Hands-On Learning in Focus: Understanding Environmental Programming for Teenagers in Museums

Thesis (Master's)--University of Washington, 2024Despite museums playing a critical role in environmental education, there remains a lack of prolonged, meaningful, environmental programming for teens across North America. This gap raises the question of how the handful of institutions running these programs are managing. This case study was carried out to understand how museums engage teenagers in prolonged, meaningful, environmental programming using hands-on learning practices. Data were collected through semi-structured interviews with 3 staff members from different museums across North America. The results suggest that A) Museums leverage their space, technology and collections as integral components of their programming; B) Effective engagement includes interactions between teens, their peers, and their communities; C) Recruiting participants is a significant hurdle in program implementation. This research solely explores programming from adult perspectives and can be strengthened by including the viewpoints of teenagers, and by conducting extended studies to investigate the long-term effects of participation

Effects of thermal stress and ocean acidification on the larval development of ascidian Boltenia villosa

Climate change and ocean acidification significantly affect the development of many marine organisms, including the solitary ascidian, Boltenia villosa. This study investigates the effects of increased temperature and decreased pH levels on the development and survival rates of B.villosa embryos. It was hypothesised that embryos at higher temperatures would show faster development but lower survival rates while embryos at lower pH conditions would develop slower. In this study, the embryos were exposed to three different temperature conditions, low (9°C), mid (12°C), and high (16°C) and were also placed in seawater that was neutral (pH 7) and a control (pH 8) within each of these temperature settings. The time required for embryos to reach key development stages was observed, as was the survival rate to the tadpole stage. Our results show that embryos subjected to higher temperatures develop faster than those at lower temperatures but have lower survival rates. However, varying pH levels did not significantly affect embryonic development. These findings suggest that warmer temperatures expedite the rate of development but reduce the survivorship of the organism

Locating The Sites of Active Plastids in Coralline Algae

Coralline algae (Corallinales) are ecologically important producers found amongst a variety of marine habitats across the globe. Their secreted calcium carbonate cell walls and the distribution of some families at deep water depths calls for a closer examination into coralline anatomy and physiology. This study located plastids across crustose and articulated morphologies using laser scanning confocal microscopy and scanning electron microscopy. Phycocyanobilin and chlorophyll a fluorescence was highest in cortical and meristematic regions in both crusts and fronds, sometimes in two fluorescent bands. These findings challenged conventional definitions for Calliarthron medulla and cortex layers and were re-defined accordingly. Extending this work across the taxon of Corallinales may provide a unifying definition for medulla and cortex, and plastid roles in medullary cells may reveal more efficient photosynthesis adaptations than previously thought

Allies, Partners, and Prospects: Global Perspectives on the Indo-Pacific

Our report offers an overview of the involvement of the roles that different actors in the region can effectively play in the United States Indo-Pacific Strategy that would also benefit them, and what the United States government should do to foster and strengthen its relations across the Indo-Pacific. At the end of each section, there are specific policy recommendations that stem from the broad strategic recommendations outlined above

Atom/defect classification in Scanning Transmission Electron Microscopy (STEM) Images using Convolutional Neural Networks

Thesis (Master's)--University of Washington, 2024Two-dimensional (2D) materials have shown great capabilities in various research fields such as physics, chemistry, and engineering because of their low dimensionality and versatility of behavior as compared to their bulk counter parts. Parameters such as twist angles between layers, defect concentrations, and strain can drastically change the properties of the 2D material. To study the interactions inside the 2D material at an atomic scale, the use of electron microscopy techniques such as scanning transmission electron microscopy (STEM) is prevalent in their characterization. However, a bottleneck is hit when it comes to interpreting the STEM image data because of the extent of manual labor and subjective decisions required to segment the atomic columns. Here, a novel approach is proposed for atom/defect classification in STEM images of twisted 2D bilayer materials using deep learning-based image segmentation model. Since it is not feasible to generate a training dataset experimentally, a Python library was developed that leverages the Atomic Simulation Environment (ASE) and abTEM to generate train/test data. This enables the user to easily generate a dataset of their 2D material of interest. For this work, the model was trained on moiré twist angles of 0, 1, and 2 degrees of hBN encapsulated CrI3 bilayer and demonstrated a remarkable ability to generalize over unknown angles (1.5°, 2.5°, 3.5°, and 4°), thereby showcasing its robustness and versatility. The model precisely segments the atomic columns with a quantification accuracy of 99.27 ± 0.75%. This work highlights the potential of deep learning algorithms in automating and enhancing the analysis of 2D materials, paving the way for more efficient research and product development in the field

Exploring culturally meaningful definitions of justice and resilience through the lens of sovereign Indigenous foodways

Thesis (Master's)--University of Washington, 2024In this thesis I explore frameworks of environmental justice, food justice, and community resilience that center Indigenous communities and their perspectives. First, I conducted an integrative literature review on environmental injustice that uniquely impacts Indigenous communities, specifically as it relates to water resources. I propose five major pathways through which environmental justice occurs: the physical manipulation of waterways, chemical contamination, the introduction of species, the exploitation of culturally significant species, and global climate change. The supplementary material for chapter one is an expanded list of all literature reviewed. In the second chapter, I present a framework for understanding food justice that integrates pre-existing theories of food justice, food sovereignty, and cultural sovereignty. In the third and final chapter, I have defined a theory of cultural-ecological resilience that builds from existing theories of social-ecological resilience to incorporate the non-tangible, cultural relationships between Indigenous Peoples and their traditional lands and waters. Using my framework for food justice from chapter two, I explore the ways justice within Indigenous food systems cultivates cultural-ecological resilience

Flee or Freeze: The Differential Role of Amygdala Subregions in Fear and Avoidance

