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Assessment Of Vegetation Dynamics After South Sugar Loaf and Snowstorm Wildfires Using Remote Sensing Spectral Indices
No full textWildfires are increasingly common in sagebrush ecosystems across the western United States, leading to vegetation loss and ecosystem restructuring. This study investigated vegetation recovery within two large Nevada burn scars, the Snowstorm Fire of 2017 and the South Sugar Loaf Fire of 2018. Landsat 8 surface reflectance imagery supplied multi temporal spectral data, and vegetation burn severity was mapped with the difference Normalized Burn Ratio. The research aimed to quantify how vegetation health spectral indicators respond over time across severity gradients and to detect shifts in land cover composition from pre fire to post fire conditions.Four spectral indices—NDVI, MSI, MCARI2, and land surface temperature—were assessed with the Mann Kendall trend test, followed by a linear mixed effects model that linked time and severity class to spectral change. ISODATA clustering was conducted to determine pre-fire and post-fire classes, with a stability matrix and change matrix tracking the fate of each pre-fire class with post-fire classification. LANDFIRE EVT maps were assessed to test their sensitivity to short term ecosystem change. Severity mapping showed contrasting fire behavior. Snowstorm burned chiefly at low severity and covered sixty nine percent of the area, whereas South Sugar Loaf contained similar proportions of high and moderate high severity at thirty-two and thirty three percent respectively. NDVI rose at both sites, confirming recovery. In Snowstorm the increase was uniform across severity classes, but in South Sugar Loaf low severity pixels gained more greenness than high severity ones, indicating that high severity had an impact on vegetation regrowth. MSI declined over time at both sites, indicating moisture recovery, with the largest decline in moderate high severity zones at South Sugar Loaf, indicating the role of burn severity, MCARI2 a chlorophyll proxy, climbed steadily and was again most responsive in the lower severity classes of South Sugar Loaf as compared to high severity, whereas there was no effect of severity in Snowstorm fire. Land surface temperature declined at Snowstorm fire area and showed localized reductions in low severity areas at South Sugar Loaf. The Mann-Kendall trend test was non-significant for fire areas but showed localized positive trends. Linear Mixed Effects model and Mann-Kendall test revealed time since fire to be the primary driver of recovery, while severity modulated local trajectories. ISODATA distinguished five pre-fire and seven post-fire classes at South Sugar Loaf and five pre-fire and post-fire classes at snowstorm. South Sugar Loaf underwent pronounced compositional change: its dominant shrubland class retained just one third of its original area, shifting largely to herbaceous and sparse vegetation categories. Conifers in South Sugarloaf fire lost most of it area to sparse vegetation in post-fire. Snowstorm exhibited greater stability for shrubs species, with more than half of the Herbs Shrubs Mix-2 class persisting. Across both fires new post fire clusters displayed lower near infrared and higher short wave infrared reflectance, signatures typical of ash and bare substrate. LANDFIRE EVT maps failed to register these changes, remaining static in both South Sugar Loaf and Snowstorm. Combining time series spectral metrics with unsupervised classification captured both gradual recovery and abrupt compositional shifts, offering a comprehensive view of postfire dynamics. The persistence of outdated classes in LANDFIRE EVT underscores the need for more agile vegetation mapping frameworks that can accommodate rapid ecological change in fire prone landscapes
A Comparative Analysis of Fife and Flute Pedagogical Methods and Resources for Amateur Musicians
No full textThis document explores the pedagogical literature and tools used by fife and drum instructors during private lessons and ensemble rehearsals. The document will address the general history of the fife and drum and how the instrumental pair has been a leading cultural, historical, and musical signifier across Europe and the United States over the past millennium. It also analyzes the strengths and pitfalls in fife pedagogical literature and highlights supplemental teaching resources from flute pedagogical literature. This research aims to strengthen the current methodological tools for amateur fife learning while providing a dialogue between different music genres and ensemble structures. The document aims to help students and teachers locate, access, and use new teaching resources. Ensemble observations, interviews with master pedagogues, and the author’s teaching experiences as a classically trained flutist served as research data
Developments on Abbreviations Towards Machine Reading Comprehension
