Lefschetz Center for Dynamical Systems Seminar
Brown University Center for Statistical Sciences Seminar
Department of Biostatistics, Rollins School of Public Health | |
Sponsored by the Charles K. Colver Lectureship Fund |
Abstract: We explore variations in the observed spatial pattern of sea turtle nesting behavior at Juno Beach, Palm Beach County, Florida for the 1996-2000 nesting seasons. Of Particular interest is an assessment of possible effects due to a 990-foot fishing pier constructed in 1998-1999. The data include approximately 8,000-10,000 emergence locations per nesting season over 6 miles of beach with locations identified by global positioning system (GPS) units with sub-meter accuracy. Typical statistical analyses (Chi-square and Kruskal-Wallis tests) suggest some significant changes between years in counts of emergences for certain marked zones but do not readily identify where significant local differences occur along the beach.
We conduct a spatial analysis by estimating the density of emergences (number of emergences per unit length of beach) as a function of beach location, and compare densities of emergences between nesting seasons, densities of nesting and non-nesting emergences within each season, and densities between species (green and loggerhead) within each season. The approach reveals significant decreases in emergence density (nesting, non-nesting, and total) near the pier in the first post construction year (1999) in contrast to 1998 and 2000. The approach also reveals a possible distributional shift in nesting locations in the second year post construction even though total emergence counts are similar. Finally, the approach suggests an impact of the pier on nesting behavior, i.e. a reduced probability of nesting per emergence in the immediate vicinity of the pier.
Brown University
Joint Materials/Solid Mechanics Seminar Series
Center for Fluid Mechanics Seminar
Abstract: By utilizing small molecules, peptides, and proteins to modulate crystal nucleation and growth, living organisms produce 3D single crystals and crystal composites that provide materials solutions to their functional requirements. In doing so, they exhibit control over the location, phase and crystallographic orientation of the nuclei, as well as the morphology and kinetics of the growing crystals. From a materials science perspective the physical and chemical principles that underlie the processes of biomineralization provide a blueprint for biomimetic synthesis of solids. A common paradigm for interpreting the observed phenomenon of shape control asserts that the steriochemistry of growth modifiers is matched to that of a particular crystallographic plane that would not naturally be expressed during nucleation or growth in pure environments. Here we review the results of AFM-based investigations into the control of solution chemistry in a number of crystal-modifier systems in which we have performed in situ imaging of growth during the introduction of both inorganic and organic modifiers--including proteins-- into the solution. While the exact mechanism of growth modification is different in each system, the one common feature is that the important molecular-scale interaction that gives rise to growth modulation is between the impurity and a specific set of steps on the existing faces. At the same time, we show that modifications of surface chemistry either through micro-printing or dip-pen nanolithography can be used to control the location and orientation of crystal nucelei fromed from supersaturated solutions. These results show that, while control over nucleation may be understood within the paradigm of sterochemical recognition, to understand the controls on growth kinetics and morphology, a model that emphasizes the importance of step-specific interactions on existing faces is required.
Brown Applied Mathematics Pattern Theory and Vision Seminar
Abstract: In everyday learning and reasoning, people frequently draw successful generalizations from very limited evidence. Even a 4-year-old child can successfully infer the meanings of words or the existence of hidden causal relations from just one or a few relevant observations -- far outstripping the capabilities of conventional learning machines. How do they do it? I will argue that the success of people's everyday inductive leaps can be understood as the product of rational statistical inferences constrained by intuitive theories of the causal structure of the world. This talk will explore the interactions between people's causal theories and their everyday inductive leaps in several different task domains, such as generalizing biological properties, learning words, and inferring physical laws. I will illustrate how causal theories generate the hypothesis spaces necessary for Bayesian generalization, and (time permitting) how these theories may themselves be acquired as the products of higher-order statistical inferences.
Brown Analysis Seminar
Special Lefschetz Center for Dynamical Systems Seminar
Abstract: The skin of vertebrates forms many specialized structures such as hair, scales, feathers, glands, etc., which are distributed over the skin in a highly ordered fashion. The mechanisms involved in the formation and distribution of these appendages are far from being well understood. In 1992, by adopting a reaction-diffusion-chemotaxis mechanism, Cruywagen and Murray introduced a tissue interaction model for vertebrate skin pattern morphogenesis in which traveling wave solutions arise as a natural biological object. This lecture will discuss the problem of existence and uniqueness of traveling wave solutions for this model, along with the application of invariant manifold methods and techniques of geometric singular perturbation.
Scientific Computing Seminar
Brown University, Division of Applied Mathematics | |
Abstract: Many fluids of industrial or biological interest such as blood, paint...are non-Newtonian, which means that their flows cannot be described by the Navier-Stokes equations. In order to simulate such a flows, it is possible to use so-called mesoscopic models. Mathematically, these models can be written in two equivalent forms: either as stochastic differential equations or as deterministic Fokker-Planck (FP) equations. The talk will introduce numerical methods which have been designed to solve efficiently those equations. Numerical results will show the superiority of the deterministic approach (solving the FP equation) over the stochastic approach.
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