2020-

Permanent URI for this collectionhttps://hdl.handle.net/10217/182111

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Open Access
Multi-channel factor analysis: properties, extensions, and applications
(Colorado State University. Libraries, 2024) Stanton, Gray, author; Wang, Haonan, advisor; Scharf, Louis, advisor; Kokoszka, Piotr, committee member; Wang, Tianying, committee member; Luo, Jie, committee member
Multi-channel Factor Analysis (MFA) extends factor analysis to the multi-channel or multi-view setting, where latent common factors influence all channels while distinct factors are specific to individual channels. The within- and across-channel covariance is determined by a low-rank matrix, a block-diagonal matrix with low-rank blocks, and a diagonal matrix, which provides a parsimonious model for both covariances. MFA and related multi-channel methods for data fusion are discussed in Chapter 1. Under conditions on the channel sizes and factor numbers, the results of Chapter 2 show that the generic global identifiability of the aforementioned covariance matrices can be guaranteed a priori, and the estimators obtained by maximizing a Gaussian likelihood are shown to be consistent and asymptotically normal even under misspecification. To handle temporal correlation in the latent factors, Chapter 3 introduces Multi-channel Factor Spectral Analysis (MFSA). Results for the identifiability and parameterization properties of the MFSA spectral density model are derived, and a Majorization-Minimization procedure to optimize the Whittle pseudo-likelihood is designed to estimate the MFSA parameters. A simulation study is conducted to explore how temporal correlations in the latent factors affect estimation, and it is demonstrated that MFSA significantly outperforms MFA when the factor series are highly autocorrelated. In Chapter 4, a locally stationary joint multivariate Gaussian process with MFA-type cross-sectional covariance is developed to model multi-vehicle trajectories in a highway environment. A dynamic model-based clustering procedure is designed to partition cohorts of nearby vehicles into pods based on the stability of the intra-pod relative vehicle configuration. The performance of this procedure is illustrated by its application to the Next GENeration SIMulation dataset of vehicle trajectories on U.S. Highway 101.
Embargo
Cooking up a better AR experience: notification design and the liabilities of imperfect cues in augmented reality
(Colorado State University. Libraries, 2024) Raikwar, Aditya R., author; Ortega, Francisco R., advisor; Ray, Indrakshi, committee member; Moraes, Marcia, committee member; Soto, Hortensia, committee member
This dissertation investigates optimizing user experience in Augmented Reality (AR). A virtual cooking environment (ARtisan Bistro) serves as a testbed to explore factors influencing user interaction with AR interfaces. The research starts with notification design, examining strategically placed visual and audio notifications in ARtisan Bistro (Chapter 4). Building on this, Chapter 5 explores optimizing these designs for user awareness and delivering critical information, especially when audio is impractical. This involved exploring visual-only notifications, revealing consistent user performance and attention capture comparable to combined visual-audio notifications (no significant difference found). The research demonstrates that well-designed notifications can significantly improve user experience, but it also raises a crucial question: can users always trust the information presented in AR environments? The possibility of imperfect information delivery underscores the importance of reliable information delivery. Chapter 6 explores the impact of imperfect cues generated by machine learning (ML) on user performance in AR visual search tasks. This research highlights the potential for automation bias when users rely heavily on unreliable cues. By investigating both notification design and the limitations of ML systems for reliable information delivery, this dissertation emphasizes the importance of creating a well-rounded user experience in AR environments. The findings underscore the need for further research on optimizing visual notifications, mitigating automation bias, and ensuring reliable information delivery in AR applications.
Open Access
Illuminating the impact of reproductive extracellular vesicles: modeling maternal signals during preimplantation embryo development
(Colorado State University. Libraries, 2024) Menjivar, Nico Graham, author; Tesfaye, Dawit, advisor; Krisher, Rebecca L., advisor; Chicco, Adam, committee member; Hollinshead, Fiona K., committee member
Pre-implantation embryo development is a complex process beginning around the time of gametic syngamy, the process of two gametes fusing to create a zygote (the first cell of a new organism). Passively transient through the oviduct, the presumptive zygote is then characterized by a series of timely cleavage divisions, activation of the embryonic genome, compaction (morula formation), cavitation (blastocyst formation), and summing in hatching from the encapsulated zona pellucida and implantation to the uterine wall. Unfortunately, the current IVF system that occurs ex vivo, completely bypasses the critical maternal-embryonic crosstalk that would inevitably persist during the primitive stages of pre-implantation development. It is thought that the low yield of developed embryos in vitro, is in part due to the failed ability to recapitulate a suitable system that mimics the maternal environment, shunting early cleavage stage embryos for failure. However, the reservations regarding maternal signals secreted to developing embryos, the reproductively inaccessible nature of the organs, and suboptimal in vitro systems to study replicate in vivo function has limited our complex understanding of these stages. In this dissertation, I aimed to interrogate multiple aspects of preimplantation embryo development, under the primary premise of modeling maternal signal during the pre-implantation period. Utilizing the intrinsic interest in the growing field of extracellular vesicle (EV) research and their significance in intercellular signaling, particularly their communicative role in selective biological information transfer, my first exertion was developing a source of EVs from in vitro cultured granulosa cells for use during IVM (necessitating maternal signals amid the follicle microenvironment). Through the analysis of this dataset (in combination with Gebremedhn et al. 2020) together with immunofluorescence and functional experiments, we characterized diverging miRNA profiles of EVs secreted by granulosa cells subjected to polarizing thermal conditions, that are abundantly up taken by COCs and modulate key developmental events that safeguard developing embryos exposed to conditions of stress. Next, I built upon this work by generating a functional 3D organoid model to study the cellular and extracellular response of the oviduct using a multi-omics approach. Using this atlas as a guide, I characterized the functional undertakings of the oviduct during applied levels of heat stress and found its crucial role in altering the metabolic activity of maternal tissues, which likely in part functionally augment developing embryos and assume failure. Given the functional applicability of reproductive EVs acting as maternal cues, I established this suitable model as a mechanism to generate physiologically relevant EVs (in vivo-like) to offset applied stress during the initial stages of development. These EVs secreted from 3D cultured oviductal organoids were then compared with those secreted from 2D OECs and from in vivo oviductal fluid (miRNAs), and used in an IVC setting, highlighting functional maternal—embryonic crosstalk. Altogether, this dissertation highlights key functional aspects of reproductive extracellular vesicles from both the follicular microenvironment and the oviduct, highlighting the novel and incredible power of suitable in vitro systems to propagate mechanisms to understand maternal signal absent in the current in vitro systems, beginning to illuminate the 'black box' of EVs in embryo development.
