Anti-inflammatory drugs such as ibuprofen and triclosan are widely used and available in many pharmaceutical and personal care products (PPCP’s). The concentrations of these drugs are increasing in public surface and groundwaters and is often linked to negative impacts on aquatic life. These impacts are due to the fact that PPCP’s bypass water treatment facilities since they are not typically regulated and water treatment methods at the facilities are not designed to remove them. My research focuses on removing PPCP’s using reactive environmental sorbents like nanocrystalline ferrihydrite. Specifically, I examined the interaction of two widely used PPCP’s (Ibuprofen and Triclosan) with nanocrystalline ferrihydrite of varying particle size (<125, 125-250, >250). Results thus far show that when Ibuprofen interacts with nanocrystalline ferrihydrite at pH 4.3-4.8; 28.29% was removed when the particle size was less than 125 microns; 45.89% was removed when the particle size was 125-250 microns; and 49.92% was removed when the particle size was greater than 250. While for Triclosan 40.55%, 54.7%, 23.80% was removed by nanocrystalline ferrihydrite with size <125, 125-250, >250 respectively. My presentation will further cover surface properties of nanocrystalline ferrihydrite controlling the sorption of ibuprofen and triclosan.

The changing climate as well as the cycling of nutrients and contaminants throughout our planet is heavily influenced by interactions involving plant biomass. For example, interactions of plant biomass with soil biota (specifically fungi)regulates climate and pollution by controlling 1) the quantity of CO2 released from the respiration of organic matter and 2) the movement of pollutants on land and in water. This study focused on 1) investigating fungal colonization of coffee grounds, as a model for understanding the fungi-plant biomass interactions in soils, and 2) studying how fungal colonization changes in the physical and chemical properties of coffee grounds after molding them for 0,3,4,5 and 7 months. The objectives of the next phase of this research will be to examine how the fungi-induced changes in physical and chemical properties of coffee grounds impact 1)carbon sequestering potential (i.e. ease of respiration to CO2) of the coffee grounds and 2) the capacity of the coffee grounds to bind Gentian violet dye (as a model for organic/cationic pollutant).

Synthetic nanomaterials continue to revolutionize how we do things industrially, medically and domestically. As we continue to utilize these materials, the inevitability of them entering the environment and the need to understand the associated consequences rises to the forefront. My research focuses on understanding the chemo-dynamics of interactions between polyamidoamine (PAMAM)-based nanomaterials (most commonly in the biomedical field through drug and gene delivery) and reactive minerals in the environment. Specifically, this presentation will cover the size-dependent binding (and debinding) dynamics of carboxyl-terminated PAMAMs (G-COOH) onto (and from) ferrihydrite (FFH), a form of naturally-occurring iron oxide mineral. Early results suggest that at pH 5, the smaller G1.5-COOH PAMAM binds to (and debinds from) FFH in higher quantities but at much slower rates that the larger G3.5-COOH PAMAM. The higher quantities of G1.5-COOH PAMAM being bound to (or debound) from FFH is attributable to its smaller size - facilitating access to internal micropore space in FFH that are inaccessible by the larger G3.5-COOH PAMAM. Difference in the accessibility of internal FFH micropore space by the different sized PAMAMs would also explain observed trends in their rates of binding and debinding. In future research, I will be targeting the confirmation of early results and the expansion of my study to include G-COOH PAMAMs larger than G3.5-COOH.

Nitrate contamination of groundwater has been a growing problem in Texas and California from increased food demands, requiring growing agricultural inputs of synthetic fertilizer and manure. Pyrolysis of pistachio agro-waste is a promising method for reducing waste products and engineering biochar with the capacity to support zerovalent iron impregnation (ZVI). This study examined the efficiency of pistachio biochar for nitrate (NO₃-N) removal in water with and without ZVI. Pistachio biochar was functionalized through varied temperature pyrolysis (400-600℃) over three heating durations (0 min, 5 min, 10 min). Biochar samples from both 400°C and 600℃ pyrolysis were tested with and without ZVI impregnation over a 5 day period in a 20 ppm solution of NO₃-N. The biochar-nitrate solutions were recorded in intervals (1 hr, 3 hr, 7 hr, 24 hr, 68 hr, 96 hr, 120 hr) and Ultraviolet-Visible Spectroscopy was utilized to measure NO₃-N absorbance of samples at 400nm. The experimental data show that pistachio biochar with and without ZVI decreased nitrate levels from water; presenting a potential low-cost and sustainable option for repurposing agro-waste for water remediation.

Rivers are an essential part of any urban or rural landscape, providing drinking water, transportation, and recreational opportunities for local residents. However, with the continuous growth and development of urban areas like Fort Worth and Dallas, flooding poses a significant risk to human life and property. This increased development creates a need for careful monitoring and forecasting of river conditions and flood probabilities. This study explores the associated historical river data for USGS Gauges on the Trinity River in Tarrant and Dallas Counties. This data, along with topographic information and land use surveys, are used to project the possible impacts of flooding scenarios. These possible impacts include damage to property, critical infrastructure, and threats to human life. This data can then be interpreted spatially to effectively inform the public and public officials of risks and monetary costs associated with future flooding events.

