Impact of Various Insurance Types on Level and Appropriateness of Health Care Consumption

The goal of this study was to examine the extent to which insurance type, or method of care management, impact the appropriate delivery of health care. Previous studies indicate a relationship between insurance type and patterns of consumption but do not directly link the incentives or disincentives inherent in each plan with trends inconsumption of health care. This study explores how different types of health insurance coverage affect the location, the degree, and the frequency of health care consumption in order to gain insight into which plans promote appropriate delivery and consumption ofcare.

THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS

The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the principles of neural science provide an instance of how biological processes may inspire novel methods in mathematical modeling and engineering. The application ofmathematical models towards understanding neural signals and systems represents a vibrant field of research that has spanned over half a century. During this period, multiple approaches to neuronal modeling have been adopted, and each approach is adept at elucidating a specific aspect of nervous system function. Thus while bio-physical models have strived to comprehend the dynamics of actual physical processes occurring within a nerve cell, the phenomenological approach has conceived models that relate the ionic properties of nerve cells to transitions in neural activity. Further-more, the field of neural networks has endeavored to explore how distributed parallel processing systems may become capable of storing memory. Through this project, we strive to explore how some of the insights gained from biophysical neuronal modeling may be incorporated within the field of neural net-works. We specifically study the capabilities of a simple neural model, the Resonate-and-Fire (RAF) neuron, whose derivation is inspired by biophysical neural modeling. While reflecting further biological plausibility, the RAF neuron is also analytically tractable, and thus may be implemented within neural networks. In the following thesis, we provide a brief overview of the different approaches that have been adopted towards comprehending the properties of nerve cells, along with the framework under which our specific neuron model relates to the field of neuronal modeling. Subsequently, we explore some of the time-dependent neurocomputational capabilities of the RAF neuron, and we utilize the model to classify logic gates, and solve the classic XOR problem. Finally we explore how the resonate-and-fire neuron may be implemented within neural networks, and how such a network could be adapted through the temporal backpropagation algorithm.

Health insurance coverage of Hispanic adults: An assessment of subgroup difference and the impact of immigration

This research explores the health insurance coverage of various Hispanic subgroups in comparison to non-Hispanic whites and blacks. The impact of immigration status is also considered as we hypothesize that nativity, duration, and naturalization tap a possible process of structural acculturation that increases access to insurance coverage for Hispanic groups. We find that the immigration variables impact the type of insurance reported. However, race/ethnic disparities continue to exist, with the various Hispanic subgroups more likely to report miscellaneous government health insurance or no health insurance coverage as compared to non-Hispanic whites.