草榴视频

Mentor: Chinasa Elue

Reimagining College Support: A Critical Exploration of the Impact of Grief and Loss on the Experiences of International College Students

International student attrition is a rising concern in higher education given the various challenges that have arisen over the past couple of years (Donohue et.al, 2021). The onset of the COVID-19 pandemic, the racial justice movements, and the current social political climate have significantly impacted our college students like never before (Borgstrom & Mallon, 2022).  Of growing concern is the rising mental health crisis that is sweeping through higher education which deserves an urgent response, especially for international students navigating unfamiliar academic and cultural terrains (Lee et al., 2021). International students are currently facing dire financial constraints, food and housing insecurity, and many other challenges that further complicate their college experiences (Duke et al., 2021). For incoming international freshman students, their college transitions are considerably different from traditional students. Specifically, international students鈥� college transitions are muddied from their various high school experiences in other countries, assimilation difficulties, and living sometimes hundreds of miles away from home. Further, the grief, loss, and trauma experienced by these first-year international college students during the pandemic warrant special attention as we contemplate the resources and support required for their successful matriculation and degree completion (Sirrine et al., 2021).). The lingering remnants of grief and trauma from the global pandemic continue to impact the college experiences of international students and their ability to successfully navigate their academic and professional goals. Hence, through a qualitative research design, our research explores the lived experiences of international college students. Specifically, our research question investigates the extent to which grief and trauma resulting from COVID-19 have influenced the educational journeys of these international students. The goal of this research is to provide an opportunity to explore and identify strategies for better supporting international students as they navigate the complexities of their academic journey, fostering an inclusive and nurturing environment that promotes their academic and personal growth.

Mentor: Jayoung Choi

Supporting Multilingual, Immigrant-Origin Students

The research project, Supporting Multilingual Learners and Their Teachers, Parents, and Communities (MLTPC), aims to enhance educational experiences for immigrant-origin and language-minority learners in our schools and communities locally and internationally. Embedded in the large MLTPC project are three current and inter-connected research projects: (a) Dual Language and Bilingual Education (DLBE) programs, with a focus on one Korean-English DLBE (KDLBE) program in a public elementary school in Georgia, (b) trilingual families鈥� languages practices from justice-oriented perspectives in the United States, and (c) bilingual education for ethnolinguistically minoritized populations in South Korea. 

1. DLBE Research 
In this university and K-12 school partnership research, I aim to (a) longitudinally and qualitatively examine the experiences of multiple stakeholders (i.e., students, teachers, parents, and administrators) and (b) enhance teaching and learning in the new KDLBE program at Parsons Elementary school. 

2. Trilingual Research 
I examine the macro-level issues (i.e., political, cultural, social, and racial factors, and language policies in schools and districts) as well as micro-level influences (i.e., linguistic and family backgrounds, language variety, language prestige, family鈥檚 cultural identities, family members鈥� agency, and family language policies) pertinent to trilingual families鈥� language development and maintenance.

3. Research on Bilingual Education for Immigrants in South Korea 
I examine diverse perspectives and experiences of stakeholders involved in educating ethnolinguistically minoritized students in South Korea, which has recently undergone a significant demographic change due to the influx of immigrants as well as inter-racial and -ethnic marriages. This research contributes to the current discussion of race, language, and immigration in the South Korean context, with the larger goal of providing transformative and decolonizing education for students who speak socially stigmatized and minoritized languages. 

The collective, inter-connected research projects described above aim to unpack the ways in which language, culture, identity, agency, power, and ideology affects learning and teaching for immigrant multilingual learners. Through the MLTPC project, this research team hopes to support teachers and immigrant families in disrupting the pervasive monolingual ideology and advocate for a more multi-lingual and -literate society.

Mentor: Preethi Titu

Exploring Preservice Teachers' Experiences of STEM Integration in an Integrated Science Course 

Recent STEM (Science, Technology, Engineering, and Mathematics) education reform initiatives call for integrated STEM education approaches in which students learn how to solve problems by connecting content and practices of various STEM fields. These reform efforts advocate 鈥渞estructuring curricula that emphasize explicit integration of STEM鈥� (NRC, 2014, Ring et al, 2018). To accomplish this successfully, it is critical to prepare our undergraduate science preservice teachers (PSTs) for teaching STEM-subjects through integrated approaches. Teacher educators face the need to design and provide teacher education programs that prepare teacher candidates to adopt this evolving context of STEM education and teach STEM through integrated approaches. A curricular approach that integrates STEM learning provides students with opportunities to engage in real-world problems while learning STEM disciplinary ideas and practices. Researchers have indicated that integrated STEM teaching approaches have enhanced science content knowledge, scientific understandings, and higher-order thinking skills. (Becker & Park, 2011; Wells, 2016). To that end, the purpose of this study is to explore how science pre-service teacher education students enrolled in the integrated science course experience STEM. The research questions guiding the study are: 

1. What are the views of pre-service teachers towards STEM integration in an integrated Science course?
2. What are the experiences of pre-service teachers with STEM integration and pedagogy after participating in STEM activities within the integrated Science course? 

Discussion posts, surveys with open-ended questions and interviews will be used as data sources to collect participants' views about STEM, STEM application and student success. This study will use the principles and techniques of grounded theory (Miles & Huberman, 1994) as the methodological approach. Qualitative analysis of the data will be conducted using Dedoose software, applying inductive coding techniques outlined by Corbin and Strauss (2015). 

Mentor: Liang Zhao

Towards a Resilient Federated Edge Intelligence: A Testbed for Design, Analysis, and Validation of Federated Learning

In recent years, with the popularization of Artificial Intelligence, there has been an increasing necessity to train Machine Learning (ML) models. One of the best approaches to train such models while preserving the end-user's privacy is Federated Learning (FL). FL is an ML approach in which a central device coordinates multiple other devices to solve machine-learning problems (Bharati et al.). By doing so, FL enhances data privacy, as it never has to be sent to a central server and can instead be trained on devices locally. Therefore, while FL is uniquely positioned to be both efficient and privacy-preserving, it also confronts the challenge of optimizing communications between devices. This has led to the proposal of various communication schemes to expedite the FL process in resource-limited wireless networks.

However, the unreliable nature of wireless channels have been less explored due to simulations often happening on a single computer. Therefore, there needs to be more understanding of the performance of FL under unreliable communication in real-world distributed low-power IoT devices. Hence, this project aims to develop a testbed for evaluating FL under unreliable communication.

The proposed testbed substantially benefits researchers and developers working on real-world federated learning systems. It provides them with a valuable platform for conducting proof-of-concept implementations and performance validation, crucial steps prior to deploying and testing their machine learning models in real-world network scenarios. Furthermore, the proposed system will have scientific impacts on various applications, such as scientific machine learning and critical infrastructure, where data privacy challenges are significant concerns.

Mentor: Kazi Islam

Understanding Susceptibility of Adversarial Attacks in multi-modal systems and Development of Mitigation Techniques

With the advancement of Artificial Intelligence (AI) technology, it is used in every part of our lives, e.g., remote sensing, healthcare, finance, security systems, autonomous vehicles, cybersecurity, and transportation system. Although AI achieved state-of-the-art performance in multimodal systems, e.g., remote sensing, actors can utilize adversarial attacks to access and manipulate the AI-based system. The attackers can use adversarial example attacks to craft a poison sample in the inference phase to predict incorrect information or perform a model poisoning attack to steal confidential data.

