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 Essays on forecasting time series with machine learning techniques(2024) Lashgari, AliThis dissertation consists of three essays on forecasting time series with machine learning techniques, delving into different financial and economic domains. The first essay investigates the forecasting accuracy of the S&P 500 stock market index during the pandemic, utilizing text mining and technical analysis. It finds that the LSTM model, which uses numerical data rather than financial news, offers superior accuracy in predicting price movements, showing the effectiveness of machine learning over traditional analysis methods. The second essay tests the hypothesis that the Federal Reserve responds to data revisions when setting monetary policy. To deal with the large number of data revisions that the Federal Reserve can potentially respond to, we use four machine learning techniques, Lasso, ridge regression, elastic net, and post-Lasso. When using our preferred method, elastic net, we conclude that the Federal Reserve responds to five types of data revision. We discuss the implications of this finding for theoretical macroeconomic models in the context of the signal extraction problem. The third essay addresses the predictability of West Texas Intermediate crude oil prices, influenced by macroeconomic factors. By comparing the performance of Long Short-Term Memory (LSTM) and Random Forest (RF) models, they are superior capability in both short and long-term forecasts during significant economic shocks like the 2008 financial crisis and the COVID-19 pandemic. The inclusion of SHAP analysis further enriches the understanding of how historical prices and macroeconomic indicators like the Consumer Price Index and exchange rates play pivotal roles in forecasting.Item Open Access Intergenerational linkages in debt delinquency behaviors among young adults(2024) Gan, Lena Su YuinThis dissertation investigates the intergenerational factors that influence financial debt delinquency behaviors in young adulthood, focusing on the roles of parent-child relationships, parental socioeconomic status, individual attitudes, norms, and perceived financial control. Guided by the Theory of Planned Behavior (TPB) and Family Financial Socialization Theory (FFST), the study employs path analysis to explore how these variables mediate financial behaviors. Using data from the National Longitudinal Survey of Youth 1979 (NLSY79) and its Child and Young Adult Survey (NLSCYA), the research examines key pathways, including the mediating effects of risky attitudes, parental debt norms, and perceived financial control on the relationship between parental influences and debt delinquency. The findings reveal that while parental socioeconomic status and debt norms significantly affect young adults' financial behaviors, the influence of parent-child relationships on perceived financial control is more nuanced. Effect size analyses highlight the varying impact of different predictors, revealing that perceived financial control exerts a substantially greater influence on debt delinquency compared to other factors, emphasizing the importance of targeted interventions. The study underscores the importance of considering both direct and indirect effects in understanding financial socialization. Practical implications suggest that policymakers, financial educators, and practitioners should focus on enhancing perceived financial control and shaping healthy debt norms within families to mitigate financial delinquency. Future research should address the limitations of secondary data and further refine the measurement of constructs to capture the complex dynamics of financial behavior socialization.Item Open Access Bayesian regularized quantile mixed models for longitudinal studies.(2024) Fan, KunIn longitudinal studies, the same subjects are measured repeatedly over time, leading to correlations among the repeated measurements. Properly accounting for the intra-cluster correlations in the presence of data heterogeneity and long tailed distributions of the disease phenotype is challenging, especially in the context of high dimensional regressions. Here, we aim at developing novel Bayesian regularized quantile mixed effect models to tackle these challenges. In the first project, we have proposed a Bayesian variable selection method in the mixed effect models for longitudinal lipidomics studies. To dissect important lipid-environment interactions, our model can simultaneously identify important main and interaction effects on the individual and group level, which have been facilitated by imposing the spike-and- slab priors through Laplacian shrinkage in the Bayesian quantile hierarchical models. The within- subject dependence among data can be accommodated by incorporating the random effects. The Gibbs sampler has been developed along with the Markov Chain Monte Carlo (MCMC). We have established the advantage of the proposed method over multiple compet- ing methods in extensive simulation studies and a high-dimensional lipidomics study with repeated measurements. In the second project, we further extend the sparse Bayesian quantile mixed models to nonlinear longitudinal interactions. Specifically, the proposed Bayesian quantile semipara- metric model is robust not only to outliers and heavy-tailed distributions of the response variable, but also to the misspecification of interaction effect in the forms other than non- linear interactions. We have developed the Gibbs sampler with the spike-and-slab priors to promote sparse identification of appropriate forms of main and interaction effects. Simula- tion results reveal superior performance in identification, estimation and statistical inference. In particular, the proposed method that incorporates the spike-and-slab priors can enable exact statistical inference by yielding Bayesian credible intervals with nominal coverage prob- abilities on parametric and nonparametric fixed effects simultaneously. Application of the proposed method on high dimensional longitudinal biomedical studies shed novel insight on disease etiology. The Bayesian regularized quantile mixed models proposed in this dissertation aim to tackle challenges arising from longitudinal gene environment interaction studies under the linear and nonlinear interaction assumption in chapter 2 and chapter 3, respectively. In a regression analysis framework, gene-environment interactions can be divided into linear and non-linear types, based on whether the effect of genetic factors on disease traits can be represented by linear or non-linear functions of these genetic factors. The two models proposed in this dissertation fill a significant technical gap since robust identification and