8413 research outputs found
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Active Learning in Undergraduate (Micro)Biology Courses
No full textThis qualitative case study explores how students experienced an undergraduate microbiology course redesigned to integrate active learning within a combined lab–lecture format. The study was grounded in Vygotsky’s theory of social constructivism and examined how this environment shaped student engagement, conceptual understanding, confidence, and retention. Data came from three rounds of student interviews, written reflections submitted after each content unit, and instructor observations documented through photographs and video. The research was conducted at a Hispanic-serving community college in Northern Nevada.The course design drew on Bybee’s 5E instructional model, which emphasizes engagement, exploration, explanation, elaboration, and evaluation. Students encountered microbiological concepts through hands-on labs, physical models, real-world inquiry, peer teaching, and collaborative discussions. Formative assessments were also used to check understanding and align with ICAP’s (Interactive, Constructive, Active, and Passive) learning modes.
Thematic analysis identified seven interconnected themes: collaboration, community, comprehension, confidence, learning experience, recall, and retention. Students described moving away from passive learning toward more active participation. Many reported greater clarity, motivation, and a sense of belonging in the classroom. They often credited the integration of lab and lecture, along with tactile and collaborative activities, for helping them retain information more effectively and connect more deeply with the content. Students also emphasized the importance of the supportive classroom climate created by peer interaction and instructor encouragement.
Overall, the findings suggest that integrated, socially supportive, and inquiry-based approaches can strengthen student success in microbiology and may hold promise for STEM education more broadly
Exploring relaxation of magnetization in paramagnetic molecules
No full textRelaxation of magnetization in paramagnetic molecules consists of several distinct mechanisms that are often difficult to elucidate. The goal of this work is to explore different theoretical approaches to uncovering contributions of different mechanisms to magnetic relaxation. We demonstrated on the examples of the DyCl6(TiCp2)3 and Dy(terpyNO2)(NO3)3 complexes that changes in molecular geometries of paramagnetic molecules due to isomerization or molecular environment (gas, solution, crystal phase) can strongly affect the magnetization relaxation mechanisms. We showed that small geometric changes induced by molecular environment can affect the resonances between the spin and vibrational states, and therefore, the Orbach relaxation rate. This finding highlights the crucial shortcoming of studying magnetic relaxation of complex molecular systems using the electronic structure of a single molecule in vacuum. The molecular dynamics simulations of the Dy(terpyNO2)(NO3)3 complex in acetonitrile solution revealed a new structure with an acetonitrile molecule coordinated directly to the Dy ion, which significantly changed the crystal field symmetry and increased the magnetic anisotropy barrier. We discovered a strong correlation between the partial atomic charges on the ligands and the effective barrier of magnetization. Based on this discovery, we proposed a new design strategy for paramagnetic molecules with large effective barrier of magnetization. Our study highlighted the important role played by the mixing of M_J pseudospin states in the relaxation of magnetization in paramagnetic molecules. We implemented a very computationally efficient crystal field based approach to calculate spin-vibrational (nonadiabatic) couplings responsible for the magnetization relaxation in lanthanide complexes. Finally, we explored the possibility of simulating the magnetization dynamics in paramagnetic molecules with multiple electron spin centers on a quantum computer. We simulated the time-evolution of a three-spin state of a paramagnetic Cu(cryptate) complex using the quantum Yang-Baxter equation (QuYBE) algorithm. We also showed that we can consider response to the external magnetic field via dielectric polarization of pairs of spins and transform the resulting Hamiltonian into that for dimerized XY chain. We argued that this can allow us to extend the applications of the QuYBE algorithm to study quench dynamics and local observables
Business Intelligence for U.S. Agricultural Trade: Design and Implementation of an Interactive Power BI Dashboard
No full textReliable agricultural trade information is essential for guiding production, policy,and market decisions, yet these datasets are often scattered, inconsistently formatted,
and difficult for non-specialists to interpret. This thesis presents an interactive vi-
sualization system that integrates multiple U.S. Department of Agriculture (USDA)
datasets including the Foreign Agricultural Trade of the United States (FATUS) and
state-level trade summaries into a unified analytical dashboard built in Microsoft
Power BI.
