Missouri University of Science and Technology

About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Control theory & Artificial neural network. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.

Application of conducting polymers in corrosion protection

Abstract: The use of oxides, such as chromates, is highly effective in corrosion protection. Scientists are looking at alternative materials to replace environmentally hazardous materials, e.g., chromates. One of the group of materials identified as corrosion inhibiting are intrinsically conducting polymers. This paper focuses on the use of ICPs as a possible corrosion inhibitive substance. This paper also reviews literature on the research of different groups on the use of polyaniline and other conducting polymers as corrosion inhibitors. Intrinsically conducting polymers, especially poly-aniline, are being studied with great interest. Studies indicate that they have the potential of replacing some of the currently available materials.

Glass and Medicine

Abstract: For centuries, glass has been an important part of both the practical and the esthetic aspects of our culture. This paper documents three areas of glass research and development pioneered over the last 40 years that have greatly enhanced the quality of life (bioactive glasses and dental glass–ceramics) and the length of life (radioactive glass microspheres).

Comparison of pure nicotine- and smokeless tobacco extract-induced toxicities and oxidative stress.

Abstract: The toxicities and oxidative stress-inducing actions of (-)-nicotine and smokeless tobacco extract (STE), containing equivalent amounts of nicotine, were studied. Toxicities were determined by colony formation assays using Chinese hamster ovary (CHO) cells. Results indicated that nicotine is less toxic than smokeless tobacco extract that contained the same amount of nicotine. The generation of reactive oxygen species, following treatment with smokeless tobacco extract and nicotine, was assessed by measurement of changes in glutathione (GSH) and malondialdehyde (MDA) levels. CHO cells (5 x 10(5) cells/5 ml media) were incubated with 4, 0.8, and 0.08 mg of nicotine and STE containing the same amounts of nicotine. All preparations of smokeless tobacco extract significantly decreased GSH levels and increased MDA generation. However, 0.08 mg of nicotine treatment did not result in a significant change in GSH level, and only 4 mg of nicotine were sufficient to increase MDA generation. Addition of free radical scavenging enzymes, superoxide dismutase (SOD) and catalase (CAT), and an intracellular GSH precursor, N-acetyl-L-cysteine (NAC), replenished the GSH levels in nicotine-treated cells. GSH levels in cells exposed to smokeless tobacco extract containing 4 and 0.8 mg nicotine remained significantly lower than the control with the addition of SOD and CAT. However, co-addition of NAC with smokeless tobacco extract preparations returned the GSH levels to the control level. Lactate dehydrogenase (LDH) activities were measured in the media to establish the membrane damage following exposure to smokeless tobacco extract and nicotine. Treatment of cells with 4 mg nicotine caused a significant increase in LDH activity, which was returned to control level in the presence of the antioxidant enzymes and NAC. Smokeless tobacco extract did not change the LDH activity. http://link.springer-ny. com/link/service/journals/00244/bibs/37n4p434.html

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions

Abstract: Three-phase grid-connected converters are widely used in renewable and electric power system applications. Traditionally, grid-connected converters are controlled with standard decoupled d-q vector control mechanisms. However, recent studies indicate that such mechanisms show limitations in their applicability to dynamic systems. This paper investigates how to mitigate such restrictions using a neural network to control a grid-connected rectifier/inverter. The neural network implements a dynamic programming algorithm and is trained by using backpropagation through time. To enhance performance and stability under disturbance, additional strategies are adopted, including the use of integrals of error signals to the network inputs and the introduction of grid disturbance voltage to the outputs of a well-trained network. The performance of the neural-network controller is studied under typical vector control conditions and compared against conventional vector control methods, which demonstrates that the neural vector control strategy proposed in this paper is effective. Even in dynamic and power converter switching environments, the neural vector controller shows strong ability to trace rapidly changing reference commands, tolerate system disturbances, and satisfy control requirements for a faulted power system.

Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming

Abstract: This paper presents an event-triggered near optimal control of uncertain nonlinear discrete-time systems. Event-driven neurodynamic programming (NDP) is utilized to design the control policy. A neural network (NN)-based identifier, with event-based state and input vectors, is utilized to learn the system dynamics. An actor–critic framework is used to learn the cost function and the optimal control input. The NN weights of the identifier, the critic, and the actor NNs are tuned aperiodically once every triggered instant. An adaptive event-trigger condition to decide the trigger instants is derived. Thus, a suitable number of events are generated to ensure a desired accuracy of approximation. A near optimal performance is achieved without using value and/or policy iterations. A detailed analysis of nontrivial inter-event times with an explicit formula to show the reduction in computation is also derived. The Lyapunov technique is used in conjunction with the event-trigger condition to guarantee the ultimate boundedness of the closed-loop system. The simulation results are included to verify the performance of the controller. The net result is the development of event-driven NDP.