Bioculture Journal
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Designing to Support Sense of Agency for Time Spent on Digital Interfaces
No full textThesis (Ph.D.)--University of Washington, 2022App designers often exploit psychological vulnerabilities to maximize clicks, views, and time on site. When people attempt to resist such media use, their failure rate is higher than for any other temptation in everyday life. Consequently, users often report feeling dissatisfied and regretful of the time that they spend in apps. In response, concerned design practitioners and researchers have innovated ‘screen time tools’ that let users track and limit the time they spend on digital devices. Yet users report that reducing screen time is a poor proxy for their actual goals, that they are concerned with not only the quantity but also the quality of the time they spend online, so the problem persists. In this dissertation, I investigate how to respect the user’s time and attention by designing digital interfaces for a greater sense of user agency, i.e., the experience of control over one’s actions and their outcomes. My research on the YouTube mobile app, a common site of problematic use, finds that a majority of user goals are about shifting the quality of the content they consume on smartphones, not the quantity. Through a survey and co-design activities, I identify specific features that lead users to feel more or less control over how they spend their time on YouTube. Based on these features, I design and develop the SwitchTube mobile app, in which users can toggle between two interfaces when watching YouTube videos: Focus Mode (search-first) and Explore Mode (recommendations-first). In a field deployment of the SwitchTube app with 46 U.S. participants, I find that Focus Mode helps them realize a greater sense of agency without reducing their time spent in the app. My work highlights the need to think beyond ‘screen time’ and advances sense of agency as an alternative lens for addressing user frustrations. I highlight how the design community might identify and call out ‘attention capture dark patterns,’ conceptualize and measure sense of agency, and how flexible interfaces might adapt support for sense of agency to suit different use cases. Ultimately, sense of agency is not only associated with positive technology use outcomes, but also matters to users in its own right as a basic psychological need
The Effects of Multiple Environmental Stressors on the Respiration Rate of Mytilus galloprovincialis
No full textIntertidal organisms are subject to environmental variations that may influence their
physiological performance. As processes such as respiration depend on gas exchange between
organisms and their environment, they are potentially affected by water temperature and velocity.
In this study, we compare the effects of multiple environmental stressors (temperature and flow
velocity) on the respiration rate in two mytilids, the Mediterranean mussel, Mytilus
galloprovincialis and the temperate bay mussel M. trossulus. Thermal performance curves (5, 11,
17, 23, and 29 °C) for respiration rate were quantified at five different flow velocities (2, 4, 6, 10,
20 cm s-1) in a fully crossed design. Well-defined thermal performance curves were present at
moderate to high water velocities, whereas, at the lowest velocity (2 cm s-1) respiration rates
remained low across all temperatures. Although Mediterranean mussels displayed higher thermal
optima than Bay mussels under moderate flow speeds (4-6 cm s-1), those differences were absent
at higher flow velocities (>10 cm s-1). These results highlight the importance of considering
hydrodynamic conditions when estimating thermal tolerance in marine mussels
Design principles for cadmium chalcogenide nanoparticle assembly via peptoids
No full textThesis (Ph.D.)--University of Washington, 2022Self-assembled organic nanomaterials can be generated by bottom-up assembly pathways where the structure is controlled by the organic sequence and altered using pH, temperature, and solvation. These nanomaterials have been used as scaffolds for assembly of inorganic materials but are limited to architectures accessible by the organic monomers. In contrast, self-assembled structures based on inorganic nanoparticles typically rely on physical packing and drying effects to achieve uniform superlattices. By combining these two chemistries to access inorganic-organic nanostructures, we aim to understand the key factors that govern the assembly pathway and structural outcomes in hybrid systems. This dissertation focuses on the assembly of peptidomimetic poly-N-substituted glycines, also known as peptoids. We explore the combination of peptoids with cadmium chalcogenide clusters and quantum dots (QDs) to generate hybrid materials. By creating a set of design principles for controlling the structure and structural evolution of hybrid peptoid-QD assemblies we are closer to the predictive synthesis of complex hybrid matter.Chapter 1 introduces the field of hybrid nanomaterials with a focus on peptoids and semiconducting nanoparticles. The properties, functions, and assembly of peptoids and nanoparticles are reviewed and the inherent challenges in coupling these two disparate building blocks are highlighted. Chapter 2 demonstrates the use of preformed peptoid nanostructures as scaffolds for CdSe nanoparticle assembly via an irreversibly formed covalent linkage. The structure of the resulting hybrid materials is explored using ex-situ transmission electron microscopy (TEM) and atomic force microscopy (AFM), and methods to control the density of nanoparticles on the peptoid surfaces are developed. Furthermore, we probe the chemistry underlying the covalent conjugation using 1H NMR spectroscopy. Chapter 3 describes a bottom-up approach to QD assembly with peptoids that relies on reversible peptoid monomer coordination to QD surfaces. The synthesis of hybrid QD/peptoid monomers is developed. The surface chemistry and size of the QD were demonstrated as viable handles to alter the hybrid monomer solubility in various solvents, ultimately resulting in rational access to different hybrid morphologies
gnss-ir derived accumulation history at the GNSS sites LTHW, UTHW, and KHLR maintained by unavco and the polenet team.
