K-State Electronic Theses, Dissertations, and Reports: 2004 -
Permanent URI for this collectionhttps://hdl.handle.net/2097/4
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 Embargo Bed-based ballistocardiography: physiological assessment and system design(2025) Knapp, CalderThe ballistocardiogram (BCG) is an information-rich bio-signal that can give researchers an additional perspective on the complex dynamics of the cardiac cycle. As a relevant alternative to the electrocardiogram (ECG), the BCG represents the transduced force produced by the ejection of blood from the heart around the aortic arch. Due to its characteristic propagation through the participant’s body and corresponding measurement system, the BCG offers a combination of physiological information about the participant. In its current state of research, integrated BCG systems are being developed to predict various physiological health measures. This thesis seeks to further develop the range of physiological predictions available to BCG, focusing on Kansas State University’s bed-based BCG acquisition system. Specific physiological prediction of instantaneous blood pressure is first investigated in this thesis. Utilizing parallel BCG sensors integrated into a bed, frequency-domain analysis is used to predict instantaneous blood pressure during simulated apnea events. With 16/20 participants resulting in strongly correlated predicted blood pressure and an average mean absolute error (MAE) across all participants less than 5 mmHg, this frequency analysis method could offer improved morphology-independent blood pressure prediction using BCG. Preliminary classification of apnea events is also performed for a single extended run (~10 minutes) of simulated apnea and rest events. With an average of 95% balanced accuracy across six folds, further investigation on a larger dataset should be performed to follow up on this preliminary connection between beat-by-beat apnea classification and the BCG frequency domain. This analysis seeks to expand the use case of the BCG as an “all-in-one” apnea detection signal. The frequency domain is chosen for investigation due to a key limitation often observed in BCG research. System-level differences and participant-specific body positions can lead to morphological changes between participants. Time-domain analysis is often limited to individual systems/participants due to a combination of factors such as system design, sensor coupling, and cardiac output. With the intuition that the bed-body system can be characterized and has an effect on the BCG’s morphology, the next logical step in the included research is to identify if the BCG can be used to predict relevant participant-specific characteristics. Using DEXA as a gold standard to measure regional and total body fat percentage, the BCG morphology is investigated to identify any features relevant to body composition. Through the use of a feature search of common BCG signal characteristics, a baseline improvement from BMI-only body composition prediction can be observed. The inclusion of BCG features in BMI-based body composition estimation provides preliminary evidence that BMI-based body composition can be improved. BCG could offer improved predictive performance, similar to current body composition estimates, using a combination of predictors (BMI, bioimpedance, anthropometric measurements, etc.). After discussing the relevant analysis performed on collected BCG data, this thesis concludes with design and analysis documentation relevant to Kansas State University’s bed-based BCG acquisition system. This documentation includes design history and implementation details that are recommended for future BCG system modifications. To expand future Kansas State research pathways, the BCG system at Kansas State should be further improved with the end goal of data collection related to the preliminary investigations discussed in this thesis.Item Open Access Wheat bran valorization for proteins and bioactive peptides(2025) Stump, MichaelOver the past several decades, significant efforts have been made towards the valorization and value-addition of agricultural waste and byproducts. One area being explored is the valorization of wheat bran: a major byproduct of the wheat milling industry. Wheat bran has excellent nutritional value, containing approximately 10 to 15% protein by weight. However, its direct incorporation in human diets has been limited due to unappealing sensory characteristics, which has resulted in wheat bran being used primarily for animal feeds. To address this challenge, we propose that the separation of proteins in wheat bran from undesirable components could enhance its suitability as a food ingredient for human consumption. In addition to the use of wheat bran protein as a food ingredient, there has also been a surge in the study of bioactive peptides for use in nutraceuticals, or ‘functional foods”. We have also proposed that wheat bran proteins could be used as a readily available feedstock for the production of bioactive peptides. The objectives of this study were specifically focused on the following goals: 1) Optimization of protein extraction efficiency and purification methods, 2) Production and characterization of peptides from purified wheat bran proteins, and 3) Screening of wheat bran proteins and peptides for antioxidant and anti-aging activities using in-vitro bioactivity assays. The experiments conducted in this study focused on optimization of protein extraction methods based on Osborne fractionation, alkaline extraction, and deep-eutectic solvent (DES) extraction methods. Each of these protocols were performed and evaluated via LECO analysis of the bran residues after extraction and by performing Bradford assays on protein extracts. A chromatographic purification method was then adapted for use with wheat bran protein extracts using inexpensive, 500Å underivatized silica gel with a two-phase capture and elution phase step gradient. The effectiveness of this method was further confirmed using size exclusion high performance liquid chromatography (SEC-HPLC) analysis. The purified proteins were then used to produce peptides via enzymatic hydrolysis catalyzed by pepsin and trypsin. Each Osborne protein fraction, and each corresponding tryptic- and peptic-peptide were then screened for potential biological activity via the DPPH assay, as well as the percent inhibition of enzymes associated with skin cellular aging. The results of these assays were evaluated using one-way ANOVA statistical analysis, and the activity of each protein or peptide sample was