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VR Farming: An Immersive Approach to Engaging the Next Generation in Agri-food Careers
No full textAs the global population reaches 9.7 billion by 2050, global food demand will increase by up to 56% [1]. However, the percentage of US farms undergoing significant labor shortages increased from 14% in 2014 to 41% in 2018 and 53% in 2022 [2], implying the urgent need to attract younger generations to the agrifood industry and encourage them to choose relevant careers in the future. To tackle this challenge, in this project, we propose VR Farming—an educational virtual reality environment (VR) for providing the younger audience—typically feeling comfortable in using new digital tools—with an immersive, engaging, and interactive learning experience, performing simplified yet realistic agricultural processes. Specifically, the simulated environment presents a virtual farm with multiple rows of tomatoes at various growth levels, allowing the user to freely navigate around in and observe them from different viewpoints. In addition, the user can interact with the crops and trigger a game with the mission to correctly identify ripe and unripe tomatoes, harvest and place only those that are ready for sale in crates for packaging. Future development will expand the environment further to include all different stages of food production, such as farming, postharvesting, retail, and cooking. Our ultimate goal in this project is to develop an innovative VR environment that enables the younger generation to learn and enjoy food production processes through immersive, hands-on experiences and help them become interested in and explore career opportunities in the agrifood industry. [1] Michiel van Dijk, Tom Morley, Marie Luise Rau, and Yashar Saghai, A meta-analysis of projected global food demand and population at risk of hunger for the period 2010–2050, Nature Food, 2022. [2] Zachariah Rutledge, Farm Labor Shortages, Their Implications, and Policy Options to Help Promote the Domestic Fresh Produce Industry, 202
Studying the relationship between EcR signaling and the Hippo Growth Pathway in developing Drosophila wings through dILP8 expression
No full textEcdysone is a hormone that binds the Ecdysone Receptor (EcR), a transcription factor, to control Drosophila development. EcR regulates development by activating or repressing transcriptional targets which is influenced by the binding of other proteins called coregulators. To better understand EcR transcriptional activity and how it influences development our lab developed a set of tools that disrupts EcR signaling by preventing coregulators from binding endogenous EcR. Interestingly, the coactivator Taiman has been shown to bind both EcR and Yorkie, a component of the Hippo Growth Control Pathway. One of the genes that both of these pathways control is dILP8, but we do not know if they work together or independently to regulate dILP8 expression. To test this, we overexpressed our genetic tools in the developing Drosophila wings in the background of a series of transcriptional reporters that contain fragments of the dILP8 promoter. Our results show that EcR signaling does regulate the dILP8 promoter independent of the Hippo Growth Pathway. These results suggest that hormone signaling does affect targets of the Hippo Growth Control Pathway
Adsorption of Methyl Acetate on Zirconium (IV) Hydroxide
No full textThe adsorption and chemisorption of methyl acetate on zirconium (IV) hydroxide were measured by gas cell Fourier Transformed Infrared Spectroscopy, using methyl acetate as an analogue of chemical warfare agents (CWA) and toxic industrial waste (TIW), to reduce impact. Liquid methyl acetate was chilled to -14˚C and 1.0 cc nitrogen gas was bubbled through to dilute the vapor. The nitrogen gas vapor mixture was flowed over 0.100 grams of zirconium (IV) hydroxide over a period of 10 hours, and the produced vapor from the reaction was then analyzed using an FTIR gas cell. Infrared Gas Cell Absorption spectra peaks were integrated during the adsorption and chemisorption of methyl acetate on zirconium (IV) hydroxide. The carbonyl function group FTIR peak of methyl acetate vapor is used in conjunction with the molar absorptivity constant to quantitatively access the rate of reaction over an extended time frame. While results are not definite, the data points to the viability of the substrate as a practical adsorbent of dangerous compounds. As the adsorption of the compound by the metal hydroxide behaves in an analogous mechanism to chemical warfare agents, such as the chemical Sarin, the rate of saturation is used to predict the feasibility of zirconium (IV) hydroxide as a remediation method of objects exposed to toxicants
Human-AI Teaming for Academic Performance Analysis
Get PDFEducators today often work with students who are struggling academically, but limited time and resources make it difficult to uncover the root causes and provide timely assistance. Artificial intelligence (AI) is a growing, viable tool for analyzing large datasets and solving problems in different domains; however, human expertise is required to enhance the AI model’s performance. This study will utilize human-AI teaming to assess student performance based on factors such as their academic involvement, hours spent studying, and grade-point-average, among others. These findings will help instructors better grasp each student\u27s academic needs. By incorporating humans into the AI pipeline, we aim to build trust and also mitigate bias. Moreover, this study aims to provide a system that can bridge the gap between student struggles and instructional methods, ultimately fostering a more adaptive and supportive learning environment
Corrosion Resistance in Co-Based Spinel Magnetocaloric Candidates
No full textSpinel-based materials are widely regarded as promising magnetocaloric materials for refrigeration technology due to their tunable structural and magnetic properties. Recently, newly explored breathing spinels, particularly sulfides and selenides, have emerged as potential next-generation magnetocaloric materials for low temperature applications owing to their highly frustrated magnetic nature enabling large entropy changes and low magnetic transition temperatures. However, the long-term viability of these materials in magnetic refrigeration devices depends not only on their magnetocaloric performance but also on their chemical stability under operational conditions. This study addresses two key aspects: (i) cryogenic temperature and magnetic field corrosion testing on Co-based spinel magnetocaloric candidates, and (ii) synthetic exploration of new cobalt-based breathing spinel materials. Cryogenic corrosion testing was conducted by immersing the materials in liquid nitrogen while the corrosion resistance under high magnetic fields was evaluated by exposing the materials to varying magnetic fields of up to 1 T. Structural and surface integrity were examined using X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy before and after testing. This work not only advances the understanding of corrosion resistance in magnetocaloric spinels but also paves the way for the discovery of high-performance Co-based materials suitable for next-generation refrigeration technologies. Furthermore, the results of this study provide critical insights into their potential for long-term use in magnetocaloric cooling devices
