Mountain Scholar (Digital Collections of Colorado and Wyoming)
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Numerical solution of the Black-Scholes equation using finite element methods
Full text link2023 Spring.Includes bibliographical references.The Black-Scholes model is a well known model for pricing financial options. This model takes the form of a partial differential equation (PDE) that, surprisingly, is deterministic. In the special case where the option only has one single underlying asset, what is called the one dimensional version of the Black-Scholes model, there exists an analytical solution. In higher dimensions, however, there is no such analytical solution. This higher dimensional version refers to what is called a Basket-Case Option. This means that to get a solution to this Basket-Case Option PDE, one must employ numerical methods. This thesis will first discuss the stochastic calculus theory necessary to derive the Black-Scholes model, then will explain in detail the time and space discretization used to solve the PDE using a Finite Element Method (FEM). Finally, this thesis will explain some of the results and convergence of this numerical solution
An examination of Middle Woodland pre-mound contexts in the Ohio and southeast regions
Full text link2023 Spring.Includes bibliographical references.Mounds are one of the oldest forms of monumental architecture in North America and have been the fascination of archaeologists and antiquarians for centuries due to their large scale and association with intricate craft goods. However, much research into mounds has focused on their use as repositories for human remains or as potential platforms for elite housing and other architecture. This is true of the Hopewell archaeological culture of the Middle Woodland period, 300 BCE-500 CE, which has been the focus of archaeological inquiry due to its large ceremonial sites and material network of items coming to the Midwest and Southeast from as far as the Rocky Mountains or the Gulf Coast. Using legacy data for 13 sites throughout Ohio and the Southeast, I examine variability in pre-mound contexts to expand on mound research by focusing on this pre-natal stage which represents the activities that people conducted before the construction of the monument itself. Using a binary model of presences and absences, I look at 26 pre-mound attributes found across the 13 sites and 64 mounds in the study and use multivariate analysis in ArcGIS as an exploratory and pattern revealing tool. I argue that these contexts are incredibly varied, and that this lack of homogeneity is material evidence of the decisions made by people to overcome dissonance created by encountering varying cultural values for these important ritual events as well as evidence for a lack of a clear Hopewell model in either the Ohio and Southeast regions, instead arguing that both regions should be included in the larger discussion of Middle Woodland ceremonialism and exchange, rejecting a core and periphery model
Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets
No full textIncludes bibliographical references.2023 Spring.This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors
Resolvin D1 modulates the pulmonary immune response to agriculture dust exposure
Full text link2023 Spring.Includes bibliographical references.Occupational exposure to agriculture dust causes a variety of acute and chronic pulmonary diseases including allergies, asthma, chronic obstructive pulmonary disease (COPD) and organic dust toxic syndrome (ODTS). These diseases have high impact on the healthcare system and limited treatments with variable efficacy. In addition, workers often display low compliance with required workplace personal protective equipment (PPE), increasing their risk for developing these diseases. Therefore, the development of new pharmacological interventions is critical to alleviate the burden on the healthcare system and improve the quality of life for patients who will inevitably develop occupational-related pulmonary diseases. Interleukin-22 (IL-22) is a cytokine in the anti-inflammatory interleukin-10 (IL-10) family of cytokines that has demonstrated a protective role in murine models of acute and chronic lung injury. It has been described as being exclusively produced by lymphocytes, however methodological limitations of the primary cited study restricted the exploration of other cell types as producers of IL-22. Upregulation of this cytokine by pharmacological means could prove beneficial for delaying the progression of occupational chronic pulmonary diseases. Omega-3 fatty acids and their metabolites have well-documented anti-inflammatory and pro-resolution functions in chronic pulmonary diseases and have been implicated in the induction of IL-22. Omega-3 fatty acids have shown overwhelming evidence in being anti-inflammatory by their function as substrates for the production of specialized pro-resolving mediators (SPMs), lipid metabolites that signal immune cells to transition to a resolution and repair state following inflammation. Resolvin D1 (RvD1), a metabolite of the omega-3 fatty acid docosahexaenoic acid (DHA), has shown to have anti-inflammatory and protective functions in a murine acute lung injury model. To evaluate the source of IL-22 in the pulmonary response to agricultural dust, mouse alveolar macrophages were co-exposed to 1% hog dust extract (DE) collected from swine confinement facilities in the Midwest US and treated with either 10 nM or 100 nM RvD1. Cells were incubated for up to 24 hours, supernate was collected at the desired timepoint, and enzyme-linked immunosorbent assays (ELISAs) were performed to assess protein expression. Cells were also lysed to determine intracellular IL-22 protein concentrations. Cells exposed to DE exhibited increased pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) as well as increased IL-10 and IL-22 production, demonstrating macrophages as a source of IL-22 in the immune response to organic dust. Cells exposed to DE and treated with RvD1 demonstrated significant decreases in IL-6 and TNF-α and increases in IL-10. To determine the efficacy of RvD1 as an inducer of IL-22, and as a potential treatment for organic dust-induced lung injury, C57BL/6 (WT) and full-body IL-22 knock-out (KO) mice were intranasally instilled (IN) with 12.5% DE 5 days/week for 3 weeks and injected intraperitoneally (IP) with 250 ng RvD1 once per week. Animals were allowed to recover for 5 hours or 3 days before sacrifice where bronchoalveolar lavage fluid (BALF) was collected for cytokine and cellular infiltrate evaluation to determine the role of RvD1 in the reduction of the immune response to organic dust exposure. BALF cytokines exhibited significant increases in the production of IL-10 in KO mice exposed to DE and treated with RvD1 with a 3-day recovery. Cellular infiltrates demonstrated decreased neutrophil infiltration and increased lymphocyte recruitment in KO mice exposed to DE after a 3-day recovery and further significant decreases in mice treated with RvD1 with a 3 day recovery. The data support the production of IL-22 by alveolar macrophages and its induction by RvD1. They also demonstrate the effects of RvD1 on the pulmonary immune response to agriculture dust and as a potential therapeutic for organic dust-induced chronic pulmonary diseases
