In the world of drugs, the chemical property that is most important is logP, the predictor of whether a drug can be taken orally and cross the cell membrane. Pharmaceutical companies will not explore molecules with logPs that are outside the ideal range. But what if predictions are wrong? The rules for predicting logP are based on small molecules, but the industry is moving towards large molecule drugs. This poster looks at synthesizing models of large molecule drugs (ring-shaped molecules called macrocycles) to determine if the logP of large molecules can be predicted. Synthesis of a hydrophobic macrocycle shows that the industry predicted logP failed. New prediction methods are needed. To develop these methods, additional macrocycles were made to serve as models for prediction. These molecules also allow us to explore another avenue in drug design challenge another paradigm in drug discovery. Pharmaceutical companies avoid hydrophilic functional groups because of ill predictions about logP. Combining these hydrophilic groups with predictable hydrophobic groups will make the molecule's logP acceptable. That is, by design, the undesirable hydrophilic group is balanced with the desirable hydrophobic group to bring polar groups through the membrane. Overall, the work will allow for a wider range of molecules to be considered for potential drug design.

Oxidative stress occurs when there is an imbalance between free radical activities, including those of reactive oxygen species (ROS), and the body’s natural antioxidant mechanism. To help restore this balance, the Green research group at TCU has developed tetradentate pyridine-containing cyclen macrocycles capable of simultaneously carrying out various modes of antioxidant activities. As drug candidates , these molecules need to be further modified with different functional groups to fine-tune their activities and pharmacological properties, resulting in a large library of up to hundreds of derivative structures. Isoelectric point (pI) and acidity (pKa) play a vital role in assessing the membrane permeability of these molecules. Given the size of the library, experimental determination of these values is an unnecessarily time-consuming endeavor. Using the state-of-the-art Density Functional Theory (DFT), this project aims to 1) show how pI values of any molecules in this library can be predicted with reference to a desired value and 2) predict the pKa of different acidic sites on these multifunctional molecules. This can potentially shed light on the effects of covalent modifications on pI and pKa values, and with further optimizations, can be applied to a virtual screening protocol for any libraries of drug candidates.

Protein crystallization is regarded as a more economically sustainable strategy for achieving protein purification compared to traditional downstream processing chromatography. However, protein crystallization is not a well understood process and still relies on empirical protocols. This work examines the rational design of protein crystallization for lysozyme, a model protein, by exploiting the formation of metastable protein-rich droplets by liquid-liquid phase separation (LLPS). Specifically, sodium chloride, which is a salting-out agent, is used to induce LLPS, while 2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid (HEPES) is a salting-in agent used to modulate LLPS conditions. It was found that HEPES enhances protein crystallization from protein-rich droplets. This effect can be explained by examining the relative shift of the LLPS boundary with respect to crystal solubility in the temperature-composition phase diagram. This work suggests that LLPS-mediated protein crystallization may be enhanced in the presence of salting-in agents.

There are a wide variety of unnatural amino acids whose properties could be used to study the structure and function of proteins and create proteins with enhanced or novel functions. The purpose of this research is to develop a method to add unnatural amino acids to proteins via site-specific modification. This is done through aminoacyl tRNA synthetases (aaRSs) which are proteins that attach the correct amino acid to its corresponding tRNA. The loaded tRNA then transports the amino acid to the ribosome where it is incorporated into an elongating protein. Usually, aaRSs have editing domains that remove any amino acids that the synthetase is not specific to. To solve this problem, we have paired Methanobacterium thermoautotrophicum leucyl tRNA synthetase (MLRS) with a removed editing domain with Halobacterium sp. NRC-1 leucyl tRNA to incorporate unnatural amino acids into proteins in Escherichia coli. The binding site of MLRS has been identified, and we have created millions of MLRS variants by randomizing the five amino acids in the binding sites. Using genetic screening procedures, we have identified variants with larger binding sites, and we are currently testing for successful incorporation of unnatural amino acids like dansyl-DAP into the z-domain model protein.