No full textAccumulation time series were determined using GNSS interferometric reflectometry and MCMC inverse methods. Sites include KHLR, LTHW, and UTHW long-term GNSS stations on the Thwaites and Kohler glaciers. Included are the daily reflector heights of the phase center of the GNSS reciever antenna derived from median filtering daily reflections from satellite azimuths below 7 degrees. Also included are the daily accumulation time series determined from reflector height change at the site of each receiver
Marine Bacteria Colonization Rates on Microplastics in the North Pacific Subtropical Gyre
No full textPlastic pollution is a growing concern in the microecology of the oceans. Studying bacteria
colonization rates on plastic provides one way of understanding of how toxic debris can move through the
food chain through ingestion. This process of toxins moving through the food chain is called
biomagnification and can eventually reach humans. To evaluate bacterial colonization rates, seawater was
collected in coastal waters of Hawaii and near the Pacific garbage patch (GPGP). Seawater
was intermixed with 5 different kinds of clean plastics then timed to determine how long it took bacteria
to colonize the plastic surfaces. Bacteria on the plastic were counted under an epifluorescence microscope
then divided by the time of colonization to determine the rate. Alongside the colonization rate, surface
microplastics were collected with a manta net; then sized and classified with a dissection microscope.
Seawater was collected from a Niskin bottle attached to a CTD rosette to calculate bacterial abundance
with the use of a Guava flow cytometer. The findings of the research displayed little to no correlation
between surface bacterial abundance and plastic density, with an R2 value of 0.1072. Bacteria were found
to colonize plastics at 48 and 96 hours in the waters near the Pacific garbage patch with a rate of 7.4E+04
cells/mm. The colonization rates and plastic abundance support evidence of plastics being integrated into
the ocean ecology
Design and Characterization of Optical Metasurface Systems
No full textThesis (Ph.D.)--University of Washington, 2022The importance of optics is increasing in our daily lives, from medical devices to the cameras that facilitate global communications. Because of their universal use, the size, scale and quality of optical elements grow in importance for technological innovations. Over the last few decades, the downscaling of complementary metal–oxide–semiconductor (CMOS) sensors thanks to Moore's law have resulted in a dramatic reduction in the size of optical systems, including imaging and non-imaging systems. However, most optical systems are now limited in size by the optical element itself, not the sensor. One promising candidate for enabling further miniaturization is metasurfaces, which are ultrathin elements comprising arrays of subwavelength-spaced scattering elements. These metasurface elements can achieve a broad class of functionalities in a flat form factor, transforming the phase, amplitude, and polarization of incident electromagnetic radiation. While metasurfaces provide a large number of degrees of freedom to design complex optical functions, their full potential and applicability have yet to be discovered. This dissertation will investigate a variety of different metasurface designs and expand on the functionality of these optical elements as solutions for imaging and non-imaging systems.In the body of this dissertation, we investigated how to design dielectric metasurface subwavelength scattering elements to optimize them for a variety of functions. The designs discussed represent the research progress made towards developing optical sensors for imaging and non-imaging systems that are more compact. In particular, this Thesis highlights designs for silicon nitride based scattering elements for 1D and 2D EDOF metasurfaces in the visible regime for full color imaging. This is followed by a more general methodology that uses EDOF lenses in conjunction with computational imaging to eliminate broadband chromatic aberrations. Lastly, there are proposed designs for composite metasurface visors that can overcome several challenges of near eye augmented reality visors, including reducing bulkiness, addressing FOV limitations, minimizing chromatic aberrations and improving the see-through quality. The demonstrated approach may find applications in microscopy, planar cameras, medical imaging, and augmented reality
Understanding Variational Autoencoders and Disentanglement Metrics
No full textThesis (Master's)--University of Washington, 2022In this thesis, we conduct a thorough study of "Variational Autoencoders". We explain the limitations of ``supervised learning" and emphasize the need for ``generative models" to solve complex problems. Variational Autoencoder (VAE) is an effective tool for generative modeling. We understand the rich mathematical basis of VAEs, the evidence lower bound (ELBO) and how regularization of original VAEs brings the trade-off between reconstruction fidelity and quality of disentanglement within the learnt representations. We validate the theory by conducting experiments on Frey's Faces image dataset using an encoder and decoder architecture using convolutional neural networks . In addition to this, we also learn what constitutes a ``good representation" and how "disentanglement metrics" helps in comparing representations obtained from two different models. We briefly describe two different types of disentanglement metrics Beta-VAE metric and Mutual Information Gap (MIG)
Curbing Fake News: A Qualitative Study of the Readiness of Academic Librarians in Ghana