In this project, students will develop tools to identify the susceptibility of these adversarial attacks and develop mitigation techniques against these attacks. Students will explore the potential security vulnerabilities primarily in multimodal systems but can be extended according to research findings. Student must read research papers, government websites, newspapers, and white papers to prove their hypothesis. Students will learn and apply machine learning algorithms and adversarial attacks to demonstrate their hypotheses empirically. 

Mentor: Xinyue Zhang

Privacy-Preserving Deep Learning for Medical Data with Generative Adversarial Networks

With its countless applications, machine learning has become an integral part of our lives. In recent years, deep learning also holds a great promise in revolutionizing healthcare and medicine. Moreover, our increasing dependency on machine learning applications presents a growing need to protect sensitive data especially for medical data. Machine learning models, dependent on extensive datasets, can inadvertently memorize training data, making them vulnerable to threats like model inversion and membership inference attacks. For example, in model inversion attacks, even with only public API access, attackers can potentially reconstruct training samples. This research aims to propose a privacy preservation approach from a different perspective that is to protect the privacy of training data samples from the source. We investigate the feasibility of training machine learning models using only synthetic data produced by Generative Adversarial Networks (GANs) protected by differential privacy (DP), eliminating the use of raw data samples. Given the sensitivity of medical data, we will evaluate the proposed method with the CheXpert (chest X-ray) dataset and the MIAS (mammography) dataset. In the experiments, we will evaluate the efficacy of synthetic data against raw data from the two datasets in training machine learning models and verify the protective capabilities of GANs. Using the two medical datasets, we will also examine performance of the models to determine the potential trade-offs between privacy preservation and the robustness of a machine learning model.

Mentor: Scott Nowak

How do We Build a Muscle? Let Me Count the Genes...

The process of muscle formation requires the careful coordinated expression of a number of genes both unknown and unknown during embryonic development. We use the fruit fly, Drosophila melanogaster, as a model organism to study the formation and patterning of muscle in the developing embryo.  Key to this process is akirin, a nuclear protein that is essential for expression of a variety of muscle patterning genes.  We have a small number (i.e., 35) known or predicted gene loci that are likely candidate interactions with Akirin during Drosophila muscle development.  This project will involve creating novel genetic lines and collection of embryos from these genetic lines for analysis of their muscles. This project will use both classical and molecular genetic techniques to uncover new genes that interact with akirin during muscle patterning.  This project will also involve high-resolution confocal microscopy to describe the phenotypes of uncovered genes.

Mentor: Masafumi Yoshinaga

Search for Novel Arsenic-Containing Antibiotics

Arsenic is one of the most persistent and ubiquitous environmental toxins. To overcome this problematic element, life has evolved and acquired a number of arsenic detoxifying mechanisms. Bacteria, due to the immense environmental adaptability and biochemical versatility, have even flexibly devised various ways to utilize arsenic for biological functions such as energy production, osmotic adjustment, phosphate sparing, etc. Our recent studies indicate a new way of bacterial arsenic utilization 鈥� offensive weapons. Notably, bacteria wage 鈥渁rsenic wars鈥�, where some members weaponize environmental arsenic, synthesizing arsenic-containing antibiotics to kill neighboring competitors, while others develop countermeasures against the arsenic weapons. This new emerging 鈥渂acterial arsenic wars鈥� concept provides a new dimension to understanding the arsenic biogeochemical cycle and brings new perspective to environmental arsenic biochemistry, as well as leads to discovery and development of new and potent antimicrobials.

In this project, students will explore novel arsenic-containing antibiotics using 1) prospective bacterial strains that possess novel gene(s) involved in arsenic metabolism/transformation, 2) a genetically manipulatable bacterial strain (Escherichia coli) engineered with the novel gene(s), and/or 3) purified protein(s) encoded by the novel gene(s). The expected outcomes are identification and characterization of 1) novel arsenic-containing antibiotics, and/or 2) novel genes/proteins that carry out novel reaction on arsenic.

The dramatic increase in bacterial resistance to antibiotics is a grave threat to global health. A dearth of new antibiotics has fostered the emergence and spread of drug-resistant bacteria, resulting in an increase of serious infections with high mortality rates. To overcome this serious health concern, discovery and development of new antibiotics are urgently needed. The future and long-term goal of this project is to demonstrate the potentials of arsenic-containing antibiotics to establish a new pipeline for our shrinking antibiotic arsenal.

Mentor: Masafumi Yoshinaga

Search for Novel Arsenic-Containing Antibiotics

Arsenic is one of the most persistent and ubiquitous environmental toxins. To overcome this problematic element, life has evolved and acquired a number of arsenic detoxifying mechanisms. Bacteria, due to the immense environmental adaptability and biochemical versatility, have even flexibly devised various ways to utilize arsenic for biological functions such as energy production, osmotic adjustment, phosphate sparing, etc. Our recent studies indicate a new way of bacterial arsenic utilization 鈥� offensive weapons. Notably, bacteria wage 鈥渁rsenic wars鈥�, where some members weaponize environmental arsenic, synthesizing arsenic-containing antibiotics to kill neighboring competitors, while others develop countermeasures against the arsenic weapons. This new emerging 鈥渂acterial arsenic wars鈥� concept provides a new dimension to understanding the arsenic biogeochemical cycle and brings new perspective to environmental arsenic biochemistry, as well as leads to discovery and development of new and potent antimicrobials.

In this project, students will explore novel arsenic-containing antibiotics using 1) prospective bacterial strains that possess novel gene(s) involved in arsenic metabolism/transformation, 2) a genetically manipulatable bacterial strain (Escherichia coli) engineered with the novel gene(s), and/or 3) purified protein(s) encoded by the novel gene(s). The expected outcomes are identification and characterization of 1) novel arsenic-containing antibiotics, and/or 2) novel genes/proteins that carry out novel reaction on arsenic.

The dramatic increase in bacterial resistance to antibiotics is a grave threat to global health. A dearth of new antibiotics has fostered the emergence and spread of drug-resistant bacteria, resulting in an increase of serious infections with high mortality rates. To overcome this serious health concern, discovery and development of new antibiotics are urgently needed. The future and long-term goal of this project is to demonstrate the potentials of arsenic-containing antibiotics to establish a new pipeline for our shrinking antibiotic arsenal.

Mentor: Mohammad Halim

Development of Therapeutic Peptide Conjugated with Blood-Brain Barrier Penetrating Peptide for Alzheimer鈥檚 Treatment

Alzheimer鈥檚 Disease (AD) is one of the costliest diseases for the American people, both in terms of the money spent and human suffering that it creates. Americans spent over $300 billion in treating over 6 million patients with AD in 2020 alone. AD is a neurodegenerative disease that produces tangles and plaques within the brain, diminishing cognitive functioning and memory in those who are afflicted with the disease. It has been theorized that the accumulation of amyloid-beta protein may be the cause of the progressive neurological disease known as Alzheimer. While there is currently no known cure, there are some small molecule drugs on the market that can help to lessen symptoms in mild to moderate forms of the disease. However, small molecule drugs have low target specificity and higher toxicity. Beside small molecule drug, several peptide-based drugs have been entered to the clinical trials, however, they failed because they could not effectively cross the blood-brain barrier (BBB). In this research, Iona will design and develop therapeutic peptide conjugated with BBB-penetrating peptide and test their inhibition efficiency against the amyloid beta fibrils. 
In last decades, peptide-based drug received countless attention, as they are highly selective, well-tolerated, and have less adverse effects. There are ~70 therapeutic peptides on the market, ~200 in clinical trials, and ~600 in the pre-clinical development stage. Currently, no BBB conjugated peptide targeting the amyloid-beta is approved or in clinical trials. The peptide-based drug market is expected to continue to grow substantially over the next 5-10 years. From preliminary studies, several peptides showed excellent binding affinity (Kd= 24-150 nanomolar) against the amyloid beta. These peptides will be conjugated with TAT peptide which is the most widely used penetration peptide for transporting proteins and nanoparticles to the brain. 

