Arginine decarboxylase (ADC) is an important enzyme in the production of putrescine and polyamines in plants. It is encoded by a single or low-copy nuclear gene that lacks introns in sequences studied to date. The rate of Adc amino acid sequence evolution is similar to that of ndhF for the angiosperm family studied. Highly conserved regions provide several target sites for PCR priming and sequencing and aid in nucleotide and amino acid sequence alignment across a range of taxonomic levels, while a variable region provides an increased number of potentially informative characters relative to ndhF for the taxa surveyed. The utility of the Adc gene in plant molecular systematic studies is demonstrated by analysis of its partial nucleotide sequences obtained from 13 representatives of Brassicaceae and 3 outgroup taxa, 2 from the mustard oil clade (order Capparales) and 1 from the related order Malvales. Two copies of the Adc gene, Adc1 and Adc2, are found in all members of the Brassicaceae studied to data except the basal genus Aethionema. The resulting Adc gene tree provides robust phylogenetic data regarding relationships within the complex mustard family, as well as independent support for proposed tribal realignments based on other molecular data sets such as those from chloroplast DNA.

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The Georgia Tech Research Institute has developed an integrated suite of software for Visual and Electro-Optical (VISEO) detection analysis, under the sponsorship of the Arniy Aviation and Troop Command, Aviation Applied Technology Directorate (ATCOM/AATD). The VISEO system is a comprehensive workstation-based tool for multi-spectral signature analysis, LO design, and visualizatiOn of targets moving through real measured backgrounds. A key component of the VISEO system is a simulation of human vision, called the Georgia Tech Vision (OW) simulation. The algorithms used in the simulation are consistent with neurophysiological evidence concerning the functions of the human visual system, from dynamic light adaptation processes in the retinal receptors and ganglia to the processing of motion, color, and edge information in the striate cortex. The simulation accepts images seen by the naked eye or through direct-view optical (DVO) systems, as well as images viewed on the displays of IR sensors, image intensifiers and night-vision devices. GTV outputs predicted probabilities that the target is fixated (Pfix) during visual search, and detected (Pd), and also identifies specific features of the target that contribute most to successful search and detection performance. This paper outlines the capabilities and structure of the VISEO system, emphasizing GTV. Example results of visible and JR signature reduction on the basis of VISEO will be shown and described.