North Carolina Agricultural and Technical State University
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New Farmers of America Association
No full textMan with a bull calf.https://digital.library.ncat.edu/photos/2021/thumbnail.jp
Broken Foundation: Generational Trauma and Systemic Neglect in Black Families
No full textThis research examines the generational cycles of instability within Black families, mainly focusing on children who lack a stable support system. Many Black children grow up in environments where one or both parents are absent due to incarceration, substance abuse, or domestic instability. Often, caregiving responsibilities fall to grandparents who have faced similar hardships, perpetuating a cycle of trauma. This study explores how these patterns contribute to childhood exposure to drugs, crime, and systemic neglect. A key aspect of this research is adultification bias, where Black children, especially Black girls, are perceived as more mature than their white counterparts. This bias results in harsher treatment, reduced empathy, and fewer necessary interventions. Additionally, this study examines the harmful stereotyping of Black youth as combative or inherently “grown” when engaging in survival-based behaviors, leading to institutional neglect. Another critical component is the failure of child welfare systems, particularly the reintroduction of predators and sex offenders into the homes of vulnerable children. This study aims to advocate for policy reforms prioritizing Black children’s safety and well-being by exposing these systemic shortcomings. Using qualitative and quantitative research methods, this study incorporates interviews, case studies, and statistical analysis to examine child welfare practices, incarceration rates, and socioeconomic impacts. The findings will illuminate the underlying causes of generational trauma, challenge harmful societal biases, and propose community-based solutions to disrupt these cycles. Ultimately, this research seeks to inform policy and promote systemic change to create safer, more supportive environments for Black youth.https://digital.library.ncat.edu/honorscollegesymposium25/1031/thumbnail.jp
Upconversion Enhancement by Plasmonic Nanocavities
No full textUpconversion is the process of converting multiple low energy photons into one high energy photon capable of driving important chemical reactions. It carries promising potential for applications including photocatalysis, bioimaging, and therapeutic technologies. The light emitted from solid state upconverting thin films, however, is too dim for many applications. This is because the solid matrix prevents diffusion of donor and acceptor molecules and thus slows the multiple intermolecular energy transfer steps required for upconversion. In order to increase this emission, we are integrating molecules known to undergo upconversion into plasmonic nanocavities which produce extreme electric fields. We build these molecules into either molecular organic frameworks (MOFs) or supramolecular assemblies to control the relative orientations of the donor and acceptor molecules. We hypothesize that orienting the donor molecules (porphyrin derivatives) and acceptor molecules (anthracene derivatives) parallel to the electric field direction in the cavities will cause the field to promote intermolecular energy transfer. In this presentation, we will report on progress in synthesis of colloidal nanocubes, synthesis of donor and acceptor molecules, and exfoliation of 3D MOFs into 2D MOFs suitable for nanocavity integration. The creation of these samples will allow us to measure emission brightness and kinetics for various molecular orientations to determine how the electric fields affect energy transfer rates and yields.https://digital.library.ncat.edu/honorscollegesymposium25/1024/thumbnail.jp
Digital Science Notebooks and Their Role in Measuring Metacognitive Skills of Elementary School Students
No full textAs the United States strives to remain competitive in Science, Technology, Engineering, and Mathematics (STEM), a higher emphasis is being placed on equipping students with strong critical thinking skills and the ability to translate content-knowledge into innovative solutions. In science education, where inquiry and problem solving are foundational, metacognitive thinking plays a crucial role in bridging the gap between theoretical concepts and practical application. Students who develop strong metacognitive skills can better navigate scientific principles, critically evaluate their understanding, and refine their approaches to experimentation and analysis. Given the significance of these skills, it’s essential to explore effective strategies that enhance students’ metacognitive processes, ensuring they engage deeply with scientific learning. One approach is the use of digital science lab notebooks, which provide a platform for recording scientific observations and encourage students to reflect on their thought processes. My research question, “How well do digital science lab notebooks measure a student’s metacognitive skills in comparison to other methods of assessment in elementary school?” investigates whether these digital tools foster a deeper understanding of scientific concepts. Using multimodal discourse analysis, I will analyze students\u27 responses in their Arduino Digital Science Notebooks to determine if they promote metacognitive processing. The study examines two fifth grade classes, a sample size of approximately 20 students, who will take pre- and post- assessments to measure content knowledge and complete metacognitive awareness surveys. While results are preliminary, I predict that digital lab notebooks will enhance students’ metacognitive skills by promoting reflection and active engagement.https://digital.library.ncat.edu/honorscollegesymposium25/1023/thumbnail.jp
