K-State Electronic Theses, Dissertations, and Reports: 2004 -
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This is the collection for doctoral dissertations and masters theses and reports submitted electronically by K-State students. Electronic submission of doctoral dissertations was required beginning Fall semester 2006. Electronic submission for masters theses and reports was required beginning Fall 2007. The collection also contains some dissertations, theses, and reports from the years 2004 and 2005 that were submitted during a pilot test project. Some items before 2004 have been digitized and are available in K-State Electronic Theses, Dissertations, and Reports: pre-2004. Check the Library catalog for dissertations, theses, and reports not found in these collections.
All items included in this collection have been approved by the K-State Graduate School. More information can be found on the ETDR Information Page. Items within this collection are protected by U.S. Copyright. Copyright on each item is held by the individual author.
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Item Open Access Communicating climate-change impacts to youth: A social influence theory perspectiveCannon, LaurenClimate change is known to have severe impacts on Earth’s temperature, organisms, human health, and habitats. Despite overwhelming scientific evidence, many individuals hold misbeliefs about climate change. Misbeliefs can prevent policy changes or environmental action to reduce climate-change impacts from taking place. Previous scholars have addressed the potential causes behind these misbeliefs, including misinformation, confirmation bias, and tribalism. Since current solutions have not yet significantly reduced these misbeliefs or their causes, this report explores the issue using a social influence theory perspective. By synthesizing literature on social influence theory, climate-change communication, and the use of youth groups and activities for education, it is concluded that communicating to youth groups and their leaders about climate-change impacts could produce the greatest change in reducing misbeliefs. This is due to the combination of normative social influence, leadership and mentorship influence, and healthy environments in youth group structures. These findings inform a communication plan for reducing misbeliefs about climate in youth groups in low socioeconomic areas of Kansas. By educating youth about climate change, we can significantly reduce misbeliefs overall through generational replacement and allow more policy changes and environmental actions to be implemented to reduce climate-change impacts.Item Open Access Use of artificial intelligence to locate and treat weeds in Midwestern United States corn (Zea mays) and soybean (Glycine max) cropping systemsBarnhart, IsaacSite-specific weed management (SSWM) is defined as the process of managing weeds where they are growing as opposed to treating the whole field and treating areas with no weeds. Artificial intelligence (AI), the process of creating intelligent machines, has become a part of everyday life in modern society. Utilizing convolutional neural networks and object detection algorithms, weeds can be distinguished from crops, and herbicide applications can target weeds where they are growing. The objectives of this dissertation were to 1) train open-sourced object detection algorithms to detect in central Kansas soybean (Glycine Max [L.] Merr.) fields, focusing on Palmer amaranth (Amaranthus palmeri S. Watson, henceforth denoted as A. palmeri), 2) determine herbicide efficacy and cost savings of SSWM herbicide applications using a ONE SMART SPRAY research sprayer, an intelligent dual-boom sprayer using AI technology to locate and spray weeds growing within crops, and 3) compare traditional broadcast (BCST) applications with spot-spray (SS) herbicide applications using a commercial-sized ONE SMART SPRAY sprayer. Images were obtained from two soybean fields in 2021 containing A. palmeri infestations and were annotated with bounding boxes to identify both A. palmeri and soybean plants. In this study, the YOLOv5 object detection algorithm was identified as having the highest mean average precision scores and was therefore selected for further analysis. The precision, recall, and F1 evaluation metrics found for the test image dataset was 0.71, 0.70, and 0.71, respectively. Regression analysis revealed that our trained YOLOv5 model evaluation metrics were higher when identifying A. palmeri plants 2 cm in height at low plants m-2. For the second objective, corn (Zea mays L) and soybean field trials were conducted in Manhattan, KS and Seymour, IL with the research-sized ONE SMART SPRAY. Simultaneous herbicide applications of residual BCST + foliar SS, base-rate foliar BCST + SS “Spike” rates, and SS only were compared in corn (Zea mays L.) and soybean trials. Specific SS thresholds tested included an herbicide efficacy, balanced, savings, and traditional BCST applications were tested for comparison. Results showed that both residual BCST + foliar SS and “Spike” approaches provided weed-free area not different than traditional broadcast applications, in many cases. The greatest savings were achieved by SS only applications, but weed-free area was almost always significantly less than for other treatments. Simultaneous BCST + SS of soil residual and foliar herbicides, respectively, provided the most weed-free area with the greatest cost savings for both crops. Thirdly, we tested a commercial-sized ONE SMART SPRAY and compared traditional broadcast applications with SS only and simulated two-boom/two-tank applications using the foliar base rate + “Spike” approach. Treatments included SS only, low rate BCST + high rate SS, and high rate BCST + low rate SS applications. Results indicated that high rate BCST + low rate SS applications provided the highest weed-free area, but savings were not different from a broadcast application in soybeans. In corn, thresholds were not different, but both applications with BCST applications demonstrated greater weed-free area than SS only treatments. Overall, this research demonstrated that 1) open-sourced object detection algorithms can be custom trained to identify A. palmeri in soybean crops, with opportunities to train and identify other weed species in other crops, 2) intelligent AI sprayers show potential in providing weed-free area comparable to traditional BCST applications, especially systems that utilize two-tank/two-boom technology for simultaneous BCST and SS applications, and 3) herbicide costs were significantly reduced for SS applications compared to traditional BCST applications.Item Open Access Assessing the impact of cover crops on soil health in a long-term no-till rotation: A case study from Northeast KansasGrünberg, JessicaMaintaining soil health is essential for sustaining agricultural productivity and ecosystem resilience. Conservation agriculture, known for minimal soil disturbance and permanent soil cover, offers