As a sophomore scholar, Iona Alator will synthesize several TAT-conjugated peptide analogues, test their inhibition efficiency against amyloid beta employing selected ion monitoring (SIM) based LCMS assay, ThT fluorescence assay and measure their BBB permeability in brain endothelial cells. The successful outcomes from this research project are (i) developing potent therapeutic peptide conjugated with BBB penetrating peptide and (ii) improving their blood-brain barrier (BBB) permeability. 

Mentor: Madalynn Marshall

Structural and Magnetic Behavior of the Sb-doped Magnetocaloric Candidate CrNiP

The demand for clean renewable energy sources continues to rise with the increasing severity of climate change from greenhouse-gas emissions. Refrigeration and air conditioning account for a significant percentage of energy consumption and current gas compression technology is falling short by enhancing the greenhouse effect and having a low cooling efficiency resulting in a larger energy consumption and worsening the energy shortage. Recent breakthroughs with the emerging solid state magnetic refrigeration competitor have shown the potential to revolutionize not only cooling in household devices but for medical health care, industry and even national defense. The exciting behavior behind magnetic refrigeration is based on the magnetocaloric effect (MCE), which can be described as a temperature change in response to an adiabatic change of the magnetic field. Not only can the MCE improve the energy efficiency of cooling and temperature control, but it is also environmentally friendly making these highly advantageous materials to design. 

However, magnetocaloric materials face a major challenge with scaling up for widespread use because they are mostly composed of expensive rare-earth elements or toxic elements. Therefore, it is crucial that we pursue nontoxic rare-earth free magnetocaloric candidates. The rare-earth free MM'X alloys where M and M' = transition metal and X = main group element, have received much attention as excellent magnetocaloric candidates. These materials can exhibit a strong magnetostructural coupling resulting in a large entropy change typically over a wide temperature range, optimal for magnetic cooling technology. Methods such as stress, temperature and chemical pressure can be utilized to drive the magnetic and structural transitions in this family and tune the MCE. 

During the First-Year Scholars Program (2023-2024) the students have successfully applied chemical pressure to induce a structural transition in the Sb-doped MM'X alloy CrNiP by preparing a series of CrNiP1-xSbx solid solutions and analyzing the polycrystalline samples using powder X-ray diffraction. With only a small percentage of Sb dopant into CrNiP1-xSbx we observe the orthorhombic structure transforms to a hexagonal structure. The resulting structural variation and chemical disorder in the CrNiP1-xSbx series can be used to tune the magnetic behavior and subsequently the MCE. The next steps of this project are to measure the magnetic behavior and determine the MCE

Mentor: Mohammad Halim

Developing Broad Spectrum Antiviral Peptides Targeting the Proteases of SARS and MARS Viruses

The fatal infectious diseases caused by various emerging viruses including severe acute respiratory syndrome coronavirus (SAR-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV) remains pervasive throughout the world. Moreover, the emerging variants are still infecting millions and killing thousands of people every day. While couple of small molecules drug received emergency approval, small molecule drugs have low target specificity and higher toxicity. Another limitation of those few drugs is that they are designed to treat one type of virus and are not effective for other viruses. In this research, Julia Franz will design and develop a broad-spectrum antiviral peptide targeting the various proteases of SARS and MARS coronavirus. 

Peptide therapeutics are very attractive over small-molecule medications, as they are highly selective, well-tolerated, and have less adverse effects. There are ~70 therapeutic peptides on the market, ~200 in clinical trials, and ~600 in the pre-clinical development stage. Currently, no antiviral peptide targeting the viral proteases of SARS/MARS is approved or in clinical trials. The peptide-based drug market is expected to continue to grow substantially over the next 5-10 years. However, all these peptide drugs need to be injected as they are degraded in the stomach if taken orally. Unlike the conventional approach of making staple peptide, Julia will develop a novel pi-pi method for our peptide analogues to produce serum stability and potentially an orally active peptide. As evident from our recent publication by several undergraduate and master鈥檚 students (Stewart, J.; Halim, M. A. et al. J. Peptide Sci. https://doi.org/10.1002/psc.3553), Temporin L (TL) is considered the most promising candidate. Although TL showed great promise inhibiting the main protease of SARS-CoV-2, however, challenges remain to test its efficacy against other viruses such as MARS and to improve its serum half-life.

As a sophomore scholar, Julia Franz will synthesize several pi-pi staple TL peptide analogues, test their inhibition efficiency against SARS and MARS proteases, determine their cytotoxicity and their serum stability. The successful outcomes from this research project are (i) developing broad spectrum pi-pi stable peptides targeting various viruses and (ii) improving oral bioavailability of the peptides. The creative approaches and innovation will lead to shifting the current paradigm of antiviral peptide-based drug discovery.

Mentor: Whitney Preisser

What's in a Fish? The relationship between fish size and parasite abundance in freshwater fish in Georgia

For the Sophomore Scholars program, Cassie will extend her First Year Scholars and SURP projects. As a First Year Scholar, Cassie dissected fish and collected their parasites to contribute to an undergraduate group project that fed into my larger research program and the research project of one of my graduate students. For this project, Cassie and the other students compared the parasite fauna of two locations around the Allatoona dam. As part of SURP, this summer, Cassie will strike out and lead an independent research project of her design, where she will look at the relationship between parasite abundance and host size using multiple species of freshwater fish collected in Cobb and Paulding counties. She will be dissecting fish, collecting their parasites, identifying the parasites, and analyzing her data this summer.

For the Sophomore Scholars Program, Cassie aims to continue and expand this research project. She will collect host and parasite data from additional fish to significantly increase her sample sizes (approximately doubling the SURP data collection). In addition, because many of these fish have not been identified, Cassie spends a good portion of her lab time identifying fish specimens, which greatly helps other students and projects going on in the lab that also use these specimens.

While previous studies have found that, in general, parasite burden tends to increase with body size, we don't know if this holds true in freshwater fish in Georgia, and we don't know if the relationship holds for every fish species, or only fish species that can attain larger body sizes. Does it hold when comparing among species as well? Does the relationship between host body size and parasite burden change over time or in response to anthropogenic stressors? Using 草榴视频's collection of preserved fish specimens collected between 1999 and 2016, Cassie will help to determine the generality of this pattern in a novel host-parasite system and over a 17 year time period.

