Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Quantifying robustness of the gap gene network(Montana State University - Bozeman, College of Letters & Science, 2024) Andreas, Elizabeth Anne; Chairperson, Graduate Committee: Tomas Gedeon; Bree Cummins (co-chair)Early development of Drosophila melanogaster (fruit fly) facilitated by the gap gene network has been shown to be incredibly robust, and the same patterns emerge even when the process is seriously disrupted. We investigate this robustness using a previously developed computational framework called DSGRN (Dynamic Signatures Generated by Regulatory Networks). Our mathematical innovations include the conceptual extension of this established modeling technique to enable modeling of spatially monotone environmental effects, as well as the development of a collection of graph theoretic robustness scores for network models. This allows us to rank order the robustness of network models of cellular systems where each cell contains the same genetic network topology but operates under a parameter regime that changes continuously from cell to cell. We demonstrate the power of this method by comparing the robustness of two previously introduced network models of gap gene expression along the anterior-posterior axis of the fruit fly embryo, both to each other and to a random sample of networks with same number of nodes and edges. We observe that there is a substantial difference in robustness scores between the two models. Our biological insight is that random network topologies are in general capable of reproducing complex patterns of expression, but that using measures of robustness to rank order networks permits a large reduction in hypothesis space for highly conserved systems such as developmental networks.Item Numerical simulation of rock ramp fishway for small-bodied Great Plains fishes(Montana State University - Bozeman, College of Engineering, 2023) Ufelle, Cindy Chidumebi; Chairperson, Graduate Committee: Kathryn PlymesserThe preservation and restoration of fish populations and their habitats have become significant aspects of environmental conservation efforts. Effectiveness of fish passage structures plays a crucial role in facilitating the successful migration of various fish species. This research focused on utilizing Computational Fluid Dynamics (CFD) models to assess the hydraulic conditions within a rock ramp fishway with varying slopes and flow rates for small-bodied Great Plains fishes. This work built upon a previous study conducted by Swarr (2018) to investigate the passage success rates of three small-bodied fish of the Great Plains of North America: Flathead Chub (Platygobio gracilis), Arkansas Darter (Etheostoma cragini), and Stonecat (Noturus flavus) within a full-scale laboratory rock ramp fishway. Using commercial software, Flow-3D Hydro, CFD models were developed to simulate and predict hydraulic parameters such as flow depths, velocities, and turbulence kinetic energies (TKEs) within the fishway. To validate the accuracy of the CFD models, predicted flow depths and velocities were compared with observed data for two slopes: 2% and 10%. The CFD model results indicated that increasing slopes and flow rates led to corresponding increases in the mean values of the studied parameters. The mean depth varied from 0.051 m on the 2% slope to 0.068 m on the 10% slope. The mean velocity increased from 0.272 m/s on the mildest slope to 1.003 m/s on the steepest slope. Additionally, the average TKE ranged from 0.003 J/kg on the 2% slope to 0.014 J/kg on the 10% slope. The study highlighted that higher velocity and TKE values at steeper slopes may have contributed to the poor upstream passage rate, particularly for weaker swimmer species, like the Arkansas Darter, at slopes greater than 4%, as observed in the physical model study. Findings demonstrated that the presence of rocks in the fishway created diverse flow conditions. Low-velocity zones observed behind rocks within the fishway may provide favorable conditions for successful fish ascent. This research showcases the capabilities of CFD in providing quantitative data for optimizing fish passage structure design and contributing to conservation efforts.Item Modeling saline fluid flow in subglacial ice-walled channels(Montana State University - Bozeman, College of Letters & Science, 2022) Jenson, Amy Jo; Chairperson, Graduate Committee: Scott McCallaSubglacial hydrological systems have impacts on ice dynamics as well as nutrient and sediment transport. There has been an extensive effort to understand the dynamics of subglacial drainage through numerical modeling, however these models have focused on freshwater, neglecting the consideration of brine. Saline fluid can exist in cold-based glacier systems where freshwater cannot. Therefore, there exist subglacial hydrological systems where the only fluid is brine. Understanding the routing of saline fluid is important for understanding geochemical and microbiological processes in these saline cryospheric habitats. In this thesis, I present a model of channelized drainage from a hypersaline subglacial lake and highlight the impact of saline fluid on melt rates in an ice-walled channel. The model results show that channel walls grow more quickly when fluid contains higher salt concentrations, which results in greater peak discharge and faster drainage for a fixed lake