Research, Inquiry, and Creative Expression (R.I.C.E.) Poster Showcase 2023

This project aims to develop a triaxial vibrating sample magnetometer for the purpose of magnetic characterization of magnetic materials. Currently, there is only infrastructure for a biaxial setup which measures magnetic properties with respect to the X- and Y- axis. Our aim is to develop and implement a coil set that can measure magnetic properties in the Z-axis with the same sensitivity as the X- and Y- axes for the use of characterizing 3D printed magnetic filaments.

Interval-censored data occurs frequently in survival analysis, in which the event-of-interest of an individual is only known to belong to an interval. To compare the survival distributions of several treatment groups, various nonparametric test procedures have been developed, such as the G^{rho, gamma} family of tests. However, it is difficult to choose the correct values of the parameters. Alternatively, a linear rank-type test derived from the proportional reversed hazard model has been developed for interval-censored data. In this work, a new linear rank-type test is developed for interval-censored data based on the proportional odds (PO) model, which assumes a multiplicative effect of covariates on the odds of the survival function. A PO model should be used over a proportional hazards model when the hazard ratio is not constant over time. Simulation results show the efficacy of the test statistic against others, and two studies illustrate the applicability of the test.  

Our immersive research team collected qualitative on-site data throughout a summer on-campus residential TRIO Upward Bound program for high school students. This presentation aligns to the three undergraduate members of the multi-layer practitioner-research team, which was also comprised of MA, PhD, EdD, faculty, and staff research team members. Our research enacted the de-siloed ideals of the TXST LBJ Research Practitioner Model that we followed in our research. Findings included the following campus belonginess and success themes: (1) Showing up, (2) Networking, (3) Applying Yourself, and (4) Pride in Yourself. Even the easy transferability and applicability of the findings demonstrated the ideals of the TXST LBJ Research Practitioner Model we utilized in the study.

Chip-firing is a game played on a graph G, where a configuration of `chips' are placed on each vertex of G and are allowed to `fire' according to local rules. Chip-firing has connections to many areas of algebra, combinatorics, and physics, and it has recently found applications in divisor theory in algebraic geometry. Certain `superstable configurations' play an important role in the theory and are called G-parking functions in other contexts.

We consider a natural notion of superstable configurations on hypergraphs and study connections to chip-firing on digraphs induced by the hypergraph and vector parking functions. We prove that the superstable configurations and critical configurations can be recovered from digraph chip-firings by constructing orderings on the incidences. For regular complete hypergraphs, we find the explicit forms of the cut ideal generators and further show that superstable configurations can be counted by vector parking functions. 

Connected vehicles (CV) are vehicles equipped with advanced sensors that allow them to communicate with their internal and external environments. CV has the capability to exchange important data and information with other vehicles about their kinematic data (i.e., speed, direction, location, etc.) through basic safety messages (BSM). This real-time communication between these interconnected vehicles is essential for road safety but prompts potential targets for cyber-attacks. This research is a continuation of Griffith et al. [1] that specifically addresses simulating different faults and attacks from the same open-source dataset and proposes a consensus-based trust algorithm.

The STEM Communities Initiative at Texas State University has implemented the use of Learning Assistants (LA) in several introductory level STEM courses. At the end of each semester, a survey is administered to students enrolled across 10 different LA-Supported courses. The survey aims to measure students’ self-perceptions, sense of belonging, perceptions of Learning Assistants (LAs), and LA interactions in an LA-supported class. The data for Fall 2022 and Spring 2023 was analyzed by comparing the survey responses across the different courses for each semester. Kruskal-Wallis (K-Wallis) and Wilcoxon rank sum (Mann-Whitney U) tests were used to compare the survey responses across the courses to determine whether there were any significant differences among students’ STEM identities and sense of belongings among the LA-supported courses. The results found several significant differences among the courses which suggests having LAs in the classroom could impact students differently.

Cookies are a very effective mechanism to authenticate users and allow for more complex website functionalities. Unfortunately, the vulnerabilities in cookie functions may lead to abuse regarding user privacy and cyber-attacks such as cross-site scripting.

To address these concerns, cookie attributes such as SameSite, HttpOnly, and Secure were created as additional protocols to the web browser to deter attackers from exploiting cookies and overall improve web security while maintaining website functionality. However, not all websites implement these safety measures. In this project, we scraped the Set-Cookie header of the top, middle, and bottom 1000 websites. We then ran an additional script over the results to analyze patterns in the usage of cookie attributes as well as their settings to determine whether a sufficient amount of safety measures were considered.
 

