Modeling and Analysis of Multiple Engine Aircraft Configurations for Fault Tolerant Control

A formal framework is presented that allows for the analysis of the potential for using engine thrust control for aircraft actuator failure accommodation. Three sets of parameters have been identified as critical: number of engines and their position, engine thrust and throttle dynamics, and type and severity of the actuator failure. A mathematical model was developed that allows for the determination of the values of some of the parameters when the others are imposed such as determining the thrust control authority when the engine locations and Euler angles are known. Additionally, the engine locations can be determined when the thrust control authority and engine Euler angles are known and the engine Euler angles can be determined when the engine locations and thrust control authority are known. A MATLAB/Simulink simulation environment was built around a model of a large transport that can accommodate up to ten engines at different locations. A fuzzy logic controller was designed and employed for failure accommodation. The fuzzy logic controller utilizes the pilot lateral, longitudinal, and directional commands as well as the aircraft\u27s pitch attitude, roll attitude, yaw attitude and respective angular rates as the inputs to the system and provides throttle commands for each engine based on its location with respect to the aircraft\u27s center of mass. Failures of varying severity on the rudder, left or right aileron, and left or right elevator were implemented. The controller was capable of accommodating an extremely severe aileron failure and moderately severe rudder failure without additional pilot input. The controller was capable of mitigating some of the pilot command required for a moderate elevator failure. The simulation environment was used to verify the analytical results and to demonstrate the fault tolerant capabilities of multiple engine configurations. It proved to be a flexible and efficient tool for analysis and control system development

Multiple genetic loci influence vaccine-induced protection against Mycobacterium tuberculosis in genetically diverse mice.

Mycobacterium tuberculosis (M.tb.) infection leads to over 1.5 million deaths annually, despite widespread vaccination with BCG at birth. Causes for the ongoing tuberculosis endemic are complex and include the failure of BCG to protect many against progressive pulmonary disease. Host genetics is one of the known factors implicated in susceptibility to primary tuberculosis, but less is known about the role that host genetics plays in controlling host responses to vaccination against M.tb. Here, we addressed this gap by utilizing Diversity Outbred (DO) mice as a small animal model to query genetic drivers of vaccine-induced protection against M.tb. DO mice are a highly genetically and phenotypically diverse outbred population that is well suited for fine genetic mapping. Similar to outcomes in people, our previous studies demonstrated that DO mice have a wide range of disease outcomes following BCG vaccination and M.tb. challenge. In the current study, we used a large population of BCG-vaccinated/M.tb.-challenged mice to perform quantitative trait loci mapping of complex infection traits; these included lung and spleen M.tb. burdens, as well as lung cytokines measured at necropsy. We found sixteen chromosomal loci associated with complex infection traits and cytokine production. QTL associated with bacterial burdens included a region encoding major histocompatibility antigens that are known to affect susceptibility to tuberculosis, supporting validity of the approach. Most of the other QTL represent novel associations with immune responses to M.tb. and novel pathways of cytokine regulation. Most importantly, we discovered that protection induced by BCG is a multigenic trait, in which genetic loci harboring functionally-distinct candidate genes influence different aspects of immune responses that are crucial collectively for successful protection. These data provide exciting new avenues to explore and exploit in developing new vaccines against M.tb

STRmix™ collaborative exercise on DNA mixture interpretation

An intra and inter-laboratory study using the probabilistic genotyping (PG) software STRmix™ is reported. Two complex mixtures from the PROVEDIt set, analysed on an Applied Biosystems™ 3500 Series Genetic Analyzer, were selected. 174 participants responded. For Sample 1 (low template, in the order of 200 rfu for major contributors) five participants described the comparison as inconclusive with respect to the POI or excluded him. Where LRs were assigned, the point estimates ranging from 2 × 10 <sup>4</sup> to 8 × 10 <sup>6</sup> . For Sample 2 (in the order of 2000 rfu for major contributors), LRs ranged from 2 × 10 <sup>28</sup> to 2 × 10 <sup>29</sup> . Where LRs were calculated, the differences between participants can be attributed to (from largest to smallest impact): This study demonstrates a high level of repeatability and reproducibility among the participants. For those results that differed from the mode, the differences in LR were almost always minor or conservative