An expert system for ultrasonic flaw classification

This thesis describes the results of a research program which focused on the use of artificial intelligence techniques to solve a problem in the domain of nondestructive evaluation (NDE). The work was performed at the Center for Nondestructive Evaluation at Iowa State University under the supervision of Dr. Charles Wright, Department of Electrical Engineering and Computer Engineering, and Dr. Lester Schmerr, Department of Engineering Science and Mechanics

IDA: An Architecture for an Intelligent Design Assistant for Assessing the Inspectability of Structures from a Description of Their Geometry

A program in integrated design, NDE, and the manufacturing sciences at the Center for Nondestructive Evaluation is developing a system that assesses the inspectability and reliability of mechanical structures from a description of their geometry, materials, and performance requirements. Part of this effort involves using techniques of artificial intelligence (AI) to integrate the various components. An Intelligent Design Assistant (IDA) couples the design team to CAD, stress, inspectability and reliability models and provides expert advice on how to improve the performance and reliability of the manufactured part

Detection of flagellin by interaction with human recombinant TLR5 immobilized in liposomes

Digestive diseases caused by flagellated bacteria are a huge public health problem worldwide and rapid detection methods are needed for contaminated environments. In this study, we propose a method to detect patterns associated with pathogens based on the properties of the innate immune system. Specifically, we use Toll-like receptor 5 (TLR5), a transmembrane protein that specifically recognizes flagellin (the structural protein of bacterial flagella). TLR5, which was obtained by recombinant production in insect cells, was immobilized into liposomes to form TLR5-proteoliposomes. Through surface plasmon resonance (SPR) and competition flow cytometry assays, the sensitivity of proteoliposomes to recognize Escherichia coli and Salmonella typhimurium flagellin was evaluated. In addition, we compared the results obtained by immobilizing anti-flagellin antibodies into liposomes. The results of the flagellin-affinity tests, expressed as an SPR kinetic rate constant ratio in the equilibrium equation K = k /k , showed values of 13.8 × 10 and 7.73 × 10 M for the TLR5-proteoliposomes and anti-flagellin antibodies, respectively, against S. typhimurium. The anti-flagellin affinity results for E. coli showed K of 84.1 × 10 M for SPR assays and K of 3.5 × 10 M for competitive flow cytometry, which was used as a detection system without the immobilization of proteoliposomes. This research demonstrates the practical possibility of using proteoliposomes as recognition elements in the generation of systems for the rapid detection of flagellated bacteria, which could help avoid consumption of contaminated food by humans and thereby prevent intestinal infections