Embargo
Changes in functional structure of aquatic insect communities across environmental gradients in mountain streams
(Colorado State University. Libraries, 2024) Gutierrez, Carolina, author; Poff, N. LeRoy, advisor; Ghalambor, Cameron, advisor; Neuwald, Jennifer, committee member; Webb, Colleen, committee member
This study investigates the functional diversity of aquatic insect communities across environmental gradients within Rocky Mountain headwater streams, aiming to better understand how elevation, water temperature, and canopy cover shape the structure and dynamics of these communities. Functional diversity (FD) is defined here as the range, distribution, and relative abundance of organismal traits, which together provide deeper insight into ecosystem functionality than species diversity alone. FD was quantified through three primary metrics: functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv), each capturing distinct aspects of how species contribute to ecosystem functioning. This multidimensional approach enables a nuanced examination of how aquatic insect communities respond to various environmental stressors and spatial constraints, particularly as altitudinal changes present unique challenges in terms of temperature variability and resource availability. Field data were collected from twenty-four stream sites distributed across elevation bands ranging from 1,500 to 3,500 meters. Sites were replicated in three different drainage systems to account for regional variation, with insect specimens collected and assessed for twenty functional traits. These traits included parameters such as voltinism (number of life cycles per year), adult lifespan, emergence synchronization, and dispersal ability, all of which are critical in determining an insect's role in the ecosystem. Canopy cover and water temperature were also measured to evaluate how localized microclimates and light availability influenced community composition. Results revealed a significant decline in functional richness with increasing elevation, with the steepest reductions observed in streams with sparse canopy cover. Functional richness was highest in areas where canopy cover ranged between 65-78%, and water temperature was between 8°C and 15°C, suggesting that moderate canopy cover and specific thermal conditions support more functionally diverse communities. Functional evenness and divergence, while showing less pronounced patterns, indicated that the most extreme trait values are critical for resilience in these systems, particularly under fluctuating environmental conditions. Trophic interactions further illustrate the importance of specific functional groups, such as predators, grazers, and filterers, in shaping community structure. The analysis of beta diversity demonstrated substantial turnover in functional traits across elevation gradients, emphasizing the heterogeneity of insect communities within low-order, high-altitude streams and reinforcing the role of environmental filtering in community assembly. These findings highlight the vulnerability of headwater stream ecosystems to environmental changes and underscore the importance of functional diversity metrics in ecological monitoring and conservation efforts. Overall, this study contributes to our understanding of how functional environmental gradients structure diversity and provides a foundation for comparative studies on functional diversity in tropical versus temperate mountain stream ecosystems, particularly in the context of global biodiversity conservation.
Embargo
Cryo-electron microscopy of cloneable inorganic nanoparticles
(Colorado State University. Libraries, 2024) Guilliams, Bradley Forrest, author; Ackerson, Christopher J., advisor; Sambur, Justin, committee member; Crans, Debbie, committee member; Stasevich, Tim, committee member
Our understanding of biology is best understood through direct, empirical measurements of biomacromolecules and biological systems. The functions of proteins are directly linked to both their structure and their intracellular organizations. Single particle cryo-electron microscopy has revolutionized modern structural biology by enabling the structural determination of proteins and protein-complexes in purified samples without the need to form large crystals as required by X-ray crystallography. With single particle cryo-EM, atomic and near-atomic resolution structures are now routine which offer insight into the functions of biomacromolecules. While these insights are invaluable, there is increasing momentum for integrative structural biology which aims to accomplish structural determination of biomacromolecules in their cellular, tissue, or organismal context. There remains a grand challenge in biological imaging where biological materials have low innate contrast. Cloneable contrast labels that impart contrast to discrete protein densities do not reliably exist for cryo-electron microscopy. In contrast, fluorescent proteins are reliable and routine for localizing fluorescent protein / protein of interest genetic fusions in visible-light microscopies. We have proposed and developed intracellularly synthesized inorganic nanoparticles called 'cloneable nanoparticles' as a solution to this grand challenge. Cloneable nanoparticles are inorganic nanoparticles, synthesized by a protein/peptide (or combination thereof) which controls and defines the properties of the inorganic nanoparticle. Here we have defined the cloneable nanoparticle paradigm and described the development of a cloneable selenium nanoparticle. Further, we show the application of the cloneable selenium nanoparticle as a cloneable contrast label for biological electron microscopy and correlative light-electron microscopy and detail progress towards adapting the cloneable selenium nanoparticle for use in cryo-electron tomography. With the aim to later expand cloneable nanoparticles to include a myriad of orthogonal cloneable contrast labels (analogous to different colored fluorophores), and to gain understanding about enzymatic nanoparticle synthesis, a single particle cryo-EM study is on-going. Lastly, we have shown the application of directed evolution for cloneable nanoparticles, suggesting that this is a viable path, alongside rational protein design, towards developing future cloneable nanoparticle cryo-electron microscopy labels.
Open Access
Evaluating the efficiency, equity, and effectiveness of wildfire suppression strategy using the microeconomic toolkit
(Colorado State University. Libraries, 2024) Bryan, Calvin R., author; Bayham, Jude, advisor; Manning, Dale T., committee member; Goemans, Chris, committee member; Wei, Yu, committee member
Most economic research related to wildfires focuses on their impact on people and populations. In my dissertation, I use economic tools to evaluate the efficiency and equity of wildfire suppression strategy. In the first chapter, I investigate whether socioeconomic factors of a community (income, race, age, etc.) are correlated with allocations of suppression effort. I use spatial data on retardant drops from large airtankers (LATs) and demographic information from the Census Bureau to find that communities threatened by wildfire with fewer minority residents, but more low-income residents, are more likely to receive LAT drops. I then find that socioeconomic factors aren't correlated with the decision to use LATs in suppression after conditioning on biophysical factors like fuels and burn probability. In my second chapter, I study whether the media's attention to wildfire influences suppression strategy. I instrument for the effect of media attention using the incidence of catastrophic events that would distract the media to find that media scrutiny of a wildfire has no tangible effect on the decision to use aviation on a fire. Finally, most economic research on wildfire suppression strategy has focused on the costs; little exists on its benefits. I use causal inference methods leveraging satellite data on wildfire growth and intensity, along with the spatial data on aerial suppression effort mentioned previously, to find that large airtankers are effective at limiting the physical extent of wildfire's spread, reducing the intensity of flames as it grows, and slows its spread.
