Tactile sensation is a complex manifestation of mechanical stimuli applied to the skin. At the most fundamental level of the somatosensory system is the cutaneous mechanoreceptor, making it the logical starting point in the bottom-up approach to understanding the somatosensory system and sensation, in general. Unfortunately, a consensus has not been reached in terms of the afferent behavior of mechanoreceptors subjected to compressive stimulation. In this study, several afferent mechanoreceptors were isolated, mechanically stimulated with controlled compressive loads. Their responses were recorded and the sensitivities of the individual receptors to compressive stimulation were statistically evaluated by correlating the compressive state of the skin to the observed“all-or-nothing" responses. A host of linear techniques have been employed previously to describe this multiple-input, binary-output system; however, each of these techniques has associated shortcomings when employed in this context. In particular, two shortcomings are the assumption of linear system input-output and the inability of the model to assess individual input-output associations relative to concurrent input in a multivariate context with interacting input. Therefore, a non-linear regression technique called logistical regression was selected for characterizing the mechanoreceptor system. From this model, the relative contributions that each component of the stimulus has upon the neural response of the receptor can be quantitatively assessed and extrapolated to the greater population of cutaneous mechanoreceptors. Since this study represents a novel approach to receptor characterization, a framework for the application of logistical regression to the time-series representation of the multiple-input, binary-output mechanoreceptor system was established and validated. Subsequently, in-vitro experiments were performed in which the afferent behavior of tactile receptors in rat hairy skin were recorded and the relative association between a number of biologically meaningful stimulus metrics and the observed neural response was evaluated for each receptor. Through the application of logistical regression, it was determined that cutaneous mechanoreceptors are preferentially sensitive to the rate of change of compressive stress when force-control stimulated and both stress and its rate of change when position-control stimulated.

Between 1994 and 2003, two related concerns were in the educational spotlight. The first concern was participation rates of low income students in higher education. The second was the apparent disparity in Internet usage by low income and other disadvantaged individuals, highlighted in the report Falling Through The Net (United States Department of Commerce, 2000). The purpose of this study is to identify the economic factors and demographic attributes that influence participation of low income students in online distance learning courses offered by a Mississippi community college. This study centers on the hypothesis that there is no statistically significant difference between low income and non low income student participation rates in online distance education courses and that the economic factors, other than income, between low income participates and non low income participants will be statistically similar. Survey data collected from analyzed through the use of logistical regression to determine the relationship of demographic and economic factors to the decision to enroll in future online courses. It was found that students who are older and married are less likely to choose to enroll in future online distance learning courses. Students with higher numbers of courses completed and who paid for college with personal funds are more likely to enroll in future online distance learning courses than those with fewer numbers of distance learning hours completed and those who experience less difficulty traveling to campus are less likely to choose to enroll in future distance learning courses.