Matching Items (3)
Filtering by

Clear all filters

155984-Thumbnail Image.png
Description
Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced

Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). I demonstrate that the inverse problem of parameter estimation might be too complicated and simply relying on data fitting can give incorrect conclusions, since there is a large error in parameter values estimated and parameters might be unidentifiable. I provide confidence intervals to give estimate forecasts using data assimilation via an ensemble Kalman Filter. Using the ensemble Kalman Filter, I perform dual estimation of parameters and state variables to test the prediction accuracy of the models. Finally, I present a novel model with time delay and a delay-dependent parameter. I provide a geometric stability result to study the behavior of this model and show that the inclusion of time delay may improve the accuracy of predictions. Also, I demonstrate with clinical data that the inclusion of the delay-dependent parameter facilitates the identification and estimation of parameters.
ContributorsBaez, Javier (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2017
135817-Thumbnail Image.png
Description
In 2010, two gamma-ray /x-ray bubbles were detected in the center of the Milky Way Galaxy. These bubbles extend symmetrically ≈ 30, 000 light years above and below the Galactic Center, with a width of ≈ 27, 000 light years. These bubbles emit gamma-rays at energies between 1 and 100

In 2010, two gamma-ray /x-ray bubbles were detected in the center of the Milky Way Galaxy. These bubbles extend symmetrically ≈ 30, 000 light years above and below the Galactic Center, with a width of ≈ 27, 000 light years. These bubbles emit gamma-rays at energies between 1 and 100 giga-electronvolts, have approximately uniform surface brightness, and are expanding at ≈ 30, 000 km/s. We believe that these Fermi Bubbles are the result of an astrophysical jet pulse that occurred millions of years ago. Utilizing high-performance computing and Euler’s Gas Dynamics Equations, we hope to find a realistic simulation that will tell us more about the age of these Fermi Bubbles and better understand the mechanism that powers the bubbles.
ContributorsWagner, Benjamin Leng (Author) / Gardner, Carl (Thesis director) / Jones, Jeremiah (Committee member) / Computing and Informatics Program (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
136412-Thumbnail Image.png
Description
This project discusses simulation results of star formation by Active Galactic Nuclei (AGN) jets using the WENO method. A typical AGN jet with velocity uj=0.3c, density ρj=10^(-2) H/cm3, and temperature Tj=10^(7) K was injected into a 425 light years square region. The jet passes through a stationary inhomogeneous ambient background

This project discusses simulation results of star formation by Active Galactic Nuclei (AGN) jets using the WENO method. A typical AGN jet with velocity uj=0.3c, density ρj=10^(-2) H/cm3, and temperature Tj=10^(7) K was injected into a 425 light years square region. The jet passes through a stationary inhomogeneous ambient background of temperature Ta=5x10^4 K and density ρa= 2 H/cm^3 to test if AGN jets, by creating bow shocks propagating through the interstellar medium and molecular clouds, can form stars in the densest regions. According to the star formation criteria for gravitational collapse of Cen and Ostriker, the resulting simulations indicate the presence of star formation via AGN jets (1992). The parameters are tuned to match Centaurs A to identify star formation in this galaxy. The simulations will also be run in three dimensions in the future and for longer time intervals to gain a better understanding of the star formation process via AGN jets.
ContributorsFindley, Christina Marie (Author) / Gardner, Carl (Thesis director) / Scannapieco, Evan (Committee member) / Barrett, The Honors College (Contributor) / School of Earth and Space Exploration (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05