Utilizing the supportive structure of hydrogels, the semiconducting character of porous silicon (pSi) membranes, and the biodegradability of both, a unique biosensor for the chemical analysis of health-relevant analytes can ideally be created.
Alginate-based hydrogels are water-infused, biodegradable polymer networks. These are particularly useful because of their environmental abundance, and their ability to interface well with human skin. These characteristics also make them an ideal medium for supporting pSi membranes and simultaneously assimilating them into a wide range of tissues.
Porous silicon (pSi), a highly porous form of the elemental semiconductor, is utilized to measure and conduct electrical signals throughout the hydrogel matrix. In diode form, these membranes exhibit measurable current values as a function of voltage, which can be used to detect bioelectrical stimuli such as the concentration of physiologically relevant ionic species (e.g. Na+, K+, and Ca2+).
Recent experiments center on integrating pSi membranes into various aqueous environments and hydrogels to test how variations in ion concentration affect the flow of electrical current as a function of applied voltage. pSi membranes are fashioned into diodes upon the attachment of 0.25 mm diameter copper wire using silver epoxy and annealing. An electrochemical cell is created by placing two pSi membranes parallel each other in an electrolyte composition. Current is measured as a function of applied voltage (typically from 0-5 V) for systems with differing NaCl concentration.
As expected, the magnitude of maximum current response is proportional to ion concentration present in the electrolyte, with an order of magnitude amplification or more of measured current for a given voltage upon immersion of the electrodes in an alginate hydrogel matrix relative to water alone.
This presentation will focus on initial diode fabrication protocols, as well as establishing limits of detection for simple ions species present in human sweat. More refined strategies are also envisioned, including the development of methods for stabilization of sensor performance along with miniaturization of the sensing platform itself.

Light-driven reactions, such as those utilized in photoelectrosynthetic applications, focus on capturing and transferring light energy to drive chemical reactions. For this purpose, light-active metal oxide semiconductor materials are used, such as BiVO4, 𝛼-Fe2O3, and WO3 to list a few. Previous work demonstrated the use of BiVO4 electrodes to drive the oxidation of benzyl alcohol to benzaldehyde in the presence of a TEMPO (2,2,6,6-tetramethylpiperidine) mediator.1 This study seeks to improve the photoelectrochemical performance of this reaction by using a heterojunction WO3-BiVO4 electrode. We hypothesize that the heterojunction would decrease charge carrier recombination and improve the photochemical yield of the reaction compared to a BiVO4 electrode.2,3 The WO3-BiVO4 interface forms a type II band alignment allowing electrons from photoexcited BiVO4 to transfer into WO3 and holes to accumulate at the BiVO4-electrolyte interface.4 Two techniques, UV-visible spectroscopy and incident photon-to-current efficiency (IPCE) measurements, were applied to better understand why the heterojunction improved the photocurrent density in the presence of reaction components in solution. UV-visible spectroscopy was used to determine the band gaps of the materials. Information about the efficiency of light energy conversion to chemical energy was obtained by IPCE measurements. IPCE values are determined by relating the proportion of incident light power to the current produced by illuminating the WO3­-BiVO4 photoanode over a small wavelength range. Photoanodes exhibiting higher IPCE % are more effective at driving photoelectrosynthetic reactions.1 To test the effect of WO3 on the energy conversion efficiency, IPCE experiments were run for the WO3-only, BiVO4-only, and WO3-BiVO4 samples. Comparing IPCE values for WO3-BiVO4 samples shows a clear increase compared to BiVO4-only photoanodes. These results demonstrate how coupled materials (WO3-BiVO4) can generate higher current densities upon illumination for driving photoelectrosynthetic reactions.

Chalk Mountain Services of Texas, LLC. is a trucking company whose business is transporting raw materials, such as fracking sand, to various oilfield sites in and around west Texas. With over 1,300 assets in their fleet, they’re presented with a number of logistical problems, like optimizing a driver’s time to make as many trips between drill sites and raw material depots as possible in a day. Such routing and scheduling applications must have accurate data—the assets are either in or out of service and their location—to schedule sensible routes.

