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Chemical Synthesis of Scytonemin and Structural Derivatives for Elucidating Photoprotective Mechanisms in Cyanobacteria
No full textPhotoprotection is a vital process for organisms to survive, especially in extreme environments. Cyanobacteria are organisms that rely on photoprotection to protect themselves from the intense UV radiation they are exposed to. One of the main pigments involved in cyanobacterial photoprotection is scytonemin, which has been shown to be an integral part of photoprotection in many different species of cyanobacteria. It has been hypothesized to provide protection for organisms that predate ozone layer formation due to its ability to detect UV-C, it also blocks 85-90% of UV-A and B, providing protection for current atmospheric conditions as well. The unique structure of scytonemin allows it to be protected and adapt to extreme environments where cyanobacteria live. Mechanistic studies of the key UV-pigment have not been widely explored resulting in very little knowledge about how scytonemin functions as a UV-protectant in for cyanobacteria and related organisms. One major limitation to these studies is the small quantities available through isolation from the natural source. A practical chemical synthesis would enable photophysical and related studies. I developed a novel and practical synthesis of scytonemin, which is described in chapter 2. This synthesis was more concise and started from economical feasible starting materials compared to previously reported syntheses. Other attempts toward the synthesis of scytonemin are included in Chapter 5, which describe alternative routes to scytonemin along with alternative reactions towards optimizing the key transformations. The chemical synthesis of scytonemin also enabled the synthesis of the scytonemin imine, which is an analogue of scytonemin. Scytonemin imine was reported in 2013 by Grant and Louda and is proposed to play an important role in cyanobacteria growing in high light environments. However, many structural ambiguities were reported in the originally proposed structure and through reisolation, DFT calculation of NMR spectra, and confirmatory synthesis, we verified that the structure was indeed a cyclic imine as opposed to the previously determined primary imine moiety. During the synthesis and characterization of the imine, it was also discovered that scytonemin imine demonstrated significant solvatochromic properties through our initial proton NMR analysis. Chapter 4 provides further detail that demonstrates that scytonemin imine forms a quinoid tautomer in polar solvents. This is a newly described structural feature of this chromophore that can have significant implications in both the photochemistry and redox properties of this scaffold. It also reveals the potential environmentally driven chromism that can be tied to adaptability to the wide range of pressures that these organisms can resist. This synthesis enabled further examination into the role of scytonemin in the photoprotection of cyanobacteria throughout the geologic time scale. The synthesis of the scytonemin imine was integral to the structural revision and led to the observation of the solvatochromic properties of the scytonemin imine. These characteristics add to the complex story of scytonemin and scytonemin analogues along with their role in the photoprotection of cyanobacteria
Nevada State Climate Office Drought Report February 2025
No full textThis report was created by the Nevada State Climate Office to provide a statewide drought summary for February 2025
Understanding Factors That Influence Attorneys’ Plea Recommendations
No full textA large portion of wrongful convictions in the United States result from false guilty pleas. To address this issue, most research has focused on factors that influence defendants’ plea decisions. However, recent research suggests that attorneys’ plea recommendations play a significant role in shaping defendants’ plea decisions. Given their influence in the plea-bargaining process, it is crucial to understand factors that influence attorneys’ plea recommendations to identify situations where they might advise clients to falsely plead guilty. My colleagues and I conducted four experiments across three articles to investigate factors that influence attorneys’ plea recommendations, utilizing diverse theoretical frameworks and methodological approaches. In the first article (Chapter 2), we conducted two experiments to examine the influence of factors from the Shadow of the Trial (SoT) theory on mock attorneys’ plea recommendations. For Experiment 1, mock attorneys read case vignettes that manipulated factors from the original SoT, including conviction probability via evidence strength and potential trial sentence. For Experiment 2, mock attorneys read case vignettes that manipulated factors from the expanded SoT, including conviction probability, potential trial sentence, and defendant guilt status. The findings from both experiments demonstrated that all the SoT factors—conviction probability, potential trial sentence, and defendant guilt status—affected mock attorneys’ plea recommendations. In the second article (Chapter 3), we conducted an experiment to examine the influence of factors from Fuzzy Trace Theory (FTT)—gist versus verbatim processing—on