inference of the two types of interactions has rarely been explored in published longitudinal studies. We have also developed C++ based R packages mixedBayes on CRAN to facilitate re- producible and fast computations using all methods under comparison in this dissertation.Item Open Access The effects of surface water availability on corn production in Weld County, Colorado(2024) Worrall, CortlandThe agriculture industry in Colorado relies heavily on the amount of snowpack and surface water to be successful and to be profitable. In Colorado they use reservoirs and ditches to disperse water to farmers and the rest to other uses and cities. The amount of water that is allocated to a single farmer can vary from year to year due to unpredictability of availability of water from snowpack and rainfall. In addition, the state has seen multiple years of population growth that has caused more of the surface water to be allocated to the rapidly growing cities instead of to farmers for agriculture use. In this study, I focus on Weld County Colorado because it is the largest agriculture producing county in Colorado and one of the fastest growing counties in terms of population Colorado. This study will look at historical data of surface water used for irrigation and the effects it has on farmers and their decision to plant corn over the last thirty years. I study the impacts on corn because corn is a major crop in Weld County and needs significantly more water than some other crops. The surface water data will come from the Colorado’s Decision Support System (CDSS) that provides all the historical and current water levels of all the reservoirs and ditches. Corn data was collected from the United State Department of Agriculture (USDA) National Agricultural Statistic Service (NASS). This study examines the correlation between surface water available for agricultural irrigation use and the amount of corn planted that year and corn yield. A regression analysis is used in this study to see how the available surface water from year to year will affects farmers and their decision to plant corn and the yield. Other variables included in the analysis to help understand the correlation between surface water and corn production are temperature and precipitation.Item Open Access Effects of vitamins, calcium, and phosphorus in nursery pig and sow diets on bone mineralization and growth performance(2024) Becker, LarissaThis dissertation is comprised of 5 chapters consisting of a literature review on calcium (Ca) and phosphorus (P) requirements in reproducing sows, two experiments evaluating the effects of vitamin D metabolites in nursery pig diets, two experiments evaluating over-supplementing folic acid in nursery pigs, a meta-regression analysis of narasin in grow-finish pigs, and an experiment evaluating two different farrowing systems during lactation. In chapter 1, a literature review was conducted to summarize Ca and P requirements in gestation and lactating sows derived from empirical and factorial models. The large variation among results of empirical studies and factorial models makes it difficult to define precise Ca and P requirements for gestating and lactating sows. However, with the most recent data a minimum level of 6.0 g/d of STTD P during gestation and 22.1 g/d of STTD P during lactation appear to meet basal requirements. The objective of chapter 2 was to determine the effects of added 25(OH)D3 with three levels of STTD P on nursery pig growth performance, bone and urine characteristics, and serum vitamin D. Overall, added 25(OH)D3 had limited effect on growth performance; however, an increase in serum concentrations of 25(OH)D3 and 24,25(OH)2D3 was observed. The addition of 25(OH)D3 to P-deficient diets increased percentage bone ash. Increasing STTD P to 100% of NRC (2012) requirement estimate increased growth and 130% of NRC maximized bone ash. The objective of chapter 3 was to determine the response to supplementation of 1,25(OH)2D3-glycoside (active form of vitamin D) provided from a plant extract on nursery pig growth performance, mortality, bone characteristics, and blood measurements. Overall, supplementation of 1,25(OH)2D3-glycoside had minimal impact on growth or serum parameters; however, increasing 1,25(OH)2D3-glycoside increased percentage bone ash. In chapter 4, two studies were conducted to determine the effect of folic acid on growth performance, SCFA concentrations, and serum homocysteine concentrations. Overall, the addition of folic acid resulted in reduced growth performance with the greatest negative impact being observed when pigs were fed 20 mg/kg. Folic acid supplementation altered SCFA concentrations and increased serum homocysteine. In chapter 5, a meta-regression analysis was conducted to evaluate the effects of added narasin in growing-finishing pig diets to predict growth rate, feed efficiency, and carcass yield. The models developed suggest important variables for predicting the percentage change in growth performance and carcass yield for pigs fed diets with added narasin include the narasin feeding duration, average weight, and growth performance of pigs fed diets without narasin. This meta-regression analysis provides equations to predict responses on growth performance and carcass yield. Lastly, in chapter 6, the effects of a pre-weaning socialization system during the lactation period on piglet growth and livability, pig lifetime performance, and subsequent sow performance were evaluated. Pigs raised in the conventional farrowing system had increased livability, lifetime growth performance, and carcass characteristics compared to the pre-weaning socialization system.Item Open Access An evolutionary consideration of stress response, biodiversity, and anthropogenic context(2024) Sharpe, Sam LipsonVariation is inherent in nature and underlies all evolutionary processes, with organismal diversity representing both a response to and a prerequisite for these processes. This dissertation considers fundamental concepts of evolutionary biology, including biodiversity, categorization of similarity and difference, and environmental heterogeneity, against the backdrop of profound threats to ecological diversity and marginalized human populations due to anthropogenic activities. In this way, evolutionary considerations of biodiversity in the Anthropocene epoch occur at the interface of nature and culture and can be understood through Donna Haraway’s term natureculture. My research uses a naturecultural framework to investigate stress response across populations of a wild plant species and explore strategies for improving representation and inclusion of sex, gender, and sexuality diversity in biology classrooms. To assess how local adaptation can impact physiological and