Digital Commons Network^™

Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang

Electronic Theses and Dissertations

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large …

Modeling Vascular Diffusion Of Oxygen In Breast Cancer, Tina Giorgadze

Senior Projects Spring 2023

Oxygen is a vital nutrient necessary for tumor cells to survive and proliferate. Oxygen is diffused from our blood vessels into the tissue, where it is consumed by our cells. This process can be modeled by partial differential equations with sinks and sources. This project focuses on adding an oxygen diffusion module to an existing 3D agent-based model of breast cancer developed in Dr. Norton’s lab. The mathematical diffusion module added to an existing agent-based model (ABM) includes deriving the 1-dimensional and multi-dimensional diffusion equations, implementing 2D and 3D oxygen diffusion models into the ABM, and numerically evaluating those equations …

Mathematical Modeling Suggests Cooperation Of Plant-Infecting Viruses, Joshua Miller, Vitaly V. Ganusov, Tessa Burch-Smith

Chancellor’s Honors Program Projects

No abstract provided.

Developing Prediction Models For Kidney Stone Disease, Joseph Palko

Honors Theses

Kidney stone disease has become more prevalent through the years, leading to high treatment cost and associated health risks. In this study, we explore a large medical database and machine learning methods to extract features and construct models for diagnosing kidney stone disease.

Data of 46,250 patients and 58,976 hospital admissions were extracted and analyzed, including patients’ demographic information, diagnoses, vital signs, and laboratory measurements of the blood and urine. We compared the kidney stone (KDS) patients to patients with abdominal and back pain (ABP), patients diagnosed with nephritis, nephrosis, renal sclerosis, chronic kidney disease, or acute and unspecified renal …

The Effect Of Initial Conditions On The Weather Research And Forecasting Model, Aaron D. Baker

Electronic Theses and Dissertations

Modeling our atmosphere and determining forecasts using numerical methods has been a challenge since the early 20th Century. Most models use a complex dynamical system of equations that prove difficult to solve by hand as they are chaotic by nature. When computer systems became more widely adopted and available, approximating the solution of these equations, numerically, became easier as computational power increased. This advancement in computing has caused numerous weather models to be created and implemented across the world. However a challenge of approximating these solutions accurately still exists as each model have varying set of equations and variables to …

Analytic Solutions For Diffusion On Path Graphs And Its Application To The Modeling Of The Evolution Of Electrically Indiscernible Conformational States Of Lysenin, K. Summer Ware

Boise State University Theses and Dissertations

Memory is traditionally thought of as a biological function of the brain. In recent years, however, researchers have found that some stimuli-responsive molecules exhibit memory-like behavior manifested as history-dependent hysteresis in response to external excitations. One example is lysenin, a pore-forming toxin found naturally in the coelomic fluid of the common earthworm Eisenia fetida. When reconstituted into a bilayer lipid membrane, this unassuming toxin undergoes conformational changes in response to applied voltages. However, lysenin is able to "remember" past history by adjusting its conformational state based not only on the amplitude of the stimulus but also on its previous …

Laser Beam Propagation Over Long Distances In Turbulent Media, Justyna O. Sotiris

Mathematics & Statistics ETDs

The propagation of lasers through different media is a broad topic of study and falls under the larger topic of wave propagation. The focus of this thesis is the development and analysis of a numerical computational model of laser beam propagation through a turbulent atmosphere over a long distance. When a beam propagates through a turbulent atmosphere over a distance exceeding several kilometers it is a strong fluctuation propagation. There exist fewer robust methods to demonstrate how strong fluctuations affect the beam. Beam propagation can be described by the Linear Schr\"{o}dinger Equation (LSE). The fluctuations in the refractive index are …

From Branches To Fibers - Investigating F-Actin Networks With Biochemistry And Mathematical Modeling, Melissa A. Riddle

Senior Honors Projects, 2020-current

F-actin networks have different structures throughout the cell depending on their location or mechanical role. For example, at the leading edge of a migrating cell, F-actin is organized in a region called the lamellipodia as a branched network responsible for pushing the membrane outwards. Behind the lamellipodia is a lamellar actin network where focal adhesions and stress fibers originate, and then within the cell cortex, actin is arranged in a gel-like network. Stress fibers are an important organization of F-actin and how they arise from either the branched lamellipodia network or the gel-like cortex network is poorly understood. Our approach …

Predicting How People Vote From How They Tweet, Rao B. Vinnakota

Senior Projects Spring 2019

In 2016 Donald Trump stunned the nation and not a single pollster predicted the outcome. For the last few decades, pollsters have relied on phone banking as their main source of information. There is reason to believe that this method does not present the complete picture it once did due to several factors--less landline usage, a younger and more active electorate, and the rise of social media. Social media specifically has grown in prominence and become a forum for political debate. This project quantitatively analyzes political twitter data and leverages machine learning techniques such as Naive-Bayes to model election results. …

The Application Of Contemporary Numerical Methods To The Modeling, Analysis, And Uncertainty Quantification Of Glacier Dynamics, Jacob Zachary Downs

Graduate Student Theses, Dissertations, & Professional Papers

Warming temperatures have led to accelerating ice loss from the Greenland ice sheet, contributing to global sea level rise. Understanding the stability of the Greenland ice sheet to further warming is crucial to estimating rates of sea level rise over the next century. Estimating sea level rise is complicated by uncertainties in the physical mechanisms governing ice motion as well as uncertainties in the broader Arctic climate system of which the ice sheet is an integral part. In chapter 2, we focus on how surface melt water input to the ice sheet bed influences the rate of basal sliding, which …

Investigation Of Pattern Formation In Marine Environments Through Mathematical Modeling And Analysis Of Remotely Sensed Data, Sofya Zaytseva

