The Stony Brook SYNCHEM system is a large knowledge-based domain-specific heuristic problem-solving program that is able to find valid synthesis routes for organic molecules of substantial interest and complexity without online guidance on the part of its user. In common with many such AI performance programs, SYNCHEM requires a substantial knowledge base to make it routinely useful, but as the designers of most of these programs have discovered, it is very difficult to engage domain experts to the long-term dedication and intensity of commitment necessary to create a production-quality knowledge base. Isolde and tristan are machine learning programs that use large computer-readable databases of specific reaction instances as a source of training examples for algorithms designed to extract the underlying reaction schemata via inductive and deductive generalization. Isolde learns principally by inductive generalization, while tristan makes use of a methodology that is primarily deductive, and which is usually described as explanation-based learning. Since the individual reaction entries in most computer-readable databases are often haphazardly sorted and classified, a taxonomy program called brangane has been written to partition the input databases into coherent reaction classes using the methodology of conceptual clustering.
During the past several years, a substantial body of experience has accumulated in the use of SYNCHEM, a large-scale program which is able to discover synthesis routes for relatively complex organic structures without on-line guidance on the part of its chemist user. These results indicate that the approach to computer-directed organic synthesis route discovery embodied in the program has been valid and reasonable, and that SYNCHEM is likely to be fruitful from the point of view of its intended users as well as for our research objectives in artificial intelligence. The experiments have revealed a number of insufficiencies in the program as well. Most of these are rectified in SYNCHEM2, a revised version of the program which includes, among other improvements, a more highly developed synthesis search algorithm and the routine consideration of stereochemistry.
A fundamental problem of cardiac electrophysiology is that of relating quantitatively the electrical activity within the heart to the complete timevarying potential distribution at the body surface. A new numerical method is described for the calculation of the surface potential on an irregularly shaped closed external surface due to an arbitrary source distribution in a medium containing regions of different conductivity, subject to the appropriate boundary conditions. The method is intended to provide an exact theoretical analysis of the experimental data acquired by A. M. Scher and others who have been mapping the pathways of ventricular depolarization in dogs and other animals. In anticipation of the above research program, a number of exploratory computations are reported. For example, the surface potential distribution has been calculated for a cylinder of human torso cross-section with a hemispherical dipole layer current source in approximate heart position and orientation and containing "lungs" of conductivity different from that of the surrounding medium. Under certain conditions, when lung-like inhomogeneities are introduced, a simple dipole source can generate a potential distribution having the multiple maxima and minima characteristic of higher multipole sources.
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