In this work, we extend the classification of solvable primitive permutation groups to rank 5 along with novel bounding techniques and algorithms to do so.

This research aims to investigate the effects of temperature on the spread of COVID-19 cases across more than 3000 counties in the United States. To the best of our knowledge, this research project is the first to explore the causal relationship between temperature and COVID-19 spread using extensive panel data set covering the monthly period from March 2020 to December 2022. We employ various regression models that control county-level economic activities and population density to establish a causal relationship between COVID-19 spread and temperature. Our findings consistently indicate that higher temperatures have a negative impact on the spread of COVID-19. Additionally, we observe a decrease in COVID-19 spread when the unemployment rate is high and an increase in spread with higher population density. Our results reveal that even with higher temperatures, COVID-19 spread remains higher when the population density is higher. Through this investigation, we aim to contribute valuable insights to understanding temperature's role in the transmission dynamics of COVID-19.

Using multi-task learning, a type of machine learning method, we aim to categorize behavioral risk factors of binge drinking and poor mental health by analyzing the CDC's 2021 BRFSS dataset.

This research focuses on the process improvement of a pneumatic press used to punch pen covers. The emphasis is on increasing operator efficiency along with improving safety. It is a comprehensive study that uses the DMAIC methodology, simulation software, time-studies and the Maynard operation sequence technique to optimize the workbench’s design and flow. The implementation of these advanced designs aims to reduce the cycle time while allowing the operators to efficiently monitor and control the workflow of the pneumatic press.

Electroactive polymers (EPs) have tunable properties when a potential is applied. Changes among EP oxidation states allow a change in volume, porosity, color or conductivity and give rise to applications. Commodity polymers are mechanically robust with a high molecular weight to provide an adequate chain entanglement that can be processed into nanofibrous sheets via electrospinning. Nanofibers are porous and provide a high surface area for modifiability. EPs typically do not have high surface area, and alone are not able to electrospin nanofibers. Electrospinning allows for the combination of desirable conductive properties of the EPs with the mechanical properties of a commodity polymer to be formed. Discussion will include synthesis of a graft polymer via Huisgen 1,3 dipolar cycloaddition (click chemistry) followed by chemical oxidative polymerization will be explored. The polymer modification will be using Poly(propargyl glycidyl ether) (PPGE) as the backbone polymer, with the attachment of an electroactive monomer via click chemistry then will be polymerized.

Current estimates suggest as many as 1 in 3 college women will experience sexual violence at least once, with most victims experiencing sexual violence on multiple occasions. An all-encompassing non-legal term, “sexual violence” refers to multiple crimes such as sexual assault, rape, and sexual abuse. While sexual assault takes many forms, the term sexual assault generally refers to sexual contact or behavior occurring without explicit consent. There are many approaches to defining consent including active and passive consent. Accurately defining sexual assault and consent has been identified as a key component to preventing sexual violence on college campuses. Therefore, the purpose of this study is to analyze college student’s definitions of sexual assault, including their interpretation of consent. Public health personal and university officials can use this information to develop comprehensive policies and educational practices to increase correct and accurate definitions of sexual assault to promote sexual equality and violence free campuses.  

Recent research has determined that soil organic matter (SOM) is one of the best indicators of soil health. Its measurement is therefore vital to understanding soil fertility and productivity. The traditional method of measuring SOM content is expensive in terms of cost, labor, and time. In this research, smart technologies are combined with the goal of predicting SOM content in a way that reduces those expenses. In the last decade, the advancement of technology and the Internet of Things has led to increased affordability in hyperspectral drones, in-ground sensors, and wireless devices. This work pursues the creation of a large-scale, multi-sensor array for real-time, wireless data collection and the use of sensor-and-drone-gathered data to predict SOM content with machine learning. Multiple machine learning models are explored, including linear regression, polynomial regression, and dense neural networks.

Pipelines repair and maintenance incur significant costs to industries, amounting to billions of dollars annually, while also posing health risks to local wildlife and contributing to water pollution. The traditional pipe inspection method is not only time-consuming but also endangers worker's life due to pressure-related issues and underwater hazards. With the current advancement of technology especially in the field of artificial intelligence, the research seeks to utilize, the most advanced object recognition technology available, YOLO  v8, to detect standard defects in pipes relying on the primary source data collected. The goal is to create a highly reliable and efficient model that enhances the accuracy of results while simultaneously ensuring worker safety and reducing operation costs. 

