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Articles 391 - 420 of 18422
Full-Text Articles in Entire DC Network
Testing For Local Adaptation In Sympatric Monkeyflowers Growing In Serpentine Seeps And Adjacent Rock Outcrops, Avin Niknafs
Testing For Local Adaptation In Sympatric Monkeyflowers Growing In Serpentine Seeps And Adjacent Rock Outcrops, Avin Niknafs
Master's Theses
Divergent selection across heterogeneous environments can drive ecological differentiation and the evolution of locally adapted populations, even when gene flow occurs. We tested for local adaptation between two sympatric monkeyflowers, Erythranthe guttata and E. serpentinicola (formerly Mimulus), which co-occur on the central coast of California. Erythranthe guttata is a perennial species primarily found in moist serpentine seeps, whereas E. serpentinicola is an annual species restricted to adjacent serpentine rock outcrops. Using a reciprocal transplant experiment with second-generation, greenhouse-derived seed, we quantified germination, survival, and reproductive success across contrasting microhabitats. We further evaluated the relative contributions of species, lineage, …
Topographic And Upwelling Effects On Surface Lagrangian Coherent Structures Of Cape Mendocino, Basil Martin Darby
Topographic And Upwelling Effects On Surface Lagrangian Coherent Structures Of Cape Mendocino, Basil Martin Darby
Master's Theses
The goal of this study is to investigate fine-scale Lagrangian coherent structure (LCS) generation in a coastal upwelling setting with prominent topography using a high-resolution global-ocean circulation model (LLC4320). I examine LCS properties, spatiotemporal evolution and vertical structure, as well as possible connections to submesoscale variability and chlorophyll. The LLC4320 simulation in the Cape Mendocino region is evaluated using high-resolution satellite and other ocean observations. Additionally, this study uses a novel dynamical systems technique by relating the LCS of flow fields to the physical dynamics of the mesoscale-to-submesesoscale transition. It is found that time series of short timescale LCS yield …
Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena
Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena
Master's Theses
The widespread use of AI-based audio deepfakes threatens severely to undermine media integrity and public trust. Speech synthesis techniques have improved dramatically in voice conversion (VC) and text-to-speech (TTS) in recent years, making forgeries sound highly realistic, and concerns are raised about possible malevolent uses. Existing state-of-the-art techniques for identifying fake speech have proven to be effective in some cases but are still limited in application and robustness when faced with novel attacking strategies, different acoustic conditions, or alternative linguistic domains. To address some of these limitations, the current research presents a novel deepfake audio detection system based on personalized …
Digital Neuropsychology And Social Anxiety: The Effect Of Observer Presence And Personality On Stress And Cognition, Ava M. Dixon
Digital Neuropsychology And Social Anxiety: The Effect Of Observer Presence And Personality On Stress And Cognition, Ava M. Dixon
Master's Theses
This study examined how observer presence and social anxiety influence stress and cognitive performance during neuropsychological assessments, focusing on the potential benefits of unsupervised digital testing environments. Eighty university students were randomly assigned to observed or unobserved digital neuropsychological conditions and completed assessments of social cognition and executive functioning and questionnaires of social anxiety and personality. Participants also completed measures of state anxiety and heart rate variability at baseline and after cognitive tests. The findings indicated that observation led to higher subjective anxiety, but it did not produce significant interactions with social anxiety on stress or cognitive performance. Post-hoc analyses …
Towards A Generalized And Optimized Apriori Approach, Artem Abdikov
Towards A Generalized And Optimized Apriori Approach, Artem Abdikov
Master's Theses
Apriori is a machine learning algorithm developed in 1994 by R. Agrawal and R. Srikant for association rule mining purposes. This family of algorithms takes transactional data and analyzes relationships between variables in large datasets. The typical output of such algorithms is a prediction that if users choose item X, it is highly likely that they will also choose item Y. Apriori is known to be a robust algorithm and is used by many large companies in order to analyze user tendencies and even make recommendations. Although Apriori is a powerful algorithm, its original implementation is known to have limitations, …
“What Are We And What’S Coming Next?”: Queer People’S Experiences During Sociopolitical Unrest In The Us, Ariana Cristal Morales
“What Are We And What’S Coming Next?”: Queer People’S Experiences During Sociopolitical Unrest In The Us, Ariana Cristal Morales
Master's Theses