strategies to address soil degradation associated with conventional management practices like conventional tillage and prolonged fallow periods. Despite its recognized benefits, there are concerns regarding potential drawbacks, such as nutrient stratification and soil acidification over time. Cover crops have emerged as a promising tool for enhancing soil health, however, long-term effects of cover crops on soil proprieties under no-till management and various intensification schemes remain to be fully understood. This study aimed to assess (i) how different preceding cover crop types and varying nitrogen (N) rates applied to corn influence pH, soil organic carbon (SOC), and nutrient concentrations and distribution in the soil profile, and (ii) the effects of different intensification strategies on soil biological indicators and their persistence throughout subsequent years of the rotation. A long-term experiment consisting of a no-till three-year wheat (Triticum aestivum L.), sorghum [Sorghum bicolor (L.) Moench], soybean [Glycine max (L.) Merr] rotation was established in 2007 near Manhattan, Kansas. Sorghum was replaced with corn (Zea mays L.) in 2020. The different fallow managements imposed between wheat and corn included chemical fallow (CF), double-crop soybean (DSB), and four cover crop treatments. To meet the first objective of this study, soil profile samples were collected in 2021 and 2022 after corn harvest to determine how different fallow management preceding corn and different N rates applied to corn affect soil pH, SOC, Total N, and Melich-3 Phosphorus (P) concentration and their distribution in the soil profile. Nutrient concentrations were higher near the soil surface, and pH tended to decrease in the upper soil layers. Differences among the fallow management options were most pronounced at the 0-5 cm depth for all measurements. Soil organic carbon was enhanced by adding cover crops and DSB compared to CF. Similarly, Total N was greater whenever any cover crop treatment or DSB replaced a portion of fallow. Soil pH increased with cover crops and DSB and decreased with higher N rates only at surface layers. Phosphorus concentrations decreased with DSB and remained similar to CF for most cover crops. Overall, cover crops and intensification alternatives like double-cropping showed potential to improve SOC and N levels in the soil surface and enhance its capacity to buffer changes. Further research should address managing the negative impacts of P stratification on soil health and water quality. To meet the second objective, soil samples were collected in May 2022 and April 2023 in all crop phases, to capture the effect of fallow management on biochemical indicators at different time intervals after cover crop termination: immediately after cover crop termination (T0), in corn stubble one year after cover crop termination (T1), and in growing wheat two years after cover crop termination (T2). Samples were collected at the 0-5 cm depth and analyzed for the following biochemical indicators: POXC, soil protein, glucosidase and glucosaminidase activities, and soil respiration. Cover crops positively impacted all soil biochemical indicators immediately after cover crop termination (T0), increasing POXC by 30%, soil protein by 17%, glucosidase activity by 63%, glucosaminidase activity by 82%, and soil respiration by 116% compared to CF. In general, cover crops with larger biomass inputs provided the largest increases in biochemical indicators. Double-crop soybeans exhibited indicator levels similar to or slightly greater than CF, yet lower than most other cover crops. These responses were most evident immediately after cover crop termination and persisted to some extent for one year thereafter. However, the responses diminished over time and were not detectable two years after cover crop termination. This information could assist in determining how frequently cover crops should be integrated into cropping systems and identify the most effective mixtures and species for sustaining soil health benefits over time.Item Open Access Synthesis, characterization, and electrocatalytic hydrogen evolution of transition metal Schiff-base calixpyrrole complexes with pendant hydrogen bond donorsTrowbridge, LoganThree novel calixpyrrole complexes with pendant hydrogen bond donors were synthesized via the condensation of 5,5’-diformyl-2,2’-diphenyldipyrromethane and an aniline precursor. Single crystal X-ray diffraction revealed that these complexes displayed distorted square planar geometries, and significantly the pendant groups remained uncoordinated from the metal. Electrochemical studies, along with density functional theory (DFT) calculations, indicated that the ligand exhibited redox non-innocence as evidenced experimentally by similar irreversible oxidations in both the ligands and complexes. Electrochemical analysis in the presence of p-toluenesulfonic acid generated an irreversible reduction about 400-500 mV more positive than the background reduction by the glassy carbon electrode, indicative of electrocatalytic hydrogen evolution. All the complexes exhibited similar catalytic waves which persisted after rinse tests signifying the generation of an electrode-adsorbed catalyst which was stable under catalytic conditions. A square planar Ni(II) complex, Ni(DPMDA) (DPMDA=2,2’-((diphenylmethylene)bis(1H-pyrrole-5,2-diyl))bis-(methaneylylidene))bis(azaneylylidene))dianiline), of the previously reported calixpyrrole ligand of was synthesized and analyzed for electrocatalytic hydrogen evolution in the presence of anilinium tetrafluoroborate. It was found that under catalytic conditions a heterogeneous species was formed on the electrode surface which was found to be stable and operate at turnover frequencies (TOF) of up to 25,900 s⁻¹ or 366,000 s⁻¹ cm⁻². Kinetic isotope effect (KIE) and Tafel analysis suggest rate-limiting proton coupled electron transfer (PCET) likely facilitated by the pendant amines which enabled high TOF despite evidence of redox-mediated outer-sphere electron transfer. Ni(DPMDA) was evaluated for electrocatalytic hydrogen evolution in the presence of a weaker proton donor, triethylammonium tetrafluoroborate. Under catalytic conditions, a heterogeneous species was similarly formed. Experimental evidence suggested that the identity of this species differed from that formed in the presence of anilinium as evidenced the absence of redox features attributable to the heterogeneous species, peak potential dependence on bulk catalyst concentration, and lower overpotential despite the use of a weaker proton donor. The lack of features attributable to the heterogeneous species indicated inner-sphere electron transfer and TOF of 5,700 s-1 or 80,000 s-1cm-2 were observed. Similarly, KIE and Tafel analysis suggest rate-limiting PCET for which the pendant groups were implicated as hydrogen bond acceptors/donors during buffered solution studies.Item Open Access An investigation of the application of autoencoders and large-language models to