Open Access
Development of a multi-breed heifer pregnancy genetic evaluation in beef cattle
(Colorado State University. Libraries, 2024) Giess, Lane Kurtis, author; Enns, R. Mark, advisor; Speidel, Scott E., advisor; Doyle, S. Patrick, committee member; Koontz, Stephen R., committee member
Heifer fertility represents a primary influence on the profitability of a beef cow-calf enterprise. Reproductive rates determine the number of calves born and thus influence the amount of beef product produced at the commercial level driving income for cow-calf operators. Heifer fertility then is an economically relevant trait, though in most cases pregnancy data are cumbersome, untimely to collect, and are considered a rare phenotype in national cattle evaluations (NCE). Despite this, there are successful examples of existing evaluations for heifer pregnancy (HP) across several beef breed associations. These HP genetic evaluations typically rely on categorical exposure (1 = exposed; 0 = not exposed) and pregnancy outcome (1 = pregnant; 0 = not pregnant) data and involve the use of threshold animal models (TM) to convert these binary observations to an underlying normally distributed range of values known as liabilities. These liabilities are then expressed as a percentage that predicts the likelihood of a bull's daughters becoming pregnant and giving birth as two-year-olds in the form of an expected progeny difference (EPD). However, despite these existing HP genetic evaluations, little improvement in the genetic trends in HP has been observed. Perhaps the reason for meager improvement in genetic trend is seedstock producers are not placing enough emphasis on HP, or with pregnancy rates already at or near 90% there is an assumption there is no need for genetic improvement. Additionally, though TM have been successfully implemented in genetic evaluations of HP, a common challenge with the methodology is the inability to evaluate data from contemporary groups that all have the same observation. Even more important is that TM are not supported in some software used for single-step genomic evaluation, such as BOLT by Theta Solutions. Because of these challenges, this study investigated the development of a multi-breed genetic evaluation for HP by performing a series of HP evaluations using TM, linear animal model (LM), and random regression model (RRM) methods. This study used HP data collected on heifers from 1974 to 2020 provided by the International Genetic Solutions (IGS) genetic evaluation, sourced from 9 partner breed associations. Because each breed organization may have its own nuanced definition of HP or differences in how data are reported, inconsistencies in HP data need to be investigated. For example, the American Simmental Association (ASA) does not have an upload format for producers to report HP data but instead uses a system of logic converting whole herd reporting (WHR) codes into HP phenotypes. The first study described the framework for how the ASA converted productivity, culling, and enrollment codes into HP phenotypes. It then evaluated the relative proportions of reasons why heifers/cows were culled. The proportion of heifers culled due to reproductive failure using this method of establishing HP phenotypes was 14%, which is consistent with the national average. The summary statistics for HP observations were cohesive with other HP observations reported to IGS partner breed organizations. Evaluating the effectiveness of these created phenotypes were investigated in the second study. Using data from the American Gelbvieh Association, the Red Angus Association of America, the North American Limousin Foundation, the American Shorthorn Association, and the Canadian Limousin Association, the second study estimated variance components, breed effects, and heterosis effects using LM and TM evaluation methods. Evaluations of HP were performed first within breed before a multibreed population was developed. The average heritability estimate across evaluations performed on 7 different breed groups for HP using LM methods was 0.026, with a minimum value of 0 and a maximum of 0.084. The average heritability for HP using TM methods was 0.17, with a minimum of 0.07 and a maximum of 0.28. Breed populations were then combined into a single multi-breed population, and the same stepwise procedure of incorporating heterosis and breed effects as fixed effects was used to generate variance components and fixed effect solutions. The heritability estimates in this multi-breed population were 0.023 and 0.088 using LM and TM methods, respectively. Heritability estimates did not change as additional fixed effects of breed and heterosis were fit. There were no statistically meaningful breed effects; however, heterosis results in a 17.2% increase (P<0.05) in the probability of HP when maximum heterosis is achieved. Results from this statistical method suggested that LM and TM may be performing equivalently for estimating HP breeding values in within-breed populations; however, in a multi-breed population, results were inconsistent, suggesting perhaps the model was over-specified with breed effects. These results suggest that LM as the model type within a genetic evaluation may be an alternative evaluation method for HP due to its simplicity, ability to use all available information, and support in modern genetic evaluation software programs. Due to being relatively simple to collect and economically important for beef producers, the third study performed a series of evaluations for age at first calving (AFC), which also served as an important investigation as AFC was a potential age covariate in HP evaluations. Models were implemented using single-breed populations and then combined into a larger multi-breed population so heterosis and breed effects could be estimated. The heritability estimates of AFC for Simmental and Red Angus were 0.19 ± 0.01 and 0.14 ± 0.01, respectively. These results demonstrate AFC in days is lowly to moderately heritable. However, when evaluating the genetic trend for both breeds the results seemed incongruous as AFC was sharply increasing over time. Many beef producers mass mate heifers at a single fixed breeding date. As a result, older heifers in a CG will not have the ability to have a younger AFC compared their younger counterparts in the same CG if conception occurs on the same day. To account for this systematic management influence which may be creating a disadvantage in some heifers, age differential (DIFF) was included to account for age differences prior to first exposure and was defined as the difference in days between an individual's birth date and the earliest birth date of an animal in a defined contemporary group. In addition to including DIFF as a fixed effect, accounting for heifer body weight prior to breeding was also considered, and subsequent bivariate animal models of AFC that included yearling weight (YW) were performed. Two bivariate multi-trait animal models for AFC and YW with random additive genetic and residual effects and fixed effects of contemporary group, breed proportion, and retained hybrid vigor were used. When DIFF was not included as a fixed effect, the additive, residual, and phenotypic variances for AFC were 126.1, 456.8, and 582.9 d2, respectively, and the genetic correlation between AFC and YW was 0.36 ± 0.02. When DIFF was included as a fixed effect, the additive, residual, and phenotypic variances for AFC were 10.0, 326.0, and 336.0 d2, respectively. The genetic correlation between AFC and YW was 0.19 ± 0.04. In the absence of DIFF, the heritability estimates for AFC and YW were 0.22 ± 0.01 and 0.44 ± 0.01, respectively, but were 0.03 ± 0.003 and 0.44 ± 0.01 respectively, when DIFF was included. Age differential had a significant effect on AFC at –0.86 (P < 0.0001). The low additive genetic variance of AFC, when accounting for DIFF, suggests that the influence of a female's age going into a fixed breeding date explains much of the variation in AFC. Because of the potential drawbacks associated with LM and TM evaluations of HP, the fourth study investigated alternative definitions of HP using RRM evaluation methods. Two fertility traits evaluated using RRM were proposed; the first being the evaluation of heifer pregnancy by calving week (HPcw), which regresses a binary calving event on the week a heifer calved within her contemporary groups calving window, and the second being the linear evaluation of binary HP which regresses HP on an age covariate such as age at first exposure (AFE) or yearling age (YAGE). In all evaluation methods, Legendre polynomials were used as the base function and observed heritability estimates at different age ranges were transformed from the (co)variances estimated for the intercept and linear term of HPcw or HP. Within the HPcw evaluations, two separate age covariates were proposed as additional fixed effects, with the first being age at first calving (AFC), and the second being AFE. Heritability estimates for HPcw fitting AFC as a fixed effect ranged from 0.39 to 0.56, though this is assuredly from AFC being a biased age estimate. Observed heritability estimates for HPcw across 10 weeks, fitting AFE as a fixed effect ranged from 0.010 to 0.20, which are more realistic and consistent with literature estimates compared to observed HPcw heritability estimates fitting AFC as an age covariate. For the HP evaluation regressing HP on YAGE, heritability estimates ranged from 0.01 to 0.14, suggesting that up to 14% of the variation in HP across ages could be attributed to differences in additive genetics. For the evaluation regressing HP on AFE, heritability estimates were 0 or near zero, so this evaluation method likely requires additional scrutiny. Differences in heifer age covariate and trait definition for the evaluation of HP provided expanded opportunities for the development of national cattle evaluations using RRM. The potential advantages of utilizing RRM in evaluations of categorical or single observation data are that it allows the use of all available data in a dataset and is more adapted to single-step genomic evaluation software systems. Because of this, RRM may be the preferred evaluation method for HP or related fertility traits, though this requires additional testing in global databases. Results from previous studies suggest there are options for evaluating HP in a multi-breed NCE, but no single method is ideal. While LM evaluations validate well, there is low variance in the EBV for the populations evaluated due to low heritability. The TM evaluations validate well and have reasonable predictions, but they cannot appropriately utilize all available data and are not supported by some modern genetic evaluation software programs. The potential of RRM evaluation methods is evident; however, further testing of this methodology must be performed before this approach can be considered.
