South Dakota State University

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    Gibney’s Guide: How to be a Student Soldier

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    This paper exemplifies originality through its unique synthesis of academic, physical, and leadership principles tailored specifically for ROTC cadets. By integrating insights from authoritative sources, such as SDSU\u27s diverse academic offerings and U.S. Army training standards, this guide provides a creative framework that bridges the gap between scholarly excellence and military preparation. Its structured approach to addressing the challenges of student soldiers, combined with actionable strategies, reflects a high level of scholarship, showcasing research-driven recommendations and practical applications. The paper’s alignment with ROTCspecific values and its emphasis on personal discipline and professional growth further highlight its innovative perspective, making it a compelling resource for aspiring military leaders.https://openprairie.sdstate.edu/honors_isp/1022/thumbnail.jp

    Generative AI for Synthetic Data Creation: Building Mastery-Focused Educational Datasets

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    Synthetic data is artificially generated data that mimics the statistical properties of real world data without exposing sensitive information. It is used in analysis, research, and deployments. Educational technology (EdTech) is an area where synthetic data can solve the problems of data scarcity, privacy concerns, regulatory compliance, bias reduction, data quality, data integrity, and cost efficiency. Our research aims to generate synthetic educational dataset by leveraging generative AI techniques such as Autoencoder, variational autoencoder and Copula-GAN. Our experimental results shows the significant progress in generating educational dataset and represents the data distribution of synthetic and real data

    Dairy and Food Science Student Newsletter, May 5, 2025

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    https://openprairie.sdstate.edu/dairy_student-news/1007/thumbnail.jp

    Presentation: \u3cem\u3eHARVESTING HOPE Storytelling and Indigenous Approaches in Social and Behavioral Science Research\u3c/em\u3e

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    SDSU Data Science Symposium, 2025

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    https://openprairie.sdstate.edu/ds_symposium_2025_gallery/1056/thumbnail.jp

    Lakota Plant Lesson Connecting Science and Culture for 2nd Graders

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    In this lesson, 2nd graders will learn about how the Lakota people use plants and why these plants are special. They will also discover the important parts of a plant—roots, stem, leaves, flowers, and seeds. Students will engage in activities like coloring, drawing, and exploring real plants found in schoolyard to help them understand each plant part and its function. This culturally responsive lesson blends science with experiential learning and emphasizes plant-people relationships. By the end, students will complete an art-based assessment to demonstrate understanding

    Evaluation of Established Perennial Clover Living Mulch and Soil Management Effects on Weed Suppression, Soil Health, and Broccolini Production for the Northern Great Plains

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    Vegetable cropping systems have long been reliant on the use of tillage to prepare favorable seedbeds and manage weed pressure. Tillage degrades soil structure, decreases water infiltration and leads to compaction. Due to recent droughts across the central United Stated, it is important for water conservation to improve infiltration and avoid run off and erosion. Changes in weather patterns not only influence drought conditions but bring heat waves that have made early and late planted cool season crops in the brassica family prone bolting, leading to unmarketable produce and economic losses for farmers. This 2023 and 2024 study was designed to evaluate living mulches of three established clover varieties, ‘Domino’ white clover (WC) (Trifolium repens), ‘Aberlasting’ white x kura clover (KC) (T. repens x ambiguum), and ‘Dynamite’ red clover (RC) (Trifolium pratense), and a bare ground control (BG); in combination with in-row soil management of tilled only (T), no-till (NT), tilled with fabric (TF), and no-till with fabric (NTF); and three broccolini cultivars, ‘Melody’ (ME), ‘BC1611’ (BC), and ‘Burgundy’ (BU). These 16 treatment combinations were evaluated for their impact on soil water infiltration, soil compaction, soil temperature and moisture; broccolini plant health metrics, growth and yield; and biomass of clover and weeds throughout two growing seasons. We hypothesized that the use of NT clover living mulch treatments would improve soil health quality and suppress weed biomass to reduce the need for tillage, and the use of in-row landscape fabric would guard against yield losses from clover living mulch competition. 2023 results showed that all three clover treatments improve soil water infiltration compared to the BG plots while there were no differences in soil resistance measurements in all treatments. Living mulch suppressed weed growth and biomass accumulation throughout the season with a significant decrease in weeds among WC, KC, and RC plots compared to BG conditions. The use of landscape fabric in the NTF treatment prevented significant yield loss in all three broccolini varieties and was comparable to the T and TF while the NT led to significant losses in yield. These results show that clover living mulch can be used to suppress weed and improve soil health. ‘Melody’ is smaller condensed variety that is quick to begin producing florets while ‘BC1611’, and ‘Burgundy’ are full sized and slower maturing. Broccolini varieties showed tolerance to heat stress that would make broccoli unmarketable. Living mulch can compete with a cash crop to reduce yield so it is important to use it in conjunction with a stress tolerant crop such as broccolini to prevent yield loss. This allows producers to spread out their economic risk while improving soil health using clover living mulch