transcriptomic responses to anthropogenically mediated sources of abiotic stress, I utilized climatically diverse populations of the wild foxtail millet, Setaria viridis. This species has many advantageous qualities as a model system, including widespread populations across a range of habitats, high genetic diversity, short generation times, small size, high rates of self-pollination, copious seed production, and a relatively small, sequenced diploid genome. Using 9 populations of S. viridis from geographically and climatically diverse home ranges, I compared photosynthetic response to drought stress in a greenhouse dry down experiment. With a subset of these populations, I assessed root surface area, aboveground biomass, and sensitivity to drought stress across plants of different ages. I found significant differences in drought tolerance by population which was not correlated with climate of origin but may be partially explained by differences in total plant size and ratio of root surface area to aboveground biomass. For S. viridis plants within the same population, plant age at the start of drought impacted both overall drought sensitivity and total production of inflorescences. To further address questions of local adaptation and abiotic stress response, I selected 2 S. viridis populations that demonstrated divergent physiological responses to drought stress and compared transcriptomic response across drought, chilling, and salinity stress conditions. I found substantial variability in the number and function of genes significantly up or down regulated between populations and treatment conditions, with only a few genes and gene functions showing similar response patterns across both populations or multiple stress conditions. There was, however, notable alignment of differently expressed genes from both S. viridis populations with a database of nearly 200 molecularly characterized drought tolerance genes. In an additional consideration of diversity, interface between science and culture, and anthropogenically mediated stress and resilience, I explored current issues in biology education that exclude or mischaracterize sex, gender, and sexuality diversity, and discussed emerging alternate pedagogical strategies for increasing inclusivity. I drew parallels between the oversimplified presentations of sex across taxa as a universal male/female binary in many biology classrooms, the ongoing social, legal and medical harms faced by queer, transgender, and intersex people, and the use of appeals to just such a universal sex binary to justify and perpetuate these harms. Importantly, biology education also offers many powerful opportunities to challenge such harmful misconceptions through providing more comprehensive, nuanced, and inclusive conceptualizations of sex, gender, and sexuality diversity across the tree of life. Through the integration of evolutionary, ecological, genomic, pedagogical, and naturecultural approaches, the research presented in this dissertation has important implications for understanding biodiversity, stress response, and resilience to anthropogenic contexts for human and non-human organisms.Item Open Access Impact of seismic reprocessing with an emphasis on improving static errors corrections on 3-D land seismic data in Ellis Co., Kansas(2024) Totten, CodySeismic datasets play an important role in petroleum exploration and development in the mid- continent. The role of good quality seismic data processing of 3D seismic surveys cannot be underestimated, as it is foundational to the creation of reliable interpretation of seismic data. It is imperative that processing is done properly, as inaccurate data can cause a multitude of problems, from simply unusable data to dry holes drilled due to incorrect placement of seismic reflectors in the subsurface. This research focuses primarily on seismic time corrections “statics” problems with processing, as well as interpreting, a seismic horizon of interest. Specifically, this project investigates the impact of remaining static errors on the fidelity of the geometrical structural seismic attributes (i.e. amplitude) and evaluates the impact on seismic resolution. As this study shows, inaccurate static-correction processing of the seismic data can have a great impact on the overall success of exploratory drilling. Land seismic data of the midcontinent present unique static time-effects challenges that must be resolved. Among the most prominent are challenges posed by both topographic elevation statics, as elevation differences arising from differentially weathered carbonates and anhydrites in the near-surface, and velocity statics arising from near surface lateral velocity variations. These types of statics need to be removed to improve the overall quality of the processed seismic. When unresolved, these issues have a large negative effects on seismic amplitude and structural fidelity of the post-stack seismic datasets. This project developed a processing workflow specific to the challenges of seismic datasets in Kansas. An iterative process was used and the processing was highly tailored to deal with the residual statics affecting seismic horizons of rock formations surfaces seen in Kansas. These formations are primarily composed of carbonates and evaporites, and so greatly affect the static solutions needed. Mapped first arrival travel-times were used as the input for travel-time tomographic inversion, creating a velocity model of the near surface. Applying this to the original dataset improves the quality of the seismic cube and removes the obvious topographic imprint present in the original post-stack interpretation. An additional benefit of this workflow was a greatly increased signal-to-noise ratio and significantly improved seismic resolution. Interpretation of this reprocessed dataset more closely corresponds to well data in the area, giving a high level of confidence in the accuracy of the reprocessing workflow.Item Open Access Assessing CyAN Satellite Accuracy: A Closer Look at Kansas' Aquatic Boundaries(2024) Angot, JordanCyanobacteria, commonly known as blue-green algae, pose significant environmental and public health challenges, producing toxins that degrade water quality and affect human health, local economies, and ecosystems. In Kansas, bodies of water like Marion Reservoir, Milford Lake, and Webster Lake are notably affected. Traditional in-situ sampling methods by the Kansas Department of Health and Environment (KDHE) often rely on public reports, potentially missing broader occurrences of harmful algal blooms (HABs). This study evaluates the efficacy of the Cyanobacteria Assessment Network (CyAN) satellite remote sensing technology as a method of bolstering existing efforts, examining its accuracy against localized in-situ measurements at the three eutrophic Kansas reservoirs. Through comparative analyses, this research assesses CyAN’s performance in estimating cyanobacteria concentrations at the water’s edge as well as when classified these into KDHE’s HAB levels: Watch, Warning, and Hazard. Findings from the cell concentration analysis demonstrate that the satellite data's accuracy varies significantly with lake geometry and spatial processing techniques, such as grid cell aggregation and zonal statistic type. However, in the KDHE HAB level classification analysis accuracy improved across all waterbodies. This research supports the potential of integrating remote sensing into existing monitoring frameworks to enhance HAB surveillance and management, providing a more comprehensive understanding of public health and environmental threats along the water’s edge in Kansas's freshwater systems.Item Open Access Contributions to ontology reasoning and modeling(2024) Eberhart, AaronThis dissertation comprises research in diverse areas related to both ontology reasoning and ontology modeling. While these two topics differ in certain important ways, fundamentally data representation and modeling is central to the development of common-sense and useful reasoning methods, and useful reasoning applications enhance and enrich semantic models with ontologies. The contributions to both topics in this document are approached separately from a unified perspective, where ontology modeling and reasoning do not merely exist as adjacent topics, but instead inform each other. The five internal chapters each correspond to unique and related publications that all orbit this core topic and are contextualized in the introduction with central themes, which are then re-examined in the conclusion.Item Open Access The impact of K-lactobionate and Bacillus subtilis on soil water retention in sandy loam soils(2024) Lincoln, MichaelDue to a combination of expanded agricultural production, global warming, and depleting water resources, semi-arid agricultural regions of the world have come under increased water stress. Such water stress results in less freshwater available for crop production and impacts the economic foundations of rural agricultural areas. One such area is the western part of Kansas. Western Kansas is an agriculturally dependent region that produces much of the nation’s crops. This area is located on top of the Ogallala aquifer, which is the water source for the large-scale irrigation farming that occurs in the area. However, due to its overuse, the aquifer has been in the process of depletion, with some areas reporting 100-foot drops in areas of pumpable water. This has spurred a need for water saving techniques. One such method is through improving soil water retention by adding amendments to the soil. Two amendments that show promise for retaining soil moisture and reducing water use requirements are Bacillus subtilis and K-lactobionate. B. subtilis is a Gram-positive bacteria that can wet soil through production of a biosurfactant molecules as secondary metabolites. K-lactobionate is a chemical compound produced from mixing lactobionic acid and KOH, and lactobionate derivatives are potentially available as a biproduct from the dairy industry. In this thesis, four studies were performed, with the goal of determining if K-lactobionate-B. subtilis amendments can be used to improve water penetration in soils, reduce runoff, and reduce water loss by increasing water retention during drought like conditions. First, water penetration and aggregation test of the two amendments in sandy loam soil was performed, which revealed that addition of a combination of K-lactobionate and B. subtilis reduced water penetration times to increase water infiltration into treated soils, and also caused the formation of large soil aggregates. B. subtilis and K-lactobionate was also studied as a means to reduce water evaporation in sandy loam soils through evaporation experiments. It was found that the addition of K-lactobionate with and without B. subtilis to the soil produced less evaporation and high water rention, while B. subtilis alone produced similar evaporation and water retention as unamended soil. Finally, an experiment testing the growth of B. subtilis when using K-lactobionate as a substrate showed that adding K-lactobionate could stabilize B. subtilis cells in otherwise nutrient-poor environments, suggesting that it could enhance the application of B. subtilis amendments while in soil or when added to irrigation water for distribution. Overall, the two paired amendments showed promise as a potential way to prevent water losses in cropland. Future studies in non-sterile environments more representative of cropland are needed as a next step to continue to evaluate the potential of these soil amendments.Item Open Access Effects of supplementing corn silage to fall-calving cows grazing tall fescue or bermudagrass, on cow and calf performance and physiology(2024) Banks, James Wyatt LangCow-calf operations across the U.S. serve as the foundation for the nation’s beef cattle industry. Cattle effectively convert forages to high quality protein by grazing pastureland often not suitable for crop production. To maximize grazing potential, producer cognizance of available forage types, their growth patterns, and nutritional value are crucial. For instance, the cool-season perennial, tall fescue, follows a bimodal growth pattern and reaches optimal forage quality in the early spring. Conversely, a warm-season perennial like bermudagrass has a unimodal forage growth curve, with forage quality peaking in early summer. Fescue has acquired the reputation of a “miracle forage”, capable of withstanding the environmental stressors of drought, insect predation, and poor soil conditions. However, the fungal endophyte that inhabits tall fescue produces ergot alkaloids, that when consumed are responsible for negative impacts on weight gain, reproduction, and endocrine function in cattle. Supplemental feeding, transitioning to a fall calving system, and the development of endophyte-free and non-toxic strands of fescue have been introduced as potential avenues for fescue toxicosis mitigation. Supplemental feeding has also been proven to improve grazed forage savings in drought management situations. Unfortunately, limited research has been conducted to evaluate cow and forage performance, and cow physiology, when supplementing corn silage to cattle grazing toxic fescue. Transitioning to bermudagrass for grazing cattle during the summer months may prove effective in mitigating drought and avoiding fescue toxicosis when ergot concentrations and ambient temperatures are highest. However, unlike fescue, little is known about the physiological