Our project compares the effectiveness of Long Short-Term Memory (LSTM) and Transformer machine learning models in the task of fall detection using a smartwatch.  The work is a continuation of research on a previous LSTM fall detection model that displays high recall but low precision, influencing its effectiveness. The new LSTM and Transformer models were trained on x,y, and z right wrist acceleration data collected from 12 student participants simulating daily activities such as walking, drinking, hand-waving, etc., and performing simulated falls. The knowledge from the trained models was transferred to create a watch model for testing model effectiveness in real-world scenarios.

Hot embossing is a cost and time effective process for accurate replication of polymer microstructures. The relatively low temperatures limit heat-related shrinkage while also maintaining a high degree of reliability. When hot embossing, the thermoplastic substrate is brought past its glass transition temperature, Tg, where it becomes less viscous. This allows for more accurate replication than cold embossing, but can still struggle when the sample is required to mate against the side of a structure on a master mold. As manufacturers often use hot embossing for its cheap, yet accurate replications, knowing the most critical conditions would allow manufacturers to focus on certain aspects of the process and standardize. As temperature is one of the most important factors in this process, the goal of this research is to find the most suitable temperature for accurate replication. 

Hispanic students traditionally underperform in first-term General Chemistry (GC1). This study sought to identify if incorporation of Learning Assistants (LAs) into the classroom can improve overall student success whilst reducing inequalities in GC1 performance. Demographic and performance data from over 5000 GC1 students was analyzed for academic years 2021-2022 (non-LA based) and 2022-2023 (LA-based). Performance factors collected include the final grade achieved, overall and subcategories of American Chemical Society (ACS) Exam scores. Statistical differences were explored using Kruskal Wallis and Wilcoxon Rank-Sum tests with respective Bonferroni corrections. It was found that in the overall and Hispanic student population, LA supported students have greater success than non-LA supported students. Furthermore, the difference in academic performance when comparing Hispanic and non-Hispanic students is reduced in a LA classroom setting.

Sexual communication is defined as the ability to communicate requests between sexual partners. People who speak about condom use, STDs, sexual histories, and boundaries are likelier to use protection overall. The paper dives deeper into communication between parents, peers, and between partners and measures the barriers and benefits of each influential person in a college student's life. Self-efficacy and sexual communication are also examined to determine how confidence influences a college student's ability to use condoms consistently and correctly. 

Risky sexual behavior is defined as having sex at an early age, having more than one sexual partner, and not using condoms  or other contraceptives (CDC, 2019). Consistent and correct use of male (external) latex condoms can reduce the risk of STI transmission (Daniels & Abma 2020). Although Hispanic/Latino populations use condoms less consistent compared to other racial/ethnic groups, only two articles met the inclusion criteria for this review. The majority of articles excluded during full text review (n=32) were excluded because the study did not directly examine condom use among Hispanic/Latino college students. From the two articles included in the review, culture was the major theme affecting condom use among Hispanic/Latino college students. 

LARP6 is a member of the La-related protein (LARPs) superfamily that binds to mRNAs to control gene expression. To probe the evolution of LARP6 in eukaryotes, we have characterized the strucutre and activity of the LARP6 from the simple four-celled algae Tetrabaena socialis. Structural characterization using limited proteolysis and circular dichroism demonstrated that the TsLa Module was stably-folded. A Förster resonance energy transfer (FRET) assay showed that TsLa Module exhibited no RNA chaperone activity, in contrast to the LARP6 La Modules of higher eukaroytes. 
Therefore, we conclude that TsLaRP6 exerts weak RNA binding activity, but its cognate ligands and cellular function are distinct from those of the previously-characterized LARP6 proteins from animals and vascular plants.

The road profile, comprising surface shape and elevation, plays a crucial role in various aspects of vehicle dynamics, such as handling, fuel efficiency, ride comfort, maintenance cost, and tire wear. Although previous profile estimation methods have shown success, there is growing interest in integrating advanced data collection technologies to attain cost reduction, improved accuracy, and enhanced overall efficiency in road management. To address this, the study aims to validate a conceptual model for road profile estimation, using friction and wear testing as the primary methodology. Through an extensive comparison, this study will evaluate the conceptual model through its accuracy, results, and necessary resources against traditional profile estimation methods. 

The goal of this research is to determine how exposure to ultrasound radiation impacts growth rates and disease resistance in Arabidopsis plants. Several different treatment groups were formulated to determine what amount of time and intensity of exposure if any is optimal for improving plant robustness. I exposed the samples to daily ultrasound radiation for two weeks and kept record of growth benchmarks such as the number of leaves and the height of the stems. After the treatment was completed, the samples were inoculated with pseudomonas to determine their response to the pathogen.  