    Deep Learning Approaches for Predicting Strain Energy in Heterogeneous Materials

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    Finite Element Analysis (FEA) faces computational challenges when analyzing nonlinear and heterogeneous materials. Utilizing the Mechanical MNIST dataset, comprising 60,000 simulated samples of 28x28 pixel domains under large deformation, the study evaluates classical regression methods (Linear Regression, Random Forest, Gradient Boosting) and advanced deep learning architectures (Convolutional Neural Networks (CNN) and Residual Networks (ResNet)). CNN models achieved superior performance, with a Mean Squared Error (MSE) of 4.21 and an R2 value of approximately 0.982, outperforming classical regression models and slightly surpassing ResNet architectures. These deep learning methods automatically learn spatial relationships from pixel-based representations, eliminating the need for manual feature extraction. The results establish deep learning as a highly effective surrogate modeling technique, enabling rapid and accurate prediction of strain energy compared to conventional FEA methods. This research advances the field towards real-time mechanical predictions, significantly reducing computational expenses in iterative design, optimization tasks, and large-scale simulations

    Finishing Location and Forage Diversity Influences Carcass Characteristics, Meat Quality Attributes, Terroir, and Color Stability of Grass-Finished Bison Bulls

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    The overall objective of this thesis is to determine the influence of finishing location and forage diversity on carcass characteristics, meat quality, terroir, and color stability of grass-finished bison bulls. The specific objectives were 1) Determine the effect of finishing location on carcass characteristics, meat quality attributes, and terroir of grass-finished bison bulls, 2) Investigate the effect of forage diversity on the carcass characteristics, meat quality attributes, and terroir of grass-finished bison bulls, and 3) Determine the effect of finishing location on the meat color stability of grass-finished bison bulls. Overall, results indicate that finishing location influenced carcass characteristics, objective tenderness, proximate composition, and trained subjective flavor attributes for grass-finished bison bulls. Furthermore, results indicated that the finishing forage diversity had a limited influence on carcass characteristics, meat quality attributes, and did not influence trained subjective texture or flavor attributes. Additionally, results illustrated that the finishing location of grass-finished bison bulls influenced objective color measurements, myoglobin concentration, and the lean antioxidant capacity of bison steaks. Bison bulls finished in Kansas had lighter (P \u3c 0.001) carcasses, decreased (P ≤ 0.014) marbling scores, and were objectively tougher (P ≤ 0.004) than those finished in Nebraska and Montana. Steaks from Kansas also had lower bison identity scores compared to Nebraska and Montana, while Nebraska steaks were rated higher (P ≤ 0.007) for liver – like and sour aromatic than those finished in Montana. Bison bulls finished on diverse forage produced carcasses with decreased (P = 0.019) marbling scores, greater (P \u3c 0.001) ash content, and greater (P = 0.010) objective tenderness than those finished with limited forage diversity. Bison from Kansas also produced steaks with increased (P ≤ 0.004) L* values and decreased (P ≤ 0.004) a* and b* values compared to those from Montana and Nebraska, regardless of packaging style. Finally, steaks from Montana finished bison bulls had greater (P ≤ 0.025) lean antioxidant capacity than those finished from Nebraska and Kansas. Very little is known about bison consumer preferences and purchasing decisions, and further research is warranted to develop color, tenderness, and flavor standards for the bison industry

    Minimizing Fasting Requirements to Maximize Patient Satisfaction Prior to a Scheduled Cardiac Catheterization

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    Background: Patients are often kept NPO (nil per os), or “nothing by mouth,” longer than necessary before cardiac catheterization procedures. Local Problem: Patients scheduled for cardiac catheterization procedures receive instructions to begin fasting at midnight on the day of their procedure regardless of their scheduled procedural start time. This directive results in patient dissatisfaction as patients are fasting longer than current guideline recommendation. Methods: The facility updated its order set to align with the American Society of Anesthesiologists (ASA) fasting guidelines for scheduled cardiac catheterizations. To evaluate patient satisfaction, a 6-item survey was administered to 169 individuals undergoing cardiac catheterization. The pre-intervention group (n=116) and postintervention group (n=53) were independent samples. An independent T-test was used to analyze differences in patient satisfaction. Results: A statistically significant difference was observed in both patient satisfaction (p= 0.046) and reported fasting duration (p= 0.0248). The pre-intervention group reported an average fasting burden score of 16.92 and an average fasting time of 12.59 hours, compared to the post-intervention group, which had an average fasting burden score of 15.62 and fasting duration of 11.08 hours. No cases of aspiration were reported with either fasting protocol. Conclusion: The results demonstrate that following ASA guidelines can improve patient satisfaction without increasing the risk of aspiration

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