Traumatic brain injury (TBI) is a widespread health issue that affects approximately 1.7 million lives per year. The effects of TBI go past the incident of primary injury, as chronic damage can follow for years and cause irreversible neurodegeneration. A potential strategy for repair that has been studied is cell transplantation, as neural stem cells improve neurological function. While promising, neural stem cell transplantation presents challenges due to a relatively low survival rate post-implantation and issues with determining the optimal method of transplantation. Shear-thinning hydrogels are a type of hydrogel whose linkages break when under shear stress, exhibiting viscous flow, but reform and recover upon relaxation. Such properties allow them to be easily injected for minimally invasive delivery, while also shielding encapsulated cells from high shear forces, which would normally degrade the function and viability of such cells. As such, it is salient to research whether shear-thinning hydrogels are feasible candidates in neural cell transplantation applications for neuroregenerative medicine. In this honors thesis, shear-thinning hydrogels were formed through guest-host interactions of adamantane modified HA (guest ad-HA) and beta-cyclodextrin modified HA (host CD-HA). The purpose of the study was to characterize the injection force profile of different weight percentages of the HA shear-thinning hydrogel. The break force and average glide force were also compared between the differing weight percentages. By understanding the force exerted on the hydrogel when being injected, we could characterize how neural cells may respond to encapsulation and injection within HA shear-thinning hydrogels. We identified that 5% weight HA hydrogel required greater injection force than 4% weight HA hydrogel to be fully delivered. Such contexts are valuable, as this implies that higher weight percentage gels impart higher shear forces on encapsulated cells than lower weight gels. Further study is required to optimize our injection force system’s sensitivity and to investigate if cell encapsulation increases the force required for injection.

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.

Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that there is some level of disconnect between ideals and practices. This project may aid in bridging the gap between the two in regard to the farmers’ sustainability goals. This project will move forward by continuing interviews with farmers as well as collecting soil and water from the farms in order to more accurately quantify the sustainability of the farms’ practices. This project demonstrates that there is some degree of misalignment between perception and reality. Two farms claimed they were sustainable when their practices did not reflect that, while 2 farms said they were not sure if they were sustainable when their practices indicated otherwise. Samples from two farms showed high concentrations of nutrients and salts, supporting the idea that there may be a mismatch between perceived and actual sustainability.

Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.

This analysis explores what the time needed to harden, and time needed to degrade is of a PLGA bead, as well as whether the size of the needle injecting the bead and the addition of a drug (Vismodegib) may affect these variables. Polymer degradation and hardening are critical to understand for the polymer’s use in clinical settings, as these factors help determine the patients’ and healthcare providers’ use of the drug and estimated treatment time. Based on the literature, it is expected that the natural logarithmic polymer mass degradation forms a linear relationship to time. Polymer hardening was tested by taking video recordings of gelatin plates as they are injected with microneedles and performing RGB analysis on the polymer “beads” created. Our results for the polymer degradation experiments showed that the polymer hardened for all solutions and trials within approximately 1 minute, presenting a small amount of time in which the patient would have to remain motionless in the affected area. Both polymer bead size and drug concentration may have had a modest impact on the hardening time experiments, while bead size may affect the time required for the polymer to degrade. Based on the results, the polymer degradation is expected to last multiple weeks, which may allow for the polymer to be used as a long-term drug delivery system in treatment of basal cell carcinoma.

The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.

This collection entitled “Poems on Home, Family, and the Self” is about the author’s role as a daughter to immigrant parents, who is finding her drive, and understanding where she comes from and how she will use that to find her purpose. The poems in this collection touch upon the author’s upbringing in Northern California, her transitioning relationship with her parents and her brother, as well as her experiences relative to her growth in Arizona. These pieces are greatly inspired by author Arundhati Roy and poet Li-Young Li. Specifically, the author is influenced by Li-Young Li’s approach to poetry – his commentary and storytelling of his life and his parents are objective, observatory, and allow the readers to make opinions for themselves. In this collection, the author aims to make statements about her family and upbringing and show the readers her new understanding of life and her ambitions.

The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.