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Enhancing Youth Learning Outcomes of Travel Programs through Storytelling
No full textWe conducted two studies to evaluate strategies that Extension educators may use to enrich youth travel program experiences. Study 1 evaluated the effects of telling stories about attractions before site visits on youth experiences and learning outcomes on site. Seventeen youth in a 4-H program designed to promote cultural understanding visited eight attractions in Costa Rica. The evening before visiting three sites, youth were told a fictional or cross-fictional story about the sites. The stories elicited imaginary travel to the site (narrative transportation). After visiting the sites, the youth reported the extent to which they felt like they were in a story (narrative re-visitation) while on-site. They also reported their anticipated impact of learning experiences on one of the program’s learning outcomes. Narrative transportation significantly increased narrative re-visitation. Both factors significantly increased the anticipated impact on learning outcomes. In Study 2, 35 4-H youth visited 12 agricultural sites in the Western U.S. and Canada. Three experimental conditions were created by an Extension educator: vastness emphasized via educator comments, vastness not emphasized, and baseline. The two treatment conditions produced greater awe than baseline. The relation between awe and anticipated impact on learning outcomes was significant
Graph Symbolic Regression to Interpret the Propagation of Vesicular Stomatitis Virus Across the U.S. and Mexico
No full textThe Vesicular Stomatitis virus (VSV) causes cases of livestock disease that occur every year in regions in Mexico. Every few years, VSV spreads northwards into the U.S. in large outbreak events affecting hundreds of livestock premises across multiple states, leading to significant economic losses due to quarantines, trade restrictions, and veterinary expenses. VSV cases are mainly driven by biting arthropod vectors from multiple genera with different ecologies, making outbreak control challenging. The sporadic nature of outbreaks and limited understanding of transmission dynamics further hinder containment efforts, reducing the effectiveness of preemptive measures. In this paper, we propose an interpretable model to elucidate the key rules governing the spread of VSV. This model employs a sparse symbolic regression model, SINDy (Sparse Identification of Nonlinear Dynamical Systems), to identify the most significant ecological variables in spread dynamics, considering both spatial and temporal factors. Since many counties did not have VSV cases during the study period, counties were clustered into 40 regions incorporating static environmental variables land cover, soil properties, livestock density, and climate data and using spatially constrained Agglomerative Clustering based on geographic adjacency, resulting in an average region size of approximately 90 counties. Ecological variables included dynamic and static variables such as temperature, humidity, wind, soil characteristics, and altitude associated with vectors and hosts (cattle, horses, and mules). The change in cases from month to month by region was modeled using two SINDy variants: a baseline model with only ecological features (Normal) and an extended model incorporating spatially derived graph features (Graph).Each alpha was chosen to minimize CV-MSE while retaining less than 11 terms. Graphical features greatly reduced model error, and the SINDy model with select graphical features had a slightly better CV-MSE score than when all graphical features were included. All models identified the infected species as important in capturing the dynamics of case differences between regions
Using quantum annealing for sampling and pattern generation in generative machine learning and catastrophic forgetting mitigation
No full textThe first goal of this dissertation was to understand the reasons for the absence in previous investigations of significant and consistent improvements in the trainability of Restricted Boltzmann Machines (RBM) when the Quantum Annealer (QA) was used for sampling from the RBM probability distribution. The second goal was to address the shortcomings of those previous investigations, explore possibilities of improving RBM training, and identify other machine learning applications that could benefit from sampling or from generating patterns by the QA. The first part of this dissertation focused on a Local-Valley (LV) centered approach to assessing the quality of sampling. QA-based and Gibbs samples were compared based on the number of the LVs to which they belonged and the energy of the corresponding local minima. Many of the LVs found by the two techniques differed. However, for higher-probability sampled states, the two techniques were (unfavorably) less complementary and more overlapping. The limited complementarity of the QA-based sampling explained the failure of many previous investigations to achieve substantial (or even any) improvements. However, the results also revealed some potential for improvement, e.g., by combining the QA-based and the classical sampling techniques to possibly include samples that would be missed by any of the two methods alone. In the second part of the dissertation, a novel hybrid sampling method was developed, combining the classical and the QA contributions. LVs found from QA solutions were combined with a subset of training patterns to initiate the Markov chain during the RBM learning. No improvements in the RBM training have been achieved in this part of the work, supporting the hypothesis that the differences between the QA-based and MCMC sampling are insufficient to benefit the training. In the third part of the dissertation, the feasibility of using QA-generated patterns for generative replay-based mitigation of Catastrophic Forgetting (CF) during Continual Learning (CL) has been demonstrated for the first time. Both the speed of generating a large number of distinct patterns, including those from the lower probability parts of the distribution, and the potential for further improvement make this approach promising for various challenging machine learning applications