Open Access
Molecular mechanisms of herbicide resistance in rice and kochia
(Colorado State University. Libraries, 2024) Gupta, Srishti, author; Dayan, Franck E., advisor; Gaines, Todd A., advisor; Reddy, Anireddy, committee member; Kumar, Vipan, committee member
Herbicide stress is an important challenge in agriculture and understanding how plants respond to herbicide exposure is crucial for developing effective weed management strategies. Transcription factors (TFs) play a pivotal role in regulating gene expression and mediating plant responses to various environmental stimuli, including herbicide stress. This dissertation aimed to elucidate the role of TFs in herbicide tolerance and sensitivity across plant species. A brief introduction was provided in Chapter 1. Subsequently, by analyzing transcriptomic data from different studies, we identified key TFs involved in herbicide responses. Our findings in Chapter 2 revealed distinct TF signatures, including bZIP, NAC, WRKY, and ERF, that were consistently upregulated in herbicide-tolerant plants. associated with herbicide tolerance or sensitivity, suggesting potential regulatory mechanisms in metabolic pathways and downstream signaling. These results underscore the importance of complex interplay between herbicide class, treatment duration, and plant species on TF expression patterns. In Chapter 3, we focused on herbicide resistance in rice, a critical staple crop. Transcriptomic analysis revealed upregulation of key detoxification genes, including glutathione S-transferase (GST) and cytochrome P450 (CYP450), in the NTSR mutant, suggesting their involvement in herbicide metabolism. Functional characterization confirmed increased glutathione S-transferase activity in the NTSR genotype. Additionally, computational studies identified a novel transcription factor, ZOS-1-16, with a potential role in regulating herbicide response. We investigated a novel non-target site resistance (NTSR) mechanism conferred by a mutation in the transcription factor ZOS-1-16. Our findings demonstrated that ZOS-1-16 upregulates genes like GSTs and CYPs involved in herbicide detoxification, leading to increased resistance to the herbicide quizalofop-p-ethyl (QPE). This study highlights the potential of targeting TFs for developing herbicide-resistant rice varieties. Finally, Chapter 4 explored glyphosate resistance in the invasive species Bassia scoparia (kochia). We investigated the inheritance of glyphosate resistance in kochia populations and found that it is primarily due to an increase in the copy number of the EPSPS (5‐enolpyruvyl‐3‐shikimate phosphate synthase) gene. Additionally, we estimated the outcrossing rate of kochia under field conditions and found a high level of outcrossing, which contributes to the rapid spread of glyphosate-resistant biotypes. Overall, this dissertation provides valuable insights into the role of TFs in herbicide responses and highlights the potential for developing novel strategies to enhance herbicide tolerance and manage herbicide-resistant weeds.
Open Access
Does orientation matter? Controlling laccase orientation on planar gold electrodes
(Colorado State University. Libraries, 2024) Perry, Collin, author; Ackerson, Christopher, advisor; Snow, Christopher, committee member; Dandy, David, committee member; Neale, Nathan, committee member
Enzyme electronics are becoming more common in modern life. Even though these technologies have been integrated into everyday life, the fundamental understanding of how an enzymes' orientation at the electrode surfaces affects the enzymes catalysis is still unknown. To understand this more we designed a library of laccase mutants, all with a single solvent exposed cysteine. These cysteine residues are used to bind to a gold electrode modified with a monolayer of sulfhydryl molecules capped with a maleimide binding group. Each mutants' single cysteine will bind to the maleimide group orienting each mutant differently at the electrode surface. The wild type enzyme (WT) and all the mutants, D113C, N264C, H470C all show activity toward a common substrate 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). Although each mutant does show catalytic activity in solution, we were unable to obtain an electrochemical response from the laccase library using the maleimide capped electrodes for either ABTS or oxygen. Modification of the electrodes via the deposition gold clusters makes the electrode surface more topographically complex. The cluster modified electrodes bound with WT laccase displayed an electrochemical response for the reduction of oxygen to water. The increased topography from using gold clusters allows for electron transfer with laccase enzymes, while the planar electrodes modified with the laccase enzymes in which we achieved an electrochemical response.