The dashboard allows users to explore trade patterns across products, states, and
years using interactive maps, bar charts, and key performance indicators. Distinct
color schemes clearly separate exports and imports, helping users follow trade flows
and compare major commodities such as corn, soybeans, and cotton. Filters support
flexible analysis, making it possible to observe how trade relationships shift over time
and across regions.
Validation included technical checks and a usability study with graduate students
and researchers at the University of Nevada, Reno. Participants completed a set of
analytical tasks and rated the dashboard’s navigation, filters, and visual clarity. Most
tasks were answered accurately, with only minor confusion on questions involving
geographic interpretation. Questionnaire ratings were consistently positive. ANOVA
results showed no significant effects of computer proficiency or frequency of data-tool
use, but familiarity with visualization tools did have a significant impact, with more
experienced users reporting smoother navigation and clearer filter interactions.
Overall, the dashboard effectively transforms fragmented agricultural trade data
into clear, interactive insights. It supports accessible exploration of U.S. trade pat-
terns for users with diverse experience levels and offers a practical, scalable model for
developing analytical dashboards in other domains requiring transparency, usability,
and data-driven understanding
Temporal Dynamics and Perceptual Consequences of Face Adaptation
No full textThis dissertation examines how the temporal dynamics and perceptual consequences of face adaptation differ for own-race and other-race faces. Across a series of psychophysical and EEG studies, we manipulated adaptor characteristics, including the number and duration of adapting events, total exposure time, and adaptor race, to determine how these factors shape adaptation magnitude and its perceptual outcomes. Our results demonstrate that adaptation is influenced not only by total exposure duration but also by the number of adapting events. Own-race faces consistently produced faster behavioral and neural renormalization than other-race faces, highlighting the role of perceptual expertise in shaping the efficiency of face adaptation. Adaptation also enhanced visual search performance, particularly when adaptor and distractor race were congruent, and these performance benefits emerged without changes in eye-movement patterns, suggesting increased stimulus salience rather than altered search strategies. Overall, these findings indicate that face adaptation is an experience-dependent process that dynamically recalibrates perceptual norms and can improve visual search performance in race-relevant contexts
Shin Buddhism as Disability Rhetoric
No full textIn this dissertation, I apply my theory of Shin Buddhism as disability rhetoric to a variety of texts within the greater corpus of Shin literature, focusing especially on The Collected Works of Shinran. This dissertation is conceptually structured around four major themes: vulnerability, metis, deep hearing, and naturalness. These four themes are the guiding threads which wend their way through the chapters of this text. In Chapter 1, I first exhibit the historical trajectory of disability rhetoric as it was employed and developed by the Seven Pure Land Masters and Shinran Shonin. After that, I explore three important Shin Buddhist topoi: dependence, spatiality, and temporality. In Chapter 2, I explore the core Shin Buddhist practice of deep hearing and conceptualize it as a sacred form of disabled rhetorical listening. In Chapter 3, I provide a rhetorical analysis of Hisako Nakamura’s autobiography, The Hands and Feet of the Heart. I use this exploration to better theorize Shin Buddhist rhetorics of touch. In Chapter 4, I provide a rhetorical analysis of Manshi Kiyozawa’s life and essays. Doing so allows me to better theorize Shin Buddhist rhetorics of failure. Finally, in Chapter 5, I explore the Shin Buddhist end-times rhetoric of mappo (the final dharma age) to conceptualize Shin Buddhism in terms of “eschatological disability.” I conceptually link this mode of rhetoric to the current breakdown of contemporary world orders, suggesting some possibilities for new beginnings. Ultimately, I find that Shin Buddhist disability rhetoric results in a reconstitution of human subjectivity characterized by greater affective sensitivity, intuitive wisdom, and psychological flexibility, all of which allows subjects to navigate precarious rhetorical and life situations with naturalness and spiritual buoyancy. In this way, Shin Buddhist disability rhetoric offers tools, techniques, and new ways of being that can help us all (disabled or not) to flourish during times of crisis and uncertainty
A Synopsis of the Lovász Local Lemma: Generalizations, Applications, and Algorithms
