3 resultados para lexical statistics

em Duke University


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Infants' speech perception abilities change through the first year of life, from broad sensitivity to a wide range of speech contrasts to becoming more finely attuned to their native language. What remains unclear, however, is how this perceptual change relates to brain responses to native language contrasts in terms of the functional specialization of the left and right hemispheres. Here, to elucidate the developmental changes in functional lateralization accompanying this perceptual change, we conducted two experiments on Japanese infants using Japanese lexical pitch-accent, which changes word meanings with the pitch pattern within words. In the first behavioral experiment, using visual habituation, we confirmed that infants at both 4 and 10 months have sensitivities to the lexical pitch-accent pattern change embedded in disyllabic words. In the second experiment, near-infrared spectroscopy was used to measure cortical hemodynamic responses in the left and right hemispheres to the same lexical pitch-accent pattern changes and their pure tone counterparts. We found that brain responses to the pitch change within words differed between 4- and 10-month-old infants in terms of functional lateralization: Left hemisphere dominance for the perception of the pitch change embedded in words was seen only in the 10-month-olds. These results suggest that the perceptual change in Japanese lexical pitch-accent may be related to a shift in functional lateralization from bilateral to left hemisphere dominance.

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Nolan and Temple Lang argue that “the ability to express statistical computations is an es- sential skill.” A key related capacity is the ability to conduct and present data analysis in a way that another person can understand and replicate. The copy-and-paste workflow that is an artifact of antiquated user-interface design makes reproducibility of statistical analysis more difficult, especially as data become increasingly complex and statistical methods become increasingly sophisticated. R Markdown is a new technology that makes creating fully-reproducible statistical analysis simple and painless. It provides a solution suitable not only for cutting edge research, but also for use in an introductory statistics course. We present experiential and statistical evidence that R Markdown can be used effectively in introductory statistics courses, and discuss its role in the rapidly-changing world of statistical computation.

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Slowly-compressed single crystals, bulk metallic glasses (BMGs), rocks, granular materials, and the earth all deform via intermittent slips or "quakes". We find that although these systems span 12 decades in length scale, they all show the same scaling behavior for their slip size distributions and other statistical properties. Remarkably, the size distributions follow the same power law multiplied with the same exponential cutoff. The cutoff grows with applied force for materials spanning length scales from nanometers to kilometers. The tuneability of the cutoff with stress reflects "tuned critical" behavior, rather than self-organized criticality (SOC), which would imply stress-independence. A simple mean field model for avalanches of slipping weak spots explains the agreement across scales. It predicts the observed slip-size distributions and the observed stress-dependent cutoff function. The results enable extrapolations from one scale to another, and from one force to another, across different materials and structures, from nanocrystals to earthquakes.