Queer (lesbian, gay, bisexual, transgender, queer, or other gender and sexual identities) folx have become a major focal point during political elections. As political climates have projected forced attacks towards queer populations, society has followed suit. Investigation on the impacts of such changes towards queer folx is important to uncover, as sociopolitical climates have shifted within the last 10 years in the US. The present study utilizes a phenomenological framework to understand the lived experiences of queer participants living in the US from 2015-2025 during political and social shifts. Semi-structured interviews were utilized to explore 10 queer participant’s lived experience …
A Triple Bottom Line Analysis Of Food Waste-To-Bioenergy At California University Campuses: Social Enablers Break Down Economic Barriers, Anjali Sharma
Master's Theses
Greenhouse gas emissions from food waste (FW) and energy generation are two major hurdles to the climate crisis. Previous research shows that waste-to-energy systems may provide a solution to both these challenges, particularly at university campuses, due to their high FW generation and high energy needs. Despite this, few academic institutions in California, US, have adopted waste-to-energy systems, and campus-specific challenges and opportunities associated with these systems remain underexplored. For this study, I use an Environmental, Economic, and Social (EES) lens to document the current landscape of FW management and implementation of food waste-to-bioenergy at campuses in each of the …
The Initial User Experience Of A Gamified Mental Health App, Angill Lynae Oliva
The Initial User Experience Of A Gamified Mental Health App, Angill Lynae Oliva
Master's Theses
Despite the availability of mobile mental health apps, high dropout rates due to low user engagement and attitudes about their effectiveness remain significant challenges. The present study examined the relationship between digital therapeutic alliance (i.e., the efficacy of therapeutic quality for digitalized mental health interventions) and college students’ engagement and perceptions of use with a gamified mental health app, SuperBetter. Digital therapeutic alliance was measured using the Working Alliance Inventory-Short Revised (WAI-SR), while engagement was assessed by the total number of completed activities in the SuperBetter app. Students’ intrinsic motivation was measured using the Intrinsic Motivation Inventory (IMI); and perceptions …
An Exploration Of Image Segmentation Techniques For Real-Time Product Detection, Andrew C. Dunton
An Exploration Of Image Segmentation Techniques For Real-Time Product Detection, Andrew C. Dunton
Master's Theses
Recent progress in LLMs enables advanced multimodal understanding, but their high computational cost necessitates monetization strategies like interactive advertising. While bounding boxes show promise for this concept, they can lack precision and visual appeal. Image segmentation offers a superior solution but faces a dual problem: traditional models demand scarce, costly training data, and open-vocabulary segmentation models like SAM are class-agnostic, unable to semantically identify a "consumer product" object class. In this research, we address these limitations by: 1) developing the Prompt-Guided Inpainting Framework (PGIF), which injects negative prompts to generate robustly annotated synthetic segmented product images; 2) investigating the Class-Agnostic …
Radiation Hardness Study Of Finfet And Gate-All-Around Fet Sram, Albert Lu
Radiation Hardness Study Of Finfet And Gate-All-Around Fet Sram, Albert Lu
Master's Theses
Radiation, such as alpha particles or neutrons, is hard to control and can come from sources such as trace impurities or cosmic rays from space. These can then strike a semiconductor device, such as a Static Random Access Memory (SRAM) cell, and cause the SRAM to have its bit flipped. This bit flip is often just a temporary effect and is thus called a single event upset (SEU). Although it is temporary, a bit flip can cause severe consequences, such as affecting program functionality by causing incorrect data to be used. This is made worse in critical environments that need …
Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken
Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken
Master's Theses
Diablo winds in northern California are known for driving some of the most destructive wildfires in state history. The Camp Fire of 2018, which caused at least 85 civilian fatalities, is just one example of the devastating outcomes associated with these rapidly developing downslope windstorms. While they are known to occur most frequently from fall through spring, much about the structure, evolution, and full spatial extent of these events remains poorly understood. Most previous studies have focused on a limited number of high-impact cases or have defined events using humidity-based thresholds in isolated regions such as the North Bay. As …
Development Of New Design Criteria For Coastal Highway Embankment Under Wave-Induced Loading, Udaya Bilas Panta
Development Of New Design Criteria For Coastal Highway Embankment Under Wave-Induced Loading, Udaya Bilas Panta
Master's Theses