privacy-utility tradeoffs in group-specific settingsMandal, BishwasMachine learning models have emerged as highly effective tools in tackling an array of practical challenges, including image classification, regression tasks, behavioral forecasting, and natural language processing, among others. Their ability to analyze substantial volumes of data endows them with significant value across diverse domains. The widespread success of machine learning models has led data analysts and scientists to extensively incorporate them into predictive and generative modeling endeavors. While leveraging data can enable professionals to gain insights into user preferences and refine predictive and generative accuracy, there exists a risk of inadvertently or intentionally inferring sensitive personal information from the data. Consequently, there is a critical need for the development of privacy mechanisms capable of sanitizing data to shield sensitive attributes while retaining data utility. Achieving this balance is pivotal in safeguarding individual privacy amidst the complexities of the digital age. In discussions revolving around privacy considerations, there is a prevalent assumption that privacy requirements are homogeneous across the populace, a construct termed as the single-group setting. This dissertation introduces an adversarial learning framework that employs various iterations of autoencoders, specifically designed to navigate the privacy-utility tradeoff within this single-group setting. While the single-group setting holds significance in numerous practical contexts, it fails to consistently capture the varied requirements of different use cases. Recognizing the imperative to address a broader spectrum of scenarios, this dissertation introduces a problem formulation focused on the privacy-utility tradeoff within two distinct user groups. These heterogeneous groups encompass users characterized by differing private and utility attributes, aiming to encompass a wider array of application scenarios within the privacy-utility tradeoff domain. Furthermore, the landscape of computer science is undergoing significant transformation, particularly in light of the recent surge in large language models (LLMs). LLMs are rapidly evolving, necessitating a thorough examination of the impact of these advancements on privacy domain. Thus, this dissertation endeavors to investigate whether LLMs, endowed with diverse capabilities, can be effectively employed for data sanitization to uphold user privacy. The straightforwardness of this approach without requiring specialized expertise underscores the adaptability of large language models in addressing privacy concerns. Collectively, this dissertation seeks to enhance the understanding of privacy-utility tradeoff in different group specific settings with adversarial learning frameworks and large language models. The findings underscore the potential of these methodologies to provide robust privacy protections while simultaneously preserving or augmenting the utility of data across a myriad of applications.Item Embargo Yes, You Can, In Fact, Reuse Your Leeches Without the Fear of Nosocomial InfectionsSoula, MariajesusIntroduction: Leeches are used in human and veterinary medicine as a treatment for venous congestion. It is recommended to discard leeches after one use. A concern with reusing leeches is potential spread of bacterial infections. If a leech were to harbor bacteria from one patient in its gastrointestinal (GI) tract, it may transmit them to another patient, potentially, even serving as a vector for multidrug resistant (MDR) infection. We sought to determine the safety of reusing leeches inoculated with an MDR Staphylococcus aureus. Study design: Experimental, ex-vivo Animals: 63 leeches were split into eight treatment groups and one control group. Methods: Treatment leeches were fed canine blood inoculated with an MDR strain of Staphylococcus aureus while control leeches were fed clean canine blood. Cultures were obtained at 1 day, 1 week, and 1-, 2-, 3- and 4-months post-inoculation. At each time point, cultures were taken of aquarium water, GI contents, and blood that the leeches were allowed to feed on. Cultures were evaluated for the presence of Staphylococcus aureus. Results: All water samples were negative except for one tank at seven days. After two months and three months, all GI tracts and blood meal samples were negative, respectively. Clinical significance: Leeches will harbor MDR Staphylococcus aureus after inoculation with infected canine blood. This bacterium is not detectable in the water after 7 days and no longer detectable in the leech or blood meal after 3 months.Item Embargo Dietary and physical activity risk and protective factors for lean non-alcoholic fatty liver disease: A scoping reviewCorrigan, JoanneNon-Alcoholic Fatty Liver Disease (NAFLD) is one of the most common causes of chronic liver disease globally and describes a spectrum of conditions ranging from simple hepatic steatosis to liver cirrhosis and/or failure. Although it is more prevalent in populations with metabolic risk factors including obesity, insulin resistance, dyslipidemia, and type 2 diabetes, it can also occur in lean populations who may or may not present with symptoms of NAFLD. Consequently, lean populations with NAFLD can be overlooked in both clinical and research settings. Despite the associations between diet and physical activity and the prevention of many chronic diseases, primary research exploring the association between diet and physical activity and NAFLD risk in lean populations is lacking. The purpose of this scoping review was to describe the available research on dietary and physical activity risk and protective factors in lean NAFLD, define key terms related to this condition, and identify knowledge gaps to inform future research. A literature search was conducted between March 2021 and August 2023 in PubMed, Global Health, ProQuest Nursing and Allied Health, Web of Science, and Scopus. Sixty-four articles were included in the review. The predominant study designs were cross-sectional and prospective. More than half of the studies were based in Asia. Research topics included the associations between specific diets, food groups, macronutrients, micronutrients, beverages, and varying physical activity characteristics, and lean NAFLD risk. Very few definitive conclusions could be made about potential dietary or physical activity risk and protective factors for lean NAFLD due to several limitations in the current body of evidence. These limitations included a high risk for bias and lack of ethnic diversity in study populations, as well as significant heterogeneity in results, definitions of key terms, and NAFLD diagnostic criteria. To address these deficits, future research is needed on topics explored in the current body of evidence, using higher quality study designs that limit the risk of bias, integrate more ethnic diversity in study populations, and implement consistent terminology and NAFLD