Thesis (Master's)--University of Washington, 2024Fear is a powerful emotion that is crucial to the survival in a complex environment. The amygdala, a key brain region implicated in processing fear, is not homogenous but comprises of several subregions, most notably the central amygdala (CEA) and the basolateral amygdala (BLA). To examine their functional differences, this study utilized a novel naturalistic approach-food avoid predator task and a standard classical fear conditioning task to examine defensive responses in CEA and BLA lesioned rats. Both lesioned groups demonstrated impaired fear responses than sham; however, BLA lesioned animals showed more impairments in active defensive responses (i.e., fleeing), while CEA lesioned animals showed more impairments in passive defensive responses (i.e., freezing). Maladaptation of fear can lead to serious mental illnesses; these findings may elucidate how fear is processed and facilitate the discovery of more effective treatment of disorders such as such as post-traumatic stress disorder (PTSD)

Nano-scale to Meso-scale: Practice and Pedagogy of Deep Learning Applied to Molecular Systems

Thesis (Ph.D.)--University of Washington, 2024Deep learning has found its way into the chemical sciences, and brought with it successes that have been observed in “traditional” applications such as computer vision and sentiment analysis.1–3 The integration of these methods into modern industry, pharma, and materials discovery makes it clear that the next generation of chemical and biological scientists and engineers will be operating at the intersection of data science and their respective fields. Unfortunately, nuances in these chemical systems mean that often methods leveraged in computer science applications are not out-of-the box translatable; expert knowledge is required to design a machine learning solution at the intersection of these fields.4–6 Here, this nuanced design process is detailed for two deep learning applications to the prediction of reaction rate constants, critical for understanding and design of reactive systems.7 Additionally, an optional learning event, designed to give undergraduate students an opportunity to learn and apply modern methods at this intersection, is detailed. Finally, work to leverage deep neural machine translation to improve protein thermal stability is presented, and the nuances highlighted. The translator has the ability to produce thermally stable variants of existing proteins or score already generated variants, allowing them to be leveraged at high temperatures where many proteins lose their applicability compared to other materials.

Towards Integrated Audio-Visual Learning: From Vision-to-Audio Generation to a Unified Audio-Visual Framework

Thesis (Ph.D.)--University of Washington, 2024The interplay between audio and visual signals, rich in correlations across various scales, significantly impacts human perception and drives a consistent demand for audio-visual applications across fields such as video production, animation, and virtual reality. Historically, the creation and adaptation of audio content has been predominantly a manual process reliant on the expertise of Foley artists. Exploring automated systems capable of assisting with such tasks and achieving comparable proficiency suggests an intriguing prospect. In recent years, deep learning-based methodologies have shown considerable promise in handling image, video, and text data. Nonetheless, the task of integrating audio with visual inputs introduces distinct challenges that stem from the fundamental differences and complexities inherent to each modality. In particular, techniques for generating non-speech audio, such as music, object material impact sounds, natural sounds, and spatial sound effects, have received limited exploration. Audio and visual signals can be represented in various ways, with their connections varying across different scenarios. The research domain of learning to connect and relate audio and visual signals, termed audio-visual learning, has traditionally focused on either audio-visual representation learning or on generative modeling of one modality conditioned on the other. My research traverses audio-visual learning and connects audio-visual representation and generation from three distinct perspectives. In the first category, my investigation focuses on vision-to-audio generation through an intermediate representation, which serves as a bridge to link visual and audio domains. For instance, musical notes can translate piano keystrokes into their corresponding sounds, and the rhythm of movement can connect dance videos to their accompanying music. The intermediate representation could also be derived from pre-trained deep learning models and act as semantic bridges to facilitate the transition from more general video and background music where the audio-visual relationship is largely subjective. In the second category, my research delves into learning implicit representation through the vision-to-audio generative process. This angle seeks not only to achieve vision-to-audio conversion but also to construct meaningful representations therein. Innovations here include unsupervised models that deduce instrumental sounds from musicians' body movements and diffusion models capable of synthesizing impact sounds from visual cues of object-physical interaction. This exploration reveals the association between visual inputs and various timbre characteristics. Additionally, by mapping indoor scene geometry to room impulse responses at discrete locations, we can infer a continuous acoustic field that enables the rendering of high-fidelity audio for any emitter-listener locations and enhances the realism and immersion of auditory experiences. Finally, in the third part of work, I proposed a unified audio-visual framework that seamlessly merges representation learning and generative modeling. This general approach enables the efficient generation of high-fidelity audio from visual stimuli while constructing robust semantic audio-visual representations. Its applications are broad, ranging from audio-visual retrieval and event classification to audio-only classification, paving the way for more immersive and contextually rich audio-visual experiences

Harmonizing Language and Music: The Potential Role of Voice Pedagogues in Advancing Foreign Language Acquisition through Music

Thesis (D.M.A.)--University of Washington, 2024In our globalized world, being able to speak multiple languages is highly valued. Traditional approaches to language learning face challenges, including mastering pronunciation, understanding cultural nuance, and applying language skills in real-life situations. Researchers have proposed that music and singing have the potential to be underexplored catalysts for linguistic learning. In “Harmonizing Music and Language: The Potential Role of Voice Pedagogues in Advancing Language Acquisition through Music,” I aggregate existing research that describes interactions between music and language cognition; describe specific ways in which voice pedagogues can apply their expertise constructively to improve pronunciation accuracy, rhythmic fluency, and cultural literacy among language learners; and report on specific language instruction projects to which I have contributed over the last year, concluding that music and singing can significantly enhance the language learning environment. This research envisions a change in language education, where language learning transcends the memorization of grammar and vocabulary and becomes a dynamic journey. I hope to encourage educators to consider partnering with voice teachers to consider music- and singing-based approaches to language learning, an approach that brings new insights into the realm of language education