Mentor: Carl Saint-Louis

Pre-Twisted Molecular Geometry's Effect on the Optical Properties of Nitrophenyl-Substituted Polycyclic Aromatic Compounds with Boron-Nitrogen Bonds

Incorporating a three-coordinate boron center into the structure of polycyclic aromatic hydrocarbons by replacing one of the C=C bonds with a B-N bond creates a more rigid and planar core. These flat-structured heterocycles partially substituted with a boron-nitrogen bond known as aromatic azaborines, are highly regarded for their unique optoelectronic properties such as photochemical stability, high molar absorption coefficient, and high fluorescent quantum yields, as well as large Stokes shifts and tunable absorption/emission spectra, making them excellent candidates for a variety of applications such organic light-emitting diodes (OLEDs). Adding a -NO2 group as a strong electron-accepting moiety to the scaffold of aromatic azaborines, particularly pyrrolinone-fused-1,2-azaborines (PFAs), in an effort to red-shift their absorbance and emission and create electron-deficient n-type organic conjugates, results in significant emission quenching due to intersystem crossing. Another issue with -NO2-substituted PFAs is that they aggregate at high concentrations due to strong intermolecular 蟺-蟺 stacking interactions. In turn, aggregate formation causes emission quenching, also known as Aggregation-Caused Quenching (ACQ). This practical limitation poses significant challenges for -NO2-substituted PFAs鈥� use in many applications. We recently published results on a novel -NO2-phenyl substituted PFA, in which we addressed the ACQ issue by inserting a phenyl spacer between the PFA scaffold and the -NO2 moiety to create a pre-twisted molecular geometry. This minor modification in molecular geometry resulted in fluorescence that can be completely ''turned off'' via ACQ and ''turned on'' via Aggregation Induced Emission (AIE). Herein, we propose to design and synthesize a second generation of -NO2-substituted PFAs that can overcome the ACQ problem by increasing the steric interactions between the phenyl spacer and the PFA scaffold and creating a larger twist in the molecular geometry by including bulkier groups such as methyl and isopropyl. The addition of bulkier groups to increase the twist in molecular geometry will result in -NO2-phenyl substituted PFAs with aggregation-induced emission, solvatochromism and thermochromism properties. These findings will aid in the development of more improved future AIE-active PFAs, as well as the understanding of how molecular geometry influences these compounds' optoelectronic properties.

Mentor: Carl Saint-Louis

Electron-Rich Polyclinic aromatic compounds containing a Boron-Nitrogen bond: Synthesis and Optical Properties

Dyes that absorb and emit long wavelength light are gaining popularity in the materials and cell imaging technology markets because they can be used in a wide range of technological applications, such as laser filters, optical recording, photodynamic (PDT) and photothermal therapy (PTT), which use reactive oxygen species or heat to kill tumor cells. Due to their ability to absorb in the red and emit in the near infrared (NIR) region of the spectrum, these dyes can be utilized in bioimaging where NIR light can be safely used since it can deeply penetrate human tissue without causing apoptosis or cell damage, as well as the detection in living organisms with minimal interference from background autofluorescence. The dye's molecular structure, however, is critical for both absorption and emission at longer wavelengths. To guarantee absorption and emission at longer wavelengths and improve the optical properties of these dyes, the scaffold should be flat and rigid, with highly conjugated 蟺-surface. We previously published findings on a new pyrrolidinone fused 1,2-azaborine (PFA) scaffold in which one of the C=C bonds of a heterocyclic hydrocarbon was replaced with a B-N bond, resulting in core rigidification. We also observed an enhancement in photophysical properties such as higher and more intense fluorescence, extraordinary thermal and photochemical stability, high fluorescence quantum yields, and even unique self-assembly behavior. Incorporating a weak electron-donating group into the left hemisphere of the unsubstituted PFA causes a red-shift (bathochromic shift) in absorbance and emission, as well as substantial Stokes shifts and quantum yields of up to 0.5. Herein, we aim to design electron-rich PFA derivatives bearing diverse strong electron-donating groups, such as amino derivatives, to the left hemisphere. We hypothesized that the addition of these amino derivatives will raise the energy of the HOMO, causing the reduction of the HOMO鈥揕UMO gap, resulting in absorption in the red and emission in the NIR region of the spectrum. We will also investigate the effect of solvent polarity on the emission maxima to test for solvatochromism. These findings will help in the design of future electron-rich PFAs that absorb and emit long wavelength light as well as understanding how different electronic groups affect these compounds鈥� optoelectronic properties.

Mentor: Andrew Haddow

Impact of Per- and Poly-Fluoroalkyl Substances (PFAS) on Mosquito Behavior

Per- and poly-fluoroalkyl substances (PFAS), also known as 鈥渇orever chemicals鈥�, are omnipresent environmental contaminants that are highly toxic to invertebrates, wildlife, and humans. These fluorinated aliphatic compounds have been used in a variety of industrial applications and consumer products since the early 1950s and are resistant to environmental degradation due to their strong carbon-fluorine bond. Worldwide and toxicologic studies investing PFAS have revealed that these chemicals cause developmental delays, endocrine disruption, reproductive harm, and immunological effects in vertebrates. PFAS primarily enter the environment through the discharge of contaminated wastewater from industrial facilities and from the use of aqueous fire-fighting foams. From there, PFAS enter aquatic ecosystems where they are readily absorbed by both vertebrates and invertebrates following oral exposure. The overall objective of this work is to determine the effect PFAS exposure has on the fitness and development of mosquitoes.

Mentor: Peter Fielding

Analysis of Visayan/Bisayan/Cebuano Philippine Traditional Vocal Repertoire

This SYSP serves to continue the in-progress survey of the scales, modes, and pitch collections of Visayan/Bisayan/Cebuano Philippine folk song repertoire. Students will use music notation software to create Kod谩ly-style pitch maps as part of the encyclopedic surveying of these repertoires. Select songs will be sung with solfa syllables, to help assess the pedagogical merits of the repertoire for use in Aural Skills curriculum. 

Request to extend into SYSP as initial FYSP work was set for two participants, but one dropped out quickly, requiring more time for one student to pursue. Additionally, field recordings housed at Indiana University have not yet been made accessible online (library restructure), so extending into AY 24-25 will enable deeper analysis and comparison of transcriptions vs original source recordings, thereby increasing the value of the work and strengthen subsequent conference proposal and analysis article submissions to academic journals.

Rationale:
This project continues to survey and appraises the pedagogical value of the traditional vocal repertoire of Canada's third largest source of new permanent residents; namely the Philippines. This work builds on prior multi-lingual Canadian folk song analysis utilizing post-tonal and Kod谩ly techniques. As a pilot study, this analysis will focus on Visayan/Bisayan/Cebuano Philippine folk song repertoire collected by Priscilla Magdamo, under the auspices of the Silliman University; utilizing her six-volume Folk Songs of the Visayas, corresponding field recordings, and her more recent unpublished transcriptions. Research outputs will be of value to the music and academic communities of the Philippines, as well as the broader Filipino diaspora, including those residing in Canada and the United States.

Note:  Should the original repertoire be fully appraised, additional Year of Canada historic French Canadian song repertoire can be assessed, thereby adding to the PI's existing cross cultural song analyses by language type.

Mentor: Danica Kulibert

Understanding How Political Parties View Moderate and Extreme Political Candidates

The current study focuses on perceptions within left and right political parties outside of the US. Democrats and Republicans in the US often misjudge each other (i.e., Democrats and Republicans alike believe the other political party views them more negatively than the other political party actually views them; Lees & Cikara, 2020; Moore-Berg et al., 2020). Meta-perceptions refer to a person鈥檚 beliefs about another person鈥檚 or group鈥檚 beliefs (Frey & Tropp, 2006). Meta-perceptions are often inaccurate as well and can exacerbate intergroup conflict (Finchilescu et al., 2010; Lee & Cikara, 2020). Research on intergroup metaperceptions in political parties has grown substantially over the last decade (Bruneau et al., 2021; Moore-Berg et al., 2020) but little has assessed political percpetions outside of the US.

My past research has demonstrated that, when evaluating political candidates in their own party (in the US), people approve of moderate political candidates less than extreme or average political members. Political deviance, however, has much stronger and more robust effects on people鈥檚 metaperceptions than actual perceptions. People believe Democrats approve of moderate Democratic candidates much less than extreme or normative candidates; similarly they also believe that Republicans approve of moderate Republican candidates much less than extreme or normative candidates. The current study will examine if outgroup metaperceptions of political deviants are more polarized than ingroup metaperceptions of political deviants outside of the US (e.g., Germany, Chile, Nigeria). 