Should an asset break down in the unforgiving terrain of west Texas, the appropriate employee should have the ability to take note of such an incident so that routing and scheduling applications have correct, up-to-date data. The company’s current solution allows for any user to make changes to any asset, regardless of authorization status. Inconsistencies in assets’ statuses can lead to an employee having to manually intervene in the scheduling process, which decreases the company’s overall efficiency. Additionally, their current application is not mobile-friendly, but a sizable portion of users nevertheless interface with the current website from their phones.

The company’s expectations come in either one of two forms: a website and a companion app or a reactive website that can be used on a desktop or mobile device. The application shall use CRUD—create, read, update, and delete—methods to keep track of the assets, and the application shall provide different users with different access levels with Active Directory authentication. We have created a reactive website that can be used from either a desktop environment or mobile one, and our implementation of their requirements exists as a three layer architecture: a Microsoft SQL Server database, a backend developed in NodeJS, and a React front end. To make the deployment as simple as possible, we did not pursue developing the application on cloud providers; the application depends on a connection to an in-house SQL server and Active Directory service both of which cannot be accessed outside their intranet and are critical to the application’s functionality.

The Instructional Equity Observing Tool is an online video/audio analysis tool that is geared towards assisting the teachers and faculty of educational institutions in analyzing and understanding how their interaction with students translates into real learning. Our platform is meant to replace the current, manual method of analysis that many teachers/instructors perform to try and quantify different metrics about their teacher-student interaction. Instructors have expressed desire to view metrics such as the time the teacher talks during a lesson, what is the response time of students to those questions, and other data points such as the types of questions being asked (as categorized by Bloom’s Taxonomy). Quantifying these instructional variables helps these instructors more accurately understand the areas that they are strong in, and more importantly, the areas in which they can be more interactive with the students as to allow them to better absorb the lessons being taught. With the help of our tool, we can allow teachers to quickly and efficiently gather this data about each of their lessons so that data driven changes in teaching techniques is possible, and moreover, so that teachers can identify potential vectors of ineffective instruction.
The process for using this application is for a user to login/sign-up for our site, then they will proceed to upload either an audio or video file to the designated location. Our tool will then take that video/audio file and execute a customized API call to AssemblyAI (https://www.assemblyai.com/) that transcribes this file into text. We then perform specialized data manipulation operations on the transcript to generate all the different metrics and display them in an easy-to-read format that the user can then scroll through and analyze the results. The user will also have the option to save this report that is generated as a pdf, which they or an administrator role will be able to access and view again at a later time.
Our application is hosted using Amazon Web Services (AWS) and utilizes many different functionalities that this service provides. AWS manages our authentication and authorization, user account management, and report storage functionalities. Our current system does not use its own machine learning model and instead offloads transcription to the AssemblyAI API, however this could be updated in the future with the addition of large datasets for training. A specifically trained machine learning model in this case could provide a more accurate categorization of questions and a more flexible tool that could eventually make predictions or suggestions to the user on the best ways to improve their teaching methods.

Open Planner is a web application designed to meet the increasing need for college students to have a way to more easily organize and access major
assignment/exam dates across all courses during busy college semesters. Open Planner seeks to ease agenda making for students by parsing uploaded student syllabi for major assignment/exam dates and generate a personalized calendar the student can access from his/her account upon sign-up and syllabus upload. Once they have access to their personal calendar, students will be able to add events, delete and modify existing events, and customize their course calendars, giving them fast access to a customized and modifiable calendar without the time demanding task of looking through course syllabi and adding major dates one by one.

