Can low domain knowledge be compensated for when using the internet? /

Previous researchers have found that learners do not benefit fi-om using the Internet when domain knowledge is low. The purpose of the current study was to investigate possible methods to compensate for low domain knowledge. Specifically, the presence of notes, more time to search the Internet, and high levels of motivation to use the Internet were examined as possible compensating factors. Sixty Political Science and Kinesiology undergraduate students were randomly assigned to one of three conditions. Students searched the Internet for an hour prior to vmting an essay with notes present, searched the Internet for an hour prior to writing an essay without notes present, or did not search the Internet prior to completing an essay. Each participant completed the same two essays, one corresponding to a high knowledge domain and another corresponding to a low knowledge domain. First, the presence of notes did not significantly improve essay scores in comparison to the absence of notes. Second, learners did benefit fi-om using the Internet for 1 hour in comparison to their peers who were not exposed to the Internet, regardless of level of domain knowledge. Third, high levels of motivation did not affect essay performance. A discussion of why time may have compensated for low domain knowledge while notes and motivation did not is included. In addition, methods that may compensate for low domain knowledge when time is restricted are suggested.

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.

A29 NMR spin-lattice relaxation study of paramagnetics -doped orthosilictes

A ~si MAS NMR study of spin-lattice relaxation behaviour in paramagnetic-doped crystalline silicates was undertaken, using synthetic magnesium orthosilicate (forsterite) and synthetic zinc orthosilicate (willemite) doped with 0.1% to 20% of Co(II), Ni(II), or CU(II), as experimental systems. All of the samples studied exhibited a longitudinal magnetization return to the Boltzmann distribution of nuclear spin states which followed a stretched-exponential function of time: Y=exp [- (tjTn) n], O