No full textThe Lovász Local Lemma, introduced by Paul Erdős and László Lovász in 1975, stands as one of the most powerful tools in the Probabilistic Method. This thesis traces the historical development of the Lovász Local Lemma from its origins in Erdős’s pioneering probabilistic arguments to its formalization and generalizations by Lovász along with other contributors. Beginning with the motivation rooted in Ramsey theory, hypergraph coloring problems, and others, we explore how the Lovász Local Lemma transformed probabilistic existence proofs in Combinatorics and explore its applications. We also examine some generalizations of the lemma, including the algorithmic versions introduced by Beck (1991) and Moser–Tardos (2010)
Enhancing Infrastructure Monitoring with Calibrated Vision Language Model Ensembles: A Graffiti Detection Case Study
No full textUrban transit authorities face significant challenges in efficiently monitoring distributed infrastructure assets. This dissertation presents a novel three-stage pipeline for automated infrastructure condition assessment: (1) GPS-based geofence creation that automatically defines inspection boundaries, (2) YOLOv11-powered detection optimized for transit infrastructure, and (3) damage assessment using a specialized Vision Language Model (VLM) ensemble. Our ensemble approach employs probability calibration and weight optimization, outperforming individual models with an 84.4% F1 score. To address extreme data scarcity, we developed a synthetic graffiti generation methodology, expanding from just 3 real examples to a comprehensive evaluation dataset with balanced color representation. Experiments utilized data collected along 227.58 miles of bus routes covering 778 unique bus stops across the Reno metro area. The system operates efficiently on standard hardware with geofence-triggered processing, making advanced VLM technology accessible for practical transit authority deployment. Key contributions include: (1) a pipeline architecture that reduces computational requirements by 95% compared to continuous processing; (2) ensemble techniques using isotonic regression calibration and differential evolution optimization that significantly improve detection accuracy; (3) a parametric graffiti generation methodology creating realistic synthetic data with controllable characteristics; and (4) a color-specific analysis framework revealing critical insights about model performance across different visual characteristics. Ablation studies demonstrate that while traditional CNN models catastrophically fail on unseen variations, VLMs maintain more consistent behavior across varied visual characteristics, highlighting their superior generalization capabilities. The system transforms infrastructure monitoring from a manual, subjective process that burdens drivers into a data-driven approach supporting proactive maintenance and strategic planning
Benefits of Balanced Mix Design: Evidence from State Implementation Efforts
No full textThis Technical Brief highlights the benefits of implementing Balanced Mix Design (BMD) for asphalt mixtures by State Departments of Transportation (DOTs). While the full impact of BMD requires time to quantify, data from States with several years of implementation demonstrate measurable improvements in pavement performance and service life. These findings offer agency and industry stakeholders valuable evidence to support broader adoption of BMD to enhance mixture durability, optimize the use of innovative and recycled materials, and improve long-term cost efficiency of asphalt pavements.U.S. Department of TransportationFederal Highway Administratio
Role Shifting and Spatial Organization for Robotic Signing of American Sign Language
No full textFluent sign languages rely on spatial structure, perspective, and the coordinated use of the upper body. Yet most existing robotic systems in sign language reproduce isolated words or alphabets, offering little support for discourse-level communication where signers shift perspectives or describe interactions between people. A major limitation is the lack of role shifting, the linguistic device through which signers adopt different viewpoints by repositioning the signing space through body orientation and arm placement. This work introduces a motion-generation framework that enables a humanoid robot to perform American Sign Language (ASL) sentences with linguistically grounded role shifting. The system organizes the signing space into referent-specific regions (“signer’s squares”), coordinates torso rotation with arm motion to shift narrative perspective, and preserves the linguistic constraints of different sign types. The framework was implemented and evaluated in simulation on the Unitree G1 humanoid robot, demonstrating that the system can reliably reposition signs and execute role-shifting behaviors across different signer’s squares. A complementary case-study evaluation with an ASL-fluent collaborator revealed issues not visible in the technical tests, which led to refinements in spatial calibration and timing. Together, these results show that modeling perspective and spatial consistency structure produce robotic signing that is clearer and more aligned with how ASL encodes meaning