In the face of intensifying hurricanes and rising sea levels, Louisiana’s coastal highways, lifelines for communities and commerce, stand increasingly vulnerable. This thesis introduces a pioneering methodology for designing geosynthetic-reinforced highway embankments capable of withstanding wave-induced loading and rapid drawdown scenarios, the most critical failure condition identified in coastal environments. By integrating statistical wave modeling, advanced numerical simulations using SEEP/W and SLOPE/W, and a comprehensive parametric analysis, the study develops a novel hybrid regression formula that accurately predicts optimal reinforcement lengths based on site-specific geotechnical and hydraulic parameters. Validated against Hurricane Katrina data and real-world soil profiles from Cameron Parish, …
The Potential Co-Occurrence Of Perfectionism, Food Insecurity, And Gpa With Orthorexia Nervosa Risk, Samantha Kay Gould
The Potential Co-Occurrence Of Perfectionism, Food Insecurity, And Gpa With Orthorexia Nervosa Risk, Samantha Kay Gould
Master's Theses
There are indeterminate risk, prevalence, and correlation data on orthorexia nervosa (ON) as shown by current literature on disordered eating (Rodgers et al., 2021). As a roughly defined disordered eating pattern, ON may be better understood after identifying associations among other attributes in a college student sample (Abdullah et al., 2020; Mavrandrea & Gonidakis, 2023; Parra-Fernández, 2019; Rogowska et al., 2021). A cooccurrence and influence of perfectionism, food insecurity, and grade point average (GPA) with ON risk was hypothesized since current literature suggests college students exhibit each of these characteristics independently (Abdullah et al., 2020; Ambwani et al., 2019; Caferoglu …
Exploring The Effectiveness Of Virtual Reality Learning Through Use Of Visual Eye-Tracking Analytics (Veta) And Biological Measurements, Mckinley Anne Sherman
Exploring The Effectiveness Of Virtual Reality Learning Through Use Of Visual Eye-Tracking Analytics (Veta) And Biological Measurements, Mckinley Anne Sherman
Master's Theses
Virtual Reality (VR) offers an immersive and interactive platform for experiential learning. The purpose of this thesis was to evaluate the relationship between physiological responses and cognitive workload within a VR learning environment and to explore VR as an effective instructional tool. This research compared participant engagement, stress, and learning performance within a 6th-grade science module developed in VR by incorporating biometric data collected via Polar H10 heart rate monitor and Varjo Areo VR headset eye-tracking. Thirty-three participants completed a pre-lesson demographic survey, post-lesson survey, VR sickness questionnaire, and the NASA Task Load Index (NASA-TLX). While completing the lesson, the …
Food Neophobia And Its Prevalence Among College Students In The United States, Joanne Mwendi Ponnappa
Food Neophobia And Its Prevalence Among College Students In The United States, Joanne Mwendi Ponnappa
Master's Theses
Food neophobia “the reluctance to try unfamiliar foods” may influence diet variety and cultural food acceptance among young adults. College students represent a critical group for studying this behavior, as they are developing independent eating habits that can persist into adulthood. This study examined the prevalence of food neophobia among U.S. college students and evaluated how academic background, travel, cultural exposure, and demographic factors influence openness to trying unfamiliar foods. A cross-sectional online survey was administered via Qualtrics to 264 college students across the United States. The Food Neophobia Scale (FNS; Pliner & Hobden, 1992) was used to assess reluctance …
Early Visual Predictors Of Progression To Alzheimer’S Disease And Dementia With Lewy Bodies, Abril Baez
Early Visual Predictors Of Progression To Alzheimer’S Disease And Dementia With Lewy Bodies, Abril Baez
Master's Theses
We examined whether specific visual cognitive skills predict progression from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD), or dementia with Lewy bodies (DLB). The Benson Complex Figure Task (BCFT) was used to measure visual perception and construction (copy), and visual memory (recall). National Alzheimer Coordination Center longitudinal dataset included participants who remained stable (MCI-stable; n =2630), progressed to AD (MCI-AD; n =798), or progressed to DLB (MCI-DLB; n =59). Baseline BCFT scores were entered into logistic regression models predicting diagnostic outcome. Impaired copy performance was significantly associated with MCI-DLB (B = 0.79, OR = 2.21, BCa CI [0.26, 1.36], …
A Convolutional Neural Network Approach To Breast Cancer Tumor Boundary Detection, James Leah Matlosz
A Convolutional Neural Network Approach To Breast Cancer Tumor Boundary Detection, James Leah Matlosz
Master's Theses
Breast cancer is the second most common form of cancer and often goes undetected in its initial stages due to its subtle symptoms. As the tumors grow, they become more difficult to surgically remove with clean borders. To minimize the chance of recurrence, a 2D convolutional neural network is developed in this work for delineating tumor boundaries. Specifically, the U-shaped network model is trained, validated, and tested with longitudinal MRI scans of patients diagnosed with breast cancer and undergoing neoadjuvant therapy. For training, image masks were generated as ground truths using signal enhancement ratio segmentation, thresholding, and contour detection. The …