Mentor: Sharon Pearcey

Exploring the Relationship among Biomarkers and Emotion, Substance Use, and Executive Function

During the 2024 鈥� 2025 academic year, my students will be working on two main projects. First, they will be finishing up the enzyme linked immunosorbent assays (ELISA) for estrogen, progesterone, and cortisol, as well as entering data from the project on self-reported stress. As first year scholars, they were able to use the biomarker data that they analyzed in relation to questionnaire data that had already been coded and create unique research projects to present at our Georgia Undergraduate Research in Psychology Conference and Symposium of Student Scholars. 

The second part of the project will be Investigating the relationship among executive function (i.e., metacognitive processes related to decision making, cognitive flexibility, and impulse control), substance use, and epigenetic and inflammatory biomarkers. My students will be involved in every aspect of this study including data collection, running participants on the cognitive tasks, collecting saliva samples, as well as learning new laboratory techniques looking for genetic markers. Specifically, we have identified candidate gene variations at the level of single nucleotides (SNPs) related to substance use, executive function, and mental health outcomes. My students will learn how to use quantitative polymerase chain reaction (qPCR) to amplify the genes to identify gene variations in the target genes BDNF and COMT. 

Mentor: Sharon Pearcey

Exploring the Relationship among Biomarkers and Emotion, Substance Use, and Executive Function

During the 2024 鈥� 2025 academic year, my students will be working on two main projects. First, they will be finishing up the enzyme linked immunosorbent assays (ELISA) for estrogen, progesterone, and cortisol, as well as entering data from the project on self-reported stress. As first year scholars, they were able to use the biomarker data that they analyzed in relation to questionnaire data that had already been coded and create unique research projects to present at our Georgia Undergraduate Research in Psychology Conference and Symposium of Student Scholars. 

The second part of the project will be Investigating the relationship among executive function (i.e., metacognitive processes related to decision making, cognitive flexibility, and impulse control), substance use, and epigenetic and inflammatory biomarkers. My students will be involved in every aspect of this study including data collection, running participants on the cognitive tasks, collecting saliva samples, as well as learning new laboratory techniques looking for genetic markers. Specifically, we have identified candidate gene variations at the level of single nucleotides (SNPs) related to substance use, executive function, and mental health outcomes. My students will learn how to use quantitative polymerase chain reaction (qPCR) to amplify the genes to identify gene variations in the target genes BDNF and COMT.

Mentor: Chanler Hilley

Dimensions and Predictors of Social Connectedness in Young Adulthood

This project explores psychosocial and contextual factors that influence social connectedness during the transition to young adulthood. Recent U.S. Surgeon General reports have called attention to the 鈥渆pidemic of loneliness鈥� as a public health crisis, based in part on data showing staggering increases in social isolation starting in 2018 and steady decreases in family social engagement over the past 2 decades (Kannan & Veazie, 2023). In subgroup analyses, late adolescents and young adults reported the lowest family social engagement and adolescents and young adults now rank third highest in isolation out of all age groups. Despite calls to attend to youths鈥� social connectedness, research in this area is lacking, focusing primarily on demographic traits rather than mutable characteristics that may be targeted for intervention. Further, normative transition to adulthood experiences establishing independence, including in adolescents鈥� residential status (e.g., leaving home), may be isolating. Thus, this study investigates potentially modifiable characteristics like sense of control, place attachment, parental relationships, and messages about the transition to adulthood as they relate to young adults鈥� connectedness. This project includes a specific emphasis on parent-young adult relationships. Although waning salience of parental influence is normative beginning in adolescence, combined with other indicators of increased social isolation at broader levels as well as qualitatively different social contexts in the wake of the COVID-19 pandemic, parental relationships may be particularly important developmental assets for young adults in the current sociohistorical context. For example, in a cross-national study, the association between COVID-related disruptions and internalizing was attenuated by lower parent-child conflict and more supportive parenting (Skinner et al., 2021). Data for this study have already been collected from three sources: a national sample using an online panel aggregator, a sample of college students at various colleges (typically enrolled in Communication courses), and 草榴视频 students in PSYC 1101. Alanna started work on this project during her First Year Scholars experience and has interests in statistics and epidemiology. Gaining experience with more complex research questions and analyses using this existing data will be beneficial for her in preparation for a career that requires a high degree of research acumen. 

Mentor: Yian Xu

Using Cognitive Psychology to Probe the Underpinnings of AI Social Bias in GPT-4

How do artificial intelligence (AI) models structure the human world? Cognitive psychologists have studied how humans represent the social world in our mind- for example, by relying on social category labels, such as race and gender, to make quick predictions about individual personal traits. Such mental shortcuts, consciously or unconsciously driven, reflect inaccurate perceptions of the world and often lead to social prejudice and discrimination. While human rationality is bounded by limited mental resources, highly capable large language models, such as GPT-4, can process vast amounts of information quickly and efficiently, showcasing a level of cognitive capacity that can potentially surpass the constraints of human rationality. This project aims to apply the cognitive framework of psychological essentialism to investigate whether GPT-4 exhibits social essentialist bias similar to humans, as a way to explore the underpinning of AI social bias and identify areas where large language models mirror or rise above human irrationality. Potential findings from this project will inform the responsible development and deployment of AI technologies in human-AI collaboration, particularly in decision-making processes typically prone to social biases. 

Based on our work last year, this project will continue to utilize a mixture of vignette-based and survey-based prompts to test GPT-4's capacity to simulate social reasoning and compare it with previously demonstrated human reasoning patterns. In particular, we will use the Switched-at-Birth Task to probe essentialist bias about social categories. This project will test how GPT-4 responds to the Switched-at-Birth task in 8 variations, including 6 familiar social domains (i.e., race, gender, nationality, religion, political affiliation, and social class), and 2 novel, fictional social categories (such as 鈥淭ezzies鈥� and 鈥淗igges鈥�, which do not exist in reality), to control the possible training effect based on GPT-4鈥檚 previous exposure to materials that have already been used in prior studies. Modeled on recent studies examining cognitive biases in large language models, we will generate 146 responses in GPT-4 through OpenAI鈥檚 API implementation (Binz & Schulz, 2023) and compare it with a human sample. 

Mentor: Alexander Crenshaw

Improving the Evaluation of Individual Change in Clinical Trials in Psychology

Establishing effective psychological treatments is essential to reducing the individual, interpersonal, and societal burdens that mental health difficulties cause each year.  A key step in the development of psychological treatments is to evaluate their efficacy through randomized clinical trials. For psychological treatments, these clinical trials tend to focus on two types of outcomes: 1) testing group differences, which test whether and by how much a treatment group shows better average outcomes than a control group, and 2) clinical significance, which evaluates whether those changes produce meaningful improvement in the lives of the individuals who receive the treatment (Baucom & Crenshaw, 2019; Kraemer et al., 2006). Each form of evaluation complements the other and both are critical to fully evaluate a treatment.

An important limitation of current practices for computing group differences and clinical significance is that researchers define these outcomes in varied ways. First, quantifying group differences in complicated data structures like those in clinical trials can be done in several different ways (Feingold, 2009). Second, methods for determining clinical significance also vary widely across studies (Lambert & Ogles, 2014). Even when studies use the same methods, the criteria for what is considered 鈥渃linically significant鈥� often differ by chance alone (Crenshaw & Monson, 2023). This situation results in treatments being evaluated by different criteria across studies, introducing statistical noise, error, and uncertainty into evaluations of a treatment鈥檚 efficacy.

