A large number of CMV strains has been reported to circulate in the human population, and the biological significance of these strains is currently an active area of research. The analysis of complex genetic information may be limited using conventional phylogenetic techniques.We constructed artificial neural networks to determine their feasibility in predicting the outcome of congenital CMV disease (defined as presence of CMV symptoms at birth) based on two data sets: 54 sequences of CMV gene UL144 obtained from 54 amniotic fluids of women who contracted acute CMV infection during their pregnancy, and 80 sequences of 4 genes (US28, UL144, UL146 and UL147) obtained from urine, saliva or blood of 20 congenitally infected infants that displayed different outcomes at birth. When data from all four genes was used in the 20-infants’ set, the artificial neural network model accurately identified outcome in 90% of cases. While US28 and UL147 had low yield in predicting outcome, UL144 and UL146 predicted outcome in 80% and 85% respectively when used separately. The model identified specific nucleotide positions that were highly relevant to prediction of outcome. The artificial neural network classified genotypes in agreement with classic phylogenetic analysis. We suggest that artificial neural networks can accurately and efficiently analyze sequences obtained from larger cohorts to determine specific outcomes.\The ANN training and analysis code is commercially available from Optimal Neural Informatics (Pikesville, MD).

The statistics of polarization-induced visibility fading is studied for fiber-optic interferometric (Michelson or Mach-Zehnder) sensor arrays made of either regular singlemode fibers or polarization-maintaining fibers. Performance is measured in terms of the probability to observe visibilities, all of which exceed a given value, for all members of the array. Very poor performance is obtained for arrays made of nonpolarization maintaining fibers, unless the input state of polarization is dynamically controlled to optimize the visibility of the worst sensor of the array. While the use of the more costly polarization-maintaining fibers could, in principle, solve this polarization-related fading problem, finite extinction ratios of couplers and splices make the performance of such arrays comparable to that of nonpolarization maintaining arrays with optimally controlled input-polarization.

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The Sensics HMD is a panoramic, wearable display based on OLED microdisplays. Using a tiled design, it simultaneously provides both wide field‐of‐view and high resolution. The display has found application around the world, especially in design/prototyping applications and research into human performance. This paper describes the design and operation of the HMD and some of the applications of the HMD to date.

A simple and novel real-time interframe operator substantially reduces short-lived noisy scintillations in low-lightlevel video imaging systems that use image intensifiers.