effects of grazing bermudagrass, let alone how supplemental feeding can impact cattle grazing bermudagrass. Chapter one is a review of the literature surrounding forage, fescue toxicosis, and supplemental feeding. Chapter two is an evaluation of the physiological impacts of supplemental feeding late-gestation fall calving cows and calves on different fescue cultivars. Chapter three investigates the supplemental feeding of late-gestation fall calving cows and calves on bermudagrass pastures.Item Open Access Classification of 3-component links up to link homotopy(2024) Wijerathna, Shashika Dilshan Palamuru ArachchigeThe concept of link-homotopy was introduced by Milnor’s paper in 1954, in which he achieved the classification of 3-component closed links up to link-homotopy. After more than thirty years Levine achieved such a classification for 4-component closed links [3]. Then, in 1990, Habeggerr and Lin provided a new approach to a classification based on the closures of two different string links in the group of link homotopy classes [2]. The closures of two string links are link-homotopic if and only if those two elements are related by a sequence of elements, such that two adjacent elements are either conjugate or partial conjugate, in the link group. We employed Habbeger-Lin’s approach to provide a full classification for 3-component string and closed links.Item Embargo On convergence of neural networks for applications in agriculture(2024) Cheppally, Rahul HarshaNeural networks, as universal function approximators, have gained increasing popularity due to the availability of abundant computational resources and data from IoT devices. This thesis investigates the applications of neural networks in agriculture, focusing specifically on seed detection, distance estimation, row detection, and multi-robot pesticide spraying tasks. The first study aims to develop an automated system for obtaining seed placement information and reducing the time required compared to manual methods like using a pogo- stick or a ruler. A 12-row planter was instrumented with cameras and a GPS, and various object detection models (YOLOR-P6, YOLOR-CSPX, YOLOX-S, YOLOX-M, YOLOX-L, YOLOX-TINY, and YOLOV4) were trained on a dedicated dataset. An algorithm was de- signed to estimate the distance between consecutive seeds by filtering out old detections using the Intersection over Union (IoU) metric and GPS stream. The system’s performance was evaluated using metrics such as Jensen–Shannon Divergenceplanting (JSD), mean, stan- dard deviation, δCount, and RMS. Results indicate that the developed system and algorithm performed better at a planting speed of 9.66 kmph compared to 12.87 kmph, reducing the time taken to detect seeds and estimate seed spacing from 2 hours (manual method) to 1 minute 14 seconds using YOLOR-CSPX. The second study addresses the challenges of multi-robotic pesticide delivery tasks, where traditional task planning and allocation strate- gies require prior knowledge of crop infection levels, typically obtained through preliminary field scouting. As this assumption becomes obsolete with autonomous robots equipped with integrated sensing and spraying capabilities, the study reformulates the problem within the context of a Partially Observable Markov Decision Process (POMDP). A novel architecture, similar to Cross Transformer, is designed to address these challenges, and comparative eval- uations against expert models trained on out-of-distribution datasets are conducted. The study demonstrated that the proposed model performs almost as well as the expert model,with a 0.5% difference in performance, and is more robust to out-of-distribution data. The evalutation metrics are the total distance travelled by the robots as well as the total re- ward obtained by the robots. The third study focuses on under-canopy robot navigation, which has seen significant demand for crop phenotyping, crop water stress assessment, and liquid application. Traditional GPS fails under canopies due to multi path issues, pos- ing challenges. The study introduces a novel approach using smooth polynomials for row and canopy identification, leveraging image space prediction and a customized loss function to enhance generalization. This method delineates navigation boundaries with polynomial functions in image space and extrapolates seamlessly into real-world navigation due to these polynomials being smooth, down streams task such as control and state estimate become easier. The approach achieves 1ms latency on edge devices and is evaluated using a met- ric similar Intersection over Union named MPD(Mean Polynomial Distance), ensuring high accuracy for under-canopy navigation tasks.Item Open Access Facebook as a Battlefield: Social Media Users' Attitudes and Engagement with Feminism and Cyberviolence(2024) Achelha, LamyaThe women's movement advocating for equality and social justice encounters significant obstacles within the ever-changing landscape of social media in Egypt. Previous research has primarily examined the broader conversation surrounding feminism and the occurrence of violence on the internet. Nevertheless, there is a dearth of research that investigates these matters from the perspective of Egyptian social media users as a whole, with a specific focus on Facebook users. The study examines the attitudes and behaviors of Egyptian social media users towards feminism and feminists, specifically focusing on the dynamics and consequences of cyber violence as well as the impact of Western feminism on individuals' understanding of feminist concepts. The study utilizes the Situational Theory of Problem Solving and Attribution Theory as its theoretical framework. These frameworks facilitate the examination of the cognitive and psychological processes that drive users' engagement with feminist content online. They aim to comprehend how individuals perceive and respond to feminist content on social media. The research utilizes a quantitative methodology to conduct a thorough investigation of social media interactions and their implications. The study encompasses a survey that collected responses from a total of 379 individuals. Out of all the respondents, 65.9% were female, whereas males accounted for only 34%. Key findings indicate that a significant proportion of Egyptian women report instances of cyber violence, with social media being a prominent medium for these attacks. The majority of respondents indicated that perpetrators of the violence are primarily driven by peer influence and social pressure. A feminism scale was employed to assess the respondents' attitudes towards feminism. The analysis showed a significant majority of 64.3% expressed a "neutral" inclination towards feminist ideas. The study also highlights a