volume. This model provides a framework to assess the relative impact of brine on discharge and drainage duration.Item Analysis of dynamic biological systems imagery(Montana State University - Bozeman, College of Letters & Science, 2022) Dudiak, Cameron Drew; Chairperson, Graduate Committee: Scott McCallaBiological systems pose considerable challenges when attempting to isolate experimental variables of interest and obtain viable data. Developments in image analysis algorithms and techniques allow for further mathematical interpretation, model integration, and even model optimization ('training'). We formulate two distinct methods for obtaining robust quantitative data from time-series imagery of two biological systems: Paenibacillus dendritiformis bacterial colonies, and human gastric organoids. Boundary parameterizations of P. dendritiformis are extracted from timelapse image sequences displaying colony repulsion, and are subsequently used to 'train' a previously developed nonlocal PDE model through the means of error minimization between observation and simulation. Particle tracking is conducted for small colloidal beads embedded within human gastric organoids, and then used to perform particle tracking analysis. This information is analyzed to quantify the local complex viscoelastic properties of organoids' interior mucosal environment.Item Development and characterization of a novel isothermal DNA amplification reaction(Montana State University - Bozeman, College of Engineering, 2021) Ozay, Burcu; Chairperson, Graduate Committee: Scott McCalla; This is a manuscript style paper that includes co-authored chapters.Isothermal nucleic acid amplification chemistries are gaining popularity as nucleic acid detection tools that can replace the current gold standard methods, PCR and its derivatives, with their simplicity, speed and applicability to point-of-care applications. In this work, we have developed and characterized a novel isothermal amplification chemistry, ultrasensitive DNA amplification reaction (UDAR). UDAR differs from similar chemistries with its unique, biphasic response with a high-gain output that can be captured with a cell-phone camera. The switch-like, nonlinear characteristics provide a definitive on/off signal for potential use in applications such as molecular diagnostics and DNA circuits. Tunability of the reaction was explored and the relationship between thermodynamic properties of the reaction templates and the reaction output was established. Limitations on fluorescent staining of reaction components by two popular commercial nucleic acid stains, SYBR Green II and SYBR Gold, were determined for a more accurate evaluation of the reaction output and reaction product analysis. A mathematical model of the reaction output was built and outputs from three different UDAR templates were successfully simulated. This model revealed important information on reaction pathways and helped identify the impact of individual reaction events. A comprehensive literature review of enhancement strategies for isothermal amplification reactions was conducted to serve as a guide to improve and modify these reactions according to different needs and applications. Lastly, UDAR was applied to microRNA detection, which are putative biomarkers for diseases such as cancer, malaria, and traumatic brain injury. Five different miRNAs were successfully detected by UDAR, down to 10 fM concentration. UDAR-based miRNA quantification is possible, with linear calibration curves provided between 10fM and 1 nM. This work has significant contributions to the growing field of isothermal nucleic acid amplification based-molecular detection systems by introducing a unique isothermal amplification chemistry, establishing design and manipulation techniques, and guiding improvement efforts of these technologies.Item The rise of caldera forming eruptions: refining tools for understanding magma ascent(Montana State University - Bozeman, College of Letters & Science, 2022) Harris, Megan Ann; Chairperson, Graduate Committee: Madison Myers; This is a manuscript style paper that includes co-authored chapters.The rate at which magma moves from the magma chamber to the surface influences the amount of degassing and crystallization that occurs, which in turn controls the style and intensity of the ensuing eruption. Thus, our understanding of magma ascent rates is crucial to understanding and mitigating future volcanic hazards. The bulk of this dissertation revolves around using the diffusion of water through melt-filled pockets (embayments) in quartz crystals as an ascent speedometer, coupled with geochemical and textural analysis of co-erupted material. In Chapter Two, I apply and refine the water diffusion speedometer to establish timescales of ascent for the two eruptions that formed the modern-day Valles Caldera, with the aim of understanding whether these rates change during subsequent eruptions from the same caldera. In Chapter Three, I apply the diffusion speedometer to the opening behavior of the 1991 eruption of Mount. Pinatubo and compare the results to ascent rates obtained using independent petrologic methods (bubble number density and microlite number density). This chapter seeks to reconcile the several orders of magnitude offset in ascent rates produced by various geospeedometers. Finally, in Chapter Four, I explore the mechanisms by which embayments are