diagnostic criteria.Item Open Access Theatre skills for conflict management: Using theatre performance techniques to teach college students better conflict management abilitiesMorrow, CaleThe life of a traditional aged college student is filled with many fast-moving decisions and new life experiences. When conflict arises in a student’s life, it can upend a student’s progression if they are not properly trained to deal with conflict. Current conflict management teaching curricula being given to students are insufficient due to overly complex language and lack of emphasis on the social and emotional intelligence skills training required for successful conflict mitigation. To correct this problem, this dissertation proposed the creation of a new conflict management curriculum that combined traditional conflict management techniques with select theatre performance techniques to account for the inadequacies in current conflict management curricula. This new curriculum was tested through a workshop process with traditional college students attending a mid-sized, Midwestern research university acting as participants. All participants either worked for or lived in a building run by university housing services. Interviews with students were conducted post-workshop, and a qualitative, narrative based, case study was conducted to test this theatre infused curriculum. Justification for this new curriculum, detailed lesson plans for the workshop, a breakdown of the creation of the new curriculum, and the results of the case study can be found within.Item Open Access Investigating changes in scientists’ ethical decision making and course designsGarcia, TylerOne way to bring about change in higher education is to introduce professional development programs for higher education, however these programs have been found to be ineffective at promoting positive change for individuals and departments. To address the need for better programs, I worked on two projects: one project attempts to identify a way to improve Responsible Conduct of Research training and the other project is an assessment designed to be distributed in a Thermal and Statistical Physics course that supports instructors on improving their curriculum. Many scientists view science as value-free, despite the fact that both epistemic and non-epistemic values structure scientific inquiry. Current Responsible Conduct of Research training usually focuses on transmitting knowledge about high-level ethical concepts or rules and is widely regarded as ineffective. We argue that Responsible Conduct of Research training will be more effective at improving ethical decision making if it focuses on connecting values to science. Due to the investigation of research ethics education in physics being relatively new, we pull from philosophy and psychology to define ethical decision making using the Four Component Model. This model states that in order to make an ethical decision someone must consider four components: moral sensitivity, moral reasoning, moral motivation, and moral implementation. For this study we formed a moderated fellowship of fourteen science faculty from different disciplines who met for ten sessions over the course of a year, where they discussed the values embedded in different scientific norms. We then conducted interviews before and after the year-long fellowship that involved guided reflection of scenarios where there was some kind of ethical misconduct where the scientific practice required value judgements (e.g using unpublished data). From this data we looked at how the fellowship affected the scientists’ ability to recognize ethical dimensions in their work. We found that this fellowship improves moral sensitivity, but their moral reasoning does not change. We then identified a more precise approach to looking at scientists’ moral reasoning. This work can inform future ethical training to align better with what scientists value and introduce useful concepts from philosophy and psychology to education research in physics. There are calls to create assessments that focus on gathering evidence that shows both knowledge of the desired subject and transferable skills between disciplines while providing useful feedback to instructors. To answer this call, we created a thermal and statistical physics assessment that provides evidence of student knowledge and skills in a thermal or statistical physics course that also provides actionable feedback to instructors. To create tasks, we use a knowledge-in-use framework that focuses on identifying the evidence we need to see in student answers to claim students are able to do physics, not just know physics. These “evidence statements" are the observable features students generate that show they have knowledge to complete a claim. We need to determine a way to validate the tasks based on the focus towards obtaining evidence of student abilities when solving tasks. Current literature focuses on bringing in experts to validate whether the tasks are at the right level for the students. We are looking to expand on literature in Physics Education Research (PER) by articulating a way to validate tasks that use evidence-centered design through looking at students’ evidence statements. To validate the assessment, we identified new components to gather evidence towards validation. Using these new components we introduced a new methodology to validate assessments that focus on delivering feedback through evidence. We have conducted and analyzed student think-aloud interviews answering the tasks in a free-response format or in a Coupled Multiple-Response format. We also conducted faculty interviews to see if the tasks are relevant to their courses. Through these interviews we developed a new methodology of contributing to the validation of assessments that focus on faculty feedback. This dissertation introduces new methodologies for future researchers to improve on Responsible Conduct of Research trainings and assessment designed for supporting instructor curriculum. Through these new methodologies scientists can address the calls for better professional development programs in higher education.Item Open Access Grain Weight Retention during Terminal Heat Stress in Hard Winter WheatSchuh, NicholasClimate-resilient wheat cultivars with tolerance to high temperatures after flowering are essential to reliable wheat production in the central and southern Great Plains. Breeders have an experiential understanding of germplasm capable of maintaining test weight under terminal heat stress, yet understanding of underlying genetics is limited. In a preliminary greenhouse/growth chamber experiment to identify post-anthesis heat stress tolerance genetic resources within central and southern Great Planes germplasm, two breeding lines were identified with contrasting tolerance phenotypes: HV9W03-1596R maintained green leaf area, and TX04M410164 maintained grain weight under post-anthesis heat stress. A recombinant inbred population (208 lines) was developed from the progeny of