This project is designed to test the viability of multiple patterns of tread design, primarily aimed at existing patterns for shoes. The tests included deformation, abrasion, and friction testing. In addition to varied designs, two types of material were tested as well to compare results.

The oxygen evolution reaction's (OER) slow kinetics and the high cost of OER catalysts, such as iridium oxide (IrO2), limit widespread adoption of electrolysis for hydrogen production. Ruthenium oxide (RuO2) is a promising OER catalyst for its decreased cost and increased activity compared to IrO2; however, RuO2 lacks stability. Our project aims to improve RuO2 stability by substituting zirconium (Zr), an OER-stable metal, into RuO2 with high energy ball milling. We examine the effect of Zr concentration, milling duration, and ball milling material on the structure and composition of ruthenium-zirconium oxides with x-ray diffraction, scanning electron microscopy, and energy dispersive x-ray spectroscopy. Preliminary results support that high energy ball milling enables Zr substitution into the rutile RuO2 lattice at low Zr concentrations. Initial data also suggests that milling time and grinding materials influence the phase integration and extent of contamination from milling materials.

Azobenzene is a widely found organic chromophore with the ability to undergo reversible cis-trans isomerization. When exposed to UV irradiation, it forms a metastable cis-isomer, which can return to the trans-isomer through spontaneous thermal isomerization or photoisomerization using visible light. Azobenzene offers several advantages, such as photostability and easy synthesis of derivatives. Our research concentrates on identifying structures where both cis- and trans-isomers exist in a liquid state and systems where the melting point (MP) of the cis-isomer is higher than that of the trans-isomer. These unique characteristics open up possibilities for using this compound in Solar Thermal Fuels. Azobenzene's capacity to capture photon energy through photoisomerization to the cis-isomer, followed by a reversion to the trans-isomer and heat release, makes it an appealing candidate for such applications.

Scanning Tunneling Microscopy (STM) has revolutionized atomic-scale visualization since the 1980s, but its high cost has prevented widespread adoption. To address this, our research project embarked on developing a Low-Cost STM (budget: $500.00 USD). We aimed to create an affordable STM for atomic resolution imaging while promoting interest in materials science.

Referencing Dan Berard's work, we adopted a resourceful approach to building the STM from scratch. The 3D-printed body, integrated hardware, and GXSM3 software facilitated varied scans of conductive surfaces, enabling visualization of different areas of the gold sample. Implementing vibration isolation techniques ensured optimal STM performance. Promising images have been captured, and parameter testing is ongoing.

Future work involves creating an operational manual and replacing the STM tip with an AFM tuning fork for enhanced capabilities. Our Low-Cost STM has the potential to revolutionize materials science education and research, making atomic imaging accessible to a broader audience.

This abstract presents an innovative application framework designed to harness the power of GPUs for simulating and gathering performance data. The framework employs the dashing framework to visualize and analyze hardware counters and their functionalities. Through an in-depth examination of specific hardware counters, this framework enables the optimization of applications. By combining the capabilities of GPUs with hardware counter analysis, the proposed approach offers a promising solution for enhancing application performance and efficiency.

Pseudogymnoascus destructans (Pd) is a fungus that is responsible for white-nose syndrome (WNS) in bats.

Main question – Does localization have an effect on BLP–mediated Cu trafficking?

Create a set of Pd BLP chimeras to select localization to the plasma membrane or cell wall.

Detecting whether BLPs are cell wall or cell membrane.
 

Many fuels and fine chemicals can be prepared by visible light photoredox catalysis, whereby a dye undergoes excitation and then engages in electron transfer with a redox catalyst. Ruthenium diimines, are good dyes because they have high molar absorptivities, are redox-active and are robust. Here, we challenge whether these complexes are indeed robust. Given that ion pairing is important in catalysis, we study the affinities that ruthenium diimines have for different anions. Moreover, we compare the ruthenium complex salts to iron analogs. We find that ruthenium diimines - particularly bipyridine moreso than phenanthroline - undergo proton- and electron-transfer. These results are relevant to designing better molecular catalysts.