Evaluation of irrigation frequencies and nitrogen treatments on furrow irrigated rice
No full textWater withdrawn from the Mississippi River Valley Alluvial Aquifer (MRVAA) is predominantly used for agricultural irrigation purposes, with almost half of the water being delivered to rice (Oryza sativa L.) fields. To maintain the MRVAA as a sustainable water source, more efficient irrigation management practices should be employed for rice cultivation. Furrow-irrigated rice (FIR) has shown promise in growing rice with less water, but overall productivity and variability among agronomic characteristics of rice is still to be determined. This study was conducted from 2021 to 2023 at the Delta Research and Extension Center in Stoneville, MS, to determine an irrigation management plan in FIR, evaluating four irrigation frequencies: daily, every three, five, and seven days. Rice grain yield, agronomic characteristics, water level depths, water usage, and irrigation water use efficiency (IWUE) were determined with Pani-Pipes, Precision King AgSense Sensors, and flowmeters for each irrigation frequency overall and spatially within the treatment plots. Irrigating every day resulted in greater rice grain yield (11,009 kg ha-1) compared to irrigating every three (10,281 kg ha-1), five (9,908 kg ha-1), and seven (9,872 kg ha-1) days. Plots irrigated every day, or every three days produced significantly greater grain yields in the bottom zone compared to the top zone. Irrigation frequency did not interact with plant height (p = 0.4311) but was influenced by spatial zone (p = 0.0142). Milling yields showed no differences across irrigation frequencies or spatial zones. Water level depths are influenced by irrigation frequency (p = 0.0008), spatial zone (p \u3c 0.0001), and irrigation frequency by spatial zone (p \u3c 0.0001). The bottom zone of plots irrigated daily was the only irrigation frequency and spatial zone to keep water level depth above ground level at 2.77 cm. Plots irrigated every day had greater water usage of 0.36 ha m, but lower IWUE of 12.87 kg mm-1 ha-1. This study suggests that anytime water level depth drops below -5.08 cm (2022) or -2.54 cm (2023), rice grain yield would be negatively influenced. The overall objective of this study is to evaluate four irrigation frequencies (irrigating every 1-d, 3-d, 5-d, and 7-d) effect on rice grain yield, agronomic characteristics, and irrigation water factors in FIR
Anxiety, stress, and depression as a predictor of established vaping among high school students
No full textPrevious research has linked initiation of e-cigarette use with mental health but has not identified how mental health factors impact patterns of use of these products in adolescents. I tested the hypothesis that adolescents who report vaping to cope with stress, depression, and anxiety have more established patterns of use with data from the National Youth Tobacco Survey. Crosstabulations and logistic regression outcome measures included current use, intensity of use, and cumulative lifetime use. Reasons for initial and current use related to mental health were associated with current e-cigarette use, more intense use, and higher cumulative use. Mental health plays a significant role in higher levels of established e-cigarette use and increased risk of dependence. Due to the temporal limitations of this cross-sectional data, future experimental research is needed to determine directionality of the relationship between e- cigarette usage and mental health
Evaluating three lightweight airfield matting systems under F-35B aircraft loading
No full textAircraft matting has been in service since WWII. It has provided a maneuverable substrate to allow aircraft forward operations to take place in austere environments. AM2 is the main matting system that has been used for generations. In recent years, the need for a lightweight matting system has come to the forefront of the matting community. This is not only to improve the maneuverability, but also the shipping restrictions. This research is on three different light weight matting systems above subgrade with two CBR values (i.e., 6 and 25). A specially designed load cart was adopted to simulate F-35B loading. The correlations of permanent deformation of subgrade underneath lightweight matting systems with number of passes under F-35B aircraft loading considering the variation of CBR of subgrade were established based on the test results. According to the test results, MAT 3 meets all the requirements, while MAT 1 and MAT 2 need improvements
A mixed-method study of African American parents’ involvement in their children’s Individualized Education Program process