profound misunderstanding of feminism in Egypt, which contributes to the perpetuation of cyber violence and broader societal prejudice against feminists. Furthermore, it emphasizes the critical role of social media in influencing public discussions on feminism, as well as the difficulties of dealing with the cultural and ideological conflicts that arise in this situation.Item Open Access Effects of wind on reservoir mixing and stratification: a case study from Kansas(2024) Baker, AveriThere is a growing concern of harmful algal blooms (HABs) in freshwater aquatic systems, including reservoirs throughout Kansas due to their toxicity and increased frequency. The impact of wind events on the stratification dynamics within reservoirs has been proven to greatly affect the surrounding environment, including mixing dynamics within reservoirs and conditions for HABs to form. This research study used the well-established General Lake Model (GLM), a one-dimensional hydrodynamic model, to analyze the effects of different wind scenarios on stratification and potential for harmful cyanobacteria blooms in Marion Reservoir. The GLM model was calibrated and verified using temperature profile data collected from Marion Reservoir in 2022 and 2023. Wind scenarios reflecting potential changes in wind speed during the algal bloom season were then applied in the model to examine the effects of wind on reservoir mixing dynamics. This research exemplifies the crucial impact of wind magnitude on stratification of lakes and reservoirs. These results further show the complex relationship between wind events and reservoir mixing.Item Open Access Narratives of resilience from Indigenous women in North America and Africa(2024) Azubuike, ChibuzorThe colonialization of Native people in different parts of the world led to grave consequences for the colonized people. Scholars have examined the various kinds of colonialism and their negative impacts on the Native people who suffered alienation from their lands, cultures, and ancestries. The findings of numerous studies reveal that many treaties signed between Indigenous nations and Europeans were disregarded at the onset of colonialism in full swing in North America and Africa. Colonialism exacerbated this issue by imposing arbitrary boundaries in various African and American societies, resulting in the loss of lands for several tribal nations and the displacement of Indigenous groups from their ancestral lands. Both Native American nations and African societies experienced the adverse effects of colonialism, enduring significant consequences such as land loss and forced displacement and the disruption of the hitherto existing leadership of the Indigenous peoples before their contact with the Europeans and subsequent colonization. The leadership structures that emerged in many colonized societies of Africa and America were in line with the colonizers’ leadership styles. These styles of leadership, as explained by many scholars, led to the emergence of social injustice movements as regards land acquisition, forceful eviction, and, in some cases, brutal treatment of the people. Such treatments include the report from the Uban Indian Health Institute, which shows that the Indigenous women of some tribal nations in the USA and Canada were murdered on their Native lands by non-Native people. Gbenenye (2016) cited the arbitrary creation of boundaries, which led to civil wars and the displacement of Indigenous people from their ancestral lands, like the Bakassi people in Africa, as an aftermath of colonialism and such injustices gave rise to movements such as Missing and Murdered Indigenous Women in the USA and Canada. However, not much has been done on the narratives of resilience among the Indigenous women of North America and Africa. This is the gap that this research sought to fill. This study utilized qualitative research methods, mainly narrative inquiry, with Indigenous women in North America and Africa to elicit data on their intersectional realities. Leadership as practice, complex adaptive system, nego-feminism/Indigenous feminism, and muted group theory constitute the theoretical framework employed in this study. This work situates resilience in the Leadership as Practice framework. As such, I argue that community resilience is a leadership practice. Resilience for Indigenous people is beyond being a trait, it is a commitment to uphold the legacies and sacrifices of their ancestors. The findings of my research show that Indigenous women practice resilience in their everyday lives. Findings from this research further show that there are factors responsible for resilience-building among Indigenous women. These factors include mentorship to acquire skills necessary for them to build resilience in their societies. Finally, the findings of my research show that resilience building is essential for Indigenous women in North America and Africa. Findings from this research would be useful in preventing violence in the event of displacement, as well as in socially integrating people who have suffered forced removal. I recommended some actions that can elevate the voices of Indigenous women in this study, contribute to the discourse on resilience and women’s leadership, and uphold the Indigenous knowledge systems while demonstrating the agency of Indigenous women in North America and Africa.Item Embargo Probing the structure and dynamics of complex hydrocarbons with ionizing radiation from free-electron lasers(2024) Borne, KurtisDirectly imaging the ultrafast changes in molecules during photochemical reactions has been a long-standing goal for chemists and physicists. Over the past three decades, ultrafast and intense light sources, including free-electron lasers (FELs), have been developed. These tools have enabled measurements that can probe the structure and dynamics of photoexcited molecules with femtosecond time-resolution. As these light sources improved, photo and electron spectroscopies have likewise developed, enabling high-dimensional measurements that provide a wealth of information on light-matter interaction. In this thesis, FELs operating from the extreme ultraviolet (XUV) to the X-ray regime are used to study the electronic and structural properties of complex isolated molecules. Specifically, ultrafast electronic relaxation processes of the quadricyclane molecule are explored. This highly strained molecule and its isomer, norbornadiene, are photoswitches with promising candidacy for solar energy storage. Here we apply time-resolved photoelectron spectroscopy at a highly coherent XUV-FEL. The experimental results are combined with non-adiabatic molecular dynamic simulations. With the high photon energy XUV-FEL source, we are able to monitor the molecule from any