Hispanic/Latinx workers are overrepresented in the agricultural sector, which has long been recognized as one of the most dangerous occupational sectors in the United States (Bethuel et al., 2021; Castillo et al., 2021; Luque, Bossak, Davila, & Tovar-Aguilar, 2019). In addition to the physical, environmental, and occupational factors increasing farmworkers vulnerability to occupation associated illnesses, injuries, and fatalities, Hispanic/Latinx farmworkers possess unique cultural characteristics further exacerbating their risk for adverse occupation associated health outcomes (Castillo et al., 2021; Hansen & Donohoe, 2003). Despite the increased risk for and prevalence of adverse occupational health and safety outcomes among Hispanic/Latinx farmworker populations, these workers report among the lowest levels of healthcare utilization and access nationwide. The present study will identify physical and cultural barriers impacting healthcare service utilization and access in a vulnerable population of Hispanic/Latinx farmworkers in the Rio Grande Valley. 

Piezoresistive sensors are made from materials whose resistivity is dependent on applied stress. We are interested specifically in piezoresistive sensors that can be 3D-printed from conductive composites and maximizing their sensitivity by altering their design and material composition. After refining the printing process itself, several rounds of printing allowed for the optimizations of potential designs for sensors. A working resin and silver-nanowire composite proved more challenging than anticipated to make, so ultimately, the testing phase did not cover piezoresistivity or sensitivity at all. Data collected from compression tests on nine samples showed various trends and properties of their respective geometries. Further studies should build on this research once a composite is successfully developed. Then, a correlation between mechanical and piezoresistive properties may be assessed, allowing for more efficient and systematic design techniques to emerge via computer simulation.

Neuroblastoma is a type of childhood cancer that develops in the nerve tissue and spreads to the adrenal glands, spinal cord, or neck, creating immature nerve tissue. MicroRNAs (miRNAs) can have an oncosuppressive effect and induce neuroblastoma cell differentiation. Systemic delivery of miRNAs is not possible due to their low stability in the presence of physiological fluids that include nucleases. Our project aims to develop biodegradable poly(lactic-co-glycolic acid) (PGLA) / polyethyleneimine (PEI) nanoparticles to deliver miRNA to neuroblastoma for differentiation into healthy nerve cells. First a PEI/miRNA polyplex was prepared to stabilize the RNA. The molar ratio of PEI:miRNA was optimized, and complex formation was confirmed via gel electrophoresis, zeta potential and dynamic light scattering. The polyplex was then encapsulated in PLGA nanospheres and the size, zeta potential, morphology, and miRNA encapsulation efficiency of the nanoparticles were characterized. Future studies will evaluate the oncosuppressive effect of the nanoparticles. 

Analyzing a cognitive state called aleifs. More specifically, looking to see if aliefs were experienced when participants were presented with information and questions about a hunting contest called predatory calling contests. 

In this project, the photochemical reactivity of a diamidocarbene, which had been explored previously, was examined using a variety of alkanes with differing characteristics looking for selectivity preferences with and without steric hindrance while also looking for the formation of alkene products due to the presence of the compound DAC-H2 seen in previous experiments. C-H insertion was shown to occur with each of the alkanes explored and preferences regarding selectivity of tertiary over secondary, over primary C-H bonds was shown, with tertiary C-H insertion being favored overall. DAC-H2 was shown to be a more prevalent product when more tertiary C-H bonds were available for insertion. This showed that alkenes were being formed in larger amounts as well which was expected due to the inherent stability of the more heavily substituted alkenes that would be formed. 

The RNA-binding protein LARP6 regulates the cellular localization of mRNAs for protein synthesis. The intrinsically-disordered C-Terminal Domain (CTD) of LaRP6 is predicted to phase-separate, forming globules through self-association. This prediction providing an attractive model in which LARP6 may associate with other phase-separating cellular components to modulate mRNA localization. To determine whether the CTD phase separates, we produced a construct that expresses an N-terminal fusion of the green fluorescent protein (GFP) to the CTD. The construct was readily expressed in E. coli, but the initial purification under native conditions resulted in substantial protein degradation. An alternative purification approach under denaturing conditions successfully produced GFP-CTD protein at ~85% purity and 12 µM. This protein will be used for in vitro tests of phase separation using both turbidity and fluorescence microscopy.

TEL-045 is a novel perylene diimide (PDI) bearing polyether side chains that displays reversible, temperature dependent remodeling of two spectroscopically distinct H- and J-type self-association forms. We believe this PDI is the first report of reversible, temperature-dependent switching between H- and J-type self association of simple, non-chromophore-modified PDIs. TEL-045 exhibits temperature-dependent self-association due to its novel imide substituents. We synthesized analogs that modified the position and presence of the methylenedioxy group to investigate why. We describe the synthesis of these two analogs and explore their self-association behavior in solution by utilizing UV/Vis and fluorescence spectroscopy. By running these spectroscopy techniques at varying solution temperatures, we are able to determine how TEL-045 differs from its structurally modified analogs in self-association behavior.

