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Item From Surviving to Thriving: A Trauma-Informed Yoga Intervention for Adolescents and Educators in Rural Montana(MDPI AG, 2024-12) Davis, Lauren; Scott, Brandon G.; Linse, Greta M.; Buchanan, Rebecca(1) Background: Due to the mental health crisis that has spiraled since the onset of COVID-19, particularly among the nation’s youth, the purpose of this study was to examine the efficacy of a novel, school-based mental health intervention for high school students (ages 15–17 years). This project’s main aim was to determine which intervention modality was more effective with students across two school districts with varying degrees of rurality (in-person delivery vs. remote delivery). A secondary aim of this study was to determine the efficacy of a remotely delivered, concurrent intervention for educators across both school districts. This study took place in rural southwestern Montana. (2) Methods: Utilizing a 6-week, trauma-informed yoga intervention, comparisons of mental and physical health outcomes were performed using cohort data drawn from participants’ physiological data and validated mental health survey measures. (3) Results: While physiological results were mixed across experimental groups, mental health outcomes were overwhelmingly positive for all groups. Additionally, educators reported improvements in career satisfaction and burnout levels. (4) Conclusions: Findings indicate a great deal of promise with this intervention in improving mental health outcomes for both students and educators. Moreover, a face-to-face intervention for students showed dramatic improvement in physiological stress indicators.Item Determinants of crop diversification and its impact on farmers' income: A case study in Rangpur District, Bangladesh(Wiley, 2024-09) Islam, Md Sayemul; Jahan, Hasneen; Ema, Nishat Sultana; Ahmed, Md RubelBackground. In the face of rising global food demand, climate change, and economic uncertainties, crop diversification has emerged as a crucial tool for achieving both economic and environmental sustainability. In Bangladesh, where the economy heavily relies on agriculture, crop diversification can play a vital role in enhancing farmers' livelihoods and domestic food production. Results. This study focuses on Rangpur district, an agricultural hub in Bangladesh, analyzing data from 122 farmers to assess the status, determinants, and effects of crop diversification. The Simpson Diversification Index (SDI) analysis revealed that 29% and 68% of the farmers exhibit very high and high degrees of crop diversification, respectively. The Tobit model identified significant drivers of crop diversification, including education, household size, farming experience, non-farm income, mobile phone information access, experience with climatic shocks, and land type. Additionally, the Log-Linear model indicated that each unit increase in the SDI score corresponds to a 2.41% increase in farmers' income. Conclusion. The study demonstrates that crop diversification is a key strategy for enhancing economic sustainability and increasing income among farmers in Bangladesh. By improving both economic outcomes and resilience, crop diversification supports sustainable agricultural practices in the region.Item Of teachers and centaurs: Exploring the interactions and intra-actions of educators on AI education platforms(Informa UK Limited, 2024-12) Fassbender, William J.Recent advancements in generative Artificial Intelligence (GenAI) were accompanied by both hype and fear regarding the ways in which such technologies of automation would replace human labor in various fields, including education. Rather than focusing on the replacement of humans in teaching, this piece uses new materialist thought [Barad, Karen. 2007. Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning. Durham, NC: Duke University Press.] to consider how a new subjectivity, the centaur, might offer a different orientation toward GenAI technologies as tools that possess potentiality for new becomings in teaching. This theoretical piece looks at three AI education (AIED) platforms as a means of diagnosing how current models of AI tools attempt to design for teacher-centaurs by ushering in a more productive teacher workforce. The article also offers an alternative perspective of what might be considered centaur teaching practices, entangling humans and AI in ways that imagine how human-technical relations might be otherwise.Item Investigating the benefits of viewing nature for components of working memory capacity(Elsevier BV, 2024-09) Charbonneau, Brooke Z.; Watson, Jason M.; Hutchison, Keith A.Prior work regarding nature's benefits to different working memory capacity processes is mixed within the existing literature. These mixed results may be due to an emphasis on tasks rather than focusing on construct validity and the underlying mental processes they are intended to measure. When considering underlying process, all might be sensitive to the benefits of nature or perhaps only specific processes of working memory capacity will receive these benefits. Attention Restoration Theory (Kaplan, 1995) would specifically predict that attentional control is the most likely process to benefit from interacting with nature. To address this possibility, three