Academic Excellence Symposium

Arbuscular mycorrhizal fungi (AMF) are symbiotic soil fungi that enhance plant nutrient and water uptake in exchange for root exudates, carbon in the form of sugar and organic acids. While past studies have found strong mutual benefits to the symbiotic relationship between alfalfa and AMF, the literature is silent about the impact of biochar on that relationship. This stu dy investigates the effects of woodchip-based biochar application on AMF colonization and growth of alfalfa (Medicago sativa). We hypothesize that increased biochar incorporation enhances the arbuscular mycorrhizal fungi colonization in the alfalfa roots, with greater biochar ratios resulting in greater AMF colonization. This study examined two key aspects: the percentage of roots colonized by AMF, and the growth performance of the plant. Measuring AMF colonization provides insights into enhanced interactions that occur between AMF and biochar. Field conditions were simulated in a controlled condition greenhouse using the ceramic Wagner pot method recognized by the scientific research community as the most effective method to test for the effects of soil amendment on field crops. The pots were filled with a topsoil collected from a local agricultural field that has recently hosted alfalfa production. The top 6 (six) inches of the pots were set up to have varying biochar to-soil ratios of 0%, 1%, 2.5%, and 3.5% w/w. The percentage of roots that have AMF colonization was measured on days 34, 48, 62, and 76 using the root staining method. Plant heights were measured every other day. Preliminary data showed a positive statistical relationship between biochar ratios and plant height. Upcoming AMF colonization measurements will provide information on the relation between biochar application and AMF population. Results from this study will support the innovative use of biochar application as a strategy to enhance Carbon sequestration in agricultural soils in Wisconsin.

Inaccessible classrooms pose numerous challenges for students, impacting their education and overall learning experience. Educational Barriers: Limited access to learning resources, difficulties in communication and collaboration, technological barriers in online classes, lack of personalized guidance, and distractions at home create significant challenges for students with disabilities. Social and Emotional Impacts: Health concerns, unequal access to resources, which exacerbates inequalities, limited social development, motivational issues, challenges in practical learning, difficulties in remote assessment, and emotional impacts from the lack of a regular classroom environment hinder the overall well-being and academic progress of students with disabilities. Addressing these multifaceted challenges requires integrating technology, employing flexible teaching methods, and establishing robust support systems to ensure effective learning for all students.

This study investigates robot navigation through an enhanced A* algorithm. The traditional A* algorithm, a well-established technique for determining the shortest path to a destination—akin to charting the most efficient course on a map—was thoroughly examined. Subsequently, a review of existing literature on the A* algorithm was conducted to identify enhancements for improving its efficiency and accuracy. A Python program was then developed to implement these advancements. To visualize and evaluate its effectiveness, CoppeliaSim, a sophisticated simulation environment for observing robotic motion, was employed. Envision a robot dexterously navigating a virtual maze, evading obstacles, and reaching its target, all guided by the refined code. The simulation confirmed that the robot adhered to the optimized trajectory as intended. The objective was to elevate the efficiency of robotic movement, and the endeavor yielded demonstrable success.

UW-Green Bay’s Cofrin Center for Biodiversity, NEW Bird Alliance, and Audubon Great Lakes formed a deep, collaborative partnership with the Oneida Nation through the successful implementation of the volunteer Oneida Bird Monitoring Program (OBMP). With the help of 100+ volunteers and student scientists, we have conducted breeding bird surveys and migratory shorebird and waterfowl surveys at multiple restoration sites on the Oneida Nation Reservation. Collectively, our dedicated volunteers have conducted nearly 1,500 surveys and counted >200,000 individual birds of 200+ species. Data collected for this program inform land management decisions, such as the Indigenous practices of prescribed burning and water level manipulation. The goals of our poster are to 1) Evaluate how shorebird and waterfowl communities change across fall and spring migrations at Oneida Nation restoration sites and 2) Determine if we are sampling migratory waterfowl and shorebirds adequately enough across sites. Understanding migratory patterns and phenology of North American bird communities can help inform land management and evaluate sampling efforts and strategies. We used R statistical software to create bar graphs documenting how migratory waterfowl and shorebirds change throughout the year across Oneida Nation’s restoration sites in terms of frequency and abundance. To evaluate sampling adequacy, we generated species accumulation curves using R. We will feature a few example bar graphs and curves and share how these data graphics can inform land management and tell the story of migratory bird communities at Oneida.

This project focuses on a creation of a 2-Dimensional simulation of a model rocket launch using MATLAB and Simulink. The simulation includes real-world factors such as time-varying thrust, rocket body drag, gravity, wind, launch angle, fuel and mass loss during flight along with the parachute deployment. Users of the program will be able to input different parameters, such as the parachute size, drag coefficients, wind speed, launch angle, and the rockets mass. The rocket's flight is set in three stages, the first being the powered ascent, the coasting period after rocket burnout, and the descent assisted from the parachute for the model rocket. Using real engine data collected and loaded in from .CSV files, the correct thrust over time can be applied, using interpolation as needed to match the time data. After the fuel is finished and the rocket is in its coasting period, the parachute deployment delay charge based on the actual delay charge time is deployed. This model uses this data to calculate how the rocket moves in both the vertical and horizontal directions and plots the results, including altitude, velocity, and flight path. Using basic physics, Fluid Dynamics, and Analysis of Dynamic Systems concepts, the model was built to better understand how different inputs can affect rocket flight. This project also includes creating free-body diagrams, writing motion equations,, and building a system model that can be tested and visualized. This project was done independently with the guidance from Professor Rasedul Islam.

Listeria monocytogenes (Lm) is a Gram-positive, intracellular bacterium found ubiquitously throughout the environment that is the causative agent of listeriosis, one of the deadliest foodborne illnesses. Approximately 1,600 cases occur in the United States annually resulting in a 20% fatality rate and a 95% hospitalization rate. Developing fetuses are especially vulnerable to Lm, as the resulting maternal immune response to infection can lead to spontaneous abortion in 25% of affected pregnancies. The bacterium preferentially infects placental trophoblasts and decidual macrophages, the latter of which play a crucial role in driving the inflammation that leads to miscarriage. Previous research has shown that Lm-derived DNA delivered to macrophages via extracellular vesicles can activate the cGAS-STING pathway, leading to the production of proinflammatory type I interferons (IFN-α/β), which are associated with suppressed macrophage bactericidal activity. Typically, Lm readily replicates in macrophages unless the cells are polarized toward a proinflammatory M1 phenotype. Widely utilized murine macrophage cell line RAW 264.7 can effectively clear intracellular Lm following treatment with IFN-γ. Surprisingly, however, treatment with extracellular vesicles from Lm-infected cells led to increased bacterial growth in these same cells, despite elevated TNF-α production — a proinflammatory cytokine typically associated with enhanced antimicrobial activity and M1 polarization. Interestingly, another commonly used murine macrophage cell line, J774, produced TNF-α and effectively killed Lm following exposure to both IFN-γ and extracellular vesicles from isolated from Lm-infected cells. The unexpected variability in permissiveness to bacterial growth suggests that small differences in baseline macrophage polarization states may influence how extracellular vesicles modulate immune function. Our research aims to develop consistent and accurate phenotypic tests for assessing M1/M2 polarization to better characterize the functional discrepancies observed across cell lines and to investigate how extracellular vesicle-mediated signaling pathways, such as cGAS-STING, impact macrophage activity. "