Simulating RF Field Propagation with Stochastic Ray Tracing

This work details the development of an application for fast simulations of the steady state far-field electromagnetic (EM) field strength and power in arbitrary environments. These environments consist of radiating antennas and solid 3-Dimensional (3D) occluding bodies. The simulation is accomplished using a variation of stochastic ray tracing that uses Monte Carlo integration to solve the light transport equation. The primary variations to the standard algorithm that are proposed here are twofold. First, a grid acceleration structure is used to reduce the number of computationally expensive ray-triangle intersection tests that need to be performed. The grid is chosen over other acceleration structures, as the requirement to compute field strength within a volume necessitates stepping the rays through the space regardless of whether the grid is used or not. The second variation is the implementation of diffraction. Existing ray tracers neglect diffraction as they typically deal with light of optical frequencies above 400 THz, where the amount of diffracted light around any large-scale object is negligible. As this application must handle much lower frequencies to simulate radio interactions, diffraction is implemented using a novel technique that involves extending the edges of triangles by constant width “diffraction margins” and allowing rays that hit the margins to bend inward probabilistically according to the Heisenberg momenta uncertainty associated with the new information about the position of the ray’s associated “photon bundle” due to its closeness to the surface.Master of Science in EngineeringComputer Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/156108/1/Timothy Kleinow Final Thesis.pdfDescription of Timothy Kleinow Final Thesis.pdf : Thesi

Evidence for roles of CYP1 and 3A family isozymes

Hole, MA 02543 (J.J.S.). Ketoconazole, clotrimazole and α -naphthoflavone all decreased the production of OH-MXC in liver microsomes, while α -naphthoflavone stimulated HPTE formation, suggesting CYP1 and CYP3 family isozymes demethylated methoxychlor. The results suggest that the formation of estrogenic metabolites from methoxychlor would be more rapid in catfish co-exposed to CYP1 inducers. DMD #9068 4 Introduction

Sex-specific mortality forecasting for UK countries: a coherent approach

This paper introduces a gender specific model for the joint mortality projection of three countries (England and Wales combined, Scotland, and Northern Ireland) of the United Kingdom. The model, called 2-tier Augmented Common Factor model, extends the classical Lee and Carter [26] and Li and Lee [32] models, with a common time factor for the whole UK population, a sex specific period factor for males and females, and a specific time factor for each country within each gender. As death counts in each subpopulation are modelled directly, a Poisson framework is used. Our results show that the 2-tier ACF model improves the in-sample fitting compared to the use of independent LC models for each subpopulation or of independent Li and Lee models for each couple of genders within each country. Mortality projections also show that the 2-tier ACF model produces coherent forecasts for the two genders within each country and different countries within each gender, thus avoiding the divergence issues arising when independent projections are used. The 2-tier ACF is further extended to include a cohort term to take into account the faster improvements of the UK ‘golden generation’

The Princeton Protein Orthology Database (P-POD): A Comparative Genomics Analysis Tool for Biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools