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Assessing the Adequacy of Morphological Models Using Posterior Predictive Simulations
No full textReconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod datasets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple datasets, indicating that there is no “one size fits all” when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa
Variations in the Foraging Ecologies of Guanay Cormorants (Leucocarbo bougainvilli) and Peruvian Boobies (Sula variegata) Across Oceanographic Conditions: Insights from Stable Isotope, Movement, and Corticosterone Analyses
No full textUnderstanding how species, populations, and individuals cope with variation in foraging conditions is essential for predicting species responses to environmental change. Guanay cormorants (Leucocarbo bougainvillii) and Peruvian boobies (Sula variegata) are seabirds endemic to the Northern Humboldt Current System (NHCS), their populations supported by its unusually high productivity and abundance of anchoveta (Engraulis ringens), a key forage fish. However, El Niño Southern Oscillation (ENSO) can significantly impact anchoveta abundance; therefore, the populations, survival rates, and breeding success of these seabirds are proposed to be tightly linked to ENSO conditions. Although both species depend on anchoveta, their responses to ENSO will likely differ due to their varying foraging strategies and plasticity in diet and foraging behaviors. Most existing studies focus on these birds’ foraging ecologies during breeding; as such, much less is known about their foraging ecologies during the nonbreeding season. Alternative methodologies, used alongside traditional techniques, can help bridge this gap in our knowledge.
This research aims to advance this area of knowledge by combining both traditional and novel approaches –– diet, GPS, multi-tissue stable isotope, and feather corticosterone analyses –– to explore seasonal, interannual, and individual variation in the foraging responses of Guanay cormorants and Peruvian boobies to differing ENSO conditions. I found that despite moderate sexual dimorphism in Peruvian boobies, there was little sex-based spatial, behavioral, or trophic niche segregation. However, there may be dietary niche partitioning, as males captured smaller and more variably-sized prey. Stable isotope analysis of blood and feather tissues revealed that while Guanay cormorants and Peruvian boobies differed in both their breeding and nonbreeding isotopic niche widths, both species displayed consistent nonbreeding niche width expansion with little evidence of seasonal individual consistency. However, cormorants were more responsive to weak El Niño conditions, with consistent niche width expansions during warm conditions. Lastly, while oceanographic condition and δ13C values were related to feather corticosterone levels, surprisingly, unfavorable conditions did not translate to higher feather corticosterone in either species. Overall, this combined use of methods across seasons and years provides multifaceted insight into the foraging ecologies of Guanay cormorants and Peruvian boobies in the NHCS
Adult Skeletal Age Estimation of Pelvic Joints: Impact of Pelvic Anomalies and Quantitative Methods
No full textThis dissertation enhances age-at-death estimation by examining the impact of pelvic anomalies on age estimation methods and exploring quantitative approaches using three-dimensional (3D) surface complexity measurements and deep learning models. Paired os coxa and sacra from four skeletal collections were analyzed.
The effects of pelvic anomalies were assessed on three age-at-death methods: Hartnett (2010a), Buckberry and Chamberlain (2002), and Passalacqua (2009). Accuracy, absolute error, and bias were evaluated across the sample, where 140 individuals (27%) exhibited pelvic anomalies. The Passalacqua 95% confidence interval (CI) demonstrated the highest accuracy when anomalies were present, while the 68% CI had the lowest. Overall, accuracy decreased, and absolute error and bias increased, when anomalies were present, indicating aging methods should be applied cautiously when anomalies are present due to their influence on joint degeneration.
Next, Dirichlet normal energy (DNE) was implemented to quantify the 3D geometry of three pelvic joint surfaces: the pubic symphysis (PS) and the iliac and sacral auricular surfaces (IAS and SAS, respectively). DNE values were calculated from 3D scanned joint surfaces, and Spearman’s rank correlation analyses found low but significant correlations between DNE values and age: R² = 0.0699 (PS), R² = 0.1076 (IAS), R² = 0.0739 (SAS), and R² = 0.1190 (Combined Joint Group), all with a p-value of 0.000. Despite weak correlations, the significance suggests a relationship between DNE values and age, with a general trend of increasing DNE values with age.