electronic state involved in the photochemical reaction, and we observe two competing relaxation pathways. One pathway is distinguished by a coupling to several valence electronic states that return the system to the ground state within 100 femtoseconds. The other pathway involves slower motion along the long-lived Rydberg states. Both pathways facilitate isomerization with a predicted branching ratio of norbornadiene/quadricyclane at approximately 3:2 in the electronic ground state. Secondly, Coulomb explosion imaging (CEI) is discussed. This experimental technique applies coincidence momentum imaging of molecules that rapidly dissociate after being photoionized to a highly-charged state. This technique has generated a lot of excitement as it is a promising candidate for probing gas-phase molecular structures, with previous results showing a beautiful molecular frame picture. In this thesis, we apply this technique to isomers with different cyclic geometries, demonstrating that CEI can differentiate gas phase hydrocarbon isomers that contain no preferential X-ray absorption sites, nor unambiguous ways to define a molecular frame due to the absence of marker ion momenta. This work contributes to the understanding of ultrafast molecular dynamics that underlies several light-induced biological processes, and potential applications in the optical control of quantum molecular systems.Item Embargo Time-Restricted Eating on Inflammation and Oxidative Stress in Overweight, Older Adults(2024) Ezzati, ArminThe aim of this dissertation was to provide innovative insights into the effects of various dietary interventions on inflammation, oxidative stress, and metabolic health. Chapter 1 presents a comprehensive review discussing the rationale for assessing inflammation and oxidative stress in the context of time-restricted eating (TRE). This review suggests the potential effects of TRE on pro-inflammatory cytokines, including tumor necrosis factor-alpha (TNF-α), interleukin-1β (IL-1β), IL-6, IL-8, and IL-10, as well as oxidative stress related to Alzheimer's disease in humans. Chapter 2 reviews the importance of different types of intermittent fasting (IF) regimens, including alternate-day fasting, the 5:2 diet, time-restricted eating, and Ramadan fasting, in mitigating inflammation and lowering oxidative stress. It highlights the potential of IF regimens in attenuating inflammatory responses. Chapter 3 presents a systematic review comparing the effects of isocaloric IF versus daily caloric restriction (DCR) on weight loss and metabolic risk factors for chronic noncommunicable diseases in adults with overweight and obesity. This review synthesized findings from randomized controlled trials and found that the effects of IF regimens on plasma lipid, glucose, insulin levels, HbA1c, and inflammatory markers were highly variable but generally comparable with DCR. IF (4:3 and 5:2 diets) was superior to DCR for improving insulin sensitivity in two studies. Reductions in body fat were significantly greater with IF (5:2 diet and TRE) than with DCR in two studies. Given the limited number of long-term studies using isocaloric or eucaloric IF interventions compared with control groups, future studies should incorporate more rigorous controls across intervention arms, as well as controls for energy intake and balance, nutrient composition, and weight loss. In Chapter 4, we conducted another systematic review on whether TRE confers additional benefits through mechanisms beyond calorie restriction (CR) alone or whether the benefits of TRE are related to unintentional reductions in calorie intake. The reviewed outcomes included anthropometric and metabolic outcomes (lipid levels, fasting blood glucose, HOMA-IR, and blood pressure). A novel finding of this review was that longer daily fasting periods (≥16 hours), combined with moderate CR, resulted in significant improvements in measures of insulin resistance (HOMA-IR) in five out of six studies where it was assessed. In contrast, CR alone did not improve this marker in short- or mid-term interventions (8 to 52 weeks) without a specific dietary intervention (e.g., Mediterranean diet). Greater weight loss and reductions in diastolic blood pressure were noted with CR + TRE compared with CR alone after 8 to 14 weeks, whereas one study reported greater improvements in triglycerides and glucose tolerance with CR + TRE (3 days/week) compared with CR alone following 26 weeks. Other metabolic outcomes did not significantly differ between the two interventions. Chapter 5 presents a secondary analysis of a pilot study investigating the effects of TRE on inflammation (TNF-alpha, IL-1beta, IL-6, high-sensitivity C-reactive protein) and oxidative stress (8-isoprostane) in older adults with overweight. No significant differences were found in the outcomes of interest compared to baseline after four-week TRE (16:8) intervention. A short-term TRE intervention produced reductions in TNF-α [43.2 (11.2) pg/ml to 39.7 (10.0) pg/ml (p = 0.101)] with a Cohen's d effect size of 0.33 and IL-1β levels [1.4 (0.8) pg/ml to 1.3 (0.6) pg/ml (p = 0.499)] with a Cohen's d effect size of 0.23, indicating potential anti-inflammatory benefits. Consistent with previous studies, IL-6 and hs-CRP levels showed no significant changes. Oxidative stress marker 8-isoprostane levels decreased slightly from 39117.6 (12787.5) pg/ml to 38694.7 (11631.4) pg/ml (p = 0.919), with a Cohen's d effect size of 0.07. Collectively, these findings provide initial insights into the potential effects of TRE on inflammatory and oxidative stress markers in older adults. Well-powered larger trials with longer durations are warranted to elucidate the potential of TRE in aging populations.Item Open Access Essays on the U.S. labor market: Evidence from immigrants' wages and the downward nominal wage rigidity constraint(2024) McKenzie, SidoniaThis dissertation consists of three essays that focus on the empirical regularities of the U.S. labor market and their consequences for economic opportunities available to native and immigrant workers. In particular, I reexamine two crucial aspects of the U.S. labor market: the disparity in the labor market outcomes of immigrants and the sluggish adjustment of nominal wages over the business cycle. The first essay addresses the question of whether various features of an occupation affect the wages of workers in that occupation. I leverage information on the variation in an occupation's English language skill requirement and the ethnic and nativity concentration in a given occupation and year to explain the native-immigrant wage differences within occupations. I show that the fraction of immigrants in an occupation plays an essential role in explaining this wage gap in the U.S. Furthermore, the