Nonlinear control techniques for an atomic force microscope system

Two nonlinear control techniques are proposed for an atomic force microscope system.Initially,a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories.Specifically,the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics.An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters.Simulation results are provided to illustrate the efficacy and performance of the control strategies.     

Numerical investigation of the energy separation effect and flow mechanism inside convergent,straight, and divergent double‐sleeve RHVT

This study provides analysis of a cooled Ranque–Hilsch vortex tube (RHVT) with various specifications. It shows how cooling influences energy conversion inside the RHVT and improves performance of the device in separation of hot gas from the cold stream within the fluid by presenting the temperature detachment (the temperature diminution of cold air (ΔT_c = T_i ? T_c), isentropic efficiency (η_is), and coefficient of performance (COP) of divergent, convergent, and straight VTs. Two key parameters including hot tube length and number of nozzles for cooling and insulated cases are investigated to find out how the performance of the VT is affected by different geometry configurations under cooling conditions. These influences were researched for straight, convergent, and divergent VT separators under different flow characteristics. The optimum geometrical conditions for the cooling cases were identified. Results are indicative of positive influence of cooling for energy separation inside a VT. The quantities of ΔT_c, η_is, and COP for the cooled RHVT are greater than uncooled RHVT for various types of VTs. Cooling the VTs leads to an increase of 12.5% in ΔT_c, 14.4% in η_is, and 15.1% in COP when the base case was an uncooled VT.     

Lifetime-oriented multi-objective optimization of structural maintenance considering system reliability, redundancy and life-cycle cost using GA

The need to design and construct structural systems with adequate levels of reliability and redundancy is widely acknowledged. It is as crucial that these desired levels are maintained above target levels throughout the life of the structure. Optimization has served well in providing safer and more economical maintenance strategies. Lifetime maintenance optimization based on system reliability has already been proposed. It is still needed, however, to incorporate redundancy in the lifetime maintenance optimization process. Treating both system reliability and redundancy as criteria in the lifetime optimization process can be highly rewarding. The complexity of the process, however, requires the automation of solving the optimization problem. Genetic algorithms (GAs) are used in this study to obtain solutions to the multi-objective optimization problems considering system reliability, redundancy and life-cycle cost (LCC). An approach to provide the optimization program the ability to optimally select what maintenance actions are applied, when they are applied, and to which structural components they are applied is presented. Two different strategies are proposed. The first strategy has the ability to optimally select mixed maintenance types to apply to different parts of the structure at the same time. This strategy can be used in cases where any combination of different maintenance options can be practically applied to any part of the structure. The application of this strategy on truss structures is shown in a numerical example. The second strategy can be used when a limited number of possibilities of practical maintenance options are available. The application of this strategy to bridge structures is shown in a numerical example. The greatest advantage of the proposed approach (both strategies) is its ability to avoid the application of maintenance interventions to structural components that are not critical.     

A review of fatty acid profiles and antioxidant content in grass-fed and grain-fed beef

Growing consumer interest in grass-fed beef products has raised a number of questions with regard to the perceived differences in nutritional quality between grass-fed and grain-fed cattle. Research spanning three decades suggests that grass-based diets can significantly improve the fatty acid (FA) composition and antioxidant content of beef, albeit with variable impacts on overall palatability. Grass-based diets have been shown to enhance total conjugated linoleic acid (CLA) (C18:2) isomers, trans vaccenic acid (TVA) (C18:1 t11), a precursor to CLA, and omega-3 (n-3) FAs on a g/g fat basis. While the overall concentration of total SFAs is not different between feeding regimens, grass-finished beef tends toward a higher proportion of cholesterol neutral stearic FA (C18:0), and less cholesterol-elevating SFAs such as myristic (C14:0) and palmitic (C16:0) FAs. Several studies suggest that grass-based diets elevate precursors for Vitamin A and E, as well as cancer fighting antioxidants such as glutathione (GT) and superoxide dismutase (SOD) activity as compared to grain-fed contemporaries. Fat conscious consumers will also prefer the overall lower fat content of a grass-fed beef product. However, consumers should be aware that the differences in FA content will also give grass-fed beef a distinct grass flavor and unique cooking qualities that should be considered when making the transition from grain-fed beef. In addition, the fat from grass-finished beef may have a yellowish appearance from the elevated carotenoid content (precursor to Vitamin A). It is also noted that grain-fed beef consumers may achieve similar intakes of both n-3 and CLA through the consumption of higher fat grain-fed portions.     

