The mis-regulation of reactive oxygen species (ROS) and transition metals contribute to the onset of Alzheimer’s Disease (AD). A tetra-aza macrocyclic pyridinophane with an indole moiety, (Ind)PyN3, was evaluated on its radical scavenging reactivity and ability to chelate and stabilize the copper (II) oxidation state; these evaluations contribute to the overall therapeutic efficacy of the ligand in treating AD. Compared to a congener replacing the indole moiety with a hydroxyl moiety, (OH)PyN3, (Ind)PyN3 displayed comparable radical scavenging reactivity to (OH)PyN3. The fluorometric CCA assay revealed that (Ind)PyN3 was able to the stabilize the copper (II) oxidation state and prevent it from generating ROS via redox cycling at both 1 and ½ equivalents, albeit (OH)PyN3 was more effective at copper (II) oxidation state stabilization than (Ind)PyN3 at half molar equivalence. Our results demonstrate that the addition of the indole moiety to a tetra-aza macrocyclic pyridinophane does not disrupt radical scavenging reactivity by the indole moiety nor the ability of the pyridinophane to stabilize transition metal ions, warranting future exploration of the indole moiety in therapeutic design for AD.

Dispersion interactions also known as van der Waals interactions are essential for everything from nanomaterials to organic chemistry to biological chemistry. Modeling that chemistry requires modeling van der Waals interactions. Approximations that start from “freshman chemistry” molecular orbital (MO) theory do not account for dispersion. For example, helium-helium interactions are unbound in molecular orbital theory as two electrons are placed in antibonding orbital, but in reality, the interactions are weakly bound and can form a liquid. We have developed a density functional theory method embodying MO theory and corrections. Dispersion corrections can be added to noncovalent interactions in order to model them by using a standard model with different parameters. By fitting these parameters, the accurate known bond energies of real noncovalent complexes can be reproduced.

This project is aimed to develop triazine-based fluorescent bivalent antibody mimics against the epidermal growth factor receptor (EGFR), a protein disease marker for cancer. A synthetic gene for the anti-EGFR Z-domain was constructed by overlapping extension PCR and inserted into the pET-Z plasmid to produce pET-Z anti-EGFR. The anti-EGFR Z-domain variant was expressed as a C-terminal His-tag fusion in BL21(DE3) E. coli cells transformed with the pET-Z anti-EGFR plasmid and purified by immobilized metal ion affinity chromatography. A dansyl fluorophore was attached to the first position of a triazine core that has three positions available for modification. To the second available position of the dansyl-triazine conjugate, an anti-EGFR Z-domain molecule was selectively attached to generate a monomeric conjugate. Another anti-EGFR Z-domain molecule will be attached to the remaining position of the triazine core to produce a dimeric conjugate. We will test the fluorescent monomeric and dimeric anti-EGFR Z-domain conjugates for binding to the EGFR by a standard ELISA method and isothermal titration calorimetry.

Alzheimer's disease is a neurodegenerative disorder that is characterized by amyloid-beta plaques, neurofibrillary tangles, and unregulated reactive oxygen species. The production of reactive oxygen species in the brain is exacerbated by an excess of free-metal ions in nervous tissue. Our team and others have shown a library of tetra-azamacrocycles to have the ability to scavenge free-metal ions and quench reactive oxygen species. These macrocyclic ligands have, thus, been considered as potential therapeutic agents for combatting Alzheimer’s disease. The ability of a neuro-active pharmaceutical to cross the blood-brain barrier is crucial to its pharmacological success and has proven to be a significant challenge to date in moving molecules from the bench to clinical treatment paradigms. The aim of this work is to enhance the pharmacological potential of these macrocyclic ligands. To accomplish this, computational analyses were performed on two tetra-azamacrocycles to predict their baseline blood-brain barrier permeability. The structures of these macrocycles were then modified with various moieties and analyzed via the same computational methods to predict their blood-brain barrier permeability potential. One target modification this project is focused on is the attachment of omega-3 fatty acids to these tetra-azamacrocycles. Omega-3 fatty acids have been shown to have beneficial anti-inflammatory properties in vivo and have the ability to assist in transporting molecules across the blood-brain barrier. Thus, the inclusion of these moieties to the structure of the Green Group ligands are attractive in regard to enhancing their pharmacological potential. To accomplish this attachment, the synthetic approach of one of the Green Group’s flagship tetra-azamacrocycles, OHPy-N3, had to be completely reimagined. New synthetic approaches and protection strategies were employed to achieve a suitable intermediate molecule primed for the addition omega-3 fatty acids. These novel synthetic methods and subsequent results are discussed in this work herein.

