64 resultados para Mathematical and statistical techniques


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The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.

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This study investigates three important issues in kanji learning strategies; namely, strategy use, effectiveness of strategy and orthographic background. A questionnaire on kanji learning strategy use and perceived effectiveness was administered to 116 beginner level, undergraduate students of Japanese from alphabetic and character backgrounds in Australia. Both descriptive and statistical analyses of the questionnaire responses revealed that the strategies used most often are the most helpful. Repeated writing was reported as the most used strategy type although alphabetic background learners reported using repeated writing strategies significantly more often than character background learners. The importance of strategy training and explicit instruction of fundamental differences between character and alphabetic background learners of Japanese is discussed in relation to teaching strategies. [Author abstract]

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Arguably the most complex conical functions are seated in human cognition, the how and why of which have been debated for centuries by theologians, philosophers and scientists alike. In his best-selling book, An Astonishing Hypothesis: A Scientific Search for the Soul, Francis Crick refined the view that these qualities are determined solely by cortical cells and circuitry. Put simply, cognition is nothing more, or less, than a biological function. Accepting this to be the case, it should be possible to identify the mechanisms that subserve cognitive processing. Since the pioneering studies of Lorent de No and Hebb, and the more recent studies of Fuster, Miller and Goldman-Rakic, to mention but a few, much attention has been focused on the role of persistent neural activity in cognitive processes. Application of modern technologies and modelling techniques has led to new hypotheses about the mechanisms of persistent activity. Here I focus on how regional variations in the pyramidal cell phenotype may determine the complexity of cortical circuitry and, in turn, influence neural activity. Data obtained from thousands of individually injected pyramidal cells in sensory, motor, association and executive cortex reveal marked differences in the numbers of putative excitatory inputs received by these cells. Pyramidal cells in prefrontal cortex have, on average, up to 23 times more dendritic spines than those in the primary visual area. I propose that without these specializations in the structure of pyramidal cells, and the circuits they form, human cognitive processing would not have evolved to its present state. I also present data from both New World and Old World monkeys that show varying degrees of complexity in the pyramidal cell phenotype in their prefrontal cortices, suggesting that cortical circuitry and, thus, cognitive styles are evolving independently in different species.