Development of a liquid argon purity monitoring system
Full text link2023 Spring.Includes bibliographical references.Liquid argon time-projection chambers (LArTPCs) are used to detect charged particles and measure their properties. Charged particles that pass through the liquid argon (LAr) in a LArTPC ionize and excite argon atoms, producing ionization electrons and prompt scintillation light. The ionization electrons drift through the LAr volume in a uniform electric field and produce a signal at the anode. The scintillation light is used to determine the drift coordinate of an event, which allows for 3D reconstruction of tracks and interactions. Electro-negative impurities lead to the reduction of the ionization electrons and scintillation light. They worsen a detector's ability to perform event reconstruction by reducing the signal-to-noise ratios. A purity monitor is a device that is often used alongside LArTPCs to monitor the LAr purity. It extracts electrons from a photo-cathode via the photoelectric effect and drifts them through LAr to an anode using an electric field. When traversing the purity monitor, some of the electrons will be lost due to impurities along the way. As a result, the drift-electron lifetime, which is related to the LAr impurity concentration, can be determined by measuring the difference in charge between the cathode and anode. This method allows for continuous purity monitoring of the LAr used in a LArTPC. This thesis describes the development and testing of a purity monitoring system that is used in conjunction with a LArTPC at Colorado State University
Beyond the case study: characterizing natural floodplain heterogeneity in the United States
Full text linkIncludes bibliographical references.2023 Spring.With human degradation of natural river corridors, the number of natural, functional floodplains is rapidly decreasing due to dams, diversions, artificial levees, draining, development, agriculture, and invasive species. At the same time, small- to large-scale interest in and implementation of river restoration is expanding, with floodplain restoration soon to take a starring role. To properly manage and restore processes to floodplains, we first need a broad understanding of what they look like and why. A key component of natural river-floodplain systems is heterogeneity, defined as the spatial variation of geomorphic and vegetation classes and patches across a floodplain. Heterogeneity of floodplains both reflects and influences the fluvial processes acting on floodplains and can help shape our understanding of the form and function of floodplains. To begin characterizing floodplain spatial heterogeneity, I present in this dissertation: 1) the development of a method to combine field measurements and remote sensing data products to calculate integrative landscape-scale metrics of floodplain spatial heterogeneity, and the demonstration of which metrics from landscape ecology are likely to be useful for identifying qualities of natural floodplains at four case study sites; 2) a sensitivity analysis to determine whether and how the values of the heterogeneity metrics change when spatial and spectral resolution of the input data are increased, and the extraction of underlying data from the classification results to determine whether using higher resolution data allows identification of the resulting unsupervised classes in relation to field and remote data at four case study sites; and 3) quantification of floodplain spatial heterogeneity, evaluation of whether statistically significant patterns are present, and interpretation of the statistical analyses with respect to the influence of channel lateral mobility and valley-floor space available using a complete dataset of 15 sites representing diverse floodplains across the continental United States. I found that "stacking" Sentinel-2A multispectral satellite imagery and digital elevation model topographic data allows for unsupervised classification of floodplains, and that metrics from landscape ecology can differentiate between different floodplain types. I also found via a sensitivity analysis that increasing the spatial resolution of the topographic data to finer than 10 m and including band ratios related to vegetation improves the classification results. Comparison of the field classes with the remote sensing classes allows for general interpretation of the results, but it is the heterogeneity within the broad classes that I expect is most important to these ecosystems. Lastly, through classification of 15 diverse river corridors across the United States, calculation of five heterogeneity metrics, and completion of a comparative analysis, I found that these natural floodplains have moderate aggregation of classes (median aggregation index = 58.8%), high evenness (median Shannon's evenness index = 0.934) and intermixing of classes (median interspersion and juxtaposition index = 74.9%), and a wide range of patch densities (range of patch density = 491–1866 patches/100 ha). I also found that the river corridor characteristics of drainage area, floodplain width ratio (space available), and elevation, precipitation, total sinuosity, large wood volume, planform, and flow regime (channel mobility) emerge as important variables to understanding floodplain heterogeneity
Familiarity-detection from different facial feature-types: is the whole greater than the sum of its parts?
Full text link2023 Spring.Includes bibliographical references.Prior research indicates that perceived familiarity with a cue during cued recall failure can be systematically increased based on the amount of feature overlap between that cue and studied items in memory (Huebert et al., 2022; McNeely-White et al., 2021, Ryals & Cleary, 2012). However, these studies used word or musical stimuli. Faces represent a special class of stimuli, as evidence suggests that unlike other types of stimuli (such as word or musical stimuli), faces may be primarily processed in a holistic fashion. A recent study demonstrated that even when a person's identity was prevented by the presence of a facial occlusion like a surgical mask or sunglasses, familiarity-detection with the occluded face could still occur, suggesting that holistic processing was not a requirement for facial familiarity-detection (Carlaw et al., 2022). However, some researchers have suggested that although faces can be decomposed into component parts when partially occluded, when faces are presented unoccluded in their entirety, the holistic face processing system may then be obligatory (Manley et al., 2019). The present study suggests that this is not the case. Isolating specific feature types at encoding through partial occlusion of faces at study (via a surgical mask or sunglasses), then embedding those familiarized feature sets in otherwise novel whole faces at test, systematically and combinedly increased the perceived familiarity of the otherwise novel whole faces. These results suggest that even whole faces are processed as sets of component parts
