Department of Mathematics
http://hdl.handle.net/10211.2/1914
Mathematics Master's Thesis Collection | Faculty Publications and ResearchSun, 19 May 2019 10:35:34 GMT2019-05-19T10:35:34ZUniqueness theorems in bioluminescence tomography
http://hdl.handle.net/10211.3/198368
Uniqueness theorems in bioluminescence tomography
Wang, Ge; Li, Yi; Jiang, Ming
Motivated by bioluminescent imaging needs for studies on gene therapy and other applications in the mouse models, a bioluminescence tomography (BLT) system is being developed in the University of Iowa. While the forward imaging model is described by the well-known diffusion equation, the inverse problem is to recover an internal bioluminescent source distribution subject to Cauchy data. Our primary goal in this paper is to establish the solution uniqueness for BLT under practical constraints despite the ill-posedness of the inverse problem in the general case. After a review on the inverse source literature, we demonstrate that in the general case the BLT solution is not unique by constructing the set of all the solutions to this inverse problem. Then, we show the uniqueness of the solution in the case of impulse sources. Finally, we present our main theorem that solid/hollow ball sources can be uniquely determined up to nonradiating sources. For better readability, the exact conditions for and rigorous proofs of the theorems are given in the Appendices. Further research directions are also discussed.
Thu, 01 Jan 2004 00:00:00 GMThttp://hdl.handle.net/10211.3/1983682004-01-01T00:00:00ZSwarming in viscous fluids: Three-dimensional patterns in swimmer- and force-induced flows
http://hdl.handle.net/10211.3/198321
Swarming in viscous fluids: Three-dimensional patterns in swimmer- and force-induced flows
Chuang, Yao-Li; Chou, Tom; D'Orsogna, Maria R.
We derive a three-dimensional theory of self-propelled particle swarming in a viscous fluid environment. Our model predicts emergent collective behavior that depends critically on fluid opacity, mechanism of self-propulsion, and type of particle-particle interaction. In “clear fluids” swimmers have full knowledge of their surroundings and can adjust their velocities with respect to the lab frame, while in “opaque fluids” they control their velocities only in relation to the local fluid flow. We also show that “social” interactions that affect only a particle's propensity to swim towards or away from neighbors induces a flow field that is qualitatively different from the long-ranged flow fields generated by direct “physical” interactions. The latter can be short-ranged but lead to much longer-ranged fluid-mediated hydrodynamic forces, effectively amplifying the range over which particles interact. These different fluid flows conspire to profoundly affect swarm morphology, kinetically stabilizing or destabilizing swarm configurations that would arise in the absence of fluid. Depending upon the overall interaction potential, the mechanism of swimming ( e.g., pushers or pullers), and the degree of fluid opaqueness, we discover a number of new collective three-dimensional patterns including flocks with prolate or oblate shapes, recirculating pelotonlike structures, and jetlike fluid flows that entrain particles mediating their escape from the center of mill-like structures. Our results reveal how the interplay among general physical elements influence fluid-mediated interactions and the self-organization, mobility, and stability of new three-dimensional swarms and suggest how they might be used to kinetically control their collective behavior.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10211.3/1983212016-01-01T00:00:00ZQuantitative Interpretation of a Genetic Model of Carcinogenesis Using Computer Simulations
http://hdl.handle.net/10211.3/177803
Quantitative Interpretation of a Genetic Model of Carcinogenesis Using Computer Simulations
Dai, Donghai; Beck, Brandon; Wang, Xiaofang; Howk, Cory; Li, Yi
The genetic model of tumorigenesis by Vogelstein et al. (V theory) and the molecular definition of cancer hallmarks by Hanahan and Weinberg (W theory) represent two of the most comprehensive and systemic understandings of cancer. Here, we develop a mathematical model that quantitatively interprets these seminal cancer theories, starting from a set of equations describing the short life cycle of an individual cell in uterine epithelium during tissue regeneration. The process of malignant transformation of an individual cell is followed and the tissue (or tumor) is described as a composite of individual cells in order to quantitatively account for intra-tumor heterogeneity. Our model describes normal tissue regeneration, malignant transformation, cancer incidence including dormant/transient tumors, and tumor evolution. Further, a novel mechanism for the initiation of metastasis resulting from substantial cell death is proposed. Finally, model simulations suggest two different mechanisms of metastatic inefficiency for aggressive and less aggressive cancer cells. Our work suggests that cellular de-differentiation is one major oncogenic pathway, a hypothesis based on a numerical description of a cell's differentiation status that can effectively and mathematically interpret some major concepts in V/W theories such as progressive transformation of normal cells, tumor evolution, and cancer hallmarks. Our model is a mathematical interpretation of cancer phenotypes that complements the well developed V/W theories based upon description of causal biological and molecular events. It is possible that further developments incorporating patient- and tissue-specific variables may build an even more comprehensive model to explain clinical observations and provide some novel insights for understanding cancer.
Sat, 01 Jan 2011 00:00:00 GMThttp://hdl.handle.net/10211.3/1778032011-01-01T00:00:00ZComputational Optical Biopsy
http://hdl.handle.net/10211.3/177802
Computational Optical Biopsy
Li, Yi; Jiang, Ming; Wang, Ge
Optical molecular imaging is based on fluorescence or bioluminescence, and hindered by photon scattering in the tissue, especially in patient studies. Here we propose a computational optical biopsy (COB) approach to localize and quantify a light source deep inside a subject. In contrast to existing optical biopsy techniques, our scheme is to collect optical signals directly from a region of interest along one or multiple biopsy paths in a subject, and then compute features of an underlying light source distribution. In this paper, we formulate this inverse problem in the framework of diffusion approximation, demonstrate the solution uniqueness properties in two representative configurations, and obtain analytic solutions for reconstruction of both optical properties and source parameters.
Sat, 01 Jan 2005 00:00:00 GMThttp://hdl.handle.net/10211.3/1778022005-01-01T00:00:00Z