Matching Items (24)

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Modeling Dynamics of Methamphetamine Markets and Use: A Case Study of Arizona and California

Description

Substance abuse has become a major problem in the USA in the past decade, with immense public health and societal consequences. Methamphetamine (meth) use has grown due to an increased

Substance abuse has become a major problem in the USA in the past decade, with immense public health and societal consequences. Methamphetamine (meth) use has grown due to an increased number of meth production and distribution markets. Border states such as Arizona and California are especially concerned with Mexico’s production and distribution of meth to their residents. A mathematical model for meth use and markets was developed and then analyzed to track multiple types of drug markets and drug-related arrests for possession or distribution. The importance of social influences as a major causal factor in the onset of illicit drug use is explicitly incorporated. The model parameters are then estimated using meth-related data from California and Arizona. A parameter sensitivity analysis on the model output was carried out. The results suggest that law enforcement policy aimed at marketers will be significantly more effective than targeting current users. Moreover, local unorganized markets have a greater role in maintaining the endemic level of meth users. Whereas, global organized markets play a role in initiating meth use outbreaks. Some implications for interventions and health promotion for the two states are also discussed.

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Agent

Created

Date Created
  • 2019-05

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Diurnal Cycle Modeling of Nutrient Transport through the Intervertebral Disc to Prevent Future Degeneration after Transplantation

Description

The intervertebral disc goes through degenerative changes with age, which leads to disc thinning, bulging, or herniation. Spinal fusion treatments are ineffective as they cause quicker degeneration of adjacent discs

The intervertebral disc goes through degenerative changes with age, which leads to disc thinning, bulging, or herniation. Spinal fusion treatments are ineffective as they cause quicker degeneration of adjacent discs and fail in nearly 20% of cases, so researchers have turned to tissue-engineering biocompatible intervertebral discs for transplantation. However novel and effective as this may seem, these transplanted discs still show evidence of degeneration after just 5 years. I hypothesize that these discs are degenerating due to a blockage of the cartilaginous endplates post-transplantation that is hindering nutrient transport through the intervertebral disc. In order to test this hypothesis, I developed a mathematical model of nutrient transport through the intervertebral disc in one diurnal daily loading cycle. This model was used to simulate open endplates and blocked endplates and then compare differences in nutrient concentration and nutrient transport to the center of the disc. Results from the math model simulations were then compared to in vitro experimental data collected in lab to verify the findings on a physiological level. Results showed significant differences, both in vitro and in the model, between nutrient transport in open endplates vs blocked endplates, lending support to the original hypothesis. This study only presents preliminary results, but could hold the key to preventing future disc degeneration post-transplantation.

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Agent

Created

Date Created
  • 2015-05

Reproductive Cheating in Harvester Ants - An Agent Based Model

Description

Pogonomyrmex californicus (a species of harvester ant) colonies typically have anywhere from one to five queens. A queen can control the ratio of female to male offspring she produces, field

Pogonomyrmex californicus (a species of harvester ant) colonies typically have anywhere from one to five queens. A queen can control the ratio of female to male offspring she produces, field research indicating that this ratio is genetically hardwired and does not change over time relative to other queens. Further, a queen has an individual reproductive advantage if she has a small reproductive ratio. A colony, however, has a reproductive advantage if it has queens with large ratios, as these queens produce many female workers to further colony success. We have developed an agent-based model to analyze the "cheating" phenotype observed in field research, in which queens extend their lifespans by producing disproportionately many male offspring. The model generates phenotypes and simulates years of reproductive cycles. The results allow us to examine the surviving phenotypes and determine conditions under which a cheating phenotype has an evolutionary advantage. Conditions generating a bimodal steady state solution would indicate a cheating phenotype's ability to invade a cooperative population.

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Created

Date Created
  • 2017-05

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Modeling Surface Brightness of the HH 901 Jets in the Carina Nebula

Description

The purpose of this thesis is to accurately simulate the surface brightness in various spectral emission lines of the HH 901 jets in the Mystic Mountain Formation of the Carina

The purpose of this thesis is to accurately simulate the surface brightness in various spectral emission lines of the HH 901 jets in the Mystic Mountain Formation of the Carina Nebula. To accomplish this goal, we gathered relevant spectral emission line data for [Fe II] 12660 Å, Hα 6563 Å, and [S II] 6720 Å to compare with Hubble Space Telescope observations of the HH 901 jets presented in Reiter et al. (2016). We derived the emissivities for these lines from the spectral synthesis code Cloudy by Ferland et al. (2017). In addition, we used WENO simulations of density, temperature, and radiative cooling to model the jet. We found that the computed surface brightness values agreed with most of the observational surface brightness values. Thus, the 3D cylindrically symmetric simulations of surface brightness using the WENO code and Cloudy spectral emission models are accurate for jets like HH 901. After detailing these agreements, we discuss the next steps for the project, like adding an external ambient wind and performing the simulations in full 3D.

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Created

Date Created
  • 2020-05

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A Mathematical Model of Cell Confluency In Vitro

Description

Cellular and molecular biologists often perform cellular assays to obtain a better understanding of how cells work. However, in order to obtain a measurable response by the end of an

Cellular and molecular biologists often perform cellular assays to obtain a better understanding of how cells work. However, in order to obtain a measurable response by the end of an experiment, the cells must reach an ideal cell confluency. Prior to conducting the cellular assays, range-finding experiments need to be conducted to determine an initial plating density that will result in this ideal confluency, which can be costly. To help alleviate this common issue, a mathematical model was developed that describes the dynamics of the cell population used in these experiments. To develop the model, images of cells from different three-day experiments were analyzed in Photoshop®, giving a measure of cell count and confluency (the percentage of surface area covered by cells). The cell count data were then fitted into an exponential growth model and were correlated to the cell confluency to obtain a relationship between the two. The resulting mathematical model was then evaluated with data from an independent experiment. Overall, the exponential growth model provided a reasonable and robust prediction of the cell confluency, though improvements to the model can be made with a larger dataset. The approach used to develop this model can be adapted to generate similar models of different cell-lines, which will reduce the number of preliminary range-finding experiments. Reducing the number of these preliminary experiments can save valuable time and experimental resources needed to conduct studies using cellular assays.