The objective of this project is to make a vaccine that will negate the effects of the powerful opioid fentanyl in the long term. Fentanyl is a strong synthetic opioid that is 50 to 100 times more potent than morphine. According to the CDC, there were over 70,000 deaths due to street drug overdoses, which has increased in the last ten years. 40 % of these deaths are related to fentanyl overdoses, therefore it is imperative that approaches are developed to combat this alarming increase in deaths. The vaccine against fentanyl will be synthesized out of molecules that will take advantage of fentanyl’s amide functional group to be hydrolyzed into safe byproducts. Any patient that is administered with the vaccine, will not feel the effects of the opioid because the immune system will hydrolyze the drug as soon as it enters. This project will exploit the properties of both catalytic antibodies (CAbs) and transition state analogs. If the molecule resembles the transition-state of fentanyl hydrolysis, then the antibodies can cleave the fentanyl in a fast and efficient manner due to their catalytic properties. Therefore, after immunization, a person who is addicted to fentanyl would no longer feel the effects of the opioid because it will be degraded as soon as an immune response is triggered, creating a long-term possible solution to one factor of the “opioid crisis.”

Alkenyl phosphorus compounds appear in multiple industrial products, from flame retardants to fungicides. Although several methods are available to synthesize these compounds, many require expensive catalysts, inaccessible starting materials, or multi-steps sequences. In response to these issues, this project sought to develop an efficient, two-step method to synthesize alkenyl phosphorus compounds from simple ketones. We compare acid and base catalysts and find both are effective in the first reaction step; furthermore, a one-pot reaction provides comparable yields to the reactions conducted with a purified intermediate. These findings lay the foundation for the exploration of more complex substrates, including those utilized in industrial applications.

Pyridine macrocycles have useful applications due to their ability to complex with metals. A library of substituted pyridine macrocycles exists along with how modifications at Carbon 4 impact compound reactivity. Despite literature about similar pyridine macrocycle structures, little is known about how an iodo-substituted pyridine macrocycle will alter the properties of the compound when complexed to Copper. To understand the fundamental characteristics of an Iodo-substituted pyridine macrocycle, the ligand is synthesized followed by electronic environment analysis via 1H NMR. Ultraviolet-Visible Spectroscopy is used to verify ligand complexation with Copper (II) metal followed by X-ray diffraction to determine metal binding nature of the complex. Cyclic Voltammetry analysis is used to support the theory that the iodo functional group behaves as an electron withdrawing group. This compound serves as a comparison to explain the results of the Chloro-substituted pyridine macrocycle as well as a gateway molecule for the synthesis of new pyridine macrocycles.

The TCU and UNTHSC School of Medicine requires its students to participate in service learning with various non-profit partner organizations in the community. Our team's goal is to make the volunteer sign-up process easier and more convenient for med students, to automate the tracking of students' hours, and to ease the burden on faculty in charge of managing the entire process. We aim to accomplish these goals with a web application that will streamline the volunteer scheduling and hour-tracking process for students and faculty.

The TCU Computer Science Department has launched an AlphaGo research project. Currently, it can only be used by those directly involved with the project, and only at certain computers on campus. In addition, the interface for conducting research is difficult to use. Our goal is to make this project more widely accessible to students and faculty alike, whether they wish to help in research, or simply want to learn to play Go. We have developed a web application for the project that allows users to play against various Go AI agents, as well as allowing researchers to train new AI. In addition, our site allows various admin functions to control and edit users and AI agents alike.

This is a brief report on a comprehensive assessment of AlphaZero-type algorithms from the viewpoint of optimal play. This study does not join an already crowded field in seeking to enhance the efficiency of these algorithms, but sets sights on more conceptual questions and more quantitatively precise results. In particular, we show that the AlphaZero-type algorithms tend to behave more conservatively when winning and more aggressively when losing. We illustrate our results with a specific example on the 7x7 board.

A common way to evaluate the performance of players in two-player games is to have them play against other players. If the player wins more games than other players, then it is said to be more capable; in other words, the strength of a player is measured relatively. In this project, we seek a way to evaluate the performance of players in terms of absolute. In recent years, self-play reinforcement learning has given rise to capable game-playing agents in a number of complex domains such as Go and Chess. We perform an analysis of a self-play agent using scaled-down versions of Go on a generic platform to measure the strength of the agent via our developed methods.