compared to the standard, ascorbic acid. The results of this study showed that the modified Osborne fractionation extraction protocol was the most efficient, achieving a percent recovery of 74.75% of the total protein in the bran. The alkaline extraction and the DES extraction achieved percent recoveries of only 24.77% and 24.84% of the total protein in the bran, respectively. The purity of each Osborne fraction extracted from wheat bran was then tested using SDS-PAGE and SEC-HPLC. Significant impurities were observed in every sample as visible in the SEC-HPLC chromatograms. These impurity peaks disappeared from the chromatograms of proteins purified by the 500Å silica gel column and matched the retention times of the species isolated during the capture phase. This confirmed that the adapted 500Å silica gel column method successfully and reliably removed lower molecular weight impurities from each protein fraction. Analysis of the bioactivity assay results using the one-way ANOVA identified seven different peptide and protein samples that were statistically comparable to ascorbic acid. UPLC-MS analysis of these samples confirmed the presence of peptides through observation of characteristic peptide clusters in the mass spectra. This study details the optimization of a protein extraction method, the adaptation of an inexpensive, efficient, and effective method for purifying wheat bran proteins, and the screening of wheat bran proteins and protein hydrolysates for in-vitro biological activity. The results of these studies suggest that wheat bran has excellent potential for valorization from a low-value industrial byproduct into more valuable nutraceutical products for the consumer market.Item Open Access Multi-agent multi-objective coordination in humanitarian logistics(2025) Farooq, AyeshaHumanitarian crises are escalating in both frequency and complexity, placing unprecedented demands on response systems composed of government agencies, non-governmental organizations, and private actors. These entities must coordinate their operations in a decentralized manner under limited resources and often competing objectives. Existing coordination frameworks rely on centralized control or assume alignment of goals, thereby falling short in settings where autonomous decision-makers require assurances of fairness to remain engaged. Addressing this deficiency requires a formal methodology capable of reconciling multiple objectives, preserving incentive compatibility, and quantifying the concessions necessary to sustain coordination. This research advances the body of knowledge in multi-objective multi-agent humanitarian logistics through a sequence of interlinked contributions. First, it delivers a systematic literature review that maps existing work at the intersection of game theory and optimization for coordination in humanitarian contexts. The review categorizes existing studies by modeling approaches, coordination mechanisms, and decision contexts. It identifies four primary coordination mechanisms: resource sharing, information sharing, contracting, and strategic action. The review also reveals the absence of models that consider fairness in decentralized settings with conflicting objectives. Building on the review insights, a new mathematical concept Chebyshev least core is introduced and formalized, extending classical cooperative game theory, to quantify the smallest uniform concession necessary to achieve near-stable outcomes when perfect equity is unattainable. Moreover, a novel mathematical framework is developed by integrating cooperative game theory with multi-objective optimization to enable equitable and sustainable coordination by computing the Chebyshev least core. Specifically, a Cooperative Goal Optimization (CGO) model is proposed to identify fair allocations by minimizing the maximum relative shortfall each actor experiences compared to their stand-alone performance. The model also incorporates the preference core and nondominance core concepts into a single model, allowing practitioners to distinguish solutions that satisfy all imposed conditions from those that involve trade-offs. Computational experiments demonstrate that the CGO approach yields more stable, equitable, and scale-invariant outcomes than conventional allocation rules, and that it accommodates objectives expressed in disparate units without the need for commensurability assumptions. Finally, the framework is validated with a case study using real-world data on hurricane staging-area planning. The case study offers empirical evidence on how coordination mechanisms reshape operational choices in hurricane response. Joint planning alters routing, and pre-positioning decisions to make the disaster response more effective, efficient, and equitable. By applying the developed framework, it is demonstrated that equitable cost and benefit-sharing rules can be constructed so that no organization has an incentive to deviate from coordinated arrangements. Lastly, the study bridges theory and practice by quantifying the exact price of coordination for multi-objective multi-agent relief operations.Item Open Access A synergetic wellness model for first responders targeting cardiovascular risk through myofascial release, nutrition, and breathwork(2025) Burgess, KimberlyFirst responders, including firefighters, paramedics, and law enforcement officers, face an escalating health crisis fueled by chronic psychological stress, physical trauma, and occupational strain. Elevated rates of myocardial infarction, substance use, PTSD, and suicide persist despite growing awareness and national intervention efforts. This thesis proposes a trauma-informed, integrative wellness model designed to enhance both cardiovascular and psychological resilience in first responders through three synergistic modalities: myofascial release therapy (MFR), structured breathwork, and targeted nutritional intervention. Drawing on over 60 peer-reviewed studies, this research outlines a theoretically grounded, 12-month randomized controlled trial involving 180 career firefighters across three study arms: control, written-only, and a hands-on intervention group receiving weekly MFR, daily breathwork, and biweekly group nutrition sessions. Primary outcomes include myocardial infarction risk (biomarkers, blood pressure, HRV), psychological stress (PSS, cortisol), substance use (AUDIT-C), and quality of life (SF-36, WHOQOL-BREF), with secondary measures assessing sleep, anxiety, depression, and physical activity. Recent evidence illustrates that nutrition profoundly influences fascial elasticity, inflammation, and recovery potential, making it a critical determinant of MFR efficacy. Additionally, manual therapy modalities such as MFR have demonstrated measurable reductions in anxiety symptoms among first responders and trauma-exposed populations, due in part to their impact on autonomic recalibration and interoception. Furthermore, emerging data from wildfire deployments underscores the need for systemic interventions to address the long-term physical and emotional toll on EMS personnel. This thesis argues that the integration of these three modalities, each with evidence of standalone benefit, can produce compounding, cross-disciplinary effects. By addressing the biological, emotional, and somatic dimensions of stress through a unified protocol, this model moves beyond symptom management toward root-cause prevention and long-term resilience building. The proposed framework represents a scalable, low-cost solution with the potential to reshape occupational health standards in high-risk service professions.Item Open Access Identifying the bottlenecks limiting medium-chain fatty acid accumulation in transgenic pennycress seeds.(2025) Alisha, FnuPennycress (Thlaspi arvense) is an emerging oilseed biofuel crop within the Brassicaceae family, closely related to Arabidopsis thaliana. It holds significant potential as a platform for the production of biotechnologically derived compounds, such as medium-chain fatty acids. These are saturated hydrocarbon chain molecules with 8 to 14 carbon atoms. These are abundant in plants like coconut and species of Cuphea, including Cuphea viscosissima and Cuphea var. avigera pulcherrima, which can comprise up to 94 mol percent of the oil content. To enhance medium chain production, pennycress was genetically engineered to express a medium chain specific thioesterase and two MCFA-specific acyltransferases, resulting in the accumulation of carbon 10 chain fatty acids at 7 mol percent. Using systems biology approaches, this study aims to identify the bottlenecks in carbon 10 chain production in transgenic pennycress. Fatty acid composition analysis reveals increased levels of carbon 16 chain fatty acids in transgenic plants compared to wild-type plants, with a higher total fatty acid content throughout seed development. Lipidomic analysis reveals the production of altered carbon-10-containing triacylglycerols and acyl-sterol glucosides in transgenic plants, particularly during the later stages of seed development. Moreover, the levels of triacylglycerol containing multiple medium-chain fatty acids decline as seed development progresses. Transcriptomic analysis shows no significant changes in gene expression for most genes associated with fatty acid and triacylglycerol synthesis, degradation, and peroxisomal beta oxidation pathways. Notably, transcriptomic data also highlight several upregulated genes in transgenic seeds related to stress responses, including heat shock proteins and genes associated with hypoxia response.Item Open Access The lived experiences of Black women who completed their doctorate through a cohort model Community College Leadership Program in the United States(2025) King, MilletteThis hermeneutic phenomenological study was designed to understand the lived experiences of Black women who completed their doctorate through a cohort model Community College Leadership Program. Black women were not completing doctoral degrees at the same rate as their peers. The National Center for Education Statistics (2023) states that in 2020-21, 61% of the doctorates earned by females were White females, 12% were earned by Black females, 10% earned by Hispanic females, 13% earned by Asian/Pacific Islanders and .4% American Indian/Alaska Native (NCES, 2023). The following research questions guided this study: What are the lived experiences of Black women who have completed their doctorate through a cohort model Community College Leadership Program? What factors supported Black women’s completion of the Community College Leadership Program? This study utilized the hermeneutic circle to gain insight into the lived experiences of 14 Black woman who completed a cohort model community college leadership program. Themes that emerged from the semi structured interviews, when viewed through the conceptual lens of Black Feminist Thought, included that Black women formed strong bonds with their cohort members that lasted well beyond the doctoral journey. The participants in this study were impacted by COVID during their journey both in a positive and negative way. Family illness and divorce also impacted the doctoral journey of the women interviewed. Finally, relationships with faculty, staff and peers impacted the doctoral journey of Black women in this study. Recommendations for future research include exploring the lived experiences of other marginalized populations, conducting a qualitative study to survey all people of color that attend a community college leadership program, exploring other doctoral concentration areas and research on how cliques impact the learning environment in cohort models.Item Open Access The development of American economic warfare in World War II, 1940-1941(2025) Richards, Robert BenjaminThis dissertation examines the development of American economic warfare during World War II, focusing on the critical years of 1940-1941. During this period, military and civilian leaders responsible for the development and direction of economic strategy conceived, built, and employed economic warfare capabilities as an integral part of American grand strategy. Since 1959, no historian has comprehensively analyzed America's complete World War II economic warfare campaign, and no published historical work has thoroughly explained its origins. Existing scholarship is fragmented—chronologically silent for over 75 years, British-centric, and overshadowed by studies of strategic bombing and submarine campaigns—leaving the role of economic warfare in U.S. grand strategy unexplored. Utilizing largely untapped archival records from the US Foreign Economic Administration (RG 169), this dissertation provides the first US-focused analysis and reestablishes economic warfare within the history of the US and Allied grand strategy. The evidence presented in this dissertation supports four key findings. First, although often overlooked by historians, economic warfare was a core component of US grand strategy by at least July 1940. Second, in July 1940, President Franklin D. Roosevelt established the Office of the Administrator of Export Control to conduct a steadily expanding economic warfare campaign that, by August 1941, had largely cut the Axis Powers off from sources of strategic raw materials in Latin America and significant parts of Asia. Third, while both derived from their respective experiences with the “blockade” in World War I, US economic warfare theory, doctrine, and organization developed independently of British economic warfare theory and practice. Finally, contrary to post-World War II assessments, both the American and combined American-British economic warfare campaigns were efficient and effective in reducing the number of suitable, feasible, or acceptable strategic options available to Germany and Japan. The economic warfare campaigns began to significantly impact Axis capabilities, resources, and morale starting in early 1941.Item Open Access Harvesting well-being: an exploration of community considerations in farming decisions across diverse social-ecological contexts(2025) Francois, Jean RibertThe historical development of agriculture in the United States has been extensively studied and well-documented in the literature. Similarly, research has thoroughly established the impacts of the U.S. agricultural sector – home to some of the most advanced farming systems in the world – on both the environment and human well-being. For example, numerous studies have explored the connections between agriculture and community well-being over the past century, often guided by the influential Goldschmidt hypothesis, which suggests that the shift toward large-scale farming operations is associated with substantial sustainability challenges for individuals and communities. These well-established negative consequences are often the result of a complex interplay of various factors and circumstances inherent in the organization, structure, and management of modern agricultural systems. Addressing these challenges requires data-driven research to inform and support potential policies and interventions to mitigate the multiple community concerns that arise from human management practices. In three specific studies, this dissertation examines the interactions between agricultural systems, farmer decision-making, and community well-being, emphasizing the extent to which and how community concerns are considered in farming decisions across different agricultural contexts in the U.S. Study 1 investigates, through spatial analysis and descriptive statistics of county-level data from 2010 to 2019, how well-being varies across communities that differ in their levels of crop diversity and productivity, and the intensity levels of farming systems. Findings suggest that community well-being is generally high across most diversity–productivity categories. However, notable exceptions and variability within groups highlight the influence of contextual factors, such as social infrastructure and economic diversification, beyond agricultural indicators alone. Next, the second study, using both interview and survey data, explores how farmers incorporate community concerns into their decisions across diverse contexts of crop diversification. The analysis identifies key themes such as economic contributions, community health, education, and community care that farmers consider when making agricultural decisions while also noting misalignment between awareness of community impacts of farming and action to include community considerations in decision-making. Lastly, study 3 investigates the core attributes of farmers and contextual factors that shape the inclusion of community considerations in farming decisions. Through modeling techniques, the analysis emphasizes the role of awareness, community values, coordination, and structural challenges in influencing individual decision-making related to considering community well-being in farming decisions. These studies, taken together, have implications for advancing the inclusion of community considerations in farming decisions, which is important for the sustainable relationship between agricultural systems and communities.Item Open Access Investigation of highly efficient particulate air filter media performance in existence of internal leak(2025) Abraham, Daniel M.High-efficiency particulate air (HEPA) and ultra-low particulate air (ULPA) filters are extensively utilized in nuclear and National Bio and Agro-Defense facilities as the last line of defense for eliminating particles from a contaminated gas stream prior to its release into the surrounding environment. The objective of the present study is to develop a computational tool capable of simulating the microstructure of such a filter medium. This tool will provide valuable information for enhancing the design and manufacturing of the scanning device used in the leak penetration test. It will also help in investigating the testing criteria set in the standards for classifying filter types. Consequently, it will assist in assessing the likelihood of a successful filtration leak test, thereby reducing the risk of an inaccurate test. The initial phase of this study was the design and construction of a biofiltration testing rig that adheres to the standards set by the American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 52.2 for HEPA testing. The purpose of this rig is to assess various prototypes of biocontainment housings used in the National Bio and Agro-Defense Facility (NBAF), along with their corresponding auto scan technologies against the traditional penetration test method. We evaluated the local and overall filter efficiency of two of the available housing units using their associated auto scanning methodologies, and we compared the results with the efficiency obtained using the conventional penetration test approach described in ASHRAE 52.2. A series of prerequisite tests were carried out to verify aerosol distribution uniformity upstream and downstream as well as the consistency of the injection and sampling probe measurements. This allowed us to investigate the impact of the filter pinholes (leaks) on the pressure drop and efficiency of the filter and enhanced our understanding of the protocols and requirements for comprehensive testing of large-scale pleated 610×610×292 mm³ HEPA and other filters at different flow rates. In the second part of the study, following an understanding of the scanning technology used to test the filter in the first part, we developed a three-dimensional fibrous computational model featuring non-homogenous fibers that replicates the HEPA filter sheet. This model was utilized to simulate and analyze the pressure drop and collection efficiency of the HEPA filter sheet, considering scenarios both with and without leaks. We expanded our work by building a small-scale filter sheet testing rig to compare experimental and computational results and determine a correlation between HEPA intact and leaky filter efficiencies. Our research revealed the optimal most penetrating particle size (MPPS) at which to test a filter and the minimum leak size at which the filter efficiency becomes independent of particle size and filtration velocity, which can be used to derive a designated leak penetration value for a successful leak penetration test under particular sampling and scanning conditions.Item Open Access Hydrogen relative permeability modeling: applications to underground hydrogen storage (UHS)(2025) Agbamu, Deborah OlabisiThe transition toward a low-carbon energy system has intensified interest in underground hydrogen storage (UHS) as a means to balance the intermittent nature of renewable energy sources. The accurate modeling of hydrogen flow in subsurface porous media is crucial for optimizing storage efficiency and ensuring successful retrieval. A key parameter in this process is hydrogen relative permeability (k_rh), which governs multiphase flow dynamics in geological formations. In this study, we develop a theoretical model for k_rh using the effective-medium approximation (EMA) and percolation theory (PT) concepts. Our model incorporates pore-scale characteristics such as pore size distribution, connectivity, and critical hydrogen saturation S_hc. The model is validated against eight experimental datasets and eleven pore-network simulations, demonstrating reasonable agreement in most cases. However, discrepancies are observed in certain carbonate samples, likely due to secondary porosity effects (e.g., vugs and fractures) and in sandstones with possible microfractures. The findings highlight the critical role of accurately estimating S_hc in predicting k_rh and suggest that improvements in pore structure characterization could enhance modeling accuracy.Item Embargo Developing a measure of intrapreneurial self-efficacy (ISE): assessing employees’ confidence in their ability to create improvements at work(2025) Warren, Chi-LeighThis thesis develops and validates an intrapreneurial self-efficacy (ISE) scale. There are two overarching goals of this study: first, to clarify and improve the construct validity of intrapreneurship (often operationalized with behavior) and subsequently, intrapreneurial selfefficacy (or one’s confidence in performing intrapreneurial behavior), with a definitional analysis, and second, to develop an improved, reliable, validated measure of intrapreneurial selfefficacy that demonstrates discriminant validity from other self-efficacy measures and predicts individual-level intrapreneurial behavior. Referencing a proposed model of intrapreneurship by Neessen et al. (2019), this study further clarifies the construct of intrapreneurship and addresses key gaps in the literature by connecting individual-level attitudes of intrapreneurship, such as ISE, to individual-level intrapreneurial behavior. RQ1: Does intrapreneurial self-efficacy have five subdimensions: innovativeness, proactiveness, risk-taking, opportunity recognition, and networking? A definitional analysis was conducted first to clarify the intrapreneurship construct and inform the writing of the 72 items in the initial item pool, which was evaluated and reduced by subject matter experts (SMEs) to 40 items. Using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), the scale’s factor structure was explored and confirmed with a 36-item measure. To test H1 and H2, factor-level second-order CFA models assessed for discriminant validity of ISE to identify if it was a unique measure from entrepreneurial self-efficacy (ESE) and general self-efficacy (GSE). H1: Intrapreneurial self-efficacy (ISE) will account for unique model variance, suggesting it is a unique construct from entrepreneurial self-efficacy (ESE). H2: Intrapreneurial self-efficacy (ISE) will account for unique model variance, suggesting it is a unique construct from general self-efficacy (GSE). Finally, hierarchical regression models predicting intrapreneurial behavior were used to test H3 and the criterion-related validity of intrapreneurial self-efficacy as additional variables were added. H3: Intrapreneurial self-efficacy (ISE) will be a positive, significant predictor intrapreneurial behavior above and beyond entrepreneurial self-efficacy (ESE) and general selfefficacy (GSE). ISE was found to be a 5-factor model with 36 items that uniquely predicts intrapreneurial behavior from GSE and ESE. ISE remained a positive, strong, and significant predictor of intrapreneurial behavior even after controlling for GSE, ESE, personality, job attitudes (job satisfaction and prior knowledge of intrapreneurship), and organizational factors (such as work discretion, time available, management support, and rewards/reinforcement). This study refines the construct of ISE and intrapreneurship, develops an improved ISE measure, and investigates the discriminant and criterion-related validity of intrapreneurial selfefficacy, finding support that ISE is unique from ESE and GSE as both a construct and predictor of intrapreneurial behavior.Item Open Access Bridging past and present: integration of modern stormwater infrastructure into a historic interpretation site(2025) Holliday, DevinHow can modern stormwater management practices be integrated into a historical preservation site like the Marlatt Homestead, ensuring both ecological health and the preservation of cultural heritage, while also creating opportunities for public education on sustainable water management? This research investigates the intricate balance between watershed management and the preservation of historical homesteads, a challenge that sits at the intersection of environmental sustainability and cultural heritage. Watershed management involves practices designed to protect and manage water resources, which can sometimes conflict with the preservation of historical structures that contribute to a site’s cultural value. This study aims to explore how landscape architecture can reconcile these competing interests through a multidisciplinary approach. By reviewing literature on both historical preservation and watershed management, conducting field assessments, and analyzing case studies, the research will identify best practices for integrating modern environmental strategies with the conservation of historical sites. Key areas of focus include evaluating the environmental impacts of preserving historical features, navigating