Counting of Microfibers in Lake Allatoona Sand
No full textMicrofibers are present in sand. This study examines six beach sites on Lake Allatoona in Georgia to determine the concentration of microfibers in certain locations on the lake. Each sand sample will be analyzed up to six times. The concentration may increase by location based on proximity to the dam as the only outlet is release by the dam. Samples are gathered in the winter when the water level is low such that the sand taken is truly under water during the summer season. The sifted sand is weighed and transferred using a salt solution to a separator where the sand and the microfibers are separated by density. An oxidation step ensures any organic matter is removed prior to further density separation and finally filtration, with microfibers appearing on a filter. Using a microscope, microfibers are counted for each sample. It is expected that more microfibers will be found south of the dam as there is less water flow from the south towards the dam compared to the flow of water from the northeast
Properties of Eigenvalues of the Fractal Laplacian
No full textWe investigate the properties of the eigenvalues of the fractal Laplacian. We begin by defining the fractal Laplacian operator in one dimension and formulate the corresponding Dirichlet eigenvalue problem. Analytical solutions are obtained for specific fractal parameters, and computational results illustrate the structure of eigenvalues and their associated eigenfunctions. We extend our analysis to two dimensions using separation of variables. Our findings contribute to a deeper understanding of how fractal geometry affects the spectral characteristics of differential operators
Preparing Students for the Quantum Era: QML Training and Applications
Get PDFQuantum Machine Learning (QML) emerges as a transformative approach to addressing the growing complexities of modern data processing and computational challenges. Classical machine learning (CML) techniques, while powerful, face limitations in handling vast amounts of high-dimensional data and solving complex optimization problems efficiently. Despite its potential, QML remains underrepresented in academia, highlighting the need for accessible, hands-on learning experiences and knowledgeable faculty. This project seeks to advance QML education by incorporating it into diverse curricula, creating practical learning materials, and fostering workforce readiness. Using Google Colab, an open source labware has been designed to provide interactive learning modules (M0 to M8), each addressing specific computational and industrial challenges. These modules cover key QML concepts, including Quantum Support Vector Machines (QSVM), Quantum Neural Networks (QNNs), and comparisons between QML and CML. Additionally, select modules demonstrate real-world applications of QML algorithms in areas such as predicting product back-orders, quality inspection in manufacturing, patient flow analysis in healthcare, and predictive maintenance for operational efficiency. To support the adoption of QML in academia, a faculty workshop was recently held with participants from universities in Georgia, Florida, and Missouri, representing fields such as Industrial and Systems Engineering, Computer Science, and Electrical Engineering. This workshop provided faculty with the tools and knowledge needed to integrate QML modules into their courses. A student workshop is scheduled for the end of March, offering hands-on experience and engagement with QML concepts. This project is shaping the future of QML education by providing accessible, hands-on learning experiences and fostering interdisciplinary collaboration. Through faculty and student workshops, it equips the next generation of professionals with the skills needed to drive advancements in QML across academia and industry
The Power of Perception in Shaping CSA Prevention Beliefs
No full textThis study examines perceptions of capacity to prevent child sexual abuse (CSA) and how attitudes toward adults attracted to children influence beliefs in the effectiveness of CSA prevention strategies and interventions. While much existing research addresses CSA and pedophilia independently, limited attention has been given to how these attitudes impact perceptions of professional intervention efforts. This study aims to provide insights into how educational programs may reduce stigmatization and enhance confidence in CSA prevention strategies. Participants will complete an adapted Attitudes Toward Sexual Offenders (ATS) scale, respond to CSA prevention vignettes, and answer Big Five personality questions, alongside demographic items. The vignettes will assess participants\u27 thoughts, feelings, and behaviors toward different CSA prevention approaches, while the Big Five questions will help identify personality traits that may influence attitudes toward CSA prevention. Results will also explore whether personal responsibility, beliefs, and attitudes toward prevention strategies impact willingness to support CSA interventions. Participants are recruited through SONA and social media, with all responses captured in Qualtrics. Data collection is underway, with results still pending. The aim of this study is to help inform educational strategies and policies aimed at improving young adults\u27 understanding and support for CSA prevention interventions
Assessing the possible resistance to cardiac glycoside toxins in Opheodrys aestivus
No full textThe coevolution of predators and prey has produced many different adaptations in each. Certain species, for example, are protected by toxins which present a physiological challenge to the predators that consume them. Similarly, others have developed defensive mechanisms such as toxin resistance. The Rough Greensnake (Opheodrys aestivus), a serpent species native to North America, is an insectivore with a diet primarily composed of crickets, grasshoppers, and other bugs. Recently, one Rough Greensnake was documented consuming a Monarch Butterfly—species protected by cardenolide toxins.. Monarchs sport bright, vibrant colors as a warning sign of toxicity to predators. This curious observation prompted this research: a study investigating the potential Rough Greensnake resistance to the toxins sequestered by Monarch Butterflies. We used two samples of snake DNA (extracted from muscle tissue and a shed skin) to conduct Polymerase Chain Reaction (PCR) and amplified the ATP1A1, ATP1A2, and ATP1A3 genes, which code for the subunits of Na⁺/K⁺-ATPase. We then sequenced this DNA and examined sequences for amino acid substitutions that have been observed in other organisms resistant to these toxins. As such, the purpose of our study was to determine whether or not such substitutions were present within the Rough Greensnake. Here, we expanded upon the previous research, report our preliminary findings, and highlight opportunities for future research in this field