Phylogenetic Comparative Vocal Evolution, Casper W. Buchanan
Phylogenetic Comparative Vocal Evolution, Casper W. Buchanan
Master's Theses
Vocal learning is a trait unique to humans, bats, cetaceans, primates, and birds (Jarvis & Nottebohm, 1997; McComb & Semple, 2005; Wilbrecht & Nottebohm, 2003). Although there has been extensive research on vocal learning in songbirds, parrots are an even closer proxy to human learning, as they are social, intelligent, and lifelong learners, with some having repertoires of over 300 sounds (Benedict et al., 2022; Péron et al., 2011; Thomsen et al., 2019; Toft & Wright, 2015). Elevated vocal learning can be attributed to the need for parrots to have strong communication skills through the sharing of information over foraging, …
Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil
Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil
Master's Theses
Healthcare remains a prime target for cyberattacks, with insider misuse and credential compromise posing major risks to Electronic Health Records (EHRs). This thesis introduces a role-aware, explainable anomaly detection and response framework integrated with OpenEMR to address post-authentication threats. Four models—Local Outlier Factor (LOF), Isolation Forest, Autoencoder, and Graph Neural Network (GNN)—detect behavioral deviations across temporal, device, and role-based features, with LOF serving as the primary runtime detector. A configurable policy engine maps anomaly severity to proportional actions, from email alerts to read-only restrictions or account suspension, all reversible and auditable. Evaluation on real EHR logs shows the system’s operational …
Development Of A Colorectal Cancer Spheroid Model To Improve The Accuracy Of Preclinical Drug Testing, Jillian Trilevsky
Development Of A Colorectal Cancer Spheroid Model To Improve The Accuracy Of Preclinical Drug Testing, Jillian Trilevsky
Master's Theses
Colorectal cancer is the second leading cause of cancer related deaths worldwide. It currently affects millions of people across the globe and is only expected to increase in impact over the coming years. The most common treatment for metastatic colon cancer is chemotherapy, however, the development of chemotherapeutic drugs is a long and expensive process. A large portion of this development process is spent in preclinical drug testing. However, the models used often lack enough physiological relevance to guarantee the drug’s success in a clinical trial. Due to this gap in testing, researchers seek to develop a more physiologically relevant …
Adjoint Enhanced Panel Methods, Christopher Sheehan
Adjoint Enhanced Panel Methods, Christopher Sheehan
Master's Theses
This thesis describes the development, implementation, and validation of an adjoint-enhanced panel method for two-dimensional airfoil analysis. While conventional panel methods are computationally efficient for flow analysis, they typically rely on relatively computationally expensive finite differencing for gradient calculation in design optimization or sensitivity studies, a limitation addressed by employing the discrete adjoint method. The core of this work involves integrating the discrete adjoint method with a Hess-Smith panel code utilizing Class-Shape Transformation (CST) for airfoil parameterization, which requires the analytical derivation of sensitivities for panel geometry, boundary conditions, and the aerodynamic influence matrix with respect to the CST design …
Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain
Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain
Master's Theses
Accurately pricing American options with market data presents a significant challenge, as foundational models like the Black-Scholes-Merton (BSM) model rely on assumptions that deviate from real-world financial data -- such as log-normal returns, constant volatility, and no dividends -- and fail to account for the key early exercise feature of American options. While parametric models can adjust for these features, the complexity of the resulting models renders them prohibitively difficult to apply in practice for nonspecialists. In response, modern machine learning (ML) techniques provide a set of flexible and powerful alternatives, and recent research has explored the application of ML …
Gene Expression Of Anthocyanin Pigments In The California Native Plant Leptosiphon Parviflorus: Interactions Between Flower Color Morphology And Abiotic Stressors, Weston Gonor
Master's Theses
For plants to survive in harsh conditions imposed by abiotic stressors, they must develop mechanisms of adaptation. One of the common types of adaptation seen in plants is the production of anthocyanin pigments, which have been shown to protect plants from UV radiation, metabolic stress, and drought. In this study, we used the flower color polymorphic species Leptosiphon parviflorus to investigate the role of anthocyanin pigments in protecting plants from abiotic stress. To accomplish this, RNA samples were taken from flower, leaf and root tissue of different flower color morphs of Leptosiphon parviflorus (Polemoniaceae) grown in high magnesium and water …