Homeopathy is a holistic natural system of medicine and helps patients recover from all types of illnesses naturally, while strengthening their immune system and increasing their energy and vitality. The Hygieia Homeopathy Clinic provides basic knowledge of homeopathy to their patients. Patients use their time-tested methods to trust in their own body’s recovery functionality. The main problem of the website is their patient’s inability to search the website for knowledge and protocols about homeopathy. Other problems with the website include the ability of patients to view and make appointments, purchase vitamins and supplements, and payment information. The Smart Homeopathy Doctor App Senior Design 2021 Team’s goal is to provide their clients a fully functional mobile app for easier content viewing, appointment making, shop, and patient messaging. Furthermore, the website needs to facilitate easy communication between the doctor and patients. The Smart Homeopathy Doctor App is a mobile application. Its primary function is to allow users to query a server-hosted database. The content of the database includes publicly available, non-sensitive data such as FAQs pertaining to homeopathy. The administrator performs database CRUD operations. Over the course of the project, our team has refined our time management skills and honed our Peer Review skills. We communication better by not only updating others on our progress but also asking members for help. We also learned Ionic Framework with Angular for our front-end user experience and learned to store our database in Firebase.

Our goal is to create a user friendly dashboard with data related to the current COVID-19 pandemic. This includes an interactive map, charts, and numbers presented to the user in a simplified manner. The data spans every county in the United States. Beyond just being a COVID-19 Tracker, our tool will be available as an API that can be used with any other state and county specific data.

Identifying new and cutting-edge investment strategies is a crucial step in establishing any large business within its relative industry. Fort Capital, whose primary investment focus is on industrial-grade buildings, is taking an innovative and insightful approach to geographic understanding. Fort Capital aims to identify trade routes used by major market players, such as Amazon and Walmart, to find the areas where industrial warehouses and large-scale distribution centers are in highest demand. To locate such trade routes, identifying the main travelers on these routes is essential, and Truck Detective aims to do exactly that. Using machine learning and artificial intelligence models such as a deep neural network, Truck Detective enables Fort Capital to detect, with high accuracy, the location of big rig trucks, and can additionally help identify where they came from or where they are heading. This, in turn, illuminates geographically important areas with promising investment opportunities for Fort Capital.

Vehicle Re-identification, which aims to retrieve matching vehicles across different cameras, is a challenging problem in Intelligent Transport System due to different factors such as illumination conditions, occlusions, and video resolution. Numerous studies are proposing the use of Deep Neural Networks, a recent advance in Artificial Intelligence, thanks to their exceptional feature embedding extraction. However, Deep Neural Networks perform poorly on cross-domain settings. Furthermore, vehicle re-identification training data is relatively limited because public videos are only accessible to the authority only. Our study tackles the above challenges by utilizing several state-of-the-art techniques on domain learning to expand the model's generalization capability. Our research shows that we can outperform other state-of-the-art models by large margins on popular vehicle re-identification benchmarks.

The purpose of this project is to create a closed loop system that will enable a continuous drying cycle of mined limestone through a rotating cylindrical dryer. Our client, Lhoist North America, has tasked us with designing this system, and our biggest issue has been putting together the system on a limited budget. We have determine that the most efficient method of designing the system is to used scrapped equipment that Lhoist has available and reconfiguring it for our design, rather than buying a new system. Another challenge we have faced is the method of transporting the mined limestone due to its sand-like qualities. We believe that the most effective method of designing the system will be by altering scrapped material from Lhoist’s scrapyard to complete a closed loop system of the limestone for the rotary dryer.

Dryer Testing
The parameters which were used to test the dryer was that the incline was set at 5 degrees, and the dryer rpm was at 5 and 10. Further, we used four rows of 90-degree lifters followed by four rows of radial lifters. We tested using a small grain limestone sample to be a middle of the road test. Originally, we started testing with one scoop (one quart) inside the cylinder, started the motor and turned to the 10 rpm, and added one quart every ten seconds until 4 total scoops were through the cylinder. The time this took was consistently right around the 90 second mark. However, when the volume was turned up, the findings were more interesting. When we started with a full five gallons inside of the cylinder, turned the motor up until 10 rpm, and added another five gallons at the 30 second mark, the time that it took for all of the material to exit the cylinder was right around the 90 second mark, the same time as when only a gallon of material went through the dryer.

We accumulate several cloud services on Amazon Web Services (AWS) into developing a serverless system in the cloud that replaces the current technical support request, which occurs via calls, in a classroom setting. The instructor can notify the so-called IT person with a press on the programmable Internet of Things (IoT) button. We plan to deploy the system at our university as a way for class instructors to request help without interrupting the lecture. The system is low-cost thanks to AWS's pay-as-you-go policy and easy to install.