practicing attorneys’ plea recommendations and related thought processes. Attorneys engaged in a plea simulation that manipulated factors from SoT and measured their cognitive processing styles. The findings revealed that attorneys’ cognitive processing styles influenced how SoT factors affected their plea recommendations, indicating that individual differences play a crucial role in attorneys’ decision-making. In the third article (Chapter 4), we conducted an experiment to examine the influence of factors from Prospect Theory (PT)—diminishing sensitivity and reference dependence—on practicing attorneys’ plea recommendations and related thought processes. Attorneys engaged in a plea simulation that manipulated the defendant guilt status and potential trial sentence. The findings showed that both factors influenced attorneys’ plea recommendations, suggesting that attorneys consider both the severity of trial outcomes and the defendant’s guilt or innocence when advising on plea deals. Collectively, these findings provide valuable insight into the cognitive and contextual factors that shape attorneys’ plea recommendations, which highlight the complexity of legal decision-making and need for further research to enhance accuracy and fairness in the plea-bargaining process
Predictive Mapping of the Moss Component of Biological Soil Crusts
No full textBiological soil crusts (biocrusts) are soil surface communities that can includecyanobacteria, lichens, and mosses. Biocrusts commonly grow in the interspaces between
vascular plants and contribute to essential ecosystem functions such as water cycling,
nutrient cycling, and the prevention of soil erosion. This study focuses on the moss
component of biocrusts because mosses can be more tolerant of land uses such as grazing
by livestock and are more successfully reintroduced through restoration than other
biocrust components. The region of interest encompasses the Eagle Lake Field Office
(ELFO) of the Bureau of Land Management (BLM) in the northwestern Great Basin.
Over 2023 and 2024, 101 randomly stratified plots were surveyed across environmental
gradients to assess how climate, soils, topography, and vascular plant cover influence the
distribution and abundance of moss, including historical fire occurrence and burn
severity, as well as use by cattle and free-roaming horses. These results show that in the
absence of fire, grazing, and vascular plant information, moss distribution was best
predicted by sand, January minimum temperatures, and January dew point. However, the
former demonstrated a great amount of influence on predicting the distribution and
abundances of tall moss, increasing our understanding of the ecology of this component
of biocrusts. By developing a predictive model and distribution map, this study provides
valuable insights on the ecology of arid land mosses. Biocrusts can improve soil health,
reduce erosion, increase water infiltration, and enhance rangeland productivity, ultimately
supporting sustainable grazing practices and wildlife management
Entrepreneurship in times of changing technology and labor markets
No full textThis dissertation investigates research questions in entrepreneurship, with a particular focus on the effects of recent and emerging technologies. Chapter One explores how entrepreneurship and market structure affect emerging technologies, while Chapters Two and Three examine the impact of these technologies on entrepreneurship. I incorporate Artificial Intelligence (AI) both as a methodological tool (Chapter One) and as a subject of inquiry (Chapter Three). The first chapter draws on data from the Google Play Store and applies Natural Language Processing techniques to measure the similarity of app descriptions, analyzing the relationship between market concentration and product differentiation. The second chapter uses data from the American Community Survey and the timing of Uber’s entry into metropolitan areas to assess the impact of rideshare on taxi drivers’ wages and labor supply. The third chapter reviews the emerging literature on AI and entrepreneurship. The first chapter, “Do Apps Play Follow the Leader? Testing the Relationship between Market Power and Product Similarity with Language Models”, coauthored with Kym Pram, examines the relationship between product similarity and market concentration. We employ Bidirectional Encoder Representations from Transformers (BERT) to embed product descriptions and use the Herfindahl-Hirschman Index (HHI) to capture market concentration. Our analysis reveals a robust U-shaped relationship that flattens for recently updated apps and apps where users interact. These findings suggest that the incentive for acquisition-driven market entry is the dominant mechanism only in markets characterized by high concentration. The second chapter, “Revisiting the Uber Effect”, is a solo-authored paper that replicates and extends a study by Berger et al. (2018) on whether Uber drivers displace conventional taxi drivers. The analysis leverages the timing of Uber’s market entry as exogenous variation in a difference-in-differences approach that analyzes taxi driver wage, salary, and labor supply. I find an 8.5-9.8% decrease in hourly earnings among wage employed drivers, no significant effect on salary, and a 7.7-12.3% decrease in labor supply of wage employed drivers. I