Multiple sets of chemotaxis genes including three cheA homologs were identified in the genome sequence of the anaerobic bacterium Desulfovibrio vulgaris Hildenborough. Each CheA is a histidine kinase (HK) and part of a two component signal transduction system. Knock out mutants in the three cheA genes were created using single cross-over homologous recombination insertion. We studied the phenotypes of the cheA mutants in detail and discovered that ?cheA-3 has a non swarming/swimming phenotype both in the soft agar plates and Palleroni chamber assays. CheA-3 shows similarity to the Shewanella oneidensis CheA-3 and the Vibrio cholerae CheA-2 that are responsible for chemotaxis in the respective organisms. We did not find any morphological or structural differences between the three Delta cheA mutants and the wild type cells in electron microscopy. Our results from these studies are presented.

This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.