Modeling and analysis of nonlinear biological systems

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on December 28, 2007)Thesis (Ph. D.) University of Missouri-Columbia 2007.[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] This dissertation focuses on the modeling and analysis of a set of biological phenomenon at a cellular (Part I) and systems (Part II) level. In Part I, the development and analysis of a biologically realistic single neuronal model that alone can mimic resonance filtering properties seen in the in behavioral data in a species of katydid is outlined. Additionally, a network level model of the BLA-NAc pathway was developed to investigate how dopamine and glutamate modulate the cue-primed relapse circuitry. In Part II, a systematic approach to determine correction factors on individual characteristics was developed to adjust the tolerance time predictions of an 'average' computational model of heat strain. Additionally, a new computational model of the human thermal system was developed that accounts for asymmetric environments and includes the arteriovenous anastomoses (AVAs) to provide finer prediction of toe and fingertip temperatures.Includes bibliographical reference

Development of a two-dimensional human thermal model for EVA applications

Dissertations, Academic -- University of Missouri--Columbia -- Mechanical and aerospace engineering.M. S. University of Missouri--Columbia 2002.Thesis advisor: Dr. Satish S. Nair.Title from PDF of title page (University of Missouri--Columbia, viewed on October 20, 2010).Includes bibliographical references.The human thermoregulatory system, with its active and passive components, is difficult to model due to nonlinearities, complex interactions, and a lack of understanding of many of the active thermoregulatory mechanisms. Part of this thesis focuses on the effect of passive system parametric uncertainties on two possible thermal comfort predictors. The effect due to each of the system parameters is quantified using a sensitivity analysis approach involving the equations of a human thermal model, the 41-node man model. A simulation based sensitivity analysis, using the Wissler 1-D model, is also performed to confirm the findings. Results show that both models display highest sensitivity to many of the same parameters. Another part of this thesis gives an overview for a 2-D human thermal model. The human thermal model incorporates 2-dimensional (radial and angular) heat transfer along with arterial and venous countercurrent blood flow. In addition, this thermal model attempts to model the human digits in order to predict toe and fingertip temperatures that are of special interest in regards to the possibility of controlling the thermal comfort of a subject