nature of this fraction, whether immigrants are co-nationals or from a different birthplace, has a salient effect on the magnitude of the gap. Notably, across state labor markets, a one percent increase in the fraction of immigrant men in the workforce of a given occupation leads to an increase in the wage gap in that occupation by about 20 percentage points on average. On the other hand, if this fraction is from the same birthplace, the within-occupation wage gap narrows substantially by nearly 32 percentage points. In the second essay, I revisit the impact of access to the Supplemental Nutrition Assistance Program (SNAP) on immigrants' labor market outcomes. SNAP stands as one of the largest safety net programs in the United States. Given its significance, the welfare implications of SNAP have been extensively studied from various angles. In particular, applied researchers often focus on the 1996 federal welfare reform, which introduced significant restrictions to SNAP eligibility, creating a clear distinction between citizens (typically the control group) and legal non-citizens (usually the treated group). Subsequent policies that reinstated eligibility for legal non-citizens at different times across states offer a natural setting for a staggered treatment adoption, which is well-suited for a difference-in-differences (DiD) analysis. As previous researchers have done, East (2018) employs this methodology using a two-way fixed effects (TWFE) model to examine the effects of SNAP eligibility. However, recent advancements in empirical estimation, often referred to as the "DiD credibility revolution,'' have highlighted inherent biases in TWFE models, including issues related to "negative weighting'' that can lead to misleading and oppositely signed estimates. These more robust methods cast significant doubt on the validity of the effects reported by earlier studies that employed staggered rollout designs. In this essay, I revisit the effects of SNAP access on immigrants' labor market outcomes, building off the work of East (2018). By employing more recent econometric techniques, I confirm that while SNAP eligibility does indeed reduce immigrants' labor supply—affecting the likelihood of employment—the magnitude of these effects is considerably smaller than previously reported. This finding implies that policy changes impacting SNAP access for vulnerable groups, such as immigrants, should account for the fact that labor supply disincentive effects are relatively modest. The third essay, with Lance Bachmeier and Benjamin Keen, investigates the response of the labor market to substantial increases in oil prices. Our analysis utilizes microdata from the Current Population Survey (CPS) spanning from 1983 to 2018 to construct a linked sample of hourly paid workers who did not change jobs over the interview cycle. The most important finding, which contributes new insights to the literature, is that overtime compensation serves as a crucial margin for firms to adjust to significant increases in oil prices. Specifically, the likelihood of receiving overtime pay declines by nearly 45\% across both blue-collar and white-collar workers due to a reduction in overtime hours. We argue that explanations for the macroeconomic response to oil price shocks may benefit from emphasizing the central role of overtime compensation as a key margin where firms adjust production costs. A second clear takeaway from our analysis is that hours worked fall in most industries in response to large oil price increases. This pattern aligns with the notion that firms are hesitant to reduce wages, opting instead to decrease working hours as a means of cost adjustment.Item Embargo Real time application of neural networks and hardware-accelerated image processing pipeline for precise autonomous agricultural systems(2024) Raitz Persch , Jose MateusThe agricultural industry is undergoing a significant transformation as it increasingly adopts automation and precision technology to optimize crop management practices 1 . In this context, this research focuses on developing an autonomous pesticide spraying rover that leverages advanced technologies to revolutionize precision agriculture. The primary objective of this project is to utilize a neural network for real-time aphid detection in sorghum crops, enabling the targeted application of pesticides only to infested plants. To achieve this goal, cutting-edge technologies and software frameworks, including ROS 2 (Robot Operating System)2 , have been integrated to create a sophisticated software system for the rover. One of the major hurdles in deploying neural networks for real-time feedback in the field is the limitations of wireless communication. Transmitting large amounts of high-resolution images can be unreliable and slow, making it impractical to deploy the neural network on a remote server. To ensure real-time processing and feedback for the sprayer, the neural network is deployed directly on the rover’s computing system. For this purpose, Nvidia’s Jetson AGX Orin platform has been chosen, which combines an ARM processor with a powerful GPU. This setup ensures exceptional model inference performance compared to CPU-based solutions, enabling real-time processing and feedback for the sprayer. In addition to deploying the neural network on the rover, this research also focuses on efficiently handling image frames captured by the cameras. The GPU in the Jetson platform is utilized to accelerate the image pipeline and leverage the hardware encoder to compress image frames to H.264 format, resulting in streamlined data recording. This comprehensive approach enhances the rover’s capabilities while ensuring energy efficiency, a critical factor for field operations. The entire system is seamlessly integrated into ROS 2, and benefits from Nvidia’s Isaac ROS packages, which provide GPU-accelerated ROS nodes. The use of hardware acceleration is a pivotal component of this research, as it enables substantial computational power while maintaining efficiency. Furthermore, a method has been implemented to estimate the depth from the camera to the aphid from a 2D aphid detection. This depth estimation is subsequently used to determine the 3D coordinates of the aphid in the world, further enhancing the precision of the pesticide application. By offloading intensive processes from the CPU to the GPU and other accelerators, it is ensured that the autonomous pesticide spraying rover can operate effectively and deliver precise results, making it a valuable asset in the quest for optimized and sustainable agriculture. This thesis will provide an in-depth look at this innovative approach and showcase the practical implications of real-time neural network deployment in precision agriculture
