Reading, Reading Ability, and Self-Perception

Abstract This study was undertaken to examine traditional forms of literacy and the newest form of literacy: technology. Students who have trouble reading traditional forms of literacy tend to have lower self-esteem. This research intended to explore if students with reading difficulties and, therefore, lower self-esteem, could use Social Networking Technologies including text messaging, Facebook, email, blogging, MySpace, or Twitter to help improve their self-esteem, in a field where spelling mistakes and grammatical errors are commonplace, if not encouraged. A collective case study was undertaken based on surveys, individual interviews, and gathered documents from 3 students 9-13 years old. The data collected in this study were analyzed and interpreted using qualitative methods. These cases were individually examined for themes, which were then analyzed across the cases to examine points of convergence and divergence in the data. The research found that students with reading difficulties do not necessarily have poor self-esteem, as prior research has suggested (Carr, Borkowski, & Maxwell, 1991; Feiler, & Logan, 2007; Meece, Wigfield, & Eccles, 1990; Pintirch & DeGroot, 1990; Pintrich & Garcia, 1991). All of the participants who had reading difficulties, were found both through interviews and the CFSEI-3 self-esteem test (Battle, 2002) to have average self-esteem, although their parents all stated that their child felt poorly about their academic abilities. The research also found that using Social Networking Technologies helped improve the self-esteem of the majority of the participants both socially and academically.

How health organizations can apply scenario based planning and analytic technologies to make strategic consequential decisions in a time of uncertainty

The magnitude of the cervical cancer problem, coupled with the potential for prevention with recent technological advances, made it imperative to step back and reassess strategic options for dealing with cervical cancer screening in Kenya. The purpose of this qualitative study was: 1) to explore the extent to which the Participatory Action Research (PAR) methodology and the Scenario Based Planning (SBP) method, with the application of analytics, could enable strategic, consequential, informed decision making, and 2) to determine how influential Kenyan decision makers could apply SBP with analytic tools and techniques to make strategic, consequential decisions regarding the implementation of a Cervical Self Sampling Program (CSSP) in both urban and rural settings. The theoretical paradigm for this study was action research; it was experiential, practical, and action oriented, and resulted in co-created knowledge that influenced study participants’ decision making. Action Africa Help International (AAHI) and Brock University collaborated with Local Decision Influencing Participants (LDIP’s) to develop innovative strategies on how to implement the CSSP. SBP tools, along with traditional approaches to data collection and analysis, were applied to collect, visualize and analyze predominately qualitative data. Outputs from the study included: a) a generic implementation scenario for a CSSP (along with scenarios unique to urban and rural settings), and b) 10 strategic directions and 22 supporting implementation strategies that address the variables of: 1) technical viability, 2) political support, 3) affordability, 4) logistical feasibility, 5) social acceptability, and 6) transformation/sustainability. In addition, study participants’ capacity to effectively engage in predictive/prescriptive strategic decision making was strengthened.