The purpose of this project is to evaluate and improve the standardization of methods for evaluating psychological treatments in clinical trials. Aim 1, which is underway, involves a systematic review of published clinical trials of psychological treatments to formally assess the methods currently used for evaluating group differences and clinical significance in these studies. Next, Aim 2 will compare the specific methods found in the systematic review to determine the extent to which differences in criteria across studies leads to different outcomes or conclusions. Finally, Aim 3 will establish standardized recommendations for future clinical trials of psychological treatments to improve how these outcomes are evaluated in future studies. This project will ultimately lead to better and more standardized evaluation criteria for evaluating psychological treatments.

Mentor: Ayse Tekes

Design and Development of a Fully Compliant Bipedal Robot

There is still an ongoing effort in the design and development of legged robots in the field of robotics. Bipedal robots can imitate the walking gait cycle, hopping, and jumping type locomotion. To accomplish the gait cycle, the four phases of the gait cycle as double support phase, the pre-swing phase, the single support phase, and the post-swing phase should be successfully alternated in a sequence. Compliant mechanisms have been utilized in biomimetic designs due to their inherent properties such as bending of their flexible members rather than joints when forced and their ability to be manufactured as a single piece. In this study, Aaron will work on the design of a fully compliant and serial linkage biped robot using compliant rolling contact and will actuate each leg through stepper motors and belts. The inclusion of compliant flexure reduces the friction, weight and undesired vibrations caused by eccentricity, and increases the overall performance. The hip design will house the motors and four propellers to maintain the balance of the robot. Motion analyses will be performed in MATLAB Simulink and Simscape to optimize link lengths and generate the biped trajectory. The mechanism will be built by 3D printing the parts in polylactic acid and polyurethane and theormoplastic filaments and experimentally tested for a successful gait cycle.

Mentor: Muhammad Hassan Tanveer

Enhancing Robo-Dog Collaboration with Agriculture Ground Vehicle: A Reverse Engineering Approach

The primary objective of this research project is to enhance the capabilities of quadruped robots and the Husky UGV through a collaborative approach. By reverse engineering both the computational and mechanical aspects of these robots, we aim to unlock their full potential for a wide range of applications.

One key aspect of our approach involves integrating obstacle avoidance and path planning algorithms into the quadruped robot, enhancing its ability to navigate autonomously in complex environments. By implementing these algorithms, we can improve the robot's efficiency and effectiveness in avoiding obstacles and reaching its destination safely. Additionally, collecting data on the robot's navigation efficiency will allow us to evaluate the performance of these algorithms and fine-tune them for optimal results.

Furthermore, to broaden the scope of our research, we plan to introduce a variety of different robot systems, including drones and ground robots, to work in tandem with the quadruped robot and the Husky UGV. This multi-robot collaboration will enable us to explore new possibilities and applications, such as coordinated surveillance missions or search and rescue operations. By leveraging the complementary strengths of different types of robots, we can enhance overall system performance and versatility.

In summary, this research project aims to push the boundaries of robotic capabilities through collaboration, reverse engineering, and algorithm development. By enhancing the computational and mechanical aspects of quadruped robots and the Husky UGV, as well as integrating diverse robot systems, we seek to enable new advancements and applications in robotics technology. Through this interdisciplinary approach, we hope to contribute to the ongoing evolution of robotics and its potential to address real-world challenges effectively.

Mentor: Muhammad Hassan Tanveer

Enhancing Robo-Dog Collaboration with Agriculture Ground Vehicle: A Reverse Engineering Approach

The primary objective of this research project is to enhance the capabilities of quadruped robots and the Husky UGV through a collaborative approach. By reverse engineering both the computational and mechanical aspects of these robots, we aim to unlock their full potential for a wide range of applications.

One key aspect of our approach involves integrating obstacle avoidance and path planning algorithms into the quadruped robot, enhancing its ability to navigate autonomously in complex environments. By implementing these algorithms, we can improve the robot's efficiency and effectiveness in avoiding obstacles and reaching its destination safely. Additionally, collecting data on the robot's navigation efficiency will allow us to evaluate the performance of these algorithms and fine-tune them for optimal results.

Furthermore, to broaden the scope of our research, we plan to introduce a variety of different robot systems, including drones and ground robots, to work in tandem with the quadruped robot and the Husky UGV. This multi-robot collaboration will enable us to explore new possibilities and applications, such as coordinated surveillance missions or search and rescue operations. By leveraging the complementary strengths of different types of robots, we can enhance overall system performance and versatility.

In summary, this research project aims to push the boundaries of robotic capabilities through collaboration, reverse engineering, and algorithm development. By enhancing the computational and mechanical aspects of quadruped robots and the Husky UGV, as well as integrating diverse robot systems, we seek to enable new advancements and applications in robotics technology. Through this interdisciplinary approach, we hope to contribute to the ongoing evolution of robotics and its potential to address real-world challenges effectively.

Mentor: Muhammad Hassan Tanveer

Enhancing Robo-Dog Collaboration with Agriculture Ground Vehicle: A Reverse Engineering Approach

The primary objective of this research project is to enhance the capabilities of quadruped robots and the Husky UGV through a collaborative approach. By reverse engineering both the computational and mechanical aspects of these robots, we aim to unlock their full potential for a wide range of applications.

One key aspect of our approach involves integrating obstacle avoidance and path planning algorithms into the quadruped robot, enhancing its ability to navigate autonomously in complex environments. By implementing these algorithms, we can improve the robot's efficiency and effectiveness in avoiding obstacles and reaching its destination safely. Additionally, collecting data on the robot's navigation efficiency will allow us to evaluate the performance of these algorithms and fine-tune them for optimal results.

Furthermore, to broaden the scope of our research, we plan to introduce a variety of different robot systems, including drones and ground robots, to work in tandem with the quadruped robot and the Husky UGV. This multi-robot collaboration will enable us to explore new possibilities and applications, such as coordinated surveillance missions or search and rescue operations. By leveraging the complementary strengths of different types of robots, we can enhance overall system performance and versatility.

In summary, this research project aims to push the boundaries of robotic capabilities through collaboration, reverse engineering, and algorithm development. By enhancing the computational and mechanical aspects of quadruped robots and the Husky UGV, as well as integrating diverse robot systems, we seek to enable new advancements and applications in robotics technology. Through this interdisciplinary approach, we hope to contribute to the ongoing evolution of robotics and its potential to address real-world challenges effectively.

Mentor: Muhammad Hassan Tanveer

Enhancing Robo-Dog Collaboration with Agriculture Ground Vehicle: A Reverse Engineering Approach

The primary objective of this research project is to enhance the capabilities of quadruped robots and the Husky UGV through a collaborative approach. By reverse engineering both the computational and mechanical aspects of these robots, we aim to unlock their full potential for a wide range of applications.

One key aspect of our approach involves integrating obstacle avoidance and path planning algorithms into the quadruped robot, enhancing its ability to navigate autonomously in complex environments. By implementing these algorithms, we can improve the robot's efficiency and effectiveness in avoiding obstacles and reaching its destination safely. Additionally, collecting data on the robot's navigation efficiency will allow us to evaluate the performance of these algorithms and fine-tune them for optimal results.

Furthermore, to broaden the scope of our research, we plan to introduce a variety of different robot systems, including drones and ground robots, to work in tandem with the quadruped robot and the Husky UGV. This multi-robot collaboration will enable us to explore new possibilities and applications, such as coordinated surveillance missions or search and rescue operations. By leveraging the complementary strengths of different types of robots, we can enhance overall system performance and versatility.