Indigenous communities have a deep-seated understanding of the importance and sacredness that their land has in their daily lives (native lands.ca); they have a deep sense of place. The primary objective of Native Meteorites (NaMe) is to amplify the work of the Native Earth | Native Sky (NENS) program by recognizing the critical importance of free-choice learning in STEM education and providing a different lens through which STEM can be made culturally relevant for students in Native American nations.
This project focuses specifically on meteorites found on the lands of the three Oklahoma Native American tribes participating in NENS and provides a concrete example of the cultural relevance of planetary science and STEM, utilizing concepts that are deeply rooted in a sense of place. The goal of this project is to increase the interest and participation of an underrepresented important people group in the national STEM workforce, as well as provide an example of the relevance of place-based STEM education for all individuals.
This project consists of an interactive map, which displays where relevant meteorites landed; and also provides supplementary resources for education. Members of the NaMe project will develop STEM resources that focus on meteorites found on Native American Lands. This will be unlike other free-choice learning because this interactive map caters specifically to indigenous peoples’ learning styles.
In collaboration with Native American individuals, the team designed the site layout, content, and imagery to be as inclusive and considerate as possible. The product of this project ultimately caters to an audience that is quite underrepresented– so we used conscious software development in the website-building process.
The interactive map feature of this site will increase the interest and participation of an underrepresented important people group in the national STEM workforce, as well as provide an example of the relevance of place-based STEM education for all individuals.

The system to be is BMW Performance Horse Database, also referred to as BMWPHD. The client is Brooke Wharton with BMW Quarter Horses. The purpose of her company is to breed and raise horses for reining and reined competitions. Currently this field faces the issue that horse data is spread over multiple different platforms that do not communicate with one another. With that, the main objective of BMWPHD is to create a user-friendly searchable database for the task of finding and ranking horses for breeding, buying, and determining show schedules. The users of this application include fans, riders, coaches, judges, and investors in the sport. The hope is to not only bring more fans to the sport through the easy access to data, but also improve the level of competition so that the horses can be bred stronger and therefore perform at a higher level within the sport. On the technical side, the system will be implemented with the following technologies: the frontend will use Vue.js, the backend will be implemented in Java Spring Boot, the database will be built in PostgreSQL. The final version of the application will be deployed on Heroku.

The Chinese Learning Platform(CPL) is a program to help students to learn the Chinese language. This platform will be used by both students of these ages attempting to learn Chinese as well as by the teachers who will use the platform as a teaching tool to help those students. As it is a teaching tool, the main motivation behind it is educational, with the hope to support students in learning the Chinese language, and in the future, this will be expanded to learning various other languages using the same CPL. The platform hopes to help these students utilize a textbook created by CPL, and will also include features that will help the students listen, read, write, and speak in the language they are learning.

The COVID-19 pandemic has made it difficult for families to stay connected, especially those separated by distance. Keepsake is a software product that was developed with the aim of helping families bridge the gap by enabling them to share stories and memories across generations. The platform provides a secure and private space where family members can record and post audio content that can be accessed by their loved ones anytime, anywhere via cloud storage.

Keepsake offers an intuitive user interface that is accessible to users of all ages, making it easy for them to navigate and listen to the audio content. By hosting the platform on Amazon Web Services (AWS), Keepsake provides a reliable and scalable solution for storing and retrieving audio files/posts across the years. The platform is designed to ensure that each family's audio files are separate and private from other family audio files, offering complete privacy to users.

To get started with Keepsake, users can easily join their families and start recording and uploading audio files. The platform allows for organization and sharing with specific family groups, making it easy to share stories and memories with those who matter most. Keepsake is a powerful tool for connecting families across generations, providing accessibility, convenience, and security for families of all sizes and backgrounds.

Power quality is the compatibility between the voltage that comes out of an electrical outlet and the power load that is being plugged into it. A power load (also known as electrical load) is any electrical device that needs to be plugged into a larger power grid to run, such as televisions and microwaves.
Different devices require different power loads to run at full efficiency and while electrical systems are capable of handling newer power loads, they are currently set to work with older ones as well. This may cause some side effects on power quality in the system. In this project, we investigate how to improve the power quality in the system caused by an inductive older load.