Sex-Specific Steroid Levels After Acute Ethanol Exposure in Adult Mice
No full textHeavy alcohol exposure can cause long-term physiological changes, with a potential for sex-specific differences in ethanol metabolism and immune response. This study investigates the impact of acute ethanol exposure on endocrine markers in adult male and female C57BL/6J mice. A total of 16 mice (8 male, 8 female) were divided into ethanol-exposed (n = 4 per sex) and control (n = 4 per sex) groups. Ethanol-exposed mice received intraperitoneal (i.p.) injections of 2.0 g/kg ethanol (20% v/v) twice, five days apart. One hour post-injection, blood samples were collected by submandibular sampling, centrifuged, and analyzed for 17B-estradiol using an enzyme-linked immunosorbent assay (ELISA). To assess immune activation post-ethanol exposure, estradiol concentrations were measured with an 17B-Estradiol ELISA Kit. The results reveal significant sex-specific and ethanol-induced effects on 17B-estradiol levels. In male mice, ethanol exposure resulted in a significant decrease in estradiol levels compared to saline controls (p = 0.0386), similar results were observed in adult female mice (p = 0.0063). In addition, a comparison between male and female saline-treated groups suggests that baseline estradiol concentrations are naturally higher in females than in males (p = 0.0193). These findings suggest that acute ethanol modulates 17B-estradiol differently in males and females, potentially contributing to sex-specific neural and immune responses to alcohol.https://digital.library.ncat.edu/honorscollegesymposium25/1010/thumbnail.jp
Fresh Food Markets Combats High Food Insecurities in Southeastern Region
No full textThis research project investigates food insecurity, defined as the lack of consistent access to sufficient, nutritious food. Food insecurity remains a significant issue across the southeastern region of the U.S. and the country at large. Studies show that food insecurity rates in some southeastern states exceed the national average, highlighting disparities in access to fresh, nutritious food. Fresh Food Markets (FFMs) serve as a potential solution to improve food access; however, their functionality and efficiency face key operational challenges. This study focuses on data collection issues, accessibility limitations, and logistical inefficiencies that impact the effectiveness of FFMs. In this study we analyze the demographic composition and travel patterns of individuals who visit FFMs in the southeastern U.S. to understand how effectively these markets serve local communities. We collect data through surveys conducted with FFM visitors. The data includes household characteristics, income ranges, and market locations. Using Tableau, we visualize the geographic distribution of FFMs and their visitors. We estimate travel distances using general location references such as intersections and landmarks. Household and travel distance data reveal demographic and accessibility differences among FFM locations. Location_1 has a higher concentration of multi-generational households, while Location_2 serves more families with children. The median travel distances ranged from 2.7 to 5.6 miles, suggesting variable accessibility across sites. This study underscores the importance of tailored strategies in FFMs placement and transportation. It also reveals a need for improved data systems and future study will explore tech-based solutions to increase access and efficiency.https://digital.library.ncat.edu/honorscollegesymposium25/1005/thumbnail.jp
Molecular Level Understanding of Epitope Binding Mimicry Leading to Onset of Type 1 Diabetes (T1D)
No full textMolecular mimicry, where foreign and self-peptides contain similar epitopes, can induce autoimmune responses. Identifying potential molecular mimics and studying their properties is key to understanding the onset of autoimmune diseases such as type 1 diabetes mellitus (T1DM). Previous work identified pairs of infectious epitopes (EINF) and T1DM epitopes (ET1D) that demonstrated sequence homology; however, structural homology was not considered. Correlating sequence homology with structural properties is important for streamlining translational investigation of potential molecular mimics. This work compares sequence homology with structural homology by calculating the structures and electrostatic potentials of 35 pairs of epitopes identified in previous work. For each epitope pair, the root mean square deviation (RMSD) was calculated between their predicted structures, and their electrostatic potentials were compared. Structures were predicted using AlphaFold and I-TASSER. A structural match of EINF and ET1D pairs was considered successful if the RMSD was \u3c 1.5 Å. AlphaFold found a 76.5% success rate and I-TASSER 82.35%. Of the pairs that could not be structurally matched (\u3c 3 residues aligned), AlphaFold found four unique pairs, and I-TASSER two. Both agreed on four structurally unmatched pairs. Despite structural differences, these four EINF/ET1D pairs show similar electrostatic distributions, indicating they may still bind to the same protein targets, major histocompatibility complex molecules, for T1DM. These findings suggest that searching for epitope pairs using sequence homology, a much less computationally demanding approach, leads to strong candidates for further study.https://digital.library.ncat.edu/honorscollegesymposium25/1034/thumbnail.jp