regulatory challenges, and engaging with community stakeholders. The research will also explore innovative design solutions and adaptive reuse strategies that respect historical integrity while addressing contemporary environmental needs. Ultimately, this study seeks to develop practical recommendations for landscape architects and policymakers to create designs that harmonize ecological health with cultural preservation, ensuring sustainable and culturally sensitive land use.Item Open Access Implications of smart spraying technology on the United States pesticide industry(2025) Frederes, MaxThis thesis investigates the financial and environmental impact of introducing “smart spraying” technologies on various stakeholders within the row crop agriculture industry. Smart spraying incorporates cameras and artificial intelligence to sense weeds and only apply herbicides in those areas. The primary focus is to analyze the future implications of these technologies on the amount of active ingredient applied to common herbicides used in corn and soybean production. By examining these factors, the research aims to provide valuable insights that enable farmers, custom applicators, retailers, distributors, basic manufacturers, and policy makers to formulate mid- and long-term strategies. The study employs a comprehensive approach, incorporating quantitative data analysis and qualitative assessments to evaluate the potential economic benefits and challenges associated with smart spraying technologies. The findings highlight significant shifts in market dynamics, offering a consideration for stakeholders navigating the evolving landscape of agricultural weed control.Item Open Access Affordable landscapes: designing cost-effective and comfortable landscapes in Cottonwood Falls(2025) Otto, TylerWhile innovative housing can be extremely beneficial for communities in need of affordable homes, these houses often ignore what can be done to make the surrounding landscape more sustainable and innovative. The outdoor living space is essential to the well-being of the residents, and a well-designed landscape can provide a multitude of benefits to the ecosystem as a whole. It can expand the home and encourage residents to be more active in their community. As housing in the United States is becoming increasingly unaffordable, more attention is being paid to public and private initiatives related to lowering housing costs. These strategies relate to house size, neighborhood layout efficiencies related to density and infrastructure, land acquisition costs, environmental regulation and compliance, and a host of other factors. Establishing and maintaining the landscape surrounding residential structures can also be a dominant part of monthly housing costs. While this report primarily focuses on affordability in the landscape, decisions on housing configuration play a large role. For example, if vehicle access and parking are spatially decoupled from individual homes, more flexibility for housing clustering is possible which has implications on how the surrounding landscape is designed and maintained. This report outlines how the costs of traditional residential landscapes can be reduced yet still be environmentally responsible and visually appealing. To best create guidelines to help these communities, it is important to assess current conditions. Forming a landscape profile of the target cities can help determine what will be needed. In addition, gathering information concerning maintenance and design services that are available, local plant nursery selection, and water usage data will help inform the guidelines. Cottonwood Falls, Kansas was chosen as an example community to create projective designs focusing on affordability. Traditional outdoor landscapes surrounding residential areas are typically composed of turfgrass lawns with low biodiversity, high maintenance costs, and negative environmental impacts. To assist homeowners, developers, and cities create more innovative landscapes to complement and support new affordable housing prototypes, this project will propose landscape guidelines that are aesthetic and support the enjoyment of comfortable outdoor spaces.Item Open Access Multilingual and multicultural backgrounds: an exploration of language attitudes toward restrictive language policies at the college level(2025) McCord, Ann ElizabethRestrictive language policies are formed by language ideologies that prevail among communities, along with the individual attitudes that support the furthering of language ideologies, whether supportive of or adverse to multilingual interests. Currently, the literature demonstrates that both second language learners (L2s) and heritage language learners of Spanish (HLLs) may perceive the restriction of language policies negatively, although some results have been mixed, yielding both positive and negative student responses (Shvidko, 2017; Vidana, 2020; Valdés, 2023). The types of language policies reviewed in current studies are limited to rules at the local, institutional level– typically taking place in a university setting. For language instructors, previous research shows they may consider the challenges standard language ideologies pose for the linguistic practices of HLLs– within the bounds of Spanish second language courses or language courses designed specifically for the needs of HLLs (Showstack, 2024). In a policymaking role as an instructor, Showstack (2024) determined that instructors' personal and linguistic backgrounds play a large role in their classroom policies and legitimation of HLLs’ linguistic practices. Until now, the attitudes of several student profiles (L2s and HLLs) and their instructors (language faculty) towards language policies at the state and federal levels have yet to be explored in a cross-sectional study. Furthermore, to what extent teachers’, L2s’, and HLLs’ personal and linguistic histories play a role in their understanding of language ideologies and attitudes towards the policies that embody them remains unknown. This study builds upon the small corpus of studies related to restrictive language policies, language ideologies, and language attitudes to examine the extent to which participants' upbringings, educational experiences, and professional preparation could affect their views towards restrictive language policies.Item Open Access Environmental risk factors and cancer incidence in rural central Kansas(2025) Romang, Luke DavidGroundwater contamination is a global concern in agricultural regions and can lead to adverse health effects for affected populations. In central