A Faraday cage is an enclosure that shields electromagnetic fields from entering or exiting the cage. While metals with high electrical conductivity are expected to effectively demonstrate the operation of a Faraday cage, preliminary observations of a sealed cast iron cylinder allowing the transmission of Bluetooth signals between a smartphone and wireless earbuds across it suggested the need for further research into electromagnetic wave propagation through closed metal systems. This research utilized Bluetooth connectivity tests through sealed metal cylinders made of cast iron, aluminum, and stainless steel to analyze the working of Faraday cages, explore related material properties, and isolate possible reasons for the conflict in expected behavior when electromagnetic transmission is detected through such cages. The research methods included conducting Bluetooth connectivity tests with different cylinder orientations and analyzing the strength of the transmitted and received Bluetooth signal. The key findings of this study suggest that material properties, spatial orientation, and the strength of the electromagnetic source influence the transmission of electromagnetic waves through sealed metal cylinders. The implications of these findings suggest potential exceptions to a common electromagnetic phenomenon and provide insights for future research.

Texas Instruments is developing a new micro-optical-electro-mechanical device called phase light modulator (PLM). The TCU senior design team developed a robust testing system that can expose 20 PLM devices to different light sources with the capability of monitoring the temperature and light intensity at each device location. The system design and construction of the testing system will be presented. In addition, the selection and operation of LEDs, temperature and light sensors, as well as the optical components that are needed for the light source and sensors will be discussed.

This research assesses the relationship between income per capita and the amount of maintenance received for the major roads across the State of Texas. Relevant datasets and analysis techniques such as demographic (census data), population density (distribution), road network, maintenance records, etc. will be carried out using ArcGIS Pro software. A series of maps highlighting analysis results derived based on the various parameters will be produced to provide a comprehensive overview of the relationship between the variables, if any, that would be useful for future decision-making.

Trees provide an array of benefits to urban communities, such as oxygen production, flood mitigation, air pollution reduction, increased property value, cooling effects, and cultural services. Tree distribution, however, varies across cities, impacting the delivery of these services from neighborhood to neighborhood. Research has shown that low-income neighborhoods are more likely to have less trees than wealthier neighborhoods, leaving these neighborhoods more vulnerable to health impacts, such as heat-related and respiratory illnesses. The purpose of this study is to analyze tree canopy cover in relation to a set of demographic variables at the US Census block group level to understand if inequities exist in Fort Worth, Texas. We used a geographic information system (GIS) to assess the extent to which age, race, income, and housing characteristics are related to tree canopy. We conducted a correlation analysis between percent canopy cover and the demographic variables. Preliminary results suggest that majority minority and low-income block groups possess less canopy cover than predominantly white, higher-income areas in Fort Worth.

The present study is aimed at comparing the annual income per household to amenities in districts within the Dallas Fort Worth metroplex. Several datasets and analysis results including the spatial distribution of public and private schools, school ratings, proximity to health facilities, parks, and other government provided services will be combined to investigate the research question. Some of the data analysis techniques that will be implemented using ArcGIS Pro include creating buffer zones which act as visual guides to better demonstrate comparisons and communicate the findings in an interactive way.

Each year, as much as 40 percent of food produced in the United States is wasted by producers or consumers. When food waste is sent to landfills, it competes for limited space and generates the greenhouse gas methane. Globally, food loss and waste represent 8 percent of anthropogenic greenhouse gas emissions. Restaurants are known to be a contributor to food waste, both in the kitchen and from consumers. The purpose of this research is to examine food recovery efforts of restaurants in Fort Worth. We sent a survey to 371 restaurants in Fort Worth asking about their food waste management practices. The survey was designed to document restaurants’ current food waste practices, interest in food donation and composting programs, and business characteristics. We analyzed the responses through descriptive statistics and other statistical methods to evaluate how practices varied by business demographics and type of establishment. From this survey, we discovered local barriers to food recovery and from these, we suggest forms of outreach or programming that would help restaurants to reduce food waste. We also used responses to identify and map ideal food waste drop-off locations for restaurants that the city could use to plan recovery efforts.

