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Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
We develop the mathematical tools necessary to describe the interaction between a resonant pole and a threshold energy. Using these tools, we analyze the properties an opening threshold has on the resonant pole mass (the "cusp effect"), leading to an effect called "pole-dragging." We consider two models for resonances: a

We develop the mathematical tools necessary to describe the interaction between a resonant pole and a threshold energy. Using these tools, we analyze the properties an opening threshold has on the resonant pole mass (the "cusp effect"), leading to an effect called "pole-dragging." We consider two models for resonances: a molecular, mesonic model, and a color-nonsinglet diquark plus antidiquark model. Then, we compare the pole-dragging effect due to these models on the masses of the f0(980), the X(3872), and the Zb(10610) and compare the effect's magnitude. We find that, while for lower masses, such as the f 0 (980), the pole-dragging effect that arises from the molecular model is more significant, the diquark model's pole-dragging effect becomes dominant at higher masses such as those of the X(3872) and the Z b (10610). This indicates that for lower threshold energies, diquark models may have less significant effects on predicted resonant masses than mesonic models, but for higher threshold energies, it is necessary to include the pole-dragging effect due to a diquark threshold in high-precision QCD calculations.
ContributorsBlitz, Samuel Harris (Author) / Richard, Lebed (Thesis director) / Comfort, Joseph (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2015-05
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Description
Preliminary feasibility studies for two possible experiments with the GlueX detector, installed in Hall D of Jefferson Laboratory, are presented. First, a general study of the feasibility of detecting the ηC at the current hadronic rate is discussed, without regard for detector or reconstruction efficiency. Second, a study of the

Preliminary feasibility studies for two possible experiments with the GlueX detector, installed in Hall D of Jefferson Laboratory, are presented. First, a general study of the feasibility of detecting the ηC at the current hadronic rate is discussed, without regard for detector or reconstruction efficiency. Second, a study of the use of statistical methods in studying exotic meson candidates is outlined, describing methods and providing preliminary data on their efficacy.
ContributorsPrather, Benjamin Scott (Author) / Ritchie, Barry G. (Thesis director) / Dugger, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
Description
Since the acceptance of Einstein's special theory of relativity by the scientific community, authors of science fiction have used the concept of time dilation to permit seemingly impossible feats. Simple spacecraft acceleration schemes involving time dilation have been considered by scientists and fiction writers alike. Using an original Java program

Since the acceptance of Einstein's special theory of relativity by the scientific community, authors of science fiction have used the concept of time dilation to permit seemingly impossible feats. Simple spacecraft acceleration schemes involving time dilation have been considered by scientists and fiction writers alike. Using an original Java program based upon the differential equations for special relativistic kinematics, several scenarios for round trip excursions at relativistic speeds are calculated and compared, with particular attention to energy budget and relativistic time passage in all relevant frames.
ContributorsAlfson, Jonathan William (Author) / Jacob, Richard (Thesis director) / Covatto, Carl (Committee member) / Foy, Joseph (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
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Description
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the

Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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Description
In this paper, optimal control routines are applied to an existing problem of electron state transfer to determine if spin information can successfully be moved across a chain of donor atoms in silicon. The additional spin degrees of freedom are introduced into the formulation of the problem as well as

In this paper, optimal control routines are applied to an existing problem of electron state transfer to determine if spin information can successfully be moved across a chain of donor atoms in silicon. The additional spin degrees of freedom are introduced into the formulation of the problem as well as the control optimization algorithm. We find a timescale of transfer for spin quantum information across the chain fitting with a t > π/A and t > 2π/A transfer pulse time corresponding with rotation of states on the electron Bloch sphere where A is the electron-nuclear coupling constant. Introduction of a magnetic field weakens transfer
efficiencies at high field strengths and prohibits anti-aligned nuclear states from transferring. We also develop a rudimentary theoretical model based on simulated results and partially validate the characteristic transfer times for spin states. This model also establishes a framework for future work including the introduction of a magnetic field.
ContributorsMorgan, Eric Robert (Author) / Treacy, Michael (Thesis director) / Whaley, K. Birgitta (Committee member) / Greenman, Loren (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
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Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic

Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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Description
In this experiment an Electrodynamic Ion Ring Trap was constructed and tested. Due to the nature of Electrostatic fields, the setup required an oscillating voltage source to stably trap the particles. It was built in a safe manner, The power supply was kept in a project box to avoid incidental

In this experiment an Electrodynamic Ion Ring Trap was constructed and tested. Due to the nature of Electrostatic fields, the setup required an oscillating voltage source to stably trap the particles. It was built in a safe manner, The power supply was kept in a project box to avoid incidental contact, and was connected to a small copper wire in the shape of a ring. The maximum voltage that could be experienced via incidental contact was well within safe ranges a 0.3mA. Within minutes of its completion the trap was able to trap small Lycopodium powder spores mass of approximately 1.7*10^{-11}kg in clusters of 15-30 for long timescales. The oscillations of these spores were observed to be roughly 1.01mm at their maximum, and in an attempt to understand the dynamics of the Ion Trap, a concept called the pseudo-potential of the trap was used. This method proved fairly inaccurate, involving much estimation and using a static field estimation of 9.39*10^8 N\C and a charge estimate on the particles of ~1e, a maximum oscillation distance of 1.37m was calculated. Though the derived static field strength was not far off from the field strength required to achieve the correct oscillation distance (Percent error of 9.92%, the small discrepancy caused major calculation errors. The trap's intended purpose however was to eventually trap protein molecules for mapping via XFEL laser, and after its successful construction that goal is fairly achievable. The trap was also housed in a vacuum chamber so that it could be more effectively implemented with the XFEL.
ContributorsNicely, Ryan Joseph (Author) / Kirian, Richard (Thesis director) / Weiterstall, Uwe (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This is a report of a study that investigated the thinking of a high-achieving precalculus student when responding to tasks that required him to define linear formulas to relate covarying quantities. Two interviews were conducted for analysis. A team of us in the mathematics education department at Arizona State University

This is a report of a study that investigated the thinking of a high-achieving precalculus student when responding to tasks that required him to define linear formulas to relate covarying quantities. Two interviews were conducted for analysis. A team of us in the mathematics education department at Arizona State University initially identified mental actions that we conjectured were needed for constructing meaningful linear formulas. This guided the development of tasks for the sequence of clinical interviews with one high-performing precalculus student. Analysis of the interview data revealed that in instances when the subject engaged in meaning making that led to him imagining and identifying the relevant quantities and how they change together, he was able to give accurate definitions of variables and was usually able to define a formula to relate the two quantities of interest. However, we found that the student sometimes had difficulty imagining how the two quantities of interest were changing together. At other times he exhibited a weak understanding of the operation of subtraction and the idea of constant rate of change. He did not appear to conceptualize subtraction as a quantitative comparison. His inability to conceptualize a constant rate of change as a proportional relationship between the changes in two quantities also presented an obstacle in his developing a meaningful formula that relied on this understanding. The results further stress the need to develop a student's ability to engage in mental operations that involve covarying quantities and a more robust understanding of constant rate of change since these abilities and understanding are critical for student success in future courses in mathematics.
ContributorsKlinger, Tana Paige (Author) / Carlson, Marilyn (Thesis director) / Thompson, Pat (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique

Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05