Open Access
Restoration of scaled quail to historic ranges in the Rolling Plains ecoregion of Texas
(Colorado State University. Libraries, 2024) Ruzicka, Rebekah Elizabeth, author; Doherty, Paul F., Jr., advisor; Rollins, Dale, committee member; Kendall, William L., committee member; Otis, David L., committee member; Webb, Colleen T., committee member
Scaled quail (Callipepla squamata) are a gallinaceous game bird native to the grasslands and deserts of the southwestern United States and northcentral Mexico experiencing range contraction and population decline due to habitat fragmentation and degradation. Once abundant in the Rolling Plains ecoregion of Texas dating back to the 1880's, scaled quail were locally extinct throughout most of the ecoregion by the late 1980's primarily due to brush encroachment and spatial aggregation of row crop agriculture. Despite state and federal landowner habitat restoration programs (e.g., Landowner Incentive Program, Environmental Quality Incentives Program) scaled quail populations in the Rolling Plains ecoregion failed to respond, likely because the same fragmentation that contributed to decline also prevented effective natural recolonization to restored habitats. Translocation of wild-caught quails to reestablish self-sustaining populations gained popularity during the 2000's, particularly due to success reestablishing northern bobwhites (Colinus virginianus) in fragmented habitats of the southeastern United States. However, many translocations in arid, western climates were either poorly documented or failed outright. Understanding factors that influence translocation outcomes and form best practices is critical for translocation to be used effectively as a management tool. I examined long-term, seasonal survival in a population of scaled quail successfully reestablished on the Rolling Plains Quail Research Ranch in Fisher County, Texas in the context of drought and demographics (Chapter 1). Competing hypotheses predict that scaled quail populations are either resistant to drought or that annual survival is negatively correlated with precipitation amounts. My findings supported the hypothesis that scaled quail are drought sensitive. Additionally, I found survival was lower during non-breeding season, for females, and adults. Scaled quail survival estimates reported here are the most comprehensive for the species and the longest-term study of a translocated scaled quail population to date. I conducted a field experiment to test the effects of source population and variation in delayed release strategy (1–9 weeks) on mortality, dispersal, nest initiation, renesting rate, and nest survival of wild-caught, translocated scaled quail (Chapters 2 and 3). I trapped and translocated quail over 2 years (2016–2017) from source populations in the Edwards Plateau and Rolling Plains ecoregions to a large (>40,000 ha), contiguous release site in Knox County, Texas. Data were analyzed using two multi-state mark-recapture models with state uncertainty to incorporate uncertainty in the process of observing location and nest initiation in radio-marked birds. The framework I used to model reproductive processes is a novel method for obtaining estimates of nest initiation and renesting rate (Chapter 3). I found that scaled quail translocated within the Rolling Plains were more likely to exhibit philopatry to the release site, but that source population did not influence reproduction. Quail with longer holding times had higher mortality, but lower dispersal rates. Additionally, increased length of holding time decreased renesting effort. Yearlings were more likely to initiate nests than adults and the probability of renesting was lower during drought conditions. Finally, I compiled estimated demographics from chapters 1–3 to inform a matrix population model (MPM) that compared asymptotic and transient dynamics under wet and drought conditions (Chapter 4). While traditional MPM analyses focus on asymptotic dynamics, transient dynamics are more relevant for modeling short-term dynamics in translocated or unstable populations. My findings showed divergence between transient and asymptotic dynamics, with asymptotic projections potentially overestimating population growth by 14%. Asymptotic growth rates were most sensitive to renesting rate changes, while transient growth rates were affected by changes in hatchability and renesting rates. The results from my research will inform management decisions and I summarize my recommendations in Chapter 5. I suggest managers avoid initiating translocations in years projected to have drought conditions. Improved accuracy of El Nino–Southern Oscillation cycle-based long-range forecasts has made predictions a useful tool for managers considering translocation. Even so, translocated populations can persist long-term in drought conditions despite the negative impacts to survival and reproduction. Longer holding times for translocated scaled quail result in lower dispersal but higher mortality and lower renesting rates, presenting a decision tradeoff for managers. Managers can hold scaled quail on the release site (up to 9 weeks) when limiting dispersal is a priority (e.g., when in habitats surrounded by a high degree of fragmentation) or holding birds makes the translocation more feasible. However, when considering all factors a holding time of 2–3 weeks is ideal (Chapter 5). The Edwards Plateau is a suitable source site for translocations in the Rolling Plains. Managers should consider transient dynamics when modeling populations where short-term outcomes are relevant such as translocation. By doing so, I show that prioritizing the translocation of yearlings, the stage class with the highest reproductive value, can result in a 16% larger population after one year compared to translocating only adults.
Open Access
Habitat variation effects on cavity-nesting bee fitness, community assemblages, and parasite interactions in the Colorado Front Range
(Colorado State University. Libraries, 2024) Dodge, Jessie M., author; Davis, Thomas S., advisor; Galbraith, Sara M., committee member; Paschke, Mark, committee member; Stewart, Jane E., committee member
Although many dry forested ecosystems in the western US are shaped by disturbances like wildfire and forest management treatments, little is known about their effects on native solitary bee fitness. This is an important knowledge gap, as most bees in the western US are solitary and are crucial for pollination in forested ecosystems. Therefore, I test how wildfire and forest management treatments affect cavity-nesting solitary bee fitness traits including diet breadth and quality, provisioning ability, reproduction and brood development, parasite abundance, and community network metrics. This was done by deploying artificial nesting boxes in the ponderosa pine forest of Boulder County, CO that either burned at higher severity, thinned by hand, or were unburned and untreated control. For my first two chapters, I used the solitary bee, Osmia lignaria as a model species to evaluate bee fitness responses to variations in forest structure, floral density, and climatic conditions. I found that O. lignaria foraged for pollen from specific flora, regardless of on-site presence, which was affected by climate and forest structure, but effects varied from year to year. Otherwise, habitat variation did not affect O. lignaria nest provisioning, reproduction, or development. However, the abundance of their kleptoparasite, Tricrania stansburyi, decreased with increased wildland urban development. Finally, in my last chapter, I utilized artificial nest boxes to collect local cavity-nesting bees and wasps to compare differences in community composition, host-parasite interactions, and emergence rates among Burned, Control, or Treated sites. The solitary bee, Osmia calla was found to be the most abundant species, indicative of burned sites whereas the kleptoparasite, Nemognatha sparsa, and parasitoid, Monodontomerus spp., were the most abundant parasites found within all habitat types. Control sites were found to have the most host-parasite interactions, with parasites exhibiting more generalist relationships with hosts, followed by treated sites, with burned sites having the most specialized host-parasite interactions. Collectively, my results demonstrate that disturbance-caused habitat variations had little effect on the fitness of the solitary bee, O. lignaria, despite affecting their access to nutritional opportunities, suggesting they can reproduce within various dry, mixed conifer forested habitats. However, urbanization in forested ecosystems likely decreases exposure to nest parasites. Alternatively, local, cavity-nesting bee-parasite interactions differed among habitat types, with hosts inhabiting control sites portraying more parasitic pressure. Thus, some cavity-nesting bee species may be more influenced by habitat variations than O. lignaria, and this is likely mediated by interactions with parasitic species. The interacting effects of disturbances and parasite pressure on bee fitness found here can be used to inform native bee conservation strategies. For one, floral surveys may not reflect floral species bees are using for foraging so alternative methods investigating pollen sources bees are using for forage are suggested. Secondly, the loss of natural habitat with increasing urbanization within forested habitats can decrease kleptoparasite abundance but provide early season solitary bees with additional foraging sources. Finally, cavity-nesting bees and wasps in unburned and untreated habitats demonstrate higher parasitic pressure than burned and treated habitats, suggesting habitat variations caused by these disturbances may relieve parasitic pressure. Overall, monitoring bee parasite abundance may indicate healthy pollinator habitats within the forests of the Colorado Front Range.