No full textMachine reading comprehension is a critical step in development of applications that require the semantic understanding of human speech-to-text driven work. Many devices such as smart home appliances like the Amazon Echo Dot, Google Home, or smart assistants like Apple Siri or Microsoft Cortana are examples of these applications. The comprehension task involves a deeper understanding and recognition of named entities such as person names, locations, medicals codes, quantities, abbreviations, and acronyms in speech or text data. In this dissertation, we explore and extend the different approaches and techniques in modern research that tackles the problem of recognition and definition of acronyms and abbreviations. Also, we offer different techniques for disambiguation of abbreviations that are caused by the abundance and frequent introduction of new abbreviations. We provide the following contributions: 1) A historical background on the rule-based and statistical methods for finding acronyms and their definitions. 2) A method based on the bidirectional encoder representations from transformers question answering model to find acronym definitions in each document. Our experiments show that this model can correctly predict 94% of acronym expansions assuming a Jaro–Winkler threshold distance of greater than 0.8. 3) An exploration of the different approaches and techniques to solve the problem of ambiguous abbreviations and their definitions. We reverse engineered the process of creating ad hoc abbreviations and found some preliminary statistics on what makes them easier or harder to define. In addition to recognition and definition of acronyms and abbreviations, this dissertation contributes to a systematic generative method to create datasets and use them to build a corpus for acronym expansion. Our approach for data generation can be used in many applications where there are no standard datasets
Chronic Exposure to Porphyromonas gingivalis Disrupts Macrophage Innate Immune Responses
No full textIntroduction: Porphyromonas gingivalis (Pg) is a pathogenic, “red-complex” bacteria found in higher concentrations in advanced gingivitis and periodontitis. Macrophages are capable of adopting numerous phenotypes depending on the surrounding environment. Classic M1 macrophages are the result of inflammatory signals including IFNγ. This study investigated whether naïve M0 macrophages can transition into classic M1 macrophages following stimulation with traditional agonists after cells have been exposed to formalin killed P. gingivalis.Methods: The THP-1 monocytes were differentiated into naïve macrophages (M0) using PMA treatment. The M0 cells were challenged with formalin killed P. gingivalis for 24 hours. After prolonged exposure to P. gingivalis, the cells were stimulated by M1 producing agonist IFNγ and Escherichia. coli lipopolysaccharide (LPS, 20ng). The resulting cytokine gene expression profiles and secreted protein concentrations of IL-6, IL-1β and TNF-α were determined. Results: Our study investigated the impact of prolonged P. gingivalis exposure on macrophage differentiation into the M1 phenotype, characterized by high IL-6, TNF-α, and IL-1β expression. While P. gingivalis and S. gordonii initially induced a modest increase in IL-6 mRNA and protein levels, P. gingivalis exposure prior to M1 stimulation significantly suppressed IL-6 expression, whereas S. gordonii did not. Similarly, P. gingivalis exposure inhibited the expected M1-associated increase in TNF-α mRNA and protein levels, reducing TNF-α secretion to levels comparable to unstimulated controls. In contrast, S. gordonii treatment resulted in robust TNF-α induction, similar to M1 stimulation. However, IL-1β expression and secretion were significantly increased by both P. gingivalis and S. gordonii, exceeding levels seen in M1-stimulated macrophages, and prior exposure to either bacterium did not alter IL-1β induction upon M1 stimulation. These findings suggest that P. gingivalis selectively suppresses IL-6 and TNF-α responses while allowing sustained IL-1β production, potentially contributing to immune evasion and chronic inflammation in periodontal disease. Conclusions: Our research identified a significant inhibitory effect of P. gingivalis on the differentiation of naïve (M0) macrophages, preventing their proper polarization into the pro-inflammatory M1 phenotype. Specifically, macrophages exposed to P. gingivalis exhibited an impaired response to M1 stimuli, suggesting that the bacterium actively disrupts classical inflammatory activation. This effect appears to be further amplified in a chronic infection state, contributing to immune dysregulation and persistent inflammation. While our study focused on key inflammatory markers, including TNF-α, IL-6, and IL-1β, the broader impact of P. gingivalis on other critical cytokines and chemokines involved in periodontitis remains to be fully elucidated. These findings highlight the bacterium’s ability to evade immune clearance and drive chronic inflammation, reinforcing its role as a keystone pathogen in periodontal disease
Musical Language and Communication: Students Connect Music Streams to Literacy, Mathematics, Science, And Movement
