Robert R. Snapp

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Robert Costanza⁎, Brendan Fisher, Saleem Ali, Caroline Beer, Lynne Bond, Roelof Boumans, Nicholas L. Danigelis, Jennifer Dickinson, Carolyn Elliott, Joshua Farley, Diane Elliott Gayer, Linda MacDonald Glenn, Thomas Hudspeth, Dennis Mahoney, Laurence McCahill, Barbara McIntosh, Brian Reed, S. Abu Turab Rizvi, Donna M. Rizzo, Thomas Simpatico, Robert Snapp(More)
Robert Costanza, Brendan Fisher, Saleem Ali, Caroline Beer, Lynne Bond, Roelof Boumans, Nicholas L. Danigelis, Jennifer Dickinson, Carolyn Elliott, Joshua Farley, Diane Elliott Gayer, Linda MacDonald Glenn, Thomas R. Hudspeth, Dennis F. Mahoney, Laurence McCahill, Barbara McIntosh, Brian Reed, Abu Turab Rizvi, Donna M. Rizzo, Thomas Simpatico and Robert(More)
Studies in cultured cells have shown that nuclear shape is an important factor influencing nuclear function, and that mechanical forces applied to the cell can directly affect nuclear shape. In a previous study, we demonstrated that stretching of whole mouse subcutaneous tissue causes dynamic cytoskeletal remodeling with perinuclear redistribution of(More)
A fast algorithm, Accelerated Kernel Feature Analysis (AKFA), that discovers salient features evidenced in a sample of n unclassified patterns, is presented. Like earlier kernel-based feature selection algorithms, AKFA implicitly embeds each pattern into a Hilbert space, H, induced by a Mercer kernel. An \ell-dimensional linear subspace of H is iteratively(More)
We study how certain smoothness constraints, for example, piecewise continuity, can be generalized from a discrete set of analog-valued data, by modifying the error backpropagation, learning algorithm. Numerical simulations demonstrate that by imposing two heuristic objectives (1) reducing the number of hidden units, and (2) minimizing the magnitudes of the(More)
Abstruct-The finite sample performance of a nearest neighbor classifier is analyzed for a two-class pattern recognition problem. An exact integral expression is derived for the m-sample risk R, given that a reference m-sample of labeled points is available to the classifier. The statistical setup assumes that the pattern classes arise in nature with fixed a(More)
We have developed a new method for classifying 3D reconstructions with missing data obtained by electron microscopy techniques. The method is based on principal component analysis (PCA) combined with expectation maximization. The missing data, together with the principal components, are treated as hidden variables that are estimated by maximizing a(More)
In this paper, we describe AQSim, an ongoing effort to design and impl ement a system to manage terabytes of scientific simulation data. The goal of this project is to reduce data storage requirements and access times while permitting ad-hoc queries using statistical and mathematical models of the data. In order to facilitate data exchange between models(More)
Ecosystem services are the effects on human well-being of the flow of benefits from ecosystems to people over given extents of space and time. The Service Path Attribution Network (SPAN) model provides a spatial framework for determining the topology and strength of these flows and identifies the human and ecological features which give rise to them. As an(More)
As simulation is gaining popularity as inexpensive means of experimentation in diverse fields of industry and government, the attention to the data generated by scientific simulation is also increasing. Scientific simulation generates mesh data, i.e., data configured in a grid structure, in a sequence of time steps. Its model is complex – understanding it(More)