Embargo
Immune-activated cellular therapies for osteoarthritis and the role of immune recognition of joint antigens
(Colorado State University. Libraries, 2024) Linde, Peter E., author; Dow, Steven, advisor; Pezzanite, Lynn, advisor; Regan, Dan, committee member; Easley, Jeremiah, committee member; McGilvray, Kirk, committee member
Osteoarthritis (OA) is a progressive, degenerative condition that affects over 550 million people worldwide – a 113% increase since 1990. Despite this high prevalence, there remains a lack of effective treatment options that improve quality of life without risk of adverse effects. Recent evidence supports that OA is a multifactorial condition in which the immune system plays a key role to perpetuate chronic inflammation. Cellular therapies to treat OA have emerged as an option, with mixed results reported in terms of efficacy. Heterogeneity within stromal cell populations has been proposed to be partially responsible for the observed variability in therapeutic responses, particularly in the context of variably inflamed recipient environments such as that seen in OA. Pre-activation, or 'inflammatory licensing' of mesenchymal stromal cells (MSC) through priming their respective ligands has been proposed as a means to generate a homogeneous population of immunomodulatory MSCs – thereby potentially improving their therapeutic consistency in the inflammatory environment of OA. The work in this defense addresses three primary aims: 1) to further investigation the role of the adaptive immune system in OA, investigating autoantibody production to synoviocytes and chondrocytes in OA progression, 2) to evaluate further mechanistically how innate immune pathway activation of mesenchymal stromal cell therapy modulates interactions of MSC with synovium and cartilage to mitigate OA progression, and 3) to examine alternate connective tissue sources of MSC for cell expansion as regenerative therapies. With the lifetime likelihood to develop symptomatic knee OA currently 45% and increasing, the need to develop improved strategies towards disease-modification is critical.
Open Access
Smart transfers: challenges and opportunities in boosting low-resource language models with high-resource language power
(Colorado State University. Libraries, 2024) Manafi, Shadi, author; Krishnaswamy, Nikhil, advisor; Ortega, Francisco R., committee member; Blanchard, Nathaniel, committee member; Chong, Edwin K. P., committee member
Large language models (LLMs) are predominantly built for high-resource languages (HRLs), leaving low-resource languages (LRLs) underrepresented. To bridge this gap, knowledge transfer from HRLs to LRLs is crucial, but it must be sensitive to low-resource language (LRL)-specific traits and not biased toward an high-resource language (HRL) with larger training data. This dissertation addresses the opportunities and challenges of cross-lingual transfer in two main streams. The first stream explores cross-lingual zero-shot learning in Multilingual Language Models (MLLMs) like mBERT and XLM-R for tasks such as Named Entity Recognition (NER) and section-title prediction. The research introduces adversarial test sets by replacing named entities and modifying common words to evaluate transfer accuracy. Results show that word overlap between languages is essential for both tasks, highlighting the need to account for language-specific features and biases. The second stream develops sentence Transformers, which generate sentence embeddings by mean-pooling contextualized word embeddings. However, these embeddings often struggle to capture sentence similarities effectively. To address this, we fine-tuned an English sentence Transformer by leveraging a word-to-word translation approach and a triplet loss function. Despite using a pre-trained English BERT model and only word-by-word translations without accounting for sentence structure, the results were competitive. This suggests that mean-pooling may weaken attention mechanisms, causing the model to rely more on word embeddings than sentence structure, potentially limiting comprehension of sentence meaning. Together, these streams reveal the complexities of cross-lingual transfer, guiding more effective and equitable use of HRLs to support LRLs in NLP applications.
Open Access
Development of advanced combustion strategies for heavy duty LPG engines to achieve near-diesel efficiency
(Colorado State University. Libraries, 2024) Fosudo, Toluwalase Jude, author; Olsen, Daniel B., advisor; Windom, Bret, committee member; Wise, Dan, committee member; Grigg, Neil, committee member
As the transportation sector evolves in response to increasingly stringent emissions regulations and economic realities in the wake of the decarbonization drive, several no/low carbon fuel options have emerged as viable options for internal combustion engines. Among these fuels, Liquefied Petroleum Gas (LPG) is uniquely positioned for spark ignited engine operation due to its favorable physical and chemical properties. Currently, much of its use as an engine fuel is limited to light-duty applications, dual fuel applications, or retrofitted gasoline engines, with a lesser degree of penetration into the heavy-duty sector where diesel fuel still dominates. A key reason for this is the deficit in performance and efficiency between diesel and other low carbon fuels, including LPG, necessitating the need for targeted research aimed at bridging this gap, and positioning LPG as a fuel of choice in the heavy-duty sector. Two prominent drawbacks responsible for this gap between diesel and LPG engine performance are the dearth of specialized fuel injection hardware and tailored injection strategies, and knock, which limits the performance of spark ignited engines. This work seeks to address these and other limitations and achieve near diesel efficiency on a heavy-duty engine platform. Two engine platforms were employed in this study. A cooperative fuel research (CFR) spark-ignited engine was used to study the knock dynamics and the performance, combustion, and emissions behavior of the LPG fuel in relation to key engine parameters, the LPG fuel composition, and other low carbon fuel options. Compression ratio, engine load, exhaust gas recirculation percents, and a novel combustion control tool, the combustion intensity metric (CIM), were all varied on the CFR engine and a computational fluid dynamics (CFD) model calibrated and validated. Key findings were then transferred to a heavy-duty engine platform, the Cummins ISX15L single cylinder engine. The engine is a converted 6-cylinder diesel engine with diesel brake thermal efficiency (BTE) of 44%. A baseline evaluation was conducted with liquid LPG port-injected at 16bar and 9.3:1 compression ratio. Then the engine was switched to direct injection (DI) configuration with a fuel delivery system capable of delivering liquid LPG at pressures up to 200bar. Three principal configurations were developed for operation of the heavy-duty engine employing a gasoline direct injector (GDI) with nozzle patterns adapted for optimal distribution of the LPG fuel in the combustion chamber, a GDI modified for higher LPG flow and a double-injector port-fuel injection (PFI) system optimized for injection location, and charge cooling and distribution. The experiments and modeling contained in this study demonstrate the impact of LPG composition on engine performance, the mitigating effect of EGR on knock and NOx emissions, the potential for a better controlled combustion using the CIM tool and the advantages in terms of knock, performance, and emissions of designing an injection strategy tailored to the LPG fuel. The results show that the heavy-duty engine operated on LPG achieved the target efficiency of 44% BTE at high EGR, high compression ratio, and high load conditions for both DI and PFI configurations. The outcomes of this study advance the literature on knock, end-gas autoignition, emissions, and EGR related to LPG and its use as a choice fuel for heavy-duty applications and advances the development of specialized fuel delivery hardware and injection strategies for the LPG fuel.