also identify data irregularities in the Berger et al. (2018) paper and find that the larger and more statistically significant results for wage and salary that they found were not robust. The third chapter, “Artificial Intelligence and Entrepreneurship”, coauthored with Frank M. Fossen and Alina Sorgner, reviews the literature on impacts of AI on entrepreneurship. It begins by clarifying definitions of AI to eliminate ambiguity and provide context to how various studies use the term. The chapter discusses theoretical frameworks and empirical evidence related to the adoption of AI technologies and how AI technologies affect entrepreneurial opportunities, decision making under uncertainty, entry barriers, and business performance. An original empirical analysis from the German Socio-economic Panel is introduced, showing that entrepreneurs demonstrate greater awareness and use of AI technologies than paid employees. We review indirect impacts of AI on entrepreneurship through the labor market, finding evidence suggesting that automation results in higher levels of necessity entrepreneurship while transformative technologies, those that do not necessarily displace workers, lead to higher levels of opportunity entrepreneurship. The entrepreneurial ecosystem literature suggests AI reshapes the importance and configuration of existing ecosystem elements and processes and may reduce the role of geography in entrepreneurial activity. We conclude with a discussion on regulation of AI, with a focus on developments within the European Union
Ethical Considerations in Biological Anthropology: A Bibliometric Review of Recently Published Articles
No full textDespite a growing number of biological anthropologists reflecting on the discipline’s colonial roots and the absence of descendant community (DC) collaboration, little work has been done to evaluate how researchers address these issues in the published literature. Through a data-driven approach we can better assess the state of the field to make recommendations for the future. To this end, this research undertook a bibliometric review over the past seven years (2017-2024) of three journals that publish bioarchaeological work (i.e., Bioarchaeology International, International Journal of Paleopathology, and the International Journal of Osteoarchaeology). Data were collected on the following variables in manuscripts of human remains (n=849): 1) Inclusion of an ethical statement, 2) whether DC was involved or consulted, 3) permission, 4) country of origin of the remains, 5) country in which the remains were housed, 6) country where the authors were based, 7) descendant community, 8) whether remains included those of Indigenous Peoples or other minorities, 9) whether remains were recovered after 1990, 10) if destructive analysis occurred, 11) imaging, and 12) funding. The results demonstrated that work can be done to more fully engage with certain ethical considerations. When the remains involved are those of Indigenous Peoples or other minorities DC collaboration was only 3% and 2%, respectively. Only 3% of articles had an ethics statement and 40% of articles had no information on how permission was received. Country-specific case studies are explored to understand how ethical considerations may present themselves depending on the country in which the research takes place, and possible avenues for change are discussed
Social Capital as a Mediator of Housing Instability and Distress Among California Latino Populations: A Multi-Sample Multi-Year Analysis
No full textLatinos are one of the largest underrepresented groups in the United States, with about 65 million people, 57.7% of whom are Mexican. In California, where Latinos comprise 40% of the population and over half are renters, they face unique structural and cultural barriers that increase vulnerability to housing instability and psychological distress. While prior research has linked these challenges, limited work has explored subgroup differences, the role of social capital, or changes over time, especially during major public health disruptions like the COVID-19 pandemic. This dissertation addresses these gaps using three studies based on weighted, multi-sample structural equation modeling (SEM) with California Health Interview Survey (CHIS) data. Paper 1 examines how housing instability impacts psychological distress among Mexican and non-Mexican Latinos. Results show strict measurement invariance and similar levels of distress between subgroups, with slightly higher effects for non-Mexicans (β = 0.24) than Mexicans (β = 0.23). Compared to Whites (β = 0.29) and the general non-Latino population (β = 0.26), both Latino groups reported lower distress, suggesting protective cultural or social influences. Paper 2 introduces neighborhood support, neighborhood trust, and civic engagement as mediators. The total effect of housing instability on distress was consistent (TE = 0.24) across Latino subgroups, but only Mexican Latinos showed significant mediation through all three indicators; for non-Mexicans, only neighborhood support was significant. Compared to Whites (TE = 0.30) and non-Latinos (TE = 0.27), Latinos again demonstrated lower total effects. Paper 3 explores temporal changes by comparing Latino Californians from 2021 (post-shutdown) and 2023 (post-state of emergency). Measurement invariance held, but structural invariance did not, indicating shifting relationships over time. The effect of housing instability on distress was stronger in 2021 (β = 0.23, TE = 0.50) than in 2023 (β = 0.17, TE = 0.39), while the mediating roles of neighborhood support and trust weakened. These findings suggest that while housing instability consistently predicts distress among Latinos, subgroup and temporal variations shape how social capital mitigates its impact. This dissertation underscores the need to disaggregate Latino subgroups, consider time-based changes, and invest in community-level supports to address housing-related distress