studies investigated whether working memory capacity and its component processes of attentional control, primary memory, and secondary memory benefit from viewing nature images. Montana State University students completed two tasks with a nature or urban image viewed before a block of trials that measured either working memory capacity (Experiment 1), attentional control (Experiment 2), or primary/secondary memory (Experiment 3). Results revealed higher performance after viewing nature images compared to urban images for attentional control but not for working memory capacity or either of its underlying memory components. These results are discussed with respect to the importance of current psychometric standards of measuring behavior when investigating the potential influence of nature on cognition.Item Using dietary dynamics to assess the efficacy of biocontrol and to predict the effects of warming water temperatures on salmonids(Montana State University - Bozeman, College of Letters & Science, 2024) Furey, Kaitlyn Marie; Chairperson, Graduate Committee: Christopher S. Guy; This is a manuscript style paper that includes co-authored chapters.Salmonids are coldwater fishes with substantial ecological and economic importance, particularly in the northern Rocky Mountains in Montana, USA, where fisheries are valued over US$750M annually. Georgetown Lake (Montana, USA) is renowned for its salmonid fishery. Although many anglers target kokanee (Oncorhynchus nerka) in Georgetown Lake, the body length of kokanee has typically been considered unsatisfactory. To reduce the density of kokanee and increase the average size, Montana Fish, Wildlife & Parks (MFWP) began stocking piscivorous Gerrard strain of rainbow trout (Oncorhynchus mykiss; hereafter Gerrard) in 2015 to consume kokanee. To assess the efficacy of biocontrol through the introduction of a piscivore to improve the size structure of kokanee, I used diet composition to determine the amount of predation on kokanee and to understand the feeding ecology of all potential predators. There was extremely low prevalence of piscivory and no evidence of Gerrards consuming kokanee. Gerrards exhibited a generalist feeding strategy and there was dietary and niche overlap and no difference in trophic position among Gerrards and trout. These findings highlight the unpredictability of predator-prey dynamics and the importance of evaluating management interventions, such as biocontrols. Additionally, this popular fishery could be in jeopardy because air temperatures in the region have warmed at twice the global average, leading to warmer water temperatures that could affect the thermal suitability for salmonids. Increased water temperatures can have sub-lethal effects, influencing growth, metabolism, and feeding rates of fish. Bioenergetics models were used to simulate the effects of warming water temperature on food consumption and growth for rainbow trout and kokanee within Georgetown Lake. My findings indicate that kokanee are more sensitive to warming than rainbow trout. While both species experience growth challenges as water temperatures exceed their optimal ranges, kokanee are particularly vulnerable, requiring higher food consumption to meet basic metabolic needs under elevated water temperatures. Thus, kokanee are likely to experience greater declines in growth compared to rainbow trout. Climate change will pose challenges for freshwater fisheries management, thus understanding how projected warming water temperatures may affect popular recreational fisheries can provide managers with information to establish reasonable expectations for fish growth.Item Sparse descriptors for whole graph embedding and dictionary based feature ranking(Montana State University - Bozeman, College of Engineering, 2024) Liyanage, Liyanpathige Kaveen Gayasara; Chairperson, Graduate Committee: Brad WhitakerGraph representation has gained wide popularity as a data representation method in many applications. Unfortunately, most data processing techniques cannot be applied directly to a graph structure. Therefore, graph embedding methods are frequently used to convert graphs to vectors. While such methods are essential in standard data processing pipelines, they often result in complicated, nonlinear, and high-dimensional mappings. The goal of this dissertation is to utilize sparse dictionary learning techniques in the context of graph embedding. In contrast to traditional graph embedding methods, sparse representations are linear by design. This linearity also leads to intuition, since the building blocks of a sparse dictionary are directly related to the input space. Despite the potential advantages of sparse processing and the ubiquitousness of sparsity in other signal processing domains, its applications in graph embedding are not well studied. This dissertation consists of three main tasks. First, a novel sparse graph descriptor algorithm is presented, inspired by the Graph2Vec graph embedding algorithm. Second, sparse representation-based feature ranking metrics are deployed to identify important sub- tree structures of the graphs that can be used to define a dictionary. The developed embedding algorithm and feature-ranking metrics are compared to existing graph embedding methods and feature-ranking algorithms on several typical benchmark