This project will consist of designing an AI application. The application will use a deep learning algorithm able to take attendance of the class as students are joining the classroom. I will further expand the patent to recognize the individual students and measure their temperature. Furthermore, the system will classify different emotions during the lecture and give helpful feedback to the professors. This tool will assist with time management, as professors spend several minutes to take attendance, and it will act as an extra tool for the prevention of spreading COVID-19 and any new virus. The patent will further provide useful feedback for the improvement of lectures through emotion detection. An external camera will be used hand in hand with the Open-CV package in python that will allow us to detect the students and identify them. The students' temperature will be measured by an infrared forehead thermometer and welcome them in the class. The algorithm will be using cascade classifiers, and transfer learning. Data for the training process of the algorithm will be collected from volunteering TCU student subjects.

The process of successful skin healing from a wound involves different combinations of interactions. Moreover, by clearly understanding this process, we can provide and determine the appropriate amount of medicine to give to patients with varying types of wounds. Thus, this can improve the healing process of patients. In this research, we use the ADI method to solve a partial differential equation that models the wound healing process. Moreover, we try to explore the relationship between parameters in the model for different patients. Wound images are used as our dataset experiment. To segment the image's wound, we implement U-Net, a deep learning-based model, as our model for this segmentation problem. We believe the combination of ADI and Deep Learning helps us understand the process of wound healing.

Markov chains are stochastic models characterized by the probability of future states depending solely on one's current state. Google's page ranking system, financial phenomena such as stock market crashes, and algorithms to predict a company's projected sales are a glimpse into the array of applications for Markov models. In this research, we analyzed the board game "The Settlers of Catan" using transition matrices. Transition matrices are composed of the current states which represent each row i and the proceeding states across the columns j with the entry (i,j) containing the probability the current state i will transition to the state j. Using these transition matrices, we delved into addressing the question of which starting positions are optimal. Furthermore, we worked on determining optimality in conjunction with a player's gameplay strategy. After building a simulation of the game in python, we tested the results of our theoretical research against the mock run throughs to observe how well our model prevailed under the limitations of time (number of turns before winner is reached).

In the field of Riemannian geometry, the condition on the Riemannian metric so that a manifold has positive scalar curvature (PSC) is important for a number of reasons. Many famous researchers have contributed gradually to this area of geometry, and in this project, we study more about PSC metrics on such manifolds. Specifically, we refine and provide some details to the proof of Gromov and Lawson that the connected sum of 2 n-dimensional manifolds will admit a PSC metric, provided each of the manifolds has a metric with the same condition. We then derive some useful formulas related to the Riemann curvature tensor, the Ricci tensor, and the scalar curvature in many different scenarios. We compute the quantities for a manifold equipped with an orthonormal frame and its dual coframe, namely the connection one-form and the curvature two-form. Then, we observe the change in the structure functions, defined as a function that determines the Lie derivative of the orthonormal frame, under a nearly conformal change of the said frame. The aim of these calculations is that, by expressing the scalar curvature of a manifold M entirely in terms of the structure functions, we can determine a condition on the conformal factor so that when dividing the tangent bundle of M into two sub-bundles, then the scalar curvature restricted to one sub-bundle will “dominate” that of the other one, so that if we know the scalar curvature of the former sub-bundle is positive, we c

Impact of the COVID-19 pandemic on diet and health-related behaviors of adults

Background:
Study objectives were to describe how diet and health habits changed and identify factors impacting diet and health behaviors during the pandemic.

Methods:
An electronic, anonymous survey was developed and distributed via local social media and through a community food-bank following IRB approval. Data were coded into and analyzed for frequencies and correlations using SPSS.

Results:
Participants (n=80) were 97% (n=77) female and 41.37+/-11.7 years. Participants receiving food assistance primarily accessed community food/mobile pantries (22%, n=17). Participants (54%, n=43) agreed that, “I was healthier before the pandemic”, while 15% (n=12) disagreed. Participants (52%, n=42) reported 13.2+/-6.8 pounds unwanted, pandemic weight gain, while 22.5% (n=18) reported 14.1+/-13.9 pounds desired, weight loss. Among participants earning <$50,000/year, 89.5% (n=17) reported inability to afford healthy food, while 2.6% (n=1) earning >$150,000/year reported inability to afford healthy food. Inability to afford healthy food correlated with BMI (ρ=.40, p<.01). Income negatively correlated with pandemic weight gain (ρ=-0.31, p<0.05) and ability to afford healthy foods (ρ=-.73, p<0.01). Participants reported increased pandemic snacking (61.25%, n=49) and alcohol consumption (37.5%, n=30). Higher pandemic stress levels correlated with increased pandemic alcohol and snack consumption, (ρ=.30, p<.01) and (ρ=.44, p<.01), respectively.

Conclusion:
Changes in health perceptions and weight were common. BMI and income impacted ability to afford healthy foods. Increased stress levels were significantly associated with increased alcohol intake and snacking, although weight changes were not associated with alcohol or snacking. This research provides information about pandemic dietary and health behavior changes and how impacts differ based upon income level.