Predicting Effects of Conservation Practices on Runoff, Sediment, and Nutrient Loads from a Commercial Cotton Field Using Machine Learning and Deep Learning
No full textEstimating real-time sources of pollutants and evaluating the effectiveness of conservation practices in agriculture are crucial for prevention of water resources contamination. Pollutant load released from agricultural fields can be estimated using process-based model or data driven models. This study utilized machine learning (ML) models to predict water pollutant loads since they need fewer input features than process-based models. Hydro-meteorological data (e.g., temperature, rainfall, runoff) were collected from control and treatment fields (2016–2022), where cover crops and filter strips were used for pollution mitigation. Pollutant loads, including sediment, total phosphorus (TP), and total nitrogen (TN), were measured and used to train nine ML models: Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Random Forest (RF), Extreme Gradient Boosting (XGB), Histogram Gradient Boosting (HGBt), Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and a hybrid CNN-LSTM model. Results showed that the hybrid model best-predicted runoff in the control field (R²=0.87) and KNN in the treatment field (R²=0.82). LSTM excelled in sediment prediction for both fields, while RF and ANN were superior for TP and TN predictions, respectively. Model performance declined from runoff to sediment to nutrient loads due to error propagation. Advanced models (e.g., LSTM, CNN, hybrid) outperformed conventional ML models, showing robustness.https://digital.library.ncat.edu/gradresearchsymposium25/1114/thumbnail.jp
Assessing the Role of Entrepreneurial Ecosystem in Hydroponic Operations: A GIS-Based Suitability Analysis
No full textHydroponics, a soilless farming method, has gained traction due to climate change, rising land costs, and water efficiency. Despite its advantages, limited research has examined the key factors influencing hydroponic operations in the U.S. This study explores critical success factors and barriers for hydroponic farming in the Southeastern U.S. using a mixed-methods approach: producer interviews, market surveys, and GIS suitability analysis. We identified 92 hydroponic farms across eight states (NC, SC, TN, MS, LA, FL, GA, AL) and validated them through online presence and direct outreach. Interviews with 10 stakeholders revealed that market demand, financing, and technological innovation are primary determinants of success. A GIS-based suitability analysis incorporated restaurant density, income levels, population density, farmers\u27 market proximity, financial institution proximity, electricity grid access, and road networks to assess ideal farm locations. Weighted overlay analysis in ArcGIS Pro indicated that while existing farms are generally well placed, high-suitability zones remain underutilized. Findings suggest that integrating entrepreneurial ecosystem elements market access, capital, technology, and policy support—enhances hydroponic viability. Future research will expand suitability models to explore strategies to strengthen hydroponic entrepreneurship in rural and urban areas. This study informs farm site selection and policy strategies to support hydroponic sector.https://digital.library.ncat.edu/gradresearchsymposium25/1115/thumbnail.jp
Investigation of Melt Rheology for Direct Powder Extrusion (DPE) 3D Printing
No full textAdditive Manufacturing (also known as 3D printing) is a versatile technology that can aid in developing personalized medicine while maintaining cost and time efficiency. Currently, fused deposition modeling (FDM) is one of the most common 3D printing techniques used in the production of pharmaceutical drugs. However, FDM faces a few limitations, such as a two-step printing process and exposing material to multiple thermal processing steps, making it disadvantageous for clinical applications. Direct Powder Extrusion (DPE) is a recently developed 3D printing technology that is gaining popularity in the pharmaceutical research industry for its single-step printing process, making it ideal for clinical applications. The present study aims to investigate melt rheology of formulations prepared for Direct Powder Extrusion to develop a pH-dependent drug matrix using Eudragit L100-55 as the base polymer. However, processing Eudragit L100-55 for extrusion application is proving to be a challenge. Thus, by assessing the melt rheology of Eudragit L100-55 based formulations, the printability of the formulation can be evaluated in advance. The Anton Paar MCR 302 Rheometer was used for the rheological investigation. The amplitude sweep test, frequency sweep test, and temperature oscillation ramp test were conducted to investigate formulation rheology at a temperature range of 120-160°C. The findings conclude that investigation of melt rheology is crucial to evaluate formulation printability.https://digital.library.ncat.edu/gradresearchsymposium25/1122/thumbnail.jp