graph datasets. Finally, these sparse representation-based techniques are applied to control flow graphs of binary files to detect malware, showing the utility of the developed algorithms.Item Redefining the gap: considering opportunity factors on academic success outcomes for Montana students(Montana State University - Bozeman, College of Education, Health & Human Development, 2024) Frieling, Nicole Pamela; Chairperson, Graduate Committee: Carrie B. MyersThis study examines educational inequity among Montana high school students by investigating the influence of social location (gender, race, and socioeconomic class) and opportunity factors (student mobility and poverty) on academic achievement and completion. Using a robust multilevel modeling approach, this research analyzes longitudinal student and school data to address four primary questions: differences in academic success based on students' social locations, and the impact of individual and school-level factors on achievement and graduation likelihood. Key findings reveal that high-poverty male and American Indian/Alaskan Native (AIAN) students face compounded barriers to academic success, with significant disparities in both ACT performance and graduation rates. Analysis of the within-group sample of AIAN students highlights the role of mobility and poverty as critical opportunity factors, underscoring the distinct challenges faced by Native students, particularly those attending on- reservation schools. The study's results contribute to the understanding of how intersecting social locations impact educational outcomes and challenge the traditional "achievement gap" framework. Recommendations include expanding Montana's educational reporting to address nuanced disparities across social locations and implementing support systems tailored to high- poverty and mobile students. This research emphasizes the need for data-driven policy reform to promote equity and address systemic barriers within Montana's educational landscape. While this study's findings show a statistically negative relationship between mobility and academic outcomes, they should be interpreted with care, as mobility encompasses complex experiences and cannot be fully understood through quantitative data alone. Recognizing mobility as an opportunity factor captures this nuance, as mobility may present significant challenges for some students while providing meaningful opportunities for others, such as a move to a more stable home environment. This study highlights the need for both quantitative and qualitative approaches to truly unearth the multifaceted role that mobility plays in Montana, reminding us that interpreting mobility solely as a barrier risks overlooking its potential as a positive force in students' lives.Item Estimating tool wear using multi-sensor data fusion and machine learning techniques(Montana State University - Bozeman, College of Engineering, 2024) Jones, Tanner Owen; Chairperson, Graduate Committee: Yang CaoModern manufacturing industries are being transformed by the integration of sensor technology, data science, and machine learning, leading to smarter, more efficient operations. Advancements in equipment health monitoring are crucial for improving productivity, extending equipment lifespan, and ensuring consistent product quality. In computer numerical control (CNC) machining, worn tools contribute to increased forces and vibrations, negatively impacting both machine performance and part quality. Traditional tool condition monitoring methods, which rely on manual offline inspections, result in machine downtime and decreased productivity. Modern tool condition monitoring methods involve monitoring tools based on single-sensor analysis. While a single sensor can detect tool wear within a machine, it fails to capture the full range of system behavior, potentially overlooking critical anomalies indictive of tool wear. To address these challenges, automated monitoring systems utilizing multisensory data and machine learning techniques have been developed, enabling real-time monitoring and prediction of tool wear. This research introduces a novel three-level data fusion framework for predicting tool flank wear in CNC machining. Force, vibration, and sound data was collected using various sensors during a CNC milling operation. The raw sensor data was processed and transformed into distinct statistical features to train machine learning models. A stacking ensemble method combining a random forest, artificial neural network, and extreme gradient boosting algorithm was employed to enhance predictive accuracy, achieving an R 2 value of 0.982, and root mean squared error of 37.146 micrometers. The proposed three-level fusion framework proved to be highly effective in predicting tool flank wear and shows great potential for monitoring the health of engineering equipment across a variety of industries.Item Soil and stream corridor biogeochemistry of nitrate and sulfate and the influence of hydrologic connectivity in an agricultural system, Judith River Watershed, Montana(Montana State University - Bozeman, College of Agriculture, 2024) Mayernik, Caitlin Marie Mitchell; Chairperson, Graduate Committee: Stephanie A. Ewing; This is a manuscript style paper that includes co-authored chapters.Human activities across landscapes