No full textThis dissertation discusses how music and literacy claim many of the same skills, ways music may be used as a motivational tool to help promote strategies for skill development, and how teachers working in teams have the innovation to generate strategic learning. By combining music symbolism with the literacy curriculum, one can create a set of elementary school lessons that integrate musical melody with the facets of literacy, mathematics, science, and movement to formulate beneficial opportunities for student engagement and learning. Students cultivate learning by using the elements of rhythmic literacy, such as identifying beat values in conjunction with their literary equivalent. Important music skill sets that are educationally meaningful for students to develop include identifying rhythmic values and observing how to problem-solve or evaluate note values by words per measure. Combining technology with the concepts mentioned above renders the music skill sets interactive and engaging. The tool of technology is crucial in the sonic-inspired classroom environment to enhance perspectives of music and literacy learning. Students creating song prose in their learning environment with these resources are motivated to engage in discourse and to educationally collaborate by creating group music themes while clapping to the beat of their practice prose. The culminating activity of this project involved students creating their rhyme, using ABA (chorus-verse-chorus) form, incorporating their knowledge of rhythmic literacy with non-locomotor movements, and engaging in group projects, to include the advancement of inspiring ideas of collaborative spoken, rhythmic sound levels. Methodological approaches include research and design of music and movement by Emile Jaques-Dalcroze, Zoltan Kodaly, Orff Schulwerk, and Gunild Keetman. Such approaches to music-meaning may promote the development of identifiable classifications for describing and interpreting one’s musical experience, however, differing confounding variables may affect study results, such as the extent to which students gather information
Beyond Monuments: The Built Environment of Las Vegas and Los Angeles in the Twentieth Century
No full textUsing Las Vegas and Los Angeles as case studies, this dissertation examines how aspects of the built environment have become emblematic of the cities where they reside, and more generally, of the modern American West. It explores how the public has interacted with and been affected by that urban built environment in the twentieth century. This history of the modern West examines how casino resorts and wedding chapels in southern Nevada and freeways and film studios in southern California became emblematic of an urban West. Drawing on urban, suburban, social, cultural, environmental, and public histories, this dissertation shows how these structures came to serve as monuments in their design, their size, their economic impact, and their place in popular culture and public memory. I argue that these structures are more accurate representations of historical processes than traditional monuments are. Still, like monuments, these structures have a more complex and compelling history than is outwardly visible to the public. This dissertation allows us to better understand the history of the modern urban West by revealing the ideological foundations on which these structures, and their host cities, were built. It examines how and why these structures were planned and constructed, the roles they have played in the growth and development of their respective metropolises, and the ways in which the public has known and interacted with them
UNLV Department of Physical Therapy and the Fine Arts Clinic for Health and Injury Prevention
No full textAt the collegiate of performing arts, those who participate in classes and performances will often be at risk for musculoskeletal injury due to repetition and specific patterns of their movements. The establishment of a pro-bono physical therapy clinic for students enrolled in undergraduate and graduate-level fine arts programs may improve healthcare access for this often underserved community. The goals of this service learning project were to provide injury-prevention screenings to dancers and administer specialized physical therapy (PT) services in the form of evaluations and treatments to all students in the UNLV (University of Las Vegas, Nevada) College of Fine Arts (CFA) school, under the direct supervision of three UNLV PT faculty therapists. This project also allowed the UNLV PT students within the project to gain hands-on PT skills in a specialized outpatient setting while completing didactic courses in their second year. To prepare for their time in the CFA PT clinic, students participated in shadowing hours in the clinic, completed an online course for specialized treatment of dancers, and helped administer dance screenings at the annual Healthy Performers Northern Nevada workshop. A total of 29 students were evaluated and treated during the 2023-2024 school year, with the majority of students in the music, dance, and theater majors. One dance screen for a patient was administered during the school year. Five exit surveys were completed by patients by the end of their treatment plans, and 15 were lost to follow-up. The PT students each completed four reflections over their time working in the clinic, and the consensus was that they all benefited from this additional time to practice their skills in the clinic under the professors’ supervision
Beyond Single Metrics: A Holistic Benchmarking Framework for Low-Power Embedded Systems