Alpine Plants And Climate Change: Tracking Community Shifts In Yosemite National, Brooke L. Wallasch
Alpine Plants And Climate Change: Tracking Community Shifts In Yosemite National, Brooke L. Wallasch
Master's Theses
As climate change progresses, alpine plant communities are predicted to shift upslope as they track temperature over time. Relative to lowland environments, alpine areas are experiencing a faster rate of temperature change due to a phenomenon referred to as elevation-dependent warming. A common approach for tracking plant communities shifts over time, is to conduct resurveys of the same area at several time points, as the Global Observational Research Initiative in Alpine Environments (GLORIA) has done on mountain summits around the world since 2001. In 2011-2013, GLORIA developed a supplemental survey method whereby belt transects were established downslope of summits in …
Using Hydraulic Simulations To Determine The Effects Of Tidal Behavior And Riparian Restoration On Chorro Creek, Jonathan L. Maas
Using Hydraulic Simulations To Determine The Effects Of Tidal Behavior And Riparian Restoration On Chorro Creek, Jonathan L. Maas
Master's Theses
This thesis examines how tidal backwater effects and riparian restoration influence flooding in the Chorro Creek watershed, a major tributary to the Morro Bay Estuary on California’s Central Coast. Restoration efforts, including levee removal, floodplain reconnection, and revegetation have attempted to improve ecological function and reduce sediment transport. However, recent flood events suggest that these changes may also affect local hydraulics in ways not fully anticipated, particularly under the influence of tides and sea level rise. To analyze these dynamics, a two-dimensional HEC-RAS model was developed using LiDAR terrain, historical imagery, and field data collected from pressure and ultrasonic gauges. …
Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff
Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff
Master's Theses
Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …
Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach
Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach
Master's Theses
As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …
Sparse-Data Orbit Estimation In Low Earth Orbit Using The Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter, Nicholas J. Oden
Sparse-Data Orbit Estimation In Low Earth Orbit Using The Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter, Nicholas J. Oden
Master's Theses
The number of space objects (SOs) in low Earth orbit (LEO) continues to increase rapidly, creating challenges for the current ground-based tracking network, which cannot accommodate the projected growth in SOs. Catalog maintenance relies on frequent observations for reliable reacquisition, with Two-Line Element (TLE) sets typically generated daily to mitigate rapid error growth from poor TLE accuracy. This constraint limits the ability to track more objects with existing infrastructure. This work evaluates the Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter (MCMC EnGMF), a nonlinear, non-Gaussian filter well-suited for sparse tracking scenarios where higher post-update accuracy is needed to reduce …
An Evaluation Of The Relationship Between Beef Cattle Grazing Activity Traits And Conception Methods During The Breeding Season, Jason Dubowsky
An Evaluation Of The Relationship Between Beef Cattle Grazing Activity Traits And Conception Methods During The Breeding Season, Jason Dubowsky
Master's Theses
Efficient use of native rangelands and improved reproductive success are primary objectives in beef cattle production. Grazing behavior during the breeding season may be influenced by pasture characteristics, including size and water availability, as well as physiological differences due to reproductive status. This study aimed to evaluate the relationship between grazing activity and conception method in crossbred Angus cows over a 2-year period. The study was conducted during the winter months (December – February) on the Central Coast of California with a mean temperate of 53 degrees Fahrenheit. Cows (n = 76) were blocked by age and then randomly assigned …
Dietary Intake And Changes In Body Composition Over The Course Of One Season In Ncaa Division 1 Football Players, Blayke W. Harrison
Dietary Intake And Changes In Body Composition Over The Course Of One Season In Ncaa Division 1 Football Players, Blayke W. Harrison
Master's Theses
Energy intake and macronutrient composition of an athlete’s diet is highly important when considering performance. Additionally, having a favorable body composition (i.e. low levels of fat mass and high levels of lean body mass) is crucial in high-level athletes.The role of nutrition-related support personnel is highly needed by many collegiate athletics programs to achieve these outcomes, yet this resource seems to be undervalued and underused in many settings. The present thesis investigates the effects of providing nutritional support to improve dietary habits and compare changes in specific body composition metrics over the course of one season (pre- and post-season) among …