In summary, this research project aims to push the boundaries of robotic capabilities through collaboration, reverse engineering, and algorithm development. By enhancing the computational and mechanical aspects of quadruped robots and the Husky UGV, as well as integrating diverse robot systems, we seek to enable new advancements and applications in robotics technology. Through this interdisciplinary approach, we hope to contribute to the ongoing evolution of robotics and its potential to address real-world challenges effectively.

Mentor: Muhammad Hassan Tanveer

Enhancing Robo-Dog Collaboration with Agriculture Ground Vehicle: A Reverse Engineering Approach

The primary objective of this research project is to enhance the capabilities of quadruped robots and the Husky UGV through a collaborative approach. By reverse engineering both the computational and mechanical aspects of these robots, we aim to unlock their full potential for a wide range of applications.

One key aspect of our approach involves integrating obstacle avoidance and path planning algorithms into the quadruped robot, enhancing its ability to navigate autonomously in complex environments. By implementing these algorithms, we can improve the robot's efficiency and effectiveness in avoiding obstacles and reaching its destination safely. Additionally, collecting data on the robot's navigation efficiency will allow us to evaluate the performance of these algorithms and fine-tune them for optimal results.

Furthermore, to broaden the scope of our research, we plan to introduce a variety of different robot systems, including drones and ground robots, to work in tandem with the quadruped robot and the Husky UGV. This multi-robot collaboration will enable us to explore new possibilities and applications, such as coordinated surveillance missions or search and rescue operations. By leveraging the complementary strengths of different types of robots, we can enhance overall system performance and versatility.

In summary, this research project aims to push the boundaries of robotic capabilities through collaboration, reverse engineering, and algorithm development. By enhancing the computational and mechanical aspects of quadruped robots and the Husky UGV, as well as integrating diverse robot systems, we seek to enable new advancements and applications in robotics technology. Through this interdisciplinary approach, we hope to contribute to the ongoing evolution of robotics and its potential to address real-world challenges effectively.

Mentor: Roneisha Worthy

Optimizing Water and Nutrient Efficiency in Hydroponic Systems for Sustainable Peach Production in Georgia

Background: In response to increasing water scarcity and the need for sustainable agricultural practices, hydroponics offers a viable solution by significantly reducing the water and nutrient requirements compared to traditional soil-based agriculture. This project aims to utilize hydroponic technologies to optimize the production of peaches, a crop of significant economic importance in Georgia, ensuring sustainability and efficiency.
Research Question: How can hydroponic systems be optimized to enhance water and nutrient use efficiency in peach production under varying environmental conditions in Georgia?

Objectives:
-To establish the efficacy of Deep Water Culture (DWC) hydroponic systems in the cultivation of peaches.
-To determine optimal water and nutrient regimes for peach production in hydroponic systems.
-To assess the environmental impacts and sustainability of using DWC hydroponic systems for peach cultivation.

Methodology: The research will involve the use of 5 Gal. Black DWC Hydroponics Grow System Deep Water Culture Bucket with Recirculating Drip Garden Kit (8-Pack). The study will compare the growth performance, water usage, and nutrient efficiency of peaches in these hydroponic systems under controlled conditions.

Mentor: Da Hu

Artificial Intelligence-Enhanced Drone-Based Detection and Mapping of Bridge Defects

The safety, reliability, and longevity of transportation infrastructure are critical for maintaining efficient and effective transportation networks. Bridge inspections are an essential part of this process, ensuring that potential issues are identified and addressed in a timely manner. Traditional bridge inspection methods, however, can be labor-intensive, time-consuming, and costly. Furthermore, these methods often require the temporary closure of bridges, causing disruptions to traffic flow and imposing additional burdens on communities. In response to these challenges, the use of drones and computer vision techniques for bridge inspection has emerged as a promising alternative. By leveraging these advanced technologies, inspection processes can be made more accurate, comprehensive, and efficient, while also reducing costs and minimizing traffic disruptions. The development of an automated bridge inspection framework, which combines drone-based image acquisition with sophisticated computer vision algorithms, has the potential to revolutionize the way bridge inspections are conducted, ensuring the safety and longevity of critical transportation infrastructure.

The proposed project aims to create an automated bridge inspection framework that leverages drone technology and state-of-the-art machine learning techniques for the precise and efficient detection of various defects, including cracks and other structural issues, on bridge decks. This framework will not only streamline the inspection process, but also provide infrastructure managers with a detailed understanding of the bridge's condition, thus promoting better decision-making regarding maintenance and repair activities. By adopting this advanced framework, transportation authorities can improve the safety, reliability, and longevity of their infrastructure assets while minimizing costs and disruptions associated with traditional inspection methods.

Mentor: Gaurav Sharma

Numerical Investigation of Vortex Breakdown Over Compound Delta Wing

The primary objective of the present research is to undertake a thorough numerical investigation into the phenomenon of vortex breakdown manifesting over a compound delta wing. This inquiry seeks to unravel the intricate fluid dynamics governing this complex aerodynamic occurrence, which involves the abrupt transition from a stable vortex flow to a chaotic state. The study places particular emphasis on the compound delta wing due to its prevalent utilization in contemporary high-performance aircraft, characterized by a multifaceted geometry with multiple surfaces and junctions.

The essence of vortex breakdown lies in the sudden and unpredictable transformation of a stable vortex, formed over an aircraft's wings, into a chaotic state. The consequences of this abrupt transition hold paramount significance in comprehending the aerodynamic performance of high-performance aircraft. An in-depth understanding of the underlying fluid dynamics is essential for the advancement of design methodologies and ensuring operational safety.

To achieve these objectives, advanced Computational Fluid Dynamics (CFD) techniques are employed to scrutinize the intricacies associated with vortex breakdown over compound delta wings. The application of CFD enables a comprehensive numerical examination by solving the governing Navier-Stokes equations, which dictate the dynamics of fluid flow. This approach facilitates meticulous scrutiny of airflow patterns and vortex dynamics, providing a detailed insight into the complex interactions at play within the aerodynamic milieu.

The research seeks to identify critical parameters influencing vortex breakdown, such as wing geometry, angle of attack, and airspeed, through a methodical numerical investigation. Moreover, the study aims to assess the consequential effects of vortex breakdown on fundamental aerodynamic parameters, including lift, drag, and overall stability. The utilization of state-of-the-art CFD tools ensures the simulation of the entire aerodynamic environment, enabling a holistic perspective on the aerodynamic behavior of compound delta wings.

In conclusion, this research project signifies a notable stride in advancing the scientific understanding of vortex breakdown over compound delta wings through the application of sophisticated CFD techniques. The outcomes of this investigation are poised to inform future design strategies for high-performance aircraft, contributing to the enhancement of efficiency and safety.

Mentor: Razvan Voicu

Artificial General Intelligence - Control of Real-time Entity (AGI CORE)

The "Artificial General Intelligence鈥擟ontrol of Real-time Entities" (AGI CORE) project aims to advance real-time control systems by integrating local AI systems with cloud-based large language models (LLMs). Artificial General Intelligence (AGI) is a type of AI that can understand, learn, and apply knowledge across various tasks, mimicking human cognitive abilities. AGI CORE specifically focuses on leveraging AGI to manage and optimize real-time systems, particularly in robotics control.
 
Previous research in this domain has explored various critical parameters for effective AI integration, such as communication mechanisms, end-to-end delay, processing time, and the system's capability to produce accurate directives. Additionally, efforts have been made to optimize the processing time to achieve directive outputs as fast as 1.9 seconds. However, this is still far from the sub-second (100ms or less) response times required by many real-time applications. Consequently, AGI CORE seeks to address this gap by developing a hybrid AI framework that combines the immediacy of local computing with the advanced capabilities of cloud computing.
 
