We present a study, based on simulations with SERDYCA, a spatially-explicit individual-based model of rodent dynamics, on the relation between population persistence and the presence of numerous isolated disturbances in the habitat. We are specifically interested in the effect of disturbances that do not fragment the environment on population persistence. Our results suggest that the presence of disturbances in the absence of fragmentation can actually increase the average time to extinction of the modeled population. The presence of disturbances decreases population density but can increase the chance for mating in monogamous species and consequently, the ratio of juveniles in the population. It thus provides a better chance for the population to restore itself after a severe period with critically low population density. We call this the ''disturbance-forced localization effect''.

Waveguides were written in soda lime silicate glasses with a composition of xNa{sub 2}O xCaO (1-2x)SiO{sub 2}, where x = 15 and 20, using an amplified femtosecond laser. The waveguides formed around, not inside the exposed regions. This is similar to the waveguide behavior our group first observed in a phosphate glass, Schott IOG-1, and is distinctly different from fused silica in which the waveguides are inside the exposed regions. This data supports the rapid quenching theory, i.e. that the exposed regions cool rapidly, locking in a glass structure with a high fictive temperature, with the dependence of the refractive index on the glass cooling rate determining the qualitative behavior of the waveguides.

The increasing rate of growth in size of currently available datasets is a well known issue. The possibility of developing fast and easy to implement frameworks able to visualize at least part of a tera-sized volume is a challenging task. Subdivision methods in recent years have been one of the most successful techniques applied to the multiresolution representation and visualization of surface meshes. Extensions of these techniques to the volumetric case presents positive effects and major challenges mainly concerning the generalization of the combinatorial structure of the refinement procedure and the analysis of the smoothness of the limit mesh. In this paper we address mainly the first part of the problem, presenting a framework that exploits a subdivision scheme suitable for extension to 3D and higher dimensional meshes.

This paper illustrates the applicability of a sequential fluid mechanics, multi-zone chemical kinetics model to analyze HCCI experimental data for two combustion chamber geometries with different levels of turbulence: a low turbulence disc geometry (flat top piston), and a high turbulence square geometry (piston with a square bowl). The model uses a fluid mechanics code to determine temperature histories in the engine as a function of crank angle. These temperature histories are then fed into a chemical kinetic solver, which determines combustion characteristics for a relatively small number of zones (40). The model makes the assumption that there is no direct linking between turbulence and combustion. The results show that the multi-zone model yields good results for both the disc and the square geometries. The model makes good predictions of pressure traces and heat release rates. The experimental results indicate that the high turbulence square geometry has longer burn duration than the low turbulence disc geometry. This difference can be explained by the sequential multi-zone model, which indicates that the cylinder with the square bowl has a thicker boundary layer that results in a broader temperature distribution. This broader temperature distribution tends to lengthen the combustion, as cold mass within …

This paper examines the use of an in-core database in place of traditional data structures in two ASC codes. Results so far indicate a dramatic reduction in code, coupled with an increase in functionality. Performance impact has been around one percent for the majority of problems tested. Debugging has been the major roadblock thus far, and a portable browser tool has been written that will soon work with a variety of debuggers.

Monte Carlo methods for radiation transport typically attempt to solve an integral by directly sampling analog or weighted particles, which are treated as physical entities. Improvements to the methods involve better sampling, probability games or physical intuition about the problem. We show that significant improvements can be achieved by recasting the equations with an analytical transform to solve for new, non-physical entities or fields. This paper looks at one such transform, the difference formulation for thermal photon transport, showing a significant advantage for Monte Carlo solution of the equations for time dependent transport. Other related areas are discussed that may also realize significant benefits from similar analytical transformations.

Nonlinear simulations with the 3D electromagnetic two-fluid BOUT code are employed to study the dynamics of edge localized modes (ELMs) driven by intermediate wavelength peeling-ballooning modes. It is found that the early behavior of the modes is similar to expectations from linear, ideal peeling-ballooning mode theory, with the modes growing linearly at a fraction of the Alfven frequency. In the non-linear phase, the modes grow explosively, forming a number of extended filaments which propagate rapidly from the outer closed flux region into the open flux region toward the outer wall. Similarities to non-linear linear ballooning theory, as well as additional complexities are observed. Comparison to observations reveals a number of similarities. Implications of the simulations and proposals for the dynamics of the full ELM crash are discussed.

Object recognition algorithms are fundamental tools in automatic matching of geometric shapes within a background scene. Many approaches have been proposed in the past to solve the object recognition problem. Two of the key aspects that distinguish them in terms of their practical usability are: (i) the type of input model description and (ii) the comparison criteria used. In this paper we introduce a novel scheme for 3D object recognition based on line segment representation of the input shapes and comparison using the Hausdor distance. This choice of model representation provides the flexibility to apply the scheme in different application areas. We define several variants of the Hausdor distance to compare the models within the framework of well defined metric spaces. We present a matching algorithm that efficiently finds a pattern in a 3D scene. The algorithm approximates a minimization procedure of the Hausdor distance. The output error due to the approximation is guaranteed to be within a known constant bound. Practical results are presented for two classes of objects: (i) polyhedral shapes extracted from segmented range images and (ii) secondary structures of large molecules. In both cases the use of our approximate algorithm allows to match correctly the pattern …

The American Academy of Microbiology convened a colloquium June 4-6, 2004 to confer about the scientific promise of systems microbiology. Participants discussed the power of applying a systems approach to the study of biology and to microbiology in particular, specifics about current research efforts, technical bottlenecks, requirements for data acquisition and maintenance, educational needs, and communication issues surrounding the field. A number of recommendations were made for removing barriers to progress in systems microbiology and for improving opportunities in education and collaboration. Systems biology, as a concept, is not new, but the recent explosion of genomic sequences and related data has revived interest in the field. Systems microbiology, a subset of systems biology, represents a different approach to investigating biological systems. It attempts to examine the emergent properties of microorganisms that arise from the interplay of genes, proteins, other macromolecules, small molecules, organelles, and the environment. It is these interactions, often nonlinear, that lead to the emergent properties of biological systems that are generally not tractable by traditional approaches. As a complement to the long-standing trend toward reductionism, systems microbiology seeks to treat the organism or community as a whole, integrating fundamental biological knowledge with genomics, metabolomics, and other data …