No full textThe major purpose of the study was to examine the unique experiences of African American parents regarding their parental involvement in their child’s Individualized Education Program process. In addition, the study aimed to investigate the perceptions of teachers and administrators regarding the experiences of the African American parents as they worked with the parents and their children during the IEP process. Epstein’s (1987, 2008) Model of Parental Involvement was used as a theoretical framework to underpin the study emphasizing six dimensions of parental involvement. The six dimensions of parental involvement include the following: parenting, communicating, volunteering, learning at home, decision-making, and collaborating with the community. A sequential mixed-method research design, integrating both quantitative and qualitative approaches, was used to explore the African American parents\u27 involvement during the IEP process. Data were collected through surveys, semi-structured interviews, and direct observations. Participants included administrators, special education teachers, and African American parents of children with disabilities enrolled in a modern, comprehensive public high school serving grades nine through twelve. Survey findings revealed an overall mean score of 4.07 out of 5 for the responses of African American parents regarding their experiences of involvement in the IEP process, indicating the African American reported favorable involvement in their child’s IEP process for all six dimensions of Epstein’s Parental Involvement Model (parenting, learning at home, communicating, decision-making, volunteering, and collaborating with community). The overall mean scores as perceived by the teachers and administrators regarding the African American parents’ involvement was 2.89 out of 5, indicating the teachers and administrators perceived minimal African American parental involvement. The analysis of data from the interviews revealed African Americans were most familiar with the initial component of the IEP process. The African American described challenges they faced during the IEP process including limitations with educational jargon, scheduling conflicts, power imbalances, and limited culturally responsive practices. General recommendations for parents, administrators, educators, and other policymakers to improve African American parental involvement in the IEP process are presented. Efforts are presented to help foster children’s success and empower parents, and families to address their child’s unique educational needs while enrolled in special education services
Physiological and behavioral impacts of a campus-based equine-assisted intervention program
No full textAs college administrators look for solutions to the mental health crisis facing campuses, alternative methods, such as equine-assisted intervention (EAI), have grown in popularity. While a review of literature found abundant evidence for animal-assisted intervention programs for college students, research on the role of EAI on college student mental health is limited. Therefore, this study targeted college students participating in a one-day equine wellness event. Saliva samples were taken for cortisol and neurotransmitter concentrations from both horse (n = 7) and human (n = 14). Students wore heart rate monitors throughout the event and completed a survey to measure stress. Heart rate reached aerobic threshold. Stress levels (P = 0.0001) and emotional state (P = 0.003) improved. A positive correlation between human and horse serotonin post-EAI (P = 0.05) was observed. These results indicate that an on-campus EAI program would be beneficial to the mental health of college students
Quantifying sea surface temperature patterns in the eastern tropical Pacific and downstream impacts on precipitation and tornado outbreaks in the United States
No full textThe El Niño Southern Oscillation (ENSO) and off-equatorial climate modes significantly impact sea surface temperature (SST) patterns in the eastern tropical Pacific and the broader downstream climate. While much of the literature highlights ENSO’s role in influencing U.S. precipitation and tornado outbreak activity, focusing solely on ENSO has limitations. Many studies also rely on empirical orthogonal function (EOF) techniques to diagnose climate-scale SST structures, limiting the ability to link individual SST patterns with downstream phenomena. EOFs require statistical adjustments to generate representative composite maps; however, these maps often fail to accurately represent observed seasonal SST patterns because each composite reflects only a portion of the total SST variability. The goal of this dissertation is to enhance the understanding of how ENSO and other SST variability affect downstream climate by using machine learning techniques, specifically hierarchical and k-means clustering. Cluster analysis provides a more direct method to link specific SST patterns with corresponding downstream impacts. This approach identifies tropical eastern Pacific SST patterns, including both equatorial and off-equatorial regions, and assesses their relationships with U.S. precipitation and tornado outbreaks (TOs). Chapter 1 introduces ENSO and related SST modes while outlining the key objectives of the study. Chapter 2 applies hierarchical and k-means clustering to SST data from the ERSST dataset (1950–2021) to identify eastern tropical Pacific patterns, encompassing both ENSO-related and off-equatorial variability. Chapter 3 investigates how the four SSTA clusters identified in Chapter 2 influence U.S. precipitation, emphasizing the physical linkages between SSTAs, the thermal wind, and the 250-hPa jet stream. Chapter 4 explores the impact of the same SSTA clusters on U.S. TOs, highlighting changes in TO activity associated with spatial shifts in 500-hPa geopotential height and 250-hPa winds. Chapter 5 synthesizes key findings, discusses broader implications, and outlines opportunities for future research