formed in magmatic systems. I do this by conducting a survey of cathodoluminescence images of crystals taken from five volcanic systems to determine how the embayments interact with the internal zoning of the crystal. I then attempt to form embayments experimentally using a cold-seal pressure vessel under variable magmatic conditions. The culmination of this work emphasizes that embayments are robust and faithful recorders of a magma's journey from its source to the surface and may be a critical piece of evidence for unraveling the magmatic history leading to eruption. This dissertation includes both previously published and unpublished co-authored work.Item Preservice teachers' construction of computational thinking practices through mathematical modeling activities(Montana State University - Bozeman, College of Letters & Science, 2022) Adeolu, Adewale Samson; Chairperson, Graduate Committee: Mary Alice Carlson and Elizabeth Burroughs (co-chair)The importance of learning computational thinking practices in K-12 settings is gaining momentum in the United States and worldwide. As a result, studies have been conducted on integrating these practices in mathematics teaching and learning. However, there is little study that focuses on how to prepare pre-service teachers who will teach the practices in K-12 settings. I investigated how pre-service teachers collaborated to develop computational thinking practices when working on modeling activities with computational tools. To carry out this research, I studied nine pre-service teachers working on modeling tasks for a semester. Five participants recorded their screens and were invited to participate in a stimulated recall interview. Using the interactional analysis procedures, findings showed that the presence of computational tools influenced the positioning (leadership and distributed authority) and collaborative processes (dividing and offloading labor, giving and receiving feedback, accommodation, and refining ideas) pre-service teachers used during modeling. This study found that pre-service teachers used ten computational thinking practices, which are sub-grouped into four broader practices -- data practices, mimicking and mathematizing, model exploration and extension, and model communication. This dissertation also found that pre-service teachers' mathematical knowledge and their ability to code were interdependent. From a research point of view, this study extends our knowledge of the social constructivist theory of doing research in the context of pre-service teachers engaging in modeling activities with computational tools. From the teacher education perspective, this study emphasizes the need to consider the impact of computational tools on the interactions of pre-service teachers during modeling. The study also reveals the need to structure the mathematical modeling curriculum to lead to a better learning experience for pre-service teachers.Item Numerical modelling of nanoparticle diffusion and microstructure formation during selective laser melting process(Montana State University - Bozeman, College of Engineering, 2022) Alam, Taosif; Chairperson, Graduate Committee: M. Ruhul AminSelective laser melting (SLM) is a popular metal additive manufacturing technique that has a wide range of industrial applications lately. This additive process allows the development of new metal matrix nanocomposites by fusing metallic powders with nanoparticles. However, the molten pool flow generated by a moving laser heat source has complex fluid dynamics which redistribute the nanoparticles. Consequently, the microstructures of the solidified molten pool are affected by the local distribution of nanoparticles, which is reflected in their mechanical properties. Smaller grains can increase the strength and isotropic behavior of the solid layers. Therefore, the current research aims to numerically investigate the relationships among the SLM process parameters, nanoparticle transport, and microstructure evolution to explore the formation of nanocomposites. The current study formulated a three-dimensional computational fluid dynamics (CFD) model of the SLM process in a commercial software package, ANSYS FLUENT. A volumetric laser heat source model melted the aluminum alloy powders and the underlying solid substrate. The difference between the powder and the solid or liquid state of the metal alloy was defined using an effective thermal conductivity model. Lagrangian particle transport calculation was performed to track TiB 2 nanoparticles in the molten pool. This model was coupled with a 2D Cellular Automata (CA) model to simulate the solidified microstructure using MATLAB. Finally, a detailed parametric analysis was conducted to study the effects of varying laser power, scanning speed, and preheating temperature. The numerical results showed that the maximum temperature and Marangoni convection in the molten pool increased at higher laser powers, higher preheating temperatures, and lower scanning speeds. The particle-voided region was significantly large with high Marangoni convection but decreased with weaker Marangoni convection. The simulated microstructure was dominated by large columnar grains when nanoparticles were not considered. The introduction of nanoparticles disrupted the columnar grain growth by promoting small, randomly oriented, equiaxed grains. A decrease of 30%-40% in average grain