Lastly, a deep learning model was implemented to classify digital images of the three pelvic joint surfaces into discrete age groups. Using an adapted ResNet50 convolutional neural network, models were trained, validated, and tested on images of the PS, IAS, and SAS. Training parameters included data augmentation, 20 epochs, and a batch size of 32 to classify images into six age groups. The SAS achieved the highest test accuracy (24%), while the IAS had the lowest (21%). After collapsing age groups into 18–69 years and 70+ years, the PS yielded the highest accuracy (59%). This study demonstrates the potential of deep learning in forensic anthropology, but highlights the need for larger training datasets to improve accuracy
On Regularity and Convergence of Solutions to the Boltzmann-Enskog Equations
Get PDFThe Boltzmann equation describes the time evolution of the density function in position-velocity space for a classical particle subjected to possible collisions by other particles in a diluted gas that expands in vacuum for a given initial distribution. While many authors have studied the probabilistic interpretation of the spatially homogeneous Boltzmann equation, there is a dearth of articles on the stochastic framework of the full (that is, spatially inhomogeneous) Boltzmann equation. In this thesis, we examine a stochastic process, developed by S. Albevario, B. Ruediger, and P. Sundar, whose law is a weak solution to a mollified Boltzmann equation. This process is aptly named the Boltzmann-Enskog process, and it is driven by a Poisson random measure whose compensator includes the law of the Boltzmann-Enskog process. We establish the existence of a probability density for the velocity component of Boltzmann-Enskog processes using a functional-analytic criterion due to A. Debussche and M. Romito. This work was inspired by a similar treatment of the spatially homogeneous Boltzmann equation, by N. Fournier. In a later work by M. Friesen, B. Ruediger, and P. Sundar, they establish the uniqueness of solutions under sufficient moment estimates. Assuming these moment estimates are satisfied, we establish the convergence in distribution of a sequence of Boltzmann-Enskog processes under the assumption of varying collision kernels using the convergence of martingale problems. To show this, we establish tightness of this sequence and use a criterion due to A.G. Bhatt and R.L. Karandikar
Voting in the Mall: Ideology, Grievance, and Political Consumerism
No full textIn this paper we consider how political ideology, attitudes toward historically-marginalized groups, and identification with grievance groups shape Americans’ self-reported participation in political consumerism (i.e., political boycotts and buycotts). Using data from the 2016 and 2020 American National Election Studies (ANES) surveys, we find that ideological intensity has an asymmetrical effect on boycott behavior in 2016, with strong liberals considerably more likely to engage in boycott behavior than strong conservatives. In 2020 the effect of ideological intensity shifts upward dramatically for conservatives, with both liberals and conservatives likely to engage in boycott behavior. We also find mixed results for the effects of attitudes toward and identification with historically-marginalized groups, though we do find that general political participation (and related variables) are strongly related to boycott activity. We discuss the implications of our findings, particularly as they relate to the effects of ideological intensity for liberals and conservatives
Enhancing Soybean Resilience to Abiotic and Biotic Stresses Through Bacterial Seed Treatment and Microbiome Analysis
No full textSoybean (Glycine max L.) productivity is increasingly threatened by abiotic stresses such as drought, flooding, and salinity, as well as biotic stressors, including Rhizoctonia solani and Cercospora infections. Current agricultural practices rely on chemical pesticides, agronomic interventions, and biotechnological approaches, which are often resource-intensive, complex, and environmentally harmful. A promising alternative is the use of naturally occurring beneficial bacteria in soybean roots and rhizospheric soil, yet most research has focused on individual bacterial strains rather than consortium-based approaches. This study investigates the potential of bacterial consortia for enhancing soybean stress tolerance through seed treatment and elucidating their impact on plant health, microbial community dynamics, and gene expression under stress conditions.
Bacterial consortia, Set2 and Setm4 (composed of Bacillus, Pseudomonas, Enterobacter, Leclercia, Kosakonia, Rhizobium, Streptomyces, Achromobacter, and Ensifer) were formulated using bacteria isolated from soybean roots and rhizospheric soil based on their plant growth-promoting characteristics, including exopolysaccharide production, nitrogen fixation, siderophore production, and phosphate solubilization. Under drought, flooding, and salinity stress conditions, soybean plants treated with these bacterial consortia exhibited significantly improved germination percentage, seedling vigor, biomass accumulation, and water content, demonstrating enhanced abiotic stress tolerance.
In addition to abiotic stress mitigation, bacterial seed treatments contributed to increased resistance against Rhizoctonia solani AG-4 infection, likely through induced systemic resistance. Quantitative PCR analysis revealed significant upregulation of defense-related genes in soybean plants treated with Setm4, supporting its role in enhancing plant immunity. Field trials further demonstrated that Setm4-treated plants exhibited greater tolerance to Cercospora leaf blight infections and soybean pod damage. Microbiome analysis of soybean plants under extreme drought conditions revealed distinct shifts in microbial community composition, with surviving plants exhibiting a higher abundance of Pseudomonas and Pantoea, while non-surviving plants were dominated by Streptomyces. Beneficial bacterial strains, including Acinetobacter pittii and Pseudomonas sp., were isolated from drought-stressed plants and demonstrated growth-promoting effects and drought tolerance enhancement in soybean through seed treatment.
These findings highlight the potential of bacterial consortia having multiple beneficial activities as an environmentally sustainable strategy for improving soybean resilience to various stressors. The results from this study contribute to a deeper understanding of plant-microbe interactions and provide a foundation for developing bioinoculants for large-scale applications in sustainable soybean production
The Influence of Conservation Adoption Practices on Crop Insurance Coverage
No full textThis study examines the relationship between conservation practices and insured acreage in U.S. agriculture using a fixed-effects model with a balanced panel dataset of 767 counties over 14 years (2010–2023). Results indicate that higher insured acreage correlates with increased conservation adoption, particularly through government programs that integrate risk management with sustainability efforts.