The primary goal is to engineer a local AI system capable of managing and controlling real-time robotics operations with minimal delay, complemented by enhanced capabilities sourced from cloud systems. This hybrid approach is crucial for applications where timing and precision are paramount, such as in autonomous vehicles, military operations, and medical technologies in biomedical labs. Through AGI CORE, we aim to optimize system responsiveness and introduce advanced contextual understanding capabilities that transcend traditional programmable systems, enabling more dynamic and adaptable applications.

Mentor: Hoseon Lee

Design of a Novel Controlled Radiation Capsule for Improved Brachytherapy Cancer Treatment  

Annually, approximately 7 million undergo cancer radiation therapy, with 3.5 million cured. Brachytherapy (internal radiotherapy) has two delivery methods: High-Dose Radiation (HDR) and Low-Dose Radiation (HDR). HDR employs high-energy radiation with higher risks to surrounding tissue; LDR has lower risks but longer treatment. In conclusion, the proposed capsule is a combination of the advantages of HDR and LDR resulting in minimizing the radiation risk and treatment time with the potential applications on intracavity cancers. A nuclear radiation simulation tool called TOPAS is used to simulate the difference between the conventional I-125 radiation seed and the proposed design. The results show that conventional seed emits radiation omnidirectionally, and the proposed device blocks the radiation everywhere except the opening 鈥渨indow鈥� where the radiation targets the tumor. For this project, the dosimetry calculations were conducted to figure out the amount of grams of I-125 and the number of radiation seeds in order to determine the dimensions of the capsule. To design the capsule, Solidworks was used to create the inner and outer cylinders and walls, as well as windows through which the radiation can be released. The dimensions are based on dosimetry calculations and TOPAS simulations. COMSOL, a Multiphysics simulation software, is used to simulate both the electromagnet and permanent magnet, allowing easy adjustments to the material and size of the permanent magnet, as well as the current in the electromagnet. These modifications enable finding optimal conditions where the permanent magnet is weak enough to repel yet strong enough to stay attached when the capsule is inactive. Target cancer types are intracavitary cancer such as esophageal, cervical, nasal, oral cavity, but can also include cancers in the eye and brain, due to very localized radiation and minimal risk to surrounding healthy cells and tissue.  

Mentor: Gerald Mangine

Agreement Between Methods for Describing the Intensity of a High-Intensity Functional Training Workout

The purpose of this study is to examine the agreement between velocity-based descriptors of high-intensity functional training workout intensity, more traditional descriptors of exercise intensity (e.g., percentage of max strength), and commonly accepted metrics of HIFT intensity (e.g., lactate, HR, and RPE). For this study, participants will be asked to report to the Human Performance Laboratory (HPL; Room 1104 in Prillaman Hall on the 草榴视频 State University Main Campus) on three separate occasions wearing athletic clothing. The first baseline visit will be used to quantify relevant physical and physiological attributes by assessing body composition (via 4-compartment model) and performance in workout-relevant exercises (i.e., power clean, toes-to-bar, and wall ball shots). The first experimental visit will begin within 48 鈥� 72 hours of the baseline visit, and the second experimental visit can begin within 48 鈥� 72 hours of the first experimental session. All visits for this study will be completed within 14 days of enrollment, and always at a time that is consistent with the participant's normal training schedule. Experimental visits will begin with a heart rate variability assessment, followed by a subjective rating of effort, and then a blood sample donation for lactate concentration analysis. Participants will then initiate a standard warm-up that will conclude with maximal speed assessments, followed by a 5-minute rest break, and then completion of either a lesser- (LV-WOD) or higher-volume (HV-WOD) workout consisting of barbell power cleans (5 or 10 repetitions), toes-to-bar (10 or 15 repetitions), and WB (15 or 20 repetitions). All pre-exercise assessments, except for maximal velocity assessments, will be repeated immediately following completion of the workout. Workout order will be randomly assigned by the research team prior to the second visit with participants being notified of the order at the beginning of the warm-up period on that visit. They will complete the remaining workout on their third visit. 

Changes in speed (i.e., repetition completion rate) for each exercise will be monitored and recorded during both experimental workout conditions, and then be calculated as a percentage of the participants' established maximal speed. Relationships and agreement between their percentage speed and established metrics of intensity will then be statistically examined.

Mentor: Mark Geil

Biomechanics of Infant Crawling Development

In 2022, the CDC removed crawling from the new list of infant developmental milestones, in part due to the lack of normative and subjective data on crawling. While we have extensive data from motion analysis on child walking development, the same techniques do not work well with infants. Using a novel non-invasive technique and a mat with distributed pressure transducers, this project will create the largest normative database on crawling in history. Over three years, we will assess typically developing infants every two weeks from onset of crawling until transition to walking, collecting crawling speed, weight distribution, cadence and step lengths, and the percent of each crawling cycle when 2, 3, or all 4 limbs are in contact with the ground. We will also collect a sample o 15 children with limb loss to represent atypical development through our partnership with Children's Healthcare of Atlanta. We will use these data to identify which variables are most sensitive to limb mechanics. The long-term goal is to enable earlier identification and intervention for pediatric neuromuscular conditions such as cerebral palsy. 

Mentor: Mark Geil

Biomechanics of Infant Crawling Development

In 2022, the CDC removed crawling from the new list of infant developmental milestones, in part due to the lack of normative and subjective data on crawling. While we have extensive data from motion analysis on child walking development, the same techniques do not work well with infants. Using a novel non-invasive technique and a mat with distributed pressure transducers, this project will create the largest normative database on crawling in history. Over three years, we will assess typically developing infants every two weeks from onset of crawling until transition to walking, collecting crawling speed, weight distribution, cadence and step lengths, and the percent of each crawling cycle when 2, 3, or all 4 limbs are in contact with the ground. We will also collect a sample o 15 children with limb loss to represent atypical development through our partnership with Children's Healthcare of Atlanta. We will use these data to identify which variables are most sensitive to limb mechanics. The long-term goal is to enable earlier identification and intervention for pediatric neuromuscular conditions such as cerebral palsy. 

Mentor: Matthew Lyons

Addressing the Social Determinants of Health Using Complex Systems Methodology

This project will focus on addressing the social determinants of health through complex systems methods. It will include continued work on an ongoing systematic review of moral distress in social workers, data scientific exploration of a large scale longitudinal data set on the homeless service system in Cobb County, and research support on a funded NIH R01 grant. 

Mentor: Daphney Carter

Assessing the Cardiovascular System in Response to Non-Traditional Exercise Interventions

Blood flow restriction is a method of temporarily reducing blood flow by inflating a cuff on the upper part of a limb. This has been shown to have promising benefits for the musculature when combined with exercise and in the absence of exercise. In certain cases, such as injury and illness, individuals may be unable to exercise or maintain their physical activity levels. These declines in physical activity may be associated with declines in the cardiovascular system. While the current application of blood flow restriction alone does not appear to improve the cardiovascular system, it seems this protocol could be altered to improve comfort and effectiveness.
Thus, this project is designed to test the effectiveness of more frequent cuff inflations that occur for a shorter duration than the typical protocol. We will collect data on the cardiovascular system and perceptions before, during, and following the protocol. If this seems to be a more comfortable and effective method of blood flow restriction, then a future study may determine whether repeated application improves the cardiovascular system or maintains the cardiovascular system during reduced physical activity levels.