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Agent

Created

Date Created
  • 2020-05

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Control of tissue homeostasis, regeneration, and degeneration by coupled bi-stable switches

Description

The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ

The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ are unable to enter the nucleus and bind with coactivators to express target genes. To understand YAP/TAZ dynamics and its role in tumorigenesis, tissue regeneration, and tissue degeneration, a regulatory network was modeled by ordinary differential equations. Using MATLAB, the deterministic behavior of the network was observed to determine YAP/TAZ activity in different states. Performing the bifurcation analysis of the system through Oscill8, three states were identified: tumorigenic/regenerative, degenerative, and homeostatic states. Further analysis through parameter modification allowed a better understanding of which proteins can be targeted for cancer and degenerative disease.

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Agent

Created

Date Created
  • 2020-05

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Stochastic parameterization of the proliferation-diffusion model of brain cancer in a Murine model

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

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.

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Agent

Created

Date Created
  • 2016-05

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Application of Optimal Control for Pharmacokinetics/Pharmacodynamics

Description

Pharmacokinetics describes the movement and processing of a drug in a body, while Pharmacodynamics describes the drug's effect on a given subject. Pharmacokinetic/Pharmacodynamic(Pk/Pd) models have become a fundamental tool when

Pharmacokinetics describes the movement and processing of a drug in a body, while Pharmacodynamics describes the drug's effect on a given subject. Pharmacokinetic/Pharmacodynamic(Pk/Pd) models have become a fundamental tool when predicting bacterial behavior and drug development. In November of 2009, Katsube et al. published their paper detailing their Pk/Pd model for the drug Doripenem and the bacteria P. aeruginosa. In their paper, they determined that there is a dependent relationship between the drug's effectiveness and the dosing strategy of the drug. Therefore, this thesis has applied optimal control in order to optimize the drug's effectiveness, while not burdening the subject with the side effects of the drug. Optimal Control is a mathematical tool used to balance two competing factors. As a result, it has become a useful tool used to make decisions involving complex behavior. By using Optimal Control, the model will maximize the drug's effect on the bacterial population of P. aeruginosa, while minimizing the drug concentration of Doripenem. In doing so, our research will enable doctors and clinicians to maximize a drug's effectiveness on the body, while minimizing side effects.

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Agent

Created

Date Created
  • 2018-05

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Modeling the Effect of Mechanical Deformation on Electrical Stimulation of Peripheral Nerve Fibers

Description

There are many challenges in designing neuroprostheses and one of them is to maintain proper axon selectivity in all situations. This project is based on an electrode that is implanted

There are many challenges in designing neuroprostheses and one of them is to maintain proper axon selectivity in all situations. This project is based on an electrode that is implanted into a fascicle in a peripheral nerve and used to provide tactile sensory feedback of a prosthetic arm. This fascicle can undergo mechanical deformation during every day motion. This work aims to characterize the effect of fascicle deformation on axon selectivity and recruitment when electrically stimulated using hybrid modeling. The main framework consists of combining finite element modeling (FEM) and simulation environment NEURON. A suite of programs was developed to first populate a fascicle with axons followed by deforming the fascicle and rearranging axons accordingly. A model of the fascicle with an implanted electrode is simulated to find the electrical potential profile through FEM. The potential profile is then used to compare which axons are activated in the two conformations of the fascicle using NERUON.

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Created

Date Created
  • 2021-05

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Exploring the consequences of permeate recycling in a photobioreactor using multi-component, community-level modelling

Description

While biodiesel production from photosynthesizing algae is a promising form of alternative energy, the process is water and nutrient intensive. I designed a mathematical model for a photobioreactor system that

While biodiesel production from photosynthesizing algae is a promising form of alternative energy, the process is water and nutrient intensive. I designed a mathematical model for a photobioreactor system that filters the reactor effluent and returns the permeate to the system so that unutilized nutrients are not wasted, addressing these problems. The model tracks soluble and biomass components that govern the rates of the processes within the photobioreactor (PBR). It considers light attenuation and inhibition, nutrient limitation, preference for ammonia consumption over nitrate, production of soluble microbial products (SMP) and extracellular polymeric substance (EPS), and competition with heterotrophic bacteria that predominately consume SMP. I model a continuous photobioreactor + microfiltration system under nine unique operation conditions - three dilution rates and three recycling rates. I also evaluate the health of a PBR under different dilution rates for two values of qpred. I evaluate the success of each run by calculating values such as biomass productivity and specific biomass yield. The model shows that for low dilution rates (D = <0.2 d-1) and high recycling rates (>66%), nutrient limitation can lead to a PBR crash. In balancing biomass productivity with water conservation, the most favorable runs were those in which the dilution rate and the recycling rate were highest. In a second part of my thesis, I developed a model that describes the interactions of phototrophs and their predators. The model also shows that dilution rates corresponding to realistic PBR operation can washout predators from the system, but the simulation outputs depend heavily on the accuracy of parameters that are not well defined.

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Agent

Created

Date Created
  • 2018-05