Kansas, three predominantly agricultural counties exhibit notably high cancer incidence rates compared to the state average. This study investigates potential links between land use practices, groundwater contamination, and elevated cancer rates in these counties while also assessing the role of radon exposure. Additionally, we sought to identify factors controlling contaminant occurrence and distribution in local groundwater. We collected 56 groundwater samples, deployed 39 indoor radon tests, and conducted 65 household cancer surveys. A GIS-based buffer analysis using CDL and NLCD land use datasets was performed to explore potential associations between land use and groundwater contamination. Geochemical analyses were used to evaluate possible controls on contaminant occurrence, including pH, redox conditions, and water-rock interactions. Our findings indicate that redox state is the primary control on groundwater geochemistry and contaminant distribution. Evaporation was a key factor influencing groundwater chemistry in Russell County, while water-rock interactions were more significant in Lincoln and Ellsworth County. In the majority of the study area, nitrate and uranium concentrations exceeded EPA and WHO maximum contaminant levels, and 48.7% of radon measurements exceeded the EPA action level of 4 pCi/L. Although no clear correlations were found between agricultural land use and contaminant occurrence, a positive association was observed between open-water land cover and nitrate concentrations. Our cancer data reveals that 64% and 77% of households surveyed in Lincoln and Russell counties, respectively, reported cancer within the household. Additionally, 83% of participants in Lincoln County have a family history of cancer. In Russell County, 6% of cases were in individuals under 20 years old, while in Ellsworth County, 18% were in individuals aged 20-40. This study provides preliminary correlational evidence linking environmental factors to cancer causation and contributes cancer data for the region, offering a glimpse of potential environmental cancers that might guide future studies and provide a framework for future public health guidelines.Item Open Access A tropical approach to Ising problems(2025) Ortiz, Jose A.Tropical geometry offers a piecewise-linear framework that translates algebraic and combinatorial structures into polyhedral geometry. In this dissertation, we explore applications of tropical and polyhedral methods to the analysis of spin systems, particularly the Ising model on graphs. Each spin configuration of a graph with n vertices corresponds to a vertex of the n-cube, and the energy associated to these configurations defines a Laurent polynomial whose Newton polytope encodes all interaction and external field parameters. We show that the tropicalization of this polynomial captures the loci in parameter space where multiple spin configurations minimize the system's energy—so-called degeneracy loci. These loci are described by tropical hypersurfaces, whose combinatorial types are determined by faces of the secondary polytope of the n-cube. Through this connection, vertex-state interactions naturally parameterize regular subdivisions of the cube, and ground-state degeneracies are encoded by the dual secondary fan. We further construct new polytope, whose vertices reflect both spin states and interaction parities, and provide a facet classification for graphs built from trees and cycles. This polyhedral perspective reveals a natural moduli space for studying phase transitions, optimization, and combinatorial symmetries in discrete physical systems.Item Open Access Inferencing with sparse spatio-temporal data in biological systems(2025) Tharzeen, AabilaSpatio-temporal data analysis plays a crucial role in many scientific domains, including biological systems, earth sciences, autonomous vehicles, and many others, providing critical insights into how spatially coherent entities evolve over time. Particularly in biological systems, accurately understanding the underlying cause-effect relationships requires systematic exploitation of both spatial and temporal variations. One of the major challenges in biological systems is that available data can be limited due to high experimental costs, ethical considerations, or logistical constraints and can hinder accurate modeling of the underlying complex spatio-temporal phenomena. Classical statistical approaches, while interpretable, frequently struggle to model complex nonlinear dependencies, whereas purely data-driven machine learning (ML) methods risk overfitting and poor generalization when dealing with limited data. Thus, addressing challenges associated with sparse spatio-temporal data is crucial to reliably inferring meaningful insights from biological systems. This dissertation addresses challenges associated with sparse spatio-temporal inference by systematically integrating uncertainty quantification (UQ) into ML frameworks specifically tailored for biological systems. Missing data is often handled by imputation based on available observations. However, the missingness itself can contain critical information. The imputation can introduce bias and information loss, while failing to effecttively capture the underlying spatio-temporal relationships. To address this “ imputation dilemma," this dissertation proposes and theoretically analyzes a novel Informative Missing Indicator Method (IMIM) specifically designed for neural networks. IMIM helps decide when imputation should occur without introducing bias or loss of information in the data. Furthermore, a graph neural network combined with a recurrent neural network-based spatio-temporal imputation framework is developed to systematically capture spatio-temporal relationships, significantly enhancing predictive capabilities in downstream tasks by effectively increasing the amount of informative data available. Additionally, learning ML models from limited data can also be challenging due to the high risk of overfitting and poor generalizability. To mitigate these issues, this dissertation introduces innovative methods to integrate prior knowledge that represents high-level abstractions of natural phenomena into ML frameworks either as observational bias or learning bias. This ensures that model predictions conform to known scientific principles. The framework also facilitates inference of uncertain parameters not directly observable from data using the uncertainty quantified on the model predictions. In safety-critical biological applications, confidence in predictions is as crucial as prediction accuracy