Key findings reveal that larger farms and those selecting higher coverage levels are more likely to participate in crop insurance, while conservation and forward contract participation complement rather than compete with insurance as risk management tools. The study highlights the importance of aligning conservation incentives with crop insurance programs to enhance both financial security and environmental sustainability. These findings support expanding conservation-linked insurance incentives and targeted financial assistance to ensure farm resilience and long-term land stewardship
Privacy at Scale: A Study of Mobile App Privacy Practices
Get PDFWhat is privacy in a world where people are more connected than ever? Due to the Internet and its rapid advancement, the way information is shared and accessed has fundamentally changed. Millions of people interact with social networks, websites, and applications daily—and with each interaction, some data is collected from the user. In many cases, users cannot access a website or application without first accepting the service’s Privacy Policy. However, these policies often obscure the details of how a consumer’s data is handled, burying important information under dense legal language. In response to growing concerns about transparency, some platforms have recently begun requiring simplified data safety descriptions. These aim to break down complex privacy policies into clear, concise language, making it easier for users to understand what data is being collected, how it’s used, and who it’s shared with. While this is a step in the right direction, questions remain about whether these simplified explanations are enough to truly inform users—or if they simply serve as another layer of compliance without meaningful transparency. Thus, in this thesis, we examine the discrepancies between the data safety labels submitted by organizations on the Google Play Store and their actual privacy practices as described in their privacy policies. This analysis is conducted on a dataset of 1,000 Android applications. To compare the stated and actual practices, we employ two distinct methods: Cosine Similarity, which measures keyword overlap using term frequency, and Contextual Analysis, which evaluates similarity based on language use and semantic meaning. The results of our study reveal a significant level of inconsistency between the data safety labels provided by applications and the actual privacy practices outlined in their policies. While Google Play’s Data Safety section represents a positive step toward enhancing transparency between users and service providers, our findings indicate that further efforts are needed to ensure greater accuracy and build a truly trustworthy digital environment
Graph-Based Analytical Solutions for Undrained Cylindrical Cavity Expansion in Elastoplastic Soils
No full textThe cavity expansion theory has been introduced to geomechanics and geotechnical engineering for over sixty years to predict the relationship between stress and displacement during cavity expansion in geomaterials. Over the past forty years, many analytical solutions have been proposed and developed for the fundamental cavity expansion problem in geomechanics, accounting for various elastoplastic models and boundary conditions. Recently, a novel and simple yet rigorous analytical approach, called the graphical method, was proposed to directly predict the limiting undrained cavity expansion pressure in modified Cam Clay critical state soils. The advantage of this graph-based analytical method lies in its ability to determine the ultimate cavity expansion pressure through the equilibrium equation in Lagrangian form with the mean effective stress as the only variable.
This dissertation aims to extend this novel graph-based analytical method to investigate the stress and displacement responses during undrained cavity expansion in various elastoplastic yield models. These models include both models with smooth yield and potential surfaces, such as original and modified Cam Clay models and shear strain-hardening Drucker-Prager models with both associated and non-associated flow rules, and those with non-smooth yield and potential surfaces, such as the perfect Mohr-Coulomb yield model. For elastoplastic models with smooth yield and potential surfaces, the limit cavity expansion can be readily solved through the Lagrangian description of the radial equilibrium function with respect to the mean effective pressure as the only variable. For those with non-smooth yield and potential surfaces, such as the perfect Mohr-Coulomb yield model addressed in this dissertation, the limit cavity expansion pressure is obtained through the radial equilibrium equation after solving the effective stress components from the constitutive equation in Lagrangian form. Rigorous analytical solutions for stresses and displacements in undrained cavity expansion for perfect Mohr-Coulomb soils can be derived in completely explicit forms, and the intermediacy assumption for the vertical stress commonly adopted in previous formulations is removed
The Influence of Life Skills, Teammate and Coach Behavior, and the Sport Environment on the Mental Well-Being of Intercollegiate Athletes
Get PDFAbstract
Intercollegiate athletics generate significant interest in the United States, where concerns about the health and well-being of student-athletes have gained increased attention in recent years. Student-athletes face the same developmental challenges as their non-athlete college peers, but they also encounter biological, psychological, sociocultural, and spiritual challenges often introduced or exacerbated by their participation in sport. To assist this subgroup of the college student population in managing their various athletic, academic, and personal responsibilities, the National Collegiate Athletic Association (NCAA) has prioritized and implemented life skills programming. Yet, while much has been documented regarding life skills development at the youth sports level, less information is available on life skills development and transfer among collegiate student-athletes.
This study analyzes the associations between life skills and mental well-being among Division I collegiate student-athletes. It also examines the role of influential factors influencing life skill development and transfer, such as coach behavior, teammate behavior, and the sport environment. The Sport Social Work Lab at the University of Kentucky provided a dataset consisting of de-identified survey responses. Through OLS regression, mediation, and moderation analyses, results indicated that general life skills and select life skills, including social and emotional skills, significantly influence mental well-being. Additionally, coach and teammate behavior partially mediate the relationship between life skills and mental well-being. Findings from this study are discussed in the context of life skill development and transfer, limitations, and implications for policy and direct practice with NCAA student-athletes