An intelligent value-driven scheduling system for Space Station Freedom with special emphasis on the electric power system

The Electric Power Control System (EPCS) created by Decision-Science Applications, Inc. (DSA) for the Lewis Research Center is discussed. This system makes decisions on what to schedule and when to schedule it, including making choices among various options or ways of performing a task. The system is goal-directed and seeks to shape resource usage in an optimal manner using a value-driven approach. Discussed here are considerations governing what makes a good schedule, how to design a value function to find the best schedule, and how to design the algorithm that finds the schedule that maximizes this value function. Results are shown which demonstrate the usefulness of the techniques employed

Electric power scheduling: A distributed problem-solving approach

Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity. The value-driven free-market economic model is such a tool

Transcriptomic Analysis of Octanoic Acid Response in Drosophila sechellia Using RNA-Sequencing

The dietary specialist fruit fly Drosophila sechellia has evolved to specialize on the toxic fruit of its host plant Morinda citrifolia. Toxicity of Morinda fruit is primarily due to high levels of octanoic acid (OA). Using RNA interference (RNAi), prior work found that knockdown of Osiris family genes Osiris 6 (Osi6), Osi7, and Osi8 led to increased susceptibility to OA in adult D. melanogaster flies, likely representing genes underlying a Quantitative Trait Locus (QTL) for OA resistance in D. sechellia. While genes in this major effect locus are beginning to be revealed, prior work has shown at least five regions of the genome contribute to OA resistance. Here, we identify new candidate OA resistance genes by performing differential gene expression analysis using RNA-sequencing (RNA-seq) on control and OA-exposed D. sechellia flies. We found 104 significantly differentially expressed genes with annotated orthologs in D. melanogaster, including six Osiris gene family members, consistent with previous functional studies and gene expression analyses. Gene ontology (GO) term enrichment showed significant enrichment for cuticle development in upregulated genes and significant enrichment of immune and defense responses in downregulated genes, suggesting important aspects of the physiology of D. sechellia that may play a role in OA resistance. In addition, we identified five candidate OA resistance genes that potentially underlie QTL peaks outside of the major effect region, representing promising new candidate genes for future functional studies