Dissertations, Theses, and Masters Projects

Pattern formation in ecological systems refers to a nonuniform distribution of animal and plant species across a landscape. Pattern formation can be observed in many aquatic and terrestrial systems and can provide important insights into their dynamics and ability to cope with environmental changes. In this dissertation, we focus on pattern formation in tidal marshes and oyster reefs, two important habitats that provide a number of essential ecosystem services. Both of these systems have also experienced dramatic losses, prompting much research to investigate their dynamics as and viable restoration and management strategies. The first part of this dissertation focuses on …

The Mathematics Of Cancer: Fitting The Gompertz Equation To Tumor Growth, Dyjuan Tatro

Senior Projects Spring 2018

Mathematical models are finding increased use in biology, and partuculary in the field of cancer research. In relation to cancer, systems of differential equations have been proven to model tumor growth for many types of cancer while taking into account one or many features of tumor growth. One feature of tumor growth that models must take into account is that tumors do not grow exponentially. One model that embodies this feature is the Gomperts Model of Cell Growth. By fitting this model to long-term breast cancer study data, this project ascertains gompertzian parameters that can be used to predicts tumor …

Dynamics And Clustering In Locust Hopper Bands, Jialun Zhang

HMC Senior Theses

In recent years, technological advances in animal tracking have renewed interests in collective animal behavior, and in particular, locust swarms. These swarms pose a major threat to agriculture in northern Africa, the Middle East, and other regions. In their early life stages, locusts move in hopper bands, which are huge aggregations traveling on the ground. Our main goal is to understand the underlying mechanisms for the emergence and organization of these bands. We construct an agent-based model that tracks individual locusts and a continuum model that tracks the evolution of locust density. Both these models are motivated by experimental observations …

Black Holes Modeled As Fluid Droplets On Membranes, Anthony Bardessono

Physics

No abstract provided.

Nonlinear Dynamics Of Filaments In Free Space And Fluids, Victoria Kelley

Senior Honors Projects, 2010-2019

The purpose of this paper is to study a straight rod, held at both ends, with a known twist and tension or compression. We study the stability of this steady state when the system is dominated either by inertia or drag. In order to do this, we first replicate the work of Goriely and Tabor to look at the case with inertia, without drag. After conducting the analysis for that case, we then apply their framework to perform a linear stability analysis of a model that is without inertia, but with hydrodynamic drag. Our motivation is the study of locomotion …

Mathematical Models For Infectious Disease Transmission With Stochastic Simulation Of Measles Outbreaks, Valerie Welty

Honors College Theses

As they are the leading cause of death among children and adolescents worldwide, it is of extreme importance to control the spread of infectious diseases. Information gained from mathematical modeling of these events often proves quite useful in establishing policy decisions to accomplish this goal. Human behavior, however, is quite difficult to recreate when using equations with pre-determined results, such as deterministic differential equations often used with epidemic models. Because of this, the focus of the research was to create a simulation of an outbreak, specifically of measles, by using an imaginary population experiencing simulated stochastic events on a discrete …

Mathematical Modeling And Optimal Control Of Alternative Pest Management For Alfalfa Agroecosystems, Cara Sulyok

Mathematics Honors Papers

This project develops mathematical models and computer simulations for cost-effective and environmentally-safe strategies to minimize plant damage from pests with optimal biodiversity levels. The desired goals are to identify tradeoffs between costs, impacts, and outcomes using the enemies hypothesis and polyculture in farming. A mathematical model including twelve size- and time-dependent parameters was created using a system of non-linear differential equations. It was shown to accurately fit results from open-field experiments and thus predict outcomes for scenarios not covered by these experiments.

The focus is on the application to alfalfa agroecosystems where field experiments and data were conducted and provided …

Fully Coupled Fluid And Electrodynamic Modeling Of Plasmas: A Two-Fluid Isomorphism And A Strong Conservative Flux-Coupled Finite Volume Framework, Richard Joel Thompson

Doctoral Dissertations

Ideal and resistive magnetohydrodynamics (MHD) have long served as the incumbent framework for modeling plasmas of engineering interest. However, new applications, such as hypersonic flight and propulsion, plasma propulsion, plasma instability in engineering devices, charge separation effects and electromagnetic wave interaction effects may demand a higher-fidelity physical model. For these cases, the two-fluid plasma model or its limiting case of a single bulk fluid, which results in a single-fluid coupled system of the Navier-Stokes and Maxwell equations, is necessary and permits a deeper physical study than the MHD framework. At present, major challenges are imposed on solving these physical models …

Software Development For A Three-Dimensional Gravity Inversion And Application To Study Of The Border Ranges Fault System, South-Central Alaska, Rolando Cardenas

Open Access Theses & Dissertations

The Border Ranges Fault System (BRFS) bounds the Cook Inlet and Susitna Basins, an important petroleum province within south-central Alaska. A primary goal in the research is to test several plausible models of structure along the Border Ranges Fault System using a novel three-dimensional inversion utilizing gravity and magnetic data, constrained with other geophysical, borehole and surface geological information. This research involves the development of inversion modeling software using a Borland C++ compiler as part of the Rapid Application Development (RAD) Studio. The novel inversion approach directly models known geology, and "a priori" uncertainties on the geologic model to allow …

Generalized Linear Inversion Using Tau-P Forward Modeling, Stephen Dade Walker

Graduate Theses

The Generalized Linear Inversion (GLI) method is used in conjunction with a tau-p forward model to successfully perform inversions of test and real-data examples. All data examples used are one-dimensional velocity profiles that represent several different cases. The stability of the technique is demonstrated in all the test-data sets. The use of simple models and wel1-control 1ed test data results in a minimum of iterations of the inversion process. Different levels of perturbation of the model and test-data examples are used to reveal insight into the robust nature of the inversion.