crossing these two lines and grown in ten Kansas field environments. Traits measured were yield, plant height, flowering time, physiological maturity time, grain fill period, test weight, kernel diameter, kernel weight, and kernel hardness. Yield, plant height, flowering time, test weight, kernel diameter, and kernel weight were all found to be highly heritable. In the 2018 field season, average high temperature during the 21 days following anthesis at three trial locations was 29.1C to 30.4C, while the optimal temperature for wheat grain filling is reported to be 21.3C. In three 2018 trial locations, mean test weight ranged from 652 to 758 g L-1, and mean kernel weight ranged from 19.8 to 23.5 mg. In contrast, in three 2020 trial locations, mean test weight ranged from 745 to 830 g L 1, and mean kernel weight ranged from 26.5 to 30.9 mg. Stress sensitivity indices (SSIs) were calculated at seven trials, using three highest yielding trials as the control environment. The SSIs for flowering time and physiological maturity had very little variation under an extreme stress environment and high variation under a moderately stressful environment. We observed the same phenomena in yield and kernel diameter SSIs. Two quantitative trait loci were found on chromosome 1B in a preliminary analysis, and SNP markers were developed. One SNP was significant for kernel diameter, kernel hardness, kernel weight, test weight, grain yield, plant height, and grain fill period length and the other was significant for kernel hardness, test weight, grain yield, plant height, and grain fill period length best linear unbiased predictors. One SNP was significant for kernel diameter and test weight stress sensitivity, and the second SNP was significant for kernel weight, grain fill period, and physiological maturity stress sensitivity. The RIL population also was segregating for the Ppd-D1 and Vrn-D3 genes that affect flowering time. These flowering time genes had significant effects on stress sensitivity. Future work will isolate near isogenic lines from RILs heterozygous at one or both of the 1B regions. These lines will be evaluated for heat tolerance in controlled environments and field environments to quantify the effects of these regions on post anthesis heat stress tolerance.Item Open Access Non-exponential reward discounting in deep reinforcement learningAli, Raja FarrukhThe science of sequential decision making, formalized through reinforcement learning (RL), has driven various recent technological breakthroughs, from mastering complex games that require strategic thinking to driving advancements in natural language processing. Central to an RL agent's learning is how it treats rewards (the learning signal) and adjusts its policy to maximize cumulative rewards. Future rewards are weighed less than immediate rewards, and traditional RL methods employ exponential discounting to balance immediate and future rewards. However, studies from neuroscience and psychology have shown that exponential discounting does not accurately reflect human and animal behavior, who instead exhibit hyperbolic discounting of future rewards. This dissertation explores non-exponential discounting, such as hyperbolic, in different facets of deep RL such that it can mirror the intricate decision-making processes found in humans, and evaluate its impact on agent performance in a variety of settings. First, I revisit the idea of hyperbolic discounting and the auxiliary task of learning over multiple horizons in RL agents while using off-policy value-based methods, studying its impact on sample efficiency and generalization to new tasks while incorporating architectural and implementation improvements. Second, I introduce a two-parameter discounting model based on generalized hyperbolic discounting in the deep RL setting. With its sensitivity-to-delay parameter, this model enriches temporal decision-making in RL, as evaluated through empirical evidence. Third, I apply hyperbolic discounting to multi-agent systems, examining its influence on collective decision-making and performance, revealing the potential for improved cooperation among agents. These contributions highlight the impact of non-exponential discounting on agent performance, linking theory with AI practice, facilitating human-like decision-making, and paving the way for new research directions.Item Open Access An examination of legal representation on plea bargained sentencing outcomes for criminal defendants.Grube, JohnathanThis dissertation examines the pervasive notion that retained attorneys offer superior legal defense compared to appointed attorneys. Such beliefs hold substantial implications for justice equity, as a defendant's financial resources should not dictate the caliber of their defense or the subsequent sentence they receive. Yet, a dearth of understanding persists regarding the influence of attorney type on sentencing outcomes. This study bridges this gap through a quantitative examination of attorney type and its impact on sentencing. Indigent defendants, unable to bear the financial burden of legal representation, are informed by a judge of the attorney appointed to represent them in criminal proceedings. Judges appoint attorneys because these defendants may lack the means to retain an attorney with a proven track record of trial success, which financially able defendants can readily secure. Consequently, a defendant's limited resources may hinder appointed attorneys from mounting a robust defense, potentially affecting the decision to pursue trial. Therefore, it is crucial to ascertain whether indigent defendants receive equitable representation compared to those capable of retaining their own legal counsel. To address this concern, this dissertation employs bivariate logistic regression models to analyze the impact of defense attorney type on the plea negotiation process, as evidenced by negotiated sentencing outcomes, within Kansas state district courts. Specifically, utilizing sentencing data from the Kansas Sentencing Commission spanning fiscal years 2015 to 2019, this study applied logistic regression analysis to investigate the impact of attorney type across three distinct research questions pertaining to sentence disposition, departure sentences, and the choice between concurrent and consecutive sentences. Notably, all three models yield statistical significance and identified significant variables for each research question. Alongside numerous significant demographic variables, the analysis reveals attorney type as a significant predictor of both sentence disposition and departure sentences. The implications of these findings, alongside theoretical and policy considerations, are thoroughly discussed, aiming to inform future academic and policymaking endeavors.Item Open Access Balancing Tradition and Tomorrow: Smart Growth Strategies for the Sustainability of Rural CommunitiesPfeifer, CadenIn the post-World War II era, the globalization of U.S. cities has triggered population decline in many rural