Studying the equilibrium of an imine synthesis using a Quadrupole Electrodynamic Trap to analyze the mechanism and driving forces behind microdroplets and their catalytic ability. 

Coral reefs are some of the most biodiverse ecosystems in the world. One of the biggest threats facing these ecosystems is coral bleaching, the breakdown of symbiosis between the coral and their algal symbiont. Bleaching events can be caused by multiple stressors including temperature and light. As marine heat waves increase in severity and frequency, it is crucial to understand how changes in symbiotic relationships affect coral fitness, and more specifically their immune system. The model anemone Exaiptasia diaphana is closely related to corals and is used to study these relationships. In this study, anemones were exposed to heat and light stress to induce bleaching. Before, during, and after the stress period, we collected samples to track symbiont density and immune response. The data generated in this project will provide insight on how anemones and corals respond to multiple stressors and how symbiosis affects their fitness and immune capacity.

Utilizing an Iro3D Model-C sand printer, 11 sand molds of varying parameters were created for the purpose of testing the surface roughness of each one. Instead of testing the surface itself, a pattern was created and 11 identical molds were made from the pattern using no-bake sand. Each mold had an insert for each sand print and aluminum castings were made from the molds. The imprint of the sand print that was made on the aluminum was then measured for surface roughness and conclusions were made as to which combination of parameters gave the print the best surface finish.

AWS DeepRacer is a fully autonomous 1/18th scale race car designed to help developers learn and practice reinforcement learning through cloud-based simulations and real-world racing. In the AWS training environment, there are multiple modes in which you can run training simulations and evaluations in. These modes include Time Trial, Object Avoidance, and a relatively new mode: Head to Bot. The research done in this project was primarily focused on testing reward functions in the Head to Bot mode as well as developing a research function that would be suited for training in this new Head to Bot mode. The developed algorithm outperformed the default Centerline reward function, as well as the Object Avoidance reward function. 

Organic synthesis is extremely important in testing and manufacturing pharmaceutical drugs. In fact, many modern drugs such as biphenomycin, vancomycin, and antitumor agents (ellagitannins) have been synthesized using cyclic amino acid derivatives. In our previous studies, a specific amine was employed for the electrochemical oxidation to produce a heterocyclic compound, which contained two enantiomers in equal amounts. Furthermore, the corresponding imine analogues can also give the same cyclic amino acid derivatives. When the imines were made from chiral aldehydes with the specific amine, one of the enantiomers can be generated in more predominant yields by electrochemical oxidation. In this study, we will synthesize two unique chiral aldehydes for a similar investigation to examine whether it can improve the product yield of the enantiomers as well as their distribution. 

Molecular biology laboratories all across the world analyze and purify DNA molecules using gel electrophoresis. Purification of DNAs by extraction of bands from agarose gels is frequently accomplished using commercially available kits; these kits simplify the process, but they are also expensive. We have developed a new extraction method based on the observation that liquid water inside a gel expands when it freezes, causing disruption of the gel matrix, and is then spontaneously expelled upon thawing. Several experiments have been performed to optimize a protocol for purification of both linear and circular DNAs from agarose gels. The new method is rapid, uses instrumentation found in most laboratories, and is much less expensive than extraction using commercial kits.

Connected Vehicles are estimated to comprise 95% of new car sales by 2030, and with this growing market comes the need for better cybersecurity approaches. Current algorithms based on assigning reputation scores to CVs perform well when the majority of the network is benevolent. However, their performance is decreased in majority-malicious conditions. The aim of this project is to apply a mathematical model of social psychology to improve reliability within CV networks. The resulting algorithm is able to detect whether a car is benevolent or malicious in networks that are up to 98% corrupt, outperforming comparable algorithms.

We continue the study of the prime graph (Gruenberg-Kegel graph) of finite groups. The prime graph of a group Γ(G) has the prime divisors of |G| as vertices, and there is an edge between p and q if there is an element of order pq. Primes graphs of solvable groups as well as prime graphs of groups with K_3-groups as composition factors have been completely classified. In this paper, we classify some prime graphs of groups with K_4-groups as composition factors. For the other groups, we give partial classifications and develop general techniques that allow us to demonstrate 3-colorability and triangle-limited in almost all cases.