THE INFLUENCE OF LENGTH CHANGE SPEED AND DIRECTION ON DYNAMIC FUNCTION POTENTIATION IN FAST MOUSE MUSCLE

The purpose of this study was to test the hypothesis that the potentiation of dynamic function was dependent upon both length change speed and direction. Mouse EDL was cycled in vitro (25º C) about optimal length (Lo) with constant peak strain (± 2.5% Lo) at 1.5, 3.3 and 6.9 Hz before and after a conditioning stimulus. A single pulse was applied during shortening or lengthening and peak dynamic (concentric or eccentric) forces were assessed at Lo. Stimulation increased peak concentric force at all frequencies (range: 19 ± 1 to 30 ± 2%) but this increase was proportional to shortening speed, as were the related changes to concentric work/power (range: -15 ± 1 to 39 ± 1 %). In contrast, stimulation did not increase eccentric force, work or power at any frequency. Thus, results reveal a unique hysteresis like effect for the potentiation of dynamic output wherein concentric and eccentric forces increase and decrease, respectively, with work cycle frequency.

An Interactive Theorem Prover for First-Order Dynamic Logic

Dynamic logic is an extension of modal logic originally intended for reasoning about computer programs. The method of proving correctness of properties of a computer program using the well-known Hoare Logic can be implemented by utilizing the robustness of dynamic logic. For a very broad range of languages and applications in program veri cation, a theorem prover named KIV (Karlsruhe Interactive Veri er) Theorem Prover has already been developed. But a high degree of automation and its complexity make it di cult to use it for educational purposes. My research work is motivated towards the design and implementation of a similar interactive theorem prover with educational use as its main design criteria. As the key purpose of this system is to serve as an educational tool, it is a self-explanatory system that explains every step of creating a derivation, i.e., proving a theorem. This deductive system is implemented in the platform-independent programming language Java. In addition, a very popular combination of a lexical analyzer generator, JFlex, and the parser generator BYacc/J for parsing formulas and programs has been used.

THE INFLUENCE OF LENGTH CHANGE SPEED AND DIRECTION ON DYNAMIC FUNCTION POTENTIATION IN FAST MOUSE MUSCLE

The purpose of this study was to test the hypothesis that the potentiation of dynamic function was dependent upon both length change speed and direction. Mouse EDL was cycled in vitro (250 C) about optimal length (Lo) with constant peak strain (± 2.5% Lo) at 1.5,3.3 and 6.9 Hz before and after a conditioning stimulus. A single pulse was applied during shortening or lengthening and peak dynamic (concentric or eccentric) forces were assessed at Lo. Stimulation increased peak concentric force at all frequencies (range: 19±1 to 30 ± 2%) but this increase was proportional to shortening speed, as were the related changes to concentric work/power (range: -15 ± 1 to 39 ± 1 %). In contrast, stimulation did not increase eccentric force, work or power at any frequency. Thus, results reveal a unique hysteresis like effect for the potentiation of dynamic output wherein concentric and eccentric forces increase and decrease, respectively, with work cycle frequency.

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.