communities, prompting a quest for solutions to sustain their prosperity. However, concerns have arisen regarding the impact of standardized development regulations on these communities, affecting their ambiance and distinctive, place-specific character. This research delves into the intricate balance required to foster growth while preserving the unique character of rural communities. Central to this investigation is exploring the Smart Growth concept as a potential solution to enhance local development regulations and safeguard the essence of small towns by taking Dodge City and Garden City, as case studies. The study aims to determine how integrating Smart Growth principles can contribute to addressing challenges related to rural community character. Doing so establishes a foundational understanding for future researchers to delve into applying Smart Growth principles in the rural context, with considerations for broader implications in sustainable planning.Item Embargo Tailored peptide hydrogel-based three-dimensional system improves stem cell maintenance, therapeutic potential and differentiationLi, QuanStem cells are a type of cells capable of self-renewal and differentiation and exist in both fetal and adult tissues. Stem cells can be totipotent, pluripotent and multipotent with decreasing differentiation potentials. Multipotent stem cells like hematopoietic stem cells have already been used to treat some diseases as they can give rise to blood cells, but application of other stem cells is still limited. Pluripotent stem cells, i.e. embryonic stem cells (ESCs) are isolated from early-stage embryos and are thus limited by donor scarcity. Thanks to the development of human induced pluripotent stem cells (hiPSCs), cell source is no longer an issue, but the maintenance of iPSC still poses challenges. Previously we developed a three-dimensional (3D) method that produces large amount of high quality hiPSCs, but the mechanism for 3D iPSC maintenance is still unexplored. Based on the previous established 3D hiPSC culture methods using peptide hydrogel PGmatrix, we found that the better proliferation performance compared to other hydrogel-based 3D culture system was due to ability of the hiPSCs to modify its surrounding environment. During growth in PGmatrix, the hydrogel strength changed. The mechanical cues can be sensed by hiPSC, leading to modulation of proliferation. The novel 3D method can help fulfill the need of high quality iPSCs for downstream applications like therapeutic treatments and differentiation. Liver hepatocytes, as an example, is in large demand not only for disease treatment but also for pharmaceutical development. However, hepatocytes derived from iPSCs are still functionally far from primary hepatocytes, there is a thus need to improve the differentiation method. Compared to differentiation in matrix-free non-adherent plate, the hepatocyte organoids obtained from PG-suspension had significantly higher expression of key hepatocytes genes, some gene expression and in vitro detoxification function were comparable to primary hepatocytes. Besides modeling and treating diseases with cells or organoids differentiated from iPSC, there are also therapies that use stem cells directly. Currently mesenchymal stem cells (MSCs) are preferred for therapeutics because these cells can release more growth factors and signaling molecules then iPSCs, but 2D-culture MSCs showed varied level of treatment effects mainly because they were not adapted to the in vivo niche. Studies showed that MSC therapeutic potential improved after adopting 3D conformation, but there’s yet a method that steady MSC 3D preparation and delivery for treatment. In therapeutic application, we encapsulated MSCs in PGmatrix overnight before treatment through injection. Compared to hyaluronic acid (HA) and Hystem hydrogel, PGmatrix preserved high cell viability, promoted pluripotency protein expression and improved skin wound healing at an early stage in mice. Together, these results demonstrated improvements in stem cell research through application of PG hydrogel 3D systems. By tailoring peptide hydrogel for different research fields, there may be more advancement in stem cell related applications.Item Open Access Bovine respiratory disease: Treatment outcomes, prevalence of antimicrobial resistance and systematic review of control methodsNeal, KyndallBovine respiratory disease (BRD) is an economically important disease in feedyards influencing both animal welfare and use of antimicrobials. While much research has been completed there are still knowledge gaps regarding the treatment plans and optimal ways to manage cattle with BRD. The objective of the first chapter of the thesis was to identify potential associations between nasopharyngeal microbiota and antimicrobial resistance patterns of clinical cases that lived or died compared to non-diseased controls. Enrolled animals were subdivided based on clinical disease status and case outcome (subsequent mortality or finishing the feeding phase). Deep nasopharyngeal swabs were collected from enrolled animals and submitted for bacterial isolation, antimicrobial susceptibility determination, and metagenomics analysis. Enrolled cattle were represented in three groups: animals at first treatment for BRD that subsequently died (BRDM, n=9), animals at first treatment for BRD that subsequently lived (BRDL, n=15), and animals that were never treated for BRD during the feeding phase (CONT, n=11). Antimicrobial resistance patterns for Pasteurella multocida illustrated that cattle in each outcome category had isolates that were pan-susceptible or only showing resistance to oxytetracycline. Nasal metagenomics analysis showed relative abundance of species and genera with few differences among the three outcomes. Higher alpha diversity was identified in BRDL compared to CONT at the species level and both BRDL and BRDM showed increased alpha diversity compared to CONT at the genera level. Overall, this work illustrated nasopharyngeal microbiota showed relatively few differences among BRD cases that lived or died compared to animals without BRD. The second chapter objective was to identify potential relationships between risk factors known at the time of initial BRD treatment with three post-treatment outcomes: first treatment success (FTS; finishing feeding phase with no further treatments), non-cause specific case fatality risk (CFRALL; post-treatment mortalities from any cause), and cause-specific case fatality risk (CFRBRD; mortalities attributed to BRD). This retrospective analysis used generalized linear mixed models to evaluate relationships between covariates of interest (arrival: sex, weight, month; treatment event: days-on-feed (DOF), rectal temperature, day-of-week, antibiotic drug class) with each outcome (FTS, CFRALL, CFRBRD). Analysis included 132,521 individual-animal initial BRD treatment records from 14 central U.S. feedyards (May 2017 to Dec 2020) with overall FTS of 67.8%, CFRALL of 10.0%, and CFRBRD of 6.3%. The FTS was