Embargo
Affective Atmospheres: cultural models for interactive narratives
(Colorado State University. Libraries, 2024) Callendar, Chaz L., author; Arthur, Tori, advisor; Champ, Joe, committee member; Humphrey, Mike, committee member; Romagni, Domenica, committee member; Aronis, Carolin, committee member
In this dissertation, I introduce a new model which I call Affective Atmospheres. This theoretical model aids in the understanding of interactive models found in video games by considering video games as systems of affordances. These systems reflect cultural ideology and work together to create emotional structures that players use to co-create narratives in games. These models focus on the emotional and narrative tensions created through gameplay and how players embodying the role structured by the game understand the story through feelings rather than the sequence of events in a story, allowing for the analysis of interactive narratives, like video games, as a text. To showcase Affective Atmosphere, I use Critical Technocultural Discourse analysis to reveal how the expected co-constructions of two video game characters, Sister Friede from Dark Souls 3 and Edelgard from Fire Emblem: Three Houses, transgress patriarchal norms in fantasy video games. This case study showcases how Affective Atmosphere allows a researcher to "read" the interactive affordances of video games as a text and how cultural ideologies are embedded deep within the co-construction of video game experiences.
Open Access
Full-wave and asymptotic computational electromagnetics methods: on their use and implementation in received signal strength, radar-cross-section, and uncertainty quantification predictions
(Colorado State University. Libraries, 2024) Kasdorf, Stephen, author; Notaroš, Branislav M., advisor; Ilić, Milan, committee member; Wilson, Jesse, committee member; Venayagamoorthy, Karan, committee member
We propose and evaluate several improvements to the accuracy of the shooting and bouncing rays (SBR) method for ray-tracing (RT) electromagnetic modeling. A per-ray cone angle calculation is introduced, with the maximum separation angle determined for each individual ray based on local neighbors, allowing the smallest theoretical error in SBR. This enables adaptive ray spawning and provides a unique analysis of the effect of ray cone sizes on accuracy. For conventional uniform angular distribution, we derive an optimal cone angle to further enhance accuracy. Both approaches are integrated with icosahedral ray spawning geometry and a double-counted ray removal technique, which avoids complex ray path searches. The results demonstrate that the advanced SBR method can perform wireless propagation modeling of tunnel environments with accuracy comparable to the image theory RT method, but with much greater efficiency. To further advance the efficiency of the SBR method, we propose a unified parallelization framework leveraging NVIDIA OptiX Prime programming interfaces on graphics processing units (GPUs). The framework achieves comprehensive parallelization of all components of the SBR algorithm, including traditionally sequential tasks like electric field computation and postprocessing. Through optimization of memory usage and GPU resources, the new SBR method achieves upwards of 99% parallelism under Amdahl's scaling law. This innovative parallelization yields dramatic speedups without sacrificing the previously enhanced accuracy of the SBR method, demonstrating an unparalleled level of computational efficiency for large-scale electromagnetic propagation simulations. Finally, we implement and validate several advanced Kriging methodologies for uncertainty quantification (UQ) in computational electromagnetics (CEM). The universal Kriging, Taylor Kriging, and gradient-enhanced Kriging methods are applied to reconstruct probability density functions, offering efficient alternatives to Monte Carlo simulations. We further propose the novel gradient-enhanced Taylor Kriging (GETK) method, which combines the advantages of gradient information and basis functions, yielding superior surrogate function accuracy and faster convergence. Numerical results using higher-order finite-element scattering modeling show that GETK dramatically outperforms other Kriging and non-Kriging methods in UQ problems, accurately predicting the impact of stochastic input parameters, such as material uncertainties, on quantities of interest like radar cross-section.
Open Access
Engineering and scaling cement-based carbon storage systems
(Colorado State University. Libraries, 2024) Winters, Dahl, author; Simske, Steven, advisor; Bradley, Thomas, committee member; Arabi, Mazdak, committee member; Troxell, Wade, committee member; Goemans, Christopher, committee member
This work is a contribution to the body of knowledge surrounding cement-based carbon storage systems, their engineering, and their scaling to meet the requirements of global sustainability in a relevant timeframe. Concrete is the most produced material by weight per year, surpassing water and all biomass we use per year, thus requiring by virtue of its total mass the largest share of total energy produced. Today, it is a source of net greenhouse gas emissions and environmental damage because of our appropriation of natural resources for its use in construction. However, it could serve as our largest land-based engineered sink for such emissions. Such potential is the focus of this work, addressed not only by experiments to improve the engineering of cement-based carbon storage systems, but also by suggested practices to achieve scale for such systems to have a beneficial impact on our economy and environment. The ubiquity of concrete means that cement-based carbon storage can also be ubiquitous, offering continued opportunities for carbon removal and sequestration within built materials. To engineer and scale the world's largest product into its largest engineered carbon sink, this research focuses on the use of biochar and calcium carbonate within structural and non-structural concrete uses, such as tetrapods: structures offering the benefits of reduced sand mining, protections against sea level rise, and enabling cement industry decarbonization. The results demonstrated that 4 wt% biochar with 1.5 wt% CaCO3 can replace cement for carbon storage while maintaining sufficient compressive strength. Along with the use of 30 wt% biochar as aggregate, 100,000 10-tonne tetrapods could sequester 1 million tonnes of CO2. Over a year of global emissions, 40 Gt CO2, could be stored in such stacked tetrapods within a land area smaller than Kuwait, 17,400 km2. Thus, this work contributes to the engineering of systems with industrial significance capable of countering the effects of global warming at meaningful scales.