itself. Therefore, recognizing the critical importance of uncertainty quantification, this dissertation presents a generic, task-agnostic UQ framework utilizing neural stochastic differential equations (Neural SDEs). This framework analytically captures epistemic uncertainty in both traditional neural networks and graph neural networks, thereby enhancing model reliability and interoperability. Additionally, this dissertation proposes an uncertainty-guided active learning framework that analytically propagates spatio-temporal measurement uncertainty to strategically select the most informative samples. This approach effectively reduces overall prediction uncertainty, optimizing resource usage and improving predictive accuracy. The methods developed in this dissertation are highly beneficial for healthcare and other data-scarce, safety-critical biological applications where reliability, accuracy, and informed decision-making are essential.Item Embargo Water absorption and dough rheology of high amylose wheat flour in relation to bread making quality and digestibility(2025) Smith, RileyThe health benefits of dietary fiber (DF) are well recognized. Yet, a large gap still exists between the recommended daily intake (28-42 g / day) and the amount that is actually consumed in the US and similarly in the world. Wheat-based foods (e.g. bread, pasta, noodles) supply about 20% of food energy for the world population. People are eating more whole grains, but many consumers still prefer foods made from refined wheat flour. These foods are low in DF and resistant starch (RS). RS functions as DF; as it is a starch fraction that is not digested or absorbed in the small intestine in healthy individuals rather fermented in the large intestine, producing short chain fatty acids with health benefits. It is difficult to make wheat-based staple foods with high DF and RS, retaining low or slow digestion, and have good sensory properties. The starch in normal wheat (about 25-30% amylose) is highly digestible. Recently, a high-amylose wheat (HAW) was developed. This is game-changing because the significant increase in amylose results in a high RS content (low digestibility) in refined wheat flour. A knowledge gap pertaining to the increased amylose content in relation to the dough rheology of HAW flour has been identified for this study. The objectives of the first part of this study were to investigate the water absorption and viscoelastic properties of hard red spring (HRS) HAW flour dough (58.90% amylose content), comparing with normal HRS and hard red winter (HRW) flour doughs. The regular wheat flours showed an average of 62.8% compared to HAW’s 79.1% for optimal water absorption across all empirical mixing methods. The effects of arabinoxylan content on water absorption of wheat flour were also examined. The colorimetric measurement of arabinoxylans in each flour revealed that the HAW flour had 1.05-1.39% more total arabinoxylans. Solvent retention capacity of sucrose and frequency sweep assessments before and after xylanase hydrolysis revealed that arabinoxylans were contributing to the heightened water absorption. The dough rheological measurements also showed an increase in absorption time as the larger amount of water was distributed, resulting in a tougher dough at the beginning of mixing. Additionally, the HAW flour produced a dough that had statistically similar viscoelasticity to normal wheat doughs when optimally hydrated. With the HAWs Mixograph and Farinograph’s 4 min and 5.62 min dough development times there were no statistical differences identified compared to the HRS wheat flour. The use of HAW flour and solubilization of water unextractable arabinoxylans also decreased the doughs resistance to deformation and recoverable strain. The high level of amylose in wheat flour leads to increases of RS and DF contents. The objectives of the second part of this study were to determine the optimal water absorption of HAW flour for bread making quality and starch digestibility. Bread made with HAW flour had a decreased volume, crumb structure, and lightness while increasing initial firmness compared to normal HRS and HRW wheat breads. The HAW bread had a specific volume of 4.61ml/g compared to the normal wheats average 5.91ml/g, resulting from a significant decrease in C-Cell number of cells data with 6610.3 cells compared to regular wheats averaged 7371.8 cells identified. The textural profile analysis of the bread crumb also revealed the bread crumb to be firmer than the regular wheat breads at the end of cooling. The use of DSC and XRD analysis showed the increased firmness to be associated with the heightened amylose content rapidly re-associating during the cooling period, increasing short-term retrogradation, while the limited amylopectin retrogradation produced insignificant long-term retrogradation. Xylanase treatment showed significant improvement to long-term firmness in breads. The in-vitro digestibility revealed a significant decrease in digestibility of starch in bread made with HAW flour due to significant increases in re-association (retrogradation) of amylose and lipid complexing of amylose molecules.Item Open Access Integration of wearable sensors into sensory room therapies for children with developmental challenges(2025) Movazzaf Gharehbagh, BitaWearable sensor technologies are becoming powerful tools in healthcare and therapy, especially for children with disabilities such as autism or sensory processing disorders. These devices can track a person’s heart rate, body temperature, movement, stress level, and even their location. When used in sensory rooms, special spaces designed to help children feel calm or focused, wearable sensors can make the therapy more personal and effective. For example, if a child is feeling stressed, the room’s lights, music, or activities can adjust automatically to help the child feel better. This creates a smart, interactive space where therapy responds to the child’s real needs in real time. This report explores how wearable sensors can improve sensory room therapy by offering three key benefits: tracking where the child is in the room, monitoring their physical and emotional responses, and recording behavior for long-term review. Examples include a spinning toy with sensors for children who show repetitive behaviors, and GPS-based systems that track which therapy zones a child visits most. These technologies help therapists understand what works best for each child and plan better therapy sessions. The goal is to make therapy more responsive, safe, and tailored to the needs of each child.