alter physical and chemical properties of soil, thereby influencing the movement and chemical composition of soil water. Soil hydrologic and biogeochemical processes thus mediate how land management influences the quality of water that passes through soil in route to groundwater aquifers and streams. Riparian areas are particularly important in mitigating the consequences of land use for the quality of water exported from watersheds. Soils, sediments, and shallow aquifers within riparian areas of stream corridors provide low oxygen environments favoring microbial transformation of solutes for energy and carbon. Despite the limited areal extent compared to the rest of the landscape, this unique biogeochemical character is disproportionately important in determining inorganic solute export, particularly in agricultural systems. For this dissertation, I investigated sources and fate of soil water in an area managed primarily for production of cattle and non-irrigated wheat within the semi-arid Northern Great Plains of North America. I explored patterns in solute concentrations and isotopic compositions across stream corridors draining cultivated soils to infer dominant hydrologic transport and biogeochemical pathways influencing solute loading to ground and surface waters. I investigated the influence of agricultural practices and soil weathering on biogeochemical processes influencing solutes, to answer the overarching research question: How do upland soils and stream corridors influence water and solute loading from upland aquifers to stream channels in a semi-arid landscape managed for agricultural production? Results show that soils are important mixing reservoirs for seasonally variable sources of precipitation, and that water movement through soil transports nitrate and sulfate from cultivated soils. Stream corridors receiving these inorganic solutes from upland groundwaters facilitate biogeochemical pathways of production, transformation, and irreversible loss. Changes in the isotopic composition of these solutes relative to changes in their mass abundance inform gross production and loss in stream corridors at the catchment scale, revealing both internal production of sulfate and/or nitrate and more substantial nitrate loss than indicated by net changes between uplands and streams. Geomorphic constraints on hydrologic connectivity and the arrangement of riparian soils and sediments determine how stream corridors mitigate the consequences of land use on downstream water quality.Item [FeFe]-hydrogenase maturation: bridging dithiomethylamine ligand assembly during the biosynthesis of the H-cluster(Montana State University - Bozeman, College of Letters & Science, 2024) Balci, Batuhan; Chairperson, Graduate Committee: Joan B. Broderick; This is a manuscript style paper that includes co-authored chapters.[FeFe]-hydrogenases (HydA) demonstrated the highest catalytic competency to synthesize hydrogen gas by reducing protons under physiological conditions and has become a model catalyst in biohydrogen production. In vivo biosynthesis of the active site H-cluster of HydA requires a complex biocatalytic process that involves two radical S- adenosyl-L-methionine enzymes: HydG and HydE, and a [4Fe-4S] cluster binding GTPase: HydF. The maturation of the H-cluster starts with HydG, which cleaves tyrosine to synthesize CO and CN- ligands and provides [Fe II(CO) 2(CN)(kappa 3-cys)]- (synthon) as the product. Synthon is directly delivered to the second radical SAM enzyme HydE that is hypothesized to adenosylate and reduce two equivalents of synthon and subsequently dimerize and form [Fe I 2(mu-SH) 2(CO) 4(CN) 2] 2- ([2Fe] E). The final step in the assembly of the [2Fe] subcluster is DTMA ligand synthesis. In addition to HydG, HydE, and HydF chemistry, the in vitro maturation of HydA was also dependent on E. coli cell extract as a separate component presumed to provide essential components for the assembly of DTMA. We discovered the activating components as H-protein and T-protein of the glycine cleavage system (GCS), serine hydroxymethyltrans-ferase (SHMT), and small molecule substrates: serine and ammonium. Isotope labeling studies and ENDOR spectroscopy analysis revealed that the carbon and nitrogen atoms of DTMA ligand originate from serine and NH 4 +. We hypothesized that the DTMA ligand is assembled by aminomethyl-lipoyl-H-protein (H met) on the HydF-[2Fe] E complex. Consecutively, we demonstrated that HydA can be matured from a chemically synthesized [2Fe] E precursor, bypassing HydG and HydE, via a lysate-free semisynthetic maturation system with GCS components, SHMT, and corresponding substrates. Results emphasized the role of H met as the precursor for DTMA ligand. Refinement to the semisynthetic maturation, which now includes the [Fe-S] cluster carrier protein NfuA and high-CO-affinity variant Mb-H64L, resulted in significantly enhanced hydrogenase activities reaching 940 micromol H 2 min -1 mg - 1 HydA, a level of activity matches with catalytic rates of HydA matured in vivo. Under the refined semisynthetic maturation conditions, we determined that the [4Fe-4S] cluster of HydF is required to mature HydA. Results from site-directed mutagenesis studies on the HydF scaffold suggest that the [4Fe-4S] cluster plays a structural role in the maturation of HydA.