associated (P < 0.05) with all covariates except sex, CFRALL was associated with all covariates, and CFRBRD was associated with all covariates except day-of-week treated. Treatment early in the feeding phase (DOF 0-10, 11-20) was associated with lower FTS (49.2% ± 0.8; 55.3% ± 0.8), higher CFRALL (12.5% ± 1.3; 12.6% ± 1.4) and higher CFRBRD (6.3% ± 1.1; 6.1% ± 1.0) compared to cattle treated on days 21-70. Rectal temperature in the 39.4-40.0°C category had higher CFRALL (15.3% ± 1.5) and CFRBRD (9.2% ± 1.5) compared to other rectal temperature categories. Increased knowledge of risk factors associated with treatment outcomes has the potential to help inform therapeutic decisions. This systematic review in the third thesis chapter sought to identify published information relative to antimicrobial use in BRD control and metaphylaxis. Specific research questions addressed case fatality risks, first treatment success, switching drug classes between treatments, switching drug classes between metaphylaxis and first treatment, post-metaphylactic or post-treatment intervals, as well as concomitant therapies. Databases searched included PubMed, CAB Direct, and Agricola, resulting in 418 publications meeting the search criteria. Manuscripts were then sorted into topic categories for review. Case fatality risk decreases with treatments of tulathromycin when compared to other antimicrobials. Similar trends were seen with first treatment success and included other macrolides as well, resulting in higher success. Studies showed longer post-treatment intervals had better morbidity resolution when compared to shorter post-treatment intervals. No prospective manuscripts were found regarding switching drug classes between metaphylaxis and first treatment or first and subsequent treatments. The research that evaluated concomitant therapy for BRD treatment did not show an advantage compared to single-antimicrobial treatment. This literature review identified several knowledge gaps related to specific application methods of treatment; and more research in these areas could be conducted to understand the optimal management practices and treatment strategies for BRD in cattle. By looking into more treatment options and outcomes there is hope to improve future BRD treatment outcomes. While much remains to be learned, research is always being conducted and new information leading to BRD successes can be found.Item Open Access Using Contemporary Compositional Techniques in Teaching Improvisation to ChildrenLasko, AgnieszkaThis lecture-recital investigates the inclusion of improvisation within the framework of beginning and intermediate piano students. It includes simplified versions of improvisational techniques known from the works of composers of the 20th and 21st centuries. Elements of improvisation based on clearly defined rules help guide the spontaneous activities of beginners and provide new ideas. To ensure the comfort of both teachers and students, a balance was maintained between structure and creative elements. Consequently, work on the pieces begins with following the score first and then improvising. Additionally, all the pieces were written with a certain musical or technical point in mind to support the development of piano skills at the early stage of their piano education.Item Embargo The effects of social media on the mental health of collegiate male athletesJazsmin, HalliburtonThe purpose of this thesis report is to research how social media is related to mental health in male student athletes focusing on the two most popular sports in the United States: football, and men’s basketball at the collegiate level. The popularity of men’s sports is more prominent than women’s sports, which is way male athletes are the focus for this research. This study is guided by the theoretical framework of framing and uses and gratification. The method of elite interviewing was used with the three division I male athletes participating with in the research. Research suggests athletes may be more likely to downplay or minimize the severity of their own mental health issues. In using the method of elite interviewing of the three former student athletes interviewed, only one said that he has experienced anxiety due to comments made about him by fans on social media platforms. One athlete is not mentally affected by the comments of fans and media due to where he grew up. The third athlete never experienced hurtful comments directed towards him, therefore, he was never mentally affected. Recommendations for future research in this topic would be a higher volume of research participants. An additional recommendation would be research into the discussion of mental health in the Black community, due to a majority of men’s football and basketball players being Black.Item Embargo Machine systems to enhance agronomic response in seeding technologiesGigena Berretta, BautistaThe importance of proper planting and crop establishment cannot be underestimated, as they directly affect crop yield, quality, and overall agricultural productivity. Growers have varying field conditions and adopt different planting strategies, and each requires a unique approach to achieve desired agronomic responses. Hence, proper selection and adoption from existing precision planting technologies suited for their conditions is essential to optimize crop input resources and enhance crop yields. This research examined two essential aspects of precision planting systems and its application into two different growers’ situation. The first study involved assessing the effectiveness of row cleaners within air-seeders in high-residue environments, and, second study analyzes the performance of high-speed planting on no-till fields. A novel methodology based on a computer vision system was developed to objectively evaluate the effectiveness of row cleaners installed on single-disc air seeders in creating optimal seed furrow conditions for improving seed placement. Through the implementation of a tailor-made data acquisition system and the operation of an air seeder across different wheat residue conditions, the study demonstrated the feasibility of quantifying row cleaner operation in real time, exposing the possibility of assessing the performance of varying row cleaner models for air seeders on an unbiased and repeatable way, and also paving the way for automating control decisions during seeding processes. High-speed planting experiment involved comparing the performance of two precision planting systems on corn, evaluating various parameters, including planting accuracy, frame flexibility, overall productivity, downforce control, and section control. Findings revealed subtle differences between the two planting systems on productivity and planting quality. Still, there are notable differences on flexibility depending on the frame of each planter utilized as well as a slight difference in plant spacing. Overall, these studies contribute to advancing agricultural technology by providing objective methodologies for