The most viable path to alleviate the Global Climate Change is the substitution of fossil fuel power plants for the generation of electricity with renewable energy units. The substitution requires the development of very large (utility-level) energy storage capacity, with the inherent thermodynamic irreversibility of the storage-recovery process. Currently the world also experiences a significant growth in the numbers of electric vehicles, which use very large batteries. A fleet of electric vehicles is equivalent to a relatively efficient storage capacity that may be used to supplement the energy storage system of the electricity grid. Calculations based on the demand-supply data of a large electricity grid show that, even though a fleet of electric vehicles cannot provide all the needed capacity for a large electricity grid, the superior round-trip storage efficiency of batteries significantly reduces the energy dissipation associated with the storage and recovery processes. A very small amount of battery storage significantly reduces the dissipated energy in the electricity grid. Also, improvements in the round-trip efficiencies of batteries are three times more effective than improvements in hydrogen storage systems.

The dryer is a steel cylinder, approximately 36 inches in diameter and five feet in length. The cylinder also spins at a rate up to 10 rpm. The inside surface contains 48 lifters. These lifters have two variants and are made of mild steel. They are designed to move limestone through the cylinder while the cylinder spins.

The drying of limestone is usually done industrially in a rotary drum dryer. The purpose of this project is to generate a model that will predict limestone particle motion as it passes through the dryer.  By creating an accurate model of the particle movement during the drying cycle, the operator will be able increase the dryer’s efficiency.  Using basic physics and through experimental testing, our team was able to produce a model that will provide detail of particle motion inside the dryer.

The Mississippi River Delta is the 7th largest river delta on Earth that consists of the Mississippi River and the Gulf of Mexico. Additionally, it contains 40% of the wetlands in the contiguous United States and over two million hectares (4,942,108 acres), an area equivalent to the size of two football fields, of agricultural lands. Due to fertilizer runoff from agricultural lands, the river delta has been experienced excess levels of nitrogen and phosphorus. The excess levels of these nutrients have contributed to water pollution in the delta and the hypoxia zone in the Gulf of Mexico. This research will focus on mapping the levels of nitrogen and phosphorous across the river delta to determine where the highest levels are

To understand wildlife ecology, one common strategy is a technique known as telemetry. This technique involves attaching radio-transmitters to animals. For volant species, such as bats, transmitters are attached to their backs with an adhesive. However, one issue is that it is easy for the bats to remove the transmitter. The loss of transmitters early in surveys is not only costly, but limits the amount of data that can be collected. Thus, there is a real need to extend the length of time a transmitter remains on a bat. To address this, we conducted a two-part behavioral observation study in the bat flight facility at TCU. In part 1 from April to September 2019, we tested 1) two currently available transmitter brands and 2) three different prototype designs to determine if the overall shape and size of the transmitter impacted the length of time they remained attached. We found that regardless of transmitter brand or design, the antennas incurred a significant amount of damage, suggesting the bats used the antennas to grab and pull them off. Thus, for part 2 from August to September 2020, we conducted a series of trials to establish the effectiveness of three coatings at preventing bats from damaging the antennas. We found that transmitters did not remain attached significantly longer with cayenne pepper, nail-biting deterrent, or Tabasco sauce on the antenna, suggesting that either 1) bats were not deterred by the three coatings we selected, or 2) bats may not be chewing the antennas or putting them in their mouths to provide leverage to remove them. Overall, our study revealed that bats can and will remove transmitters by grooming them off using the antennas and recommend that future research focuses on integrating the antenna into the body of the transmitter as a preventative measure.

Agricultural soils require the presence of three basic plant nutrients: Nitrogen, phosphorus, and Potassium (NPK). Each nutrient has its role in plant growth and their deficiencies have adverse effects. Therefore, detailed analysis was required to analyze whether soils from a lake were sufficient in terms of these nutrients and could be suggested for use as an agricultural soil amendment on a particular plot of land. Experimental study by way of specific chemical analysis methods (LOI, spectroscopy, etc.) looked at water content, pH, EC, SOC (Soil Organic Carbon), phosphorus and nitrogen content in the lake sediments; these values were used to determine what contents/nutrients in the lake sediments would need to be optimized for crops of interest. Results from the concluding experimental procedures would allow the property owner to effectively make use of their resources.

The Atlantic Forest, which extends over 17 Brazilian States, is one of the richest biomes in the world. Historically it has been a hot spot for biodiversity including endangered and endemic species. Despite this, only 15% of the forest’s original range remains. This loss is disproportionally distributed as 4 of the 17 states accounts for 90% of the loss. The source of this deforestation can be attributed primarily to logging developments and eucalyptus plantations. Through using public geodatabases, satellite imagery, and ArcGIS Pro we will show this forest loss and fragmentation in a visually accessible way.