No full textModern embedded systems encounter a notable challenge in evaluation. While devices may meet traditional benchmarks, they often underperform in real-world applications due to neglected interactions at the system level. Current benchmarking suites, such as MLPerf Tiny and EEMBC ULPMark, evaluate specific metrics including computational throughput, energy efficiency, and memory usage. However, they do not consider the complex interdependencies that affect real-world performance. This thesis presents a benchmarking framework that concurrently evaluates multiple performance dimensions under realistic workloads, revealing system behaviors that are often hidden in conventional benchmarks.Through the comprehensive evaluation of three representative algorithms: Fast Fourier Transform, quantized neural network inference, and Dijkstra\u27s shortest-path algorithm, across 33 hardware platforms, including ARM Cortex-M microcontrollers, ultra-low-power FPGAs, and edge AI accelerators. By integrating cycle-accurate hardware models with RTOS scheduling, power state transitions, and I/O emulation, our framework uncovers critical system-level effects: memory requirements 2.5×-9.6× higher than algorithm size alone (averaging 8.4×), performance degradation up to 42.8% from I/O interference, and power state transition overheads that can dominate energy consumption at low duty cycles. Our simulation-based analysis identifies previously overlooked factors, including bus contention between CPU and DMA operations, interrupt-induced cache pollution, and priority inversion penalties, which collectively impact performance by 20-40%. We present the following contributions: (1) a cohesive measurement architecture that links previously isolated metrics, (2) quantitative evidence revealing systematic measurement errors in current benchmarks, and (3) empirically derived design guidelines that incorporate 2-3× memory safety margins and platform selection criteria informed by observed system behavior. This research allows precise performance forecasting for resource-limited systems, shifting embedded system design from intuition-based approaches to data-driven optimization
Understanding Ore Deposit Scale Controls On AU Enrichment in Carlin-Type AU Mineralization: A High-Resolution Study of The Rita K Deposit
No full textControls on the distribution of gold (Au) within the Rita K Carlin-type deposit are poorly understood. The primary Au-bearing carbonate unit Wispy, is a bioturbated muddy limestone with debris flow clasts that range in size but are typically \u3e5 cm occurring in the lower sections. The orebody is described as a syncline-anticline pair that hosts high-grade Au ore in the fold hinges. The spatial relationship between Au mineralization and fold hinges suggests that shortening due to folding is an important mechanism producing Au-enriched zones. However, the exact mechanism of Au enrichment and deposit-scale controls on Au distribution and fluid evolution through time remains unknown. The goal of this research is to investigate mechanisms causing variations in Au content throughout the Rita K deposit to inform future exploration and mining practices for Carlin-type deposits. Determining the relationship between structure, fluid flow, Au enrichment, and alteration is fundamental in building an ore deposit model at Rita K. For this study, we have selected two core holes based on the presence of debris flow deposits and vein networks to investigate fluid pathways at Rita K by utilizing a combination of bulk-rock geochemistry, reflected and transmitted light petrography, etching studies, micro-X-ray fluorescence mapping, and electron probe micro-analysis. Bulk-rock geochemistry data from our high-resolution study shows that debris flow samples are highly silicified, with an average of 86 wt.% (n=24, ±1σ, 1.34 wt.%) SiO2, when compared to vein network samples that average 39 wt.% (n=17, ±1σ, 10.0 wt.%) SiO2. The distribution of Si in micro-X-ray fluorescence element maps indicates that while vein networks facilitate fluid flow, debris flow deposits promote intergranular fluid flow enhancing wall rock interaction, sulfidation and Au deposition. Moreover, element mapping of pyrite grains challenges the well-established model that all arsenian pyrite rims on preexisting pyrite grains have a high Au content. Bulk rock geochemical data shows no correlation between Au and As in both debris flow samples (r2=0.002) and vein network samples (r2=0.12). The lack of correlation between Au and As suggests that intergranular fluid flow enhances fluid rock interaction leading to the formation of arsenian pyrite rims both with and without Au, and that pyrite rims are not necessarily required for the formation of Carlin-type Au deposits
School Absenteeism in Children with Disabilities: An Analysis of School Climate and Academic Mindset
No full textStudents with disabilities (SWDs) are more likely to be chronically absent than general education peers (Anderson, 2021; Gee, 2018, U.S. Department of Education, 2016). Etiology for SWDs is complex with influencing factors spanning multiple ecological levels, but bolstering protective factors for SWDs may address attendance disparities. Multi-tiered systems of support (MTSS) models have the potential to address absenteeism in SWDs via school-wide preventative and/or intervention efforts (Tier 1 & 2) aimed at increasing or decreasing influencing factors in students with disabilities. School climate and academic mindset may influence students with disabilities’ attendance. The purpose of the present study was to inform equitable and inclusive MTSS models by identifying influencing factors on school absenteeism for SWDs. The study aimed to (1) identify school climate and academic mindset factors that were linearly related to chronic absenteeism in students with disabilities and (2) identify differences in school climate and academic mindset variables between students with and without disabilities across age groups