assessing and improving seeding and planting practices, ultimately enhancing efficiency and productivity in modern farming operations. The learning also set a baseline for future research on air seeder row cleaners and for upcoming research on row crop planter performance.Item Open Access Predicting harmful algal blooms and uncovering mortgage bias: a data-intensive thesisKompella, KavyaThis thesis presents two data science approaches for important environmental and social problems: predicting harmful algal blooms (HABs) resulting from cyanobacteria and identifying racial biases inherent in home mortgage systems. In the first chapter, a machine learning model is developed to forecast HABs in Marion Reservoir, Kansas. HABs are a threat to water resources as they emit toxic chemicals that are harmful to agriculture and aquatic species. Early prediction of algae growth will help manage and prevent further growth. Various models are utilized for the prediction, including Random Forest, Support Vector Machine, Gaussian Bayes, Decision Tree, Long Short-Term Memory models, and XGBoost. In addition, using feature analysis, several factors were found that do not significantly affect the accuracy of predictions. Furthermore, the research extends its scope by comparing the algal bloom trends observed in Owasco Lake, New York, with those in Marion Reservoir. The findings of this research highlight the capacity of data science methodologies to tackle environmental issues, hence offering insights into the topic of proactive regulation of the water ecosystem. The second chapter examines an extensive dataset of federal home mortgage data in the United States. This dataset covers 13 years and includes a vast number of loans. By utilizing machine learning methodologies, we reveal a significant correlation between the qualities of borrowers and mortgage data, particularly concerning the borrower's racial background. The results of our study indicate an association between the personal attributes of borrowers and loan data, suggesting that borrower race plays a significant role in the observed racial discrepancies in mortgage lending. Although other historical and present prejudices may be at play, this study offers quantitative evidence of racial biases across the home mortgage system. By identifying and examining these biases, our study makes a valuable contribution to enhancing comprehension of the social concerns about equality and discrimination within the financial industry. Together, these chapters emphasize the significance of employing data-driven research methodologies to address complex environmental challenges and uncover disparities in social equity. This highlights the multidisciplinary capacity of data science in the pursuit of achieving a more sustainable and equitable future.Item Open Access Feminism and Feminist Pedagogy in Two Helping ProfessionsStrowbridge, MichelleIn the past century there has been a significant amount of literature regarding the waves of feminism and the advancement of womxn in higher education. In addition to the waves of feminism and womxn’s influence on higher education, there has also been a thorough recounting of the history of academic advising. However, despite all three of these areas being studied in great detail, the connections between all three has not yet been explored in the literature. This dissertation explored feminism and feminist pedagogy in two helping professions though (a) an examination of the use of feminist pedagogy existing literature in nursing, and (b) the lived experience of female primary-role academic advisors. These findings then shaped a model of feminist academic advising grounded by feminist pedagogy. This dissertation was guided by the following research questions: How do scholars discuss feminist pedagogy in nursing, an exemplary helping profession? How do female primary-role advisors who identify as womxn and feminists express feminist identity in the academic advising workplace? This dissertation consists of three related papers. Paper #1, a structured literature review, explored the available literature of the use of feminist pedagogy in an exemplary helping profession, nursing. Articles from were pulled from Nursing Allied Health and Google Scholar under the designators of including “feminist pedagog*” in nursing and written in English to include articles that used the term feminist pedagogy and feminist pedagogies. After a 5-phase protocol, 12 articles were accepted into the final sample. Three themes emerged: classroom climate, curriculum design, and care versus cure. The implications for the field were: the need of feminist pedagogy in the education of nurses due to the hierarchical nature of medical fields, the need for nurses to be prepared to fight against the policies in healthcare that oppress certain populations, and the importance of feminist pedagogy in nursing for the education of all gender identities. Paper #2, a phenomenology, explored how primary-role advisors who identify as womxn and feminists describe the role feminism plays in their advising practice. This study explored the use of feminism in the practice of 22 participants. Data was collected through three semi-structured interviews and analyzed using thematic analysis. Three themes emerged: mindfulness of physical space as a cornerstone for comfort, power of communication in forging meaningful connection and relationships, and empowering students to make their own decisions. There were three implications for this research: the focus on the experience of the academic advisor themselves, the impact personal identity has on advising practice, and how feminism can impact academic advising as a field. In Paper # 3, I introduce a new approach to academic advising incorporating feminist pedagogy with seven tenets: the positionality of the advisor, relationship-centered approach, mindful of power dynamics, intentionality of physical space, social justice and advocacy, a holistic understanding, and resilience and community building. The adoption of a feminist model in academic advising promises a transformative shift within the educational landscape, poised to redefine interactions between advisors and students, the institutional approach to student support, and the broader scholarly understanding of advising practices. Collectively, the papers from this dissertation suggest four important overarching themes: an emphasis on inclusive and welcoming environments, challenging traditional power dynamics, integrating personal experiences and social justice, and a holistic approach to education and advising. These findings have important implications for the profession of academic advising in the available research that advisors and institutions can use as a basis for new advising approaches. Additionally, this dissertation will introduce new ways to increase social justice, advocacy, and inclusion, and use other helping professions as examples of how to incorporate new and potentially innovative ideas into advising practice.