Urban forests are a common way to integrate nature into heavily populated areas. Urban forests provide a range of benefits to urban communities. Trees provide economic, social, and cultural benefits. For instance, trees provide opportunities for individuals to engage with the environment, reduce stress, and increase property values. Trees also contribute to ecosystem services as well by filtering air pollution, providing habitat for wildlife, and mitigating storm water runoff. The purpose of this research is to assess the biodiversity and the climate resiliency of trees in an urban forest in Arlington, Texas that was part of a program for environmental mitigation of a flood plain. To assess the biodiversity and climate resiliency of the area’s trees, we collected the following data: tree diameter measured at 4.5 feet above the ground (DBH), GPS coordinates of trees, species, and tree condition. We analyzed the data using the Simpson’s Biodiversity Index and the Shannon Diversity Index values to assess the biodiversity of present tree species and identify their climate resiliency. We compared these results to two Representative Concentration Pathways (RCPs) to understand the potential impact of climate change on the urban forest. Finally, we offer suggestions to increase the resiliency of this urban forest and the potential for incorporating these findings in future urban forest management plans.

At the Water and Society Lab at TCU, we are studying the presence of Escherichia coli (E. coli). The Village Creek tributary of the Trinity River is the subject of this testing, and it is one of the many water bodies monitored by the US Geological Service. Using information provided by the monitoring location alongside the data gathered from our research, we can assess and monitor the concentration of E. coli in the Village Creek.

Through weekly sample collection and analysis, we can determine the prevalence of E. coli in the Village Creek. Our method is to collect water samples, add EPA-approved Colilert testing chemicals, and incubate the samples at 35℃ for 24 hours. During analysis, the presence of E. coli is quantified by colony forming units (CFU). This research indicates whether or not the sample contains unsafe levels of E. coli. According to the Texas Commission on Environmental Quality and the US EPA, 126 CFU per 100 mL of water is deemed unsafe. In addition to recording CFU, we also document certain hydro-climatological variables such as ambient and water temperature, rainfall, and turbidity. Through these findings, we can be applied to water management and quality decisions throughout the Dallas-Fort Worth and north-central Texas regions.

Wildfires are a global concern as they are unpredicted fires that cause harm to their surrounding environment, local wildlife, and humans. The negatives of these wildfires outweigh the positives as their occurrence is natural but also caused by human negligence. This past year there were about 69,000 wildfires reported nationally; of these fires, 835 were from Colorado. This study assesses the risk of wildfires in Colorado by using GIS and spatial data to map fire risk and determine possible mitigation techniques through utilizing livestock.
For the past 20 years, Colorado has experienced their largest wildfires, and with no decrease in the number of wildfires each year, mitigation techniques are crucial. In determining what method to use, it is valuable to focus on all the factors that add to these fires, such as the amount of rainfall, elevation, humidity, human activities, and more. Multiple past studies have used livestock as a form of wildfire mitigation. Using grazers to eat the fuel these fires thrive on can decrease the spread of future fires. Grazers are an environmentally stable form of fire mitigation as they eat the vegetation and then process it to become nutrients for the soil. We can determine the areas of high risk in Colorado by assessing how the stated factors contribute to Colorado wildfires and see if grazers are a possible mitigation method.

The objective of this research is to conduct wind farm suitability analysis (for energy generation) with a focus on areas that either heavily rely non-renewable sources of energy (parts of Australia) or areas that have limited access to energy. The study will combine several spatial datasets (road networks, population distribution, high mean windspeed, etc.) and analysis products (proximity to roads, national grids, etc.) to determine, through the suitability analysis, whether the wind energy is ideal and economical source of energy for the investigated areas.

As we move further into the 21st century, Earth's functional processes are experiencing a steady shift, particularly in terms of climate and sea levels. Anthropogenic warming has accelerated the rise of sea levels and increased the frequency, intensity, and rainfall of cyclones and hurricanes. To investigate the impact of rising sea levels on storm surges in vulnerable areas, we utilized remote sensing and GIS technology to come up with an understanding of the influence land cover type has on flood intensity and assess the vulnerability of the Houston area based on storm surges from 2015 - 2022. Our findings underscore the critical need for urgent adaptation and mitigation measures to mitigate the risks associated with changing weather patterns and rising sea levels.