diameter was measured at the cross-section of the solidified layer when nanoparticles were present. The qualitative comparison of the microstructures showed that the grains were smaller in the uniformly distributed particle region compared to the particle-voided region.Item Bayesian hierarchical latent variable models for ecological data types(Montana State University - Bozeman, College of Letters & Science, 2022) Stratton, Christian Alexander; Chairperson, Graduate Committee: Jennifer Green and Andrew Hoegh (co-chair); This is a manuscript style paper that includes co-authored chapters.Ecologists and environmental scientists employ increasingly complicated sampling designs to address research questions that can help explain the impacts of climate change, disease, and other emerging threats. To understand these impacts, statistical methodology must be developed to address the nuance of the sampling design and provide inferences about the quantities of interest; this methodology must also be accessible and easily implemented by scientists. Recently, hierarchical latent variable modeling has emerged as a comprehensive framework for modeling a variety of ecological data types. In this dissertation, we discuss hierarchical modeling of multi-scale occupancy data and multi-species abundance data. Within the multi-scale occupancy framework, we propose new methodology to improve computational performance of existing modeling approaches, resulting in a 98% decrease in computation time. This methodology is implemented in an R package developed to encourage community uptake of our method. Additionally, we propose a new modeling framework capable of simultaneous clustering and ordination of ecological abundance data that allows for estimation of the number of clusters present in the latent ordination space. This modeling framework is also extended to accommodate hierarchical sampling designs. The proposed modeling framework is applied to two data sets and code to fit our model is provided. The software and statistical methodology proposed in this dissertation illustrate the flexibility of hierarchical latent variable modeling to accommodate a variety of data types.Item Analysis of transport in the brain(Montana State University - Bozeman, College of Engineering, 2021) Ray, Lori Ann; Chairperson, Graduate Committee: Jeffrey Heys; Jeffrey J. Heys was a co-author of the article, 'Fluid flow and mass transport in brain tissue: a literature review' in the journal 'Fluids' which is contained within this dissertation.; Jeffrey J. Iliff and Jeffrey J. Heys were co-authors of the article, 'Analysis of convective and diffusive transport in the brain interstitium' in the journal 'Fluids and barriers of the CNS' which is contained within this dissertation.; Martin Pike, Jeffrey J. Iliff and Jeffrey J. Heys were co-authors of the article, 'Quantification of transport in the whole mouse brain' which is contained within this dissertation.Neurodegeneration is one of the most significant medical challenges facing our time, yet the gap between therapies and understanding of the inner workings of the brain is great. Impairment of waste clearance has been identified as one key underlying factor in the vulnerability of the brain to neurodegeneration, stimulating research towards understanding transport of molecules in the brain. Based on experimental findings, a unique-to-the-brain circulation has been proposed, the glymphatic system, where cerebrospinal fluid surrounding the brain moves into the brain along the periarterial space that surrounds cerebral arteries, flows through the interstitial space between brain cells, where cellular wastes reside, and carries waste out of the brain tissue along perivenous routes. However, current gaps in knowledge about the driving force for fluid flow have generated scientific skepticism, and an independent method for quantifying transport and demonstrating the presence or absence of convection is desirable. In this work, computational transport models are developed and used to analyze published experimental data to determine fundamental transport parameters for different aspects of the glymphatic circulation. Calculated transport parameters are compared to the known diffusivity of tracers through brain tissue to draw conclusions about the presence and significance of bulk flow, or convection. Based on these analyses, transport in the periarterial spaces surrounding major arteries is over 10,000 times faster than diffusion and in brain tissue, containing both periarterial and interstitial space, transport is around 10 times faster than diffusion alone (for characteristic transport lengths around 1 mm). Interstitial velocity is determined to be on the order of 0.01 mm/min, making convection in the interstitial spaces of the brain critical to the transport of large, slow-to-diffuse molecules implicated in neurodegeneration. Convection is demonstrated to be a significant mechanism of transport throughout the brain. Observations and analyses from this work contribute further evidence to a circulatory-like system in the brain with relatively rapid convection along periarterial space, branching throughout the brain tissue and slower convection across that tissue, in the interstitial spaces of the brain. Transport models developed in this work are demonstrated to be useful tools for gleaning further information from experimental data.