State Estimation of Glucose and Insulin Dynamics

Process simulation and state estimation have very important applications in chemical engineering as well as the biomedical field. Diabetes is a rapidly growing disease in the United States with 29 million people already diagnosed. The estimation of glucose and insulin concentration in patients is necessary in order to effectively treat diabetes. The Bergman Minimal Model is a popular process model that is used to simulate glucose and insulin dynamics. A simulation of this model was created based on estimated parameters for the model from historical data. This thesis investigated the estimation of glucose concentration, insulin concentration, and effect of active insulin using the extended Kalman filter, unscented Kalman filter, ensemble Kalman filter, and sequential Monte Carlo Particle filter. The performance of the filters was compared using root mean squared error. The filters were studied for the cases of good filter initialization, poor filter initialization, plant-model mismatch, increased measurement noise, and multiple glucose ingestions

Measuring and Modeling Bare Desert Wind Erosion From Steppe Grassland of Northern China as Affected By Soil Moisture and Climate

Soil erosion by wind has been found to be negatively related to soil water content, as evidenced by that for a given area, such a soil erosion can be much less in a wet than a dry year. However, few studies have examined the functional relationship between wind erosion and soil moisture, primarily due to lack of field measured data. The objectives of this study were to: 1) measure wind erosion in field using a portable wind tunnel devised and made by the author; 2) use the measured data to calibrate/validate a wind erosion model previously developed by the author; 3) model the potential effects of climate change via changes in moisture and wind speed. The study was conducted in the steppe grassland within the Balagaer river watershed located in north China. As part of a larger project funded by the National Science Foundation, this study focused on soil conditions with a minimal vegetation coverage to understand the functional relationship between wind erosion, soil moisture, and climate. These conditions are similar with those during winter and spring and/or when the grassland degrades and ultimately becomes a desert. Field samples were analyzed in a laboratory to determine the soil characteristics (e.g., moisture content, texture, hydraulic conductivity, and organic content)

State Estimation of Glucose and Insulin Dynamics

Process simulation and state estimation have very important applications in chemical engineering as well as the biomedical field. Diabetes is a rapidly growing disease in the United States with 29 million people already diagnosed. The estimation of glucose and insulin concentration in patients is necessary in order to effectively treat diabetes. The Bergman Minimal Model is a popular process model that is used to simulate glucose and insulin dynamics. A simulation of this model was created based on estimated parameters for the model from historical data. This thesis investigated the estimation of glucose concentration, insulin concentration, and effect of active insulin using the extended Kalman filter, unscented Kalman filter, ensemble Kalman filter, and sequential Monte Carlo Particle filter. The performance of the filters was compared using root mean squared error. The filters were studied for the cases of good filter initialization, poor filter initialization, plant-model mismatch, increased measurement noise, and multiple glucose ingestions

State Estimation of Glucose and Insulin Dynamics

Process simulation and state estimation have very important applications in chemical engineering as well as the biomedical field. Diabetes is a rapidly growing disease in the United States with 29 million people already diagnosed. The estimation of glucose and insulin concentration in patients is necessary in order to effectively treat diabetes. The Bergman Minimal Model is a popular process model that is used to simulate glucose and insulin dynamics. A simulation of this model was created based on estimated parameters for the model from historical data. This thesis investigated the estimation of glucose concentration, insulin concentration, and effect of active insulin using the extended Kalman filter, unscented Kalman filter, ensemble Kalman filter, and sequential Monte Carlo Particle filter. The performance of the filters was compared using root mean squared error. The filters were studied for the cases of good filter initialization, poor filter initialization, plant-model mismatch, increased measurement noise, and multiple glucose ingestions

Ranking the importance of nuclear reactions for activation and transmutation events

Pathways-reduced analysis is one of the techniques used by the Fispact-II nuclear activation and transmutation software to study the sensitivity of the computed inventories to uncertainties in reaction cross-sections. Although deciding which pathways are most important is very helpful in for example determining which nuclear data would benefit from further refinement, pathways-reduced analysis need not necessarily define the most critical reaction, since one reaction may contribute to several different pathways. This work examines three different techniques for ranking reactions in their order of importance in determining the final inventory, comparing the pathways based metric (PBM), the direct method and one based on the Pearson correlation coefficient. Reasons why the PBM is to be preferred are presented.Comment: 30 pages, 10 figure

Substituted phenylarsonic acids; structures and spectroscopy

Full NMR and ESI-MS spectra, and differential scanning calorimeter data are presented for 15 substituted phenylarsonic acids, including two new fluoro-substituted examples. X-ray crystal structure determinations of five examples (phenylarsonic acid and the 4-fluoro-, 4-fluoro-3-nitro-, 3-amino-4-hydroxy- and 3-amino-4-methoxy-substituted derivatives) were determined and the H-bonding crystal-packing patterns analysed

The Post-Cuno Litigation Landscape

In 1996, Northeastern University School of Law Professor Peter Enrich wrote a groundbreaking article, in which he argued that certain state tax incentives are unconstitutional as violations of the Commerce Clause. This article begins by describing the constitutional landscape into which Enrich cast his argument, and them turns describe the litigation that Enrich’s article has generated, including the much-watched case, Cuno v. DaimlerChrysler Corp., which held the promise of resolving this dormant Commerce Clause question, only to wither away on the vine of standing. Following the discussion of Cuno, this article will turn to an exploration of the litigation that proceeded in two state courts: Minnesota and North Carolina. The authors conclude by offering their perspective on the trends that appear from the state court litigation