Multifaceted Impacts of the COVID-19 Pandemic: Smoking, Influenza Vaccine Uptake, and Respiratory Mortality
No full textThe COVID-19 pandemic fundamentally altered public health dynamics, impacting disease transmission, healthcare utilization, and mortality outcomes. This dissertation examines three interrelated aspects of the pandemic’s effects: (1) behavioral risk factors influencing COVID-19 hospitalization, (2) factors affecting influenza vaccine uptake among caregivers, and (3) excess pneumonia and influenza (P&I) mortality patterns. Using a social determinants of health framework, this research explores how individual behaviors, preventive practices, and systemic disparities collectively shaped health outcomes during the pandemic.The first study assesses the association between smoking and COVID-19 hospitalization by integrating individual and regional factors. Employing a retrospective cohort design with surveillance data using multilevel regression models to quantify how smoking status and community characteristics influenced hospitalization risk. The findings provide insight into the complex relationship between smoking and COVID-19 severity, addressing inconsistencies observed in early pandemic studies.
The second study investigates influenza vaccine uptake among caregivers during the pandemic. Using Behavioral Risk Factor Surveillance System (BRFSS) data, multivariable logistic regression models evaluate how sociodemographic characteristics, health-related factors, and risk perceptions affected vaccination decisions. The study examines whether pandemic-driven risk awareness led to increased caregiver vaccination rates, contributing to improved public health strategies.
The third study analyzes shifts in P&I mortality trends using death certificate data from the Nevada Vital Records Office. A zero-inflated negative binomial regression model estimated expected and excess P&I mortality during the pandemic, stratifying results by age, sex, race/ethnicity, and geographic location. The findings reveal significant deviations from pre-pandemic mortality trends, underscoring disparities in healthcare access and disease burden across different populations.
Collectively, these studies provide a comprehensive assessment of how the COVID-19 pandemic influenced respiratory disease outcomes and preventive health behaviors. By utilizing individual and population-level factors incorporating a social determinants of health perspective, this research highlights critical gaps in public health response and offers actionable insights for future emergency preparedness. The findings emphasize the necessity of targeted interventions that address both individual behaviors and systemic inequities, ensuring more equitable health outcomes in future health crises
Investigating the Role of Polyvinylidene Fluoride and the Effect of Microwave Treatment on Surface Properties of Graphite and Floatability from Spent Lithium-Ion Batteries
No full textA fundamental understanding of the surface properties of minerals is crucial for identifying interfacial reactions and developing more efficient technologies for their recovery. This research investigates the impact of polyvinylidene fluoride (PVDF) and microwave treatment on the surface properties of graphite and its floatability from spent lithium-ion batteries (LIBs). The study systematically examines graphite's surface characteristics in the presence and absence of PVDF, as well as before and after microwave treatment, using a suite of advanced characterization techniques, including scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Raman spectroscopy, thermogravimetric analysis (TGA), X-ray diffraction (XRD), and surface roughness analysis. The wetting behavior of graphite was evaluated using sessile drop contact angle measurements, and surface energy components—polar and non-polar—were quantified using the Van Oss−Chaudhury−Good and Owens−Wendt−Rabel−Kaelble models. The study further explores the effects of PVDF and microwave treatment on the surface energy components, focusing on shifts in non-polar forces and polar interactions, including acid-base electron donor and acceptor contributions. The findings reveal significant modifications in the surface properties and hydrophobic/hydrophilic character of graphite and black mass due to PVDF and microwave treatment, resulting in substantial changes in flotation behavior. Microwave treatment was found to enhance graphite’s surface characteristics and flotation efficiency. The insights derived from this study offer promising implications for optimizing graphite recovery from spent LIBs and developing advanced separation techniques through tailored surface property modifications