Melvin K. Simmons

Hybrid simulation of cellular behavior

MOTIVATION To be valuable to biological or biomedical research, in silico methods must be scaled to complex pathways and large numbers of interacting molecular species. The correct method for performing such simulations, discrete event simulation by Monte Carlo generation, is computationally costly for large complex systems. Approximation of molecular behavior by continuous models fails to capture stochastic behavior that is essential to many biological phenomena. RESULTS We present a novel approach to building hybrid simulations in which some processes are simulated discretely, while other processes are handled in a continuous simulation by differential equations. This approach preserves the stochastic behavior of cellular pathways, yet enables scaling to large populations of molecules. We present an algorithm for synchronizing data in a hybrid simulation and discuss the trade-offs in such simulation. We have implemented the hybrid simulation algorithm and have validated it by simulating the statistical behavior of the well-known lambda phage switch. Hybrid simulation provides a new method for exploring the sources and nature of stochastic behavior in cells.

Expert systems for mechanical design: Examples of symbolic representations of design geometries

A major issue in the development of computer-integrated manufacturing systems is the creation and maintenance of a suitable data base that will serveall the various functions in the design through manufacturing sequence. These functions include the designer interface, graphics output, evaluation of manufacturability, functional evaluation (including possibly finite element analyses), process design, process planning, process control, and quality control. Since design is the beginning of this design manufacturing spectrum, it is incumbent on the design process to produce the required data structure that will allow input and access by the other functions. A key element in such a multipurpose data base is the method by which the design geometry is represented, and an essential ingredient of this representation is information about the geometricfeatures of the design that are relevant to the various parts of the sequence. We are exploring “design with features” as a design method to obtain the needed feature information and experimenting with different data structures for symbolic representation of the resulting designs. In this paper, we describe three examples of different types of features for use as design primitives and four data structures (in LISP) that result from their use. The domains of the examples are extrusion, injection molding, and casting.

DOMINIC: A DOMAIN-INDEPENDENT PROGRAM FOR MECHANICAL ENGINEERING DESIGN.

Abstract We describe an Artificial Intelligence (AI) program for mechanical engineering design. The program, called Dominic, characterizes design as best-first search through a space of possible designs. Dominic is a general architecture for a class of mechanical engineering design problems; within its redesign framework, in which a design is iteratively modified and improved, one can design a variety of mechanical devices. Dominics performance on two design problems is evaluated, and a battery of experiments with Dominic is discussed.

Computer environments for the design of mechanical assemblies: A research review

This paper reviews the most relevant literature dealing with the development of computer environments for the conceptual design of mechanical systems and assemblies. Selected literature is reviewed and discussed in relation to meeting the following requirements of such an environment: (1) representing and supporting top-down design, (2) representing and supporting multiple functional viewpoints, (3) representing functional knowledge, (4) representing spatial relationships and geometry, (5) maintaining consistency, and (6) providing analysis and other support. An appendix listing related readings is included.

Dominic I: Progress toward domain independence in design by iterative redesign

This paper describes the first working version of a program called Dominic that performs design by iterative redesign in a domain-independent manner. The paper describes in detail the programs strategy, which stresses the concept of redesign dependencies to guide its redesign process. Dominic has been successfully tested in four different domains. Its performance on two of these (v-belt drive design and design of extruded heat sinks) is presented here. The redesign class of design problems on which Dominic works is that large class of problems that are intellectually manageable and solvable without subdivision into smaller parts. This includes the various subproblems ultimately created when large complex problems are decomposed for solution. Dominic is a hill-climbing algorithm, similar in this respect to standard optimization methods. However, its problem formulation or input language is more flexible for some design applications than optimization techniques. Work is continuing on a Dominic II in an effort to overcome some of the limitations of Dominic.

A Computational Positron Emission Tomography Simulation Model for Imaging β-Amyloid in Mice

PurposeWe aimed to develop a computational simulation model for β-amyloid (Aβ) positron emission tomography (PET) imaging.ProceduresModel parameters were set to reproduce levels of Aβ within the PDAPP mouse. Pharmacokinetic curves of virtual tracers were computed and a PET detector simulator was configured for a commercially available preclinical PET-imaging system.ResultsWe modeled the effects of Aβ therapy and tracer affinity on the ability to differentiate Aβ levels by PET. Varying affinity had a significant effect on the ability to quantitate Aβ. Further, PET tracers for Aβ monomers were more sensitive to the therapeutic reduction in Aβ levels than total brain amyloid. Following therapy, the decrease in total brain Aβ corresponded to the slow rate of change in total amyloid load as expected.ConclusionsWe have developed a first proof-of-concept Aβ-PET simulation model that will be a useful tool in the interpretation of preclinical Aβ imaging data and tracer development.