Effects of a preventive cardiology curriculum on behavioral cardiovascular risk factors and knowledge of medical students

We evaluated a Preventive Cardiology Academic Award (PCAA) program designed to integrate preventive cardiology concepts into the medical school curriculum. Diet, preventive cardiology knowledge, preventive cardiology attitudes, exercise behavior, and body mass index were compared at entrance to medical school and during the graduation year. Complete data were available on 94 students (65 men and 29 women). Similar data from students who graduated in 1987, prior to the introduction of the PCAA curriculum, served as a control. Women showed a significant enhancement in attitude towards cardiovascular disease (CVD) prevention, while both men and women significantly increased their knowledge about CVD prevention. The frequency of planned physical activity decreased significantly in both sexes and men showed a significant increase in body mass index. Men significantly reduced total calories, percent of calories from fat and saturated fat and dietary cholesterol and increased fiber intake. In women, the only significant reduction was in total calories. In comparison to the control class that did not have the program, men receiving the PCAA curriculum reduced dietary cholesterol, dietary fat, saturated fat and monounsaturated fat. Changes in these dietary parameters were nonsignificant for women in comparison to the control class women. Additional analyses showed no systematic secular trends in dietary or other variables in classes entering from 1986 to 1990. We conclude that the PCAA curriculum changes have favorably affected the preventive cardiology knowledge, attitudes and diet of medical students.     

Pattern recognition of control charts using artificial neural networks—analyzing the effect of the training parameters

In this paper, we have utilized artificial neural networks (ANN) for pattern recognition of the most common patterns which occur in quality control charts. After detecting such patterns, it is possible to relate these patterns to their causes. This could find extreme importance for on-line quality monitoring and on-line trouble shooting. It could be possible to detect problems before they become serious and the operator has to shut the line down or the process may produce defective parts. In this work, we have attempted to explore the effect of the training parameters on the performance of the neural network. The training parameters are important because they emphasis the required performance and the accuracy required from the neural network. A resolution IV fractional factorial experiment is utilized to explore a portion of the range of selected parameters to obtain better performance of the neural network. The results showed that many parameters usually assigned by experience such as minimum shift, shift range, population size and shift percentage, have significant effect on the performance of the ANN, while others such as network size and window size do not have major significance on the performance of the net.     

Drugs in the physician's bag for emergency conditions

The list of drugs for the physician's bag depends on several factors, including practice location, conditions most likely to be found, costs and availability of drugs, organization of the emergency medicine in the region, shelf life and climatic vulnerability of certain drugs, population age, and size and design of the bag. Most of the drugs carried should be in an injectable form. However, the non-injectable drugs with relatively rapid systemic onset may be also included. Separation of drugs in the bag according to their usage may help in providing an organized treatment. For example, one could separate drugs for treatment of the following emergencies: cardiovascular, altered mental status, respiratory, gastrointestinal, bleeding, infections, and toxicological emergencies. The list of drugs needed for medical emergencies when physician makes house-calls is presented with short notes on their usage. Oncologic, toxicologic and pediatric emergencies are commented.     

A more efficient approach for investigation of effect of various HDD components on the shock tolerance

This paper emphasizes the importance of a fast and reliable tool for design parametric studies. Three methods that have been used in studying the shock phenomena in hard disk drives (HDD) are discussed briefly. A more efficient (i.e. faster and reasonably accurate) method is proposed. This new method uses state-space formulation to model the structural components of the HDD and quasi-static concept to model the non-linearity of the air bearing. The structural and the air bearing response, and their coupled interaction are evaluated simultaneously. The computation time and the accuracy of the proposed method are compared against two existing methods: the full finite element model and CML’s HDD dynamics event simulator. The proposed method is found to be much faster with reasonably good accuracy. Experimental shock tests also show that the method is reliable in predicting the shock tolerance of the HDD. A procedure on how to do parametric study with this method is proposed and the effect of overmold and voice coil stiffness on the shock tolerance is studied.     

Design and Implementation of the MorphoSys Reconfigurable Computing Processor

In this paper, we describe the implementation of MorphoSys, a reconfigurable processing system targeted at data-parallel and computation-intensive applications. The MorphoSys architecture consists of a reconfigurable component (an array of reconfigurable cells) combined with a RISC control processor and a high bandwidth memory interface. We briefly discuss the system-level model, array architecture, and control processor. Next, we present the detailed design implementation and the various aspects of physical layout of different sub-blocks of MorphoSys. The physical layout was constrained for 100 MHz operation, with low power consumption, and was implemented using 0.35 m, four metal layer CMOS (3.3 Volts) technology. We provide simulation results for the MorphoSys architecture (based on VHDL model) for some typical data-parallel applications (video compression and automatic target recognition). The results indicate that the MorphoSys system can achieve significantly better performance for most of these applications in comparison with other systems and processors.