Apollo experience report: Guidance and control systems: Automated control system for unmanned mission AS-201

The Apollo command module heat shield and Apollo command and service module/Saturn launch vehicle structural integrity were evaluated in an unmanned test flight. An automated control system was developed to provide the mission event sequencing, the real-time ground control interface, and the backup attitude reference system for the unmanned flight. The required mission events, the design logic, the redundancy concept, and the ground-support-equipment concept are described and some development problem areas are discussed. The mission event time line and the real-time ground command list are included to provide an outline of the control system capabilities and requirements. The mission was accomplished with the automated control system, which functioned without flight anomalies

Assembling networks of microbial genomes using linear programming

<p>Abstract</p> <p>Background</p> <p>Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem.</p> <p>Results</p> <p>We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values) as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising <it>Aquifex aeolicus </it>and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus <it>Pseudomonas</it>.</p> <p>Conclusions</p> <p>The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.</p