Embargo
Analysis of municipal water use in urban regions across the contiguous United States
(Colorado State University. Libraries, 2024) Dezfooli, Donya, author; Arabi, Mazdak, advisor; Sharvelle, Sybil, committee member; Carter, Ellison, committee member; Goemans, Christopher G., committee member
Urban water use in the United States faces increasing social and environmental pressures. Challenges such as population growth, urbanization, extreme weather events, and climate change threaten the balance between water supply and demand, jeopardizing access to safe and reliable drinking water for city dwellers. Additionally, the traditional linear "take-make-waste" approach, once common in addressing water-related issues, has proven unsustainable due to its reliance on finite energy and resources. Therefore, it is imperative to shift from this linear model to a more integrated and sustainable approach, known as "One Water". This shift requires a comprehensive understanding of the mechanisms enabling transitions to sustainable and resilient urban water systems, as well as the development of models and methodologies to guide the transition toward net-zero water communities. To achieve this, the dissertation first aims to deepen the understanding of factors influencing transitions towards sustainable urban water management. This is based on a series of expert interviews conducted with different utilities across North America. The qualitative data analysis provides valuable insights into the complex context of urban water management. The results revealed that achieving social and environmental justice is a prominent driver for utilities to initiate their transition, followed by concerns about climate change, water quality impairments, groundwater depletion, and population growth. Further investigations identified several barriers to the One Water transition. These barriers are not merely financial and technical but also stem from a lack of regulatory frameworks, insufficient community support, and institutional obstacles. Therefore, institutional and regulatory solutions are needed more than technological innovations to support this paradigm shift. Our findings also emphasized the importance of cultural change and the necessity of fostering a One Water mindset among stakeholders at all levels. Additionally, feedback from the participants contributed to a more comprehensive and inclusive definition of One Water. Second, a municipal water demand model was developed using the Integrated Urban Water Model (IUWM) to understand urban water use patterns and influencing factors across urban areas within the Contiguous United States (CONUS). Municipal water use data from 99 cities across the U.S. from 2005 to 2017 was used to calibrate and regionalize model parameters for urban regions across the CONUS. The results identified key factors influencing the regionalization of water model parameters, including "July vapor pressure deficit," "number of employees in other services (except public administration)," and "July precipitation." The study reveals that predictive water use and related uncertainty vary across ecohydrological regions within the CONUS. This variation is significantly influenced by climatic and socio-economic factors, with arid and southern cities showing the highest uncertainty. While densely populated areas exhibit more predictable patterns, small cities demonstrate the highest level of uncertainty in water use projections, primarily due to a higher share of single-family homes and increased outdoor water consumption compared to larger cities. Third, the developed IUWM model was used to estimate municipal water demand across urban areas within the CONUS for the period of 2035-2065 under different future climate and land use scenarios. The results indicated that population growth and land use change are primary drivers of urban water demand. While there are minor annual fluctuations reflecting the effects of different climate scenarios, the hot climate model presents the worst-case scenario, with the lowest reduction in water use intensity and the highest increase in water demand. In this scenario, the average water use demand is projected to increase by 52%, while the average water use intensity (ML/sq.km) will fall by 10%. The projected changes in water use are highly variable across the CONUS, with significant increases expected in urban areas located in the West and Northwest (e.g., Washington and California), Southwest (e.g., Arizona, Utah, Colorado, and New Mexico), Midwest (e.g., Michigan and Wisconsin), and Great Lakes region (e.g., New York and Pennsylvania). Our findings suggest that projections of future municipal water demand are surrounded by considerable uncertainties, particularly in cities located in arid and tropical regions. Furthermore, the results show that while increased urban density typically reduces water use intensity in most areas, increases are expected in parts of the Midwest, Northeast, and West. These trends suggest that once cities reach certain development thresholds (around 50% developed area), densification may no longer effectively reduce municipal water demand, leading to increased indoor and CII (commercial, industrial, and institutional) water consumption, thereby undermining the expected benefits. This highlights the need for effective mitigation strategies, such as demand management and the use of alternative water sources, alongside higher-density development policies to ensure sustainable urban water management in the future. Overall, this dissertation provides a comprehensive understanding of urban water demand in the United States, aiming to achieve sustainable urban water management. The insights gained from this study highlight the importance of integrating land use and water management and fostering collaboration among all stakeholders to achieve the One Water paradigm shift. The results will benefit urban planners and water managers, helping them develop effective strategies to mitigate adverse effects and ensure sustainable water resources for the future.
Open Access
Unresolved homicide: a cross-national perspective
(Colorado State University. Libraries, 2024) Greenwood, Ian Daniel, author; Unnithan, N. Prabha, advisor; Hogan, Michael, committee member; Mao, KuoRay, committee member; Snodgrass, Jeffrey, committee member
Administrative justice research seeks to understand both the intended and unintended consequences of social action, institutional outcomes, and resulting sociological meanings. The study of homicide informs social science of one set of phenomena, while investigating unresolved victimization provides a contrasting framework of analysis. Unsolved or cold case homicides represent both terrible acts of harm and indicators of some deficiency in the ability of law enforcement to adequately respond. This dissertation expands on the current understanding of unresolved homicide by conducting a cross-national comparison of outcomes. Beginning with a framework for understanding homicide, an analysis of unresolved homicide as a unique outcome is examined from a hierarchical theoretical perspective. This research proposes that there are linkages across social strata of macro governance, meso law enforcement institutions, and micro direct-contact predatory violations that display distinct patterns at an international level. This dissertation investigates the macro and meso Weberian (1947) bureaucratic structures that engages a micro Routine Activities Theory (Cohen and Felson 1979) process of post-homicide administrative justice outcomes. The research is informed by a combination of recommendations from prior literature, as well as introducing new techniques for measuring complex data. Utilizing information from the United Nations, World Bank, the Varieties of Democracy dataset from the Department of Political Sciences at the University of Gothenburg, Sweden, and relevant secondary sources, a multiple step process analyzes thirteen hypotheses. This includes verification of the constructed dataset, the replication of prior studies, and the implementation of speculative exploratory abductive research (i.e., inferential observational testing). Moving from the bivariate correlations of homicide to measures of formal contact by the police, to judicial convictions for homicide, 100 nations are compared across two sets of predictive independent variables through a process of multiple linear regression analyses. The first set of predictive independent variables tests are for macro level societal indicators, while the second set examines aspects of meso to micro interactions that affect opportunities for offending and victimization. The findings support the validity of the dataset, achieve replication of prior cross-national homicide research, and from this a speculative unresolved homicide proxy measure is constructed. Deriving from the difference between the number of reported homicides and the reported number of formal contact police events in a country for a given year, a speculative examination of outcomes is conducted. Further exploration of the unique patterns identified by the unresolved homicide proxy measures are tested to provide further opportunities for theoretical explication. Most of the hypotheses support past findings for homicide rates in producing patterns of correlations and significant predictive relationships. Mixed results from subsequent analyses contribute to a broader understanding of cross-national homicide and unresolved homicide events in context to macro and meso level social indicators. Measures of social inequality, economic development, civil unrest, impartial enforcement of the law, fairness of public administration, and equity of available public services contribute to the understanding of cross–national patterns affecting unresolved homicide rates.
Open Access
Investigating the adaptive genetic landscape of global crop species
(Colorado State University. Libraries, 2024) Hein, Kirsten Marie, author; McKay, John, advisor; Morris, Geoffrey, committee member; Ross-Ibarra, Jeffrey, committee member; Schipanski, Meagan, committee member
Improving environmental adaptation in crops is essential for sustaining food security in the face of global climate change. Recent advances in high-throughput genomic sequencing and phenotyping technologies have enabled researchers to identify and validate the genetic factors shaping adaptation. In this dissertation, I investigated the genetic basis of environmental adaptation in global cereal crops, focusing on the staple crop, maize (Zea mays L.), and the orphan crop, tef (Eragrostis tef Zucc.). In Chapter 2, I employed a landscape genomics approach to identify the genetic and environmental drivers of adaptation in a georeferenced collection of Ethiopian tef. In Chapter 3, I utilized both forward and reverse genetic approaches to evaluate the precision of phenotype-genotype mapping across multiple phenotyping methods for quantifying root system architecture in field-excavated maize. In Chapter 4, I applied a functional genetics approach to characterize a novel gene model in maize predicted to regulate root system development and nitrogen capture under field conditions. Collectively, this work provides valuable insights into the complex relationships between phenotype, genotype, and environment, contributing to our understanding of adaptation in two distinct and vital crop systems.

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