No full texthttps://doi.org/10.1080/10572317.2022.2046438While fake news has been a common problem for well over a century, the emergence of social media and smartphones has escalated its spread. This study adopts a qualitative approach to explore the readiness of academic librarians in curbing fake news. Data was drawn from interviews with reference library staff and head librarians who were purposively selected from 12 academic libraries and evaluated through the lens of the International Federation of Library Associations and Institutions [IFLA] guide on ‘how to spot fake news’. The study revealed that although academic librarians were aware of fake news, they do not grasp the complexity and intricacies of the phenomenon. Therefore, the study recommends regular on-the-job training for academic librarians in identifying fake news. The Library and Information Science departments of universities in Ghana should review their curriculum to
include training and education on problematic information. There should be collaboration between libraries and social media organization on curbing fake news. We support the call for information literacy, critical thinking and media literacy instructions to be embedded in all subjects with academic librarians as co-instructors
Non-likelihood based methods for the estimation and inference in econometric models
No full textThesis (Ph.D.)--University of Washington, 2022This dissertation aims to address estimation and inference in econometric models when the likelihood-based estimations may not be applicable. Chapter 1 proposes simple, robust estimation and inference methods for the transition matrix of a high-dimensional semiparametric Gaussian copula vector autoregressive (VAR) process with unknown, possibly fat-tailed marginal distributions. In this model, the observable variable is a monotonic transformation of the latent variable, and the latent variable follows the Gaussian VAR process. Since the marginal distribution is unknown, conventional approaches that use the sample variance and auto-covariances such as OLS are not applicable. This chapter circumvents the problem by constructing the rank estimators of the variance and auto-covariance matrices of the latent process. This chapter derives rates of convergence of the estimator based on which we develop de-biased inference for Granger causality. Chapter 2 develops a simple, robust method for the estimation and inference in structural models using sliced distances between empirical and model-induced quantile functions (distribution functions). In state-space models, observable variables could be driven by fewer latent variables. This causes stochastic singularity, and the likelihood function does not exist. For the models with parameter-dependent support such as in the one-sided and two-sided models, the likelihood function may not be smooth depending on the parameter. Therefore, the asymptotic theory for MLE may not be robust to the parameter. We handle these issues using sliced distances since they are well-defined for stochastic singular models and models with parameter-dependent support. In contrast to MLE and likelihood-based inference, we show that under mild regularity conditions, our estimator is asymptotically normally distributed, leading to simple inference regardless of the possible presence of ”stochastic singularity” and parameter-dependent supports. Furthermore, our estimator applies to generative models with intractable likelihood functions but from which one can easily draw synthetic samples. We provide simulation results based on a stochastic singular state-space model, a term structure model, and an auction model
Structural Studies of Viral RNAs and Peptide Targeting
No full textThesis (Ph.D.)--University of Washington, 2022RNA structures are involved in many biological processes and the progression of human disease, making them potential targets for therapeutic development. The first chapter introduces topics relevant to targeting RNA structures and to the subsequent chapters of this thesis: disease-associated RNA classes, the characteristics of RNA-binding ligands of different sizes (e.g., small molecules, peptides, engineered proteins), and NMR-based methods for RNA structure determination.Chapter 2 describes the strategy and result of my research on designing cyclic β-hairpin peptidomimetics targeting pre-microRNA-20b (pre-miR-20b). Small cyclic peptidomimetics were rationally designed based on the sequence of β2-β3 hairpin of Rbfox2 protein, that recognize the terminal loop of precursor miR-20b. I identified a peptide with low µ-molar affinity for the miR-20b precursor and specifically targets the apical loop of pre-miR-20b. This work demonstrates that it is possible to mimic RNA-binding proteins with a minimal structurally pre-organized peptide, which provide a starting point for designing or evolving small peptide mimetics of RNA-binding proteins.
Chapter 3 describes the results of structural analysis of a 70 nucleotides stem-loop RNA structure (called SLA) from Dengue virus serotype 1 (DENV1), which functions as the promoter for viral replication. NMR structure of a monomeric DENV1 SLA is assembled to high-resolution from independently folded structural elements, and SAXS modeling is used for independent validation. Both NMR structure determination and SAXS modeling result in an L-shape of RNA structure. It is very likely that the three-dimensional structure of SLA is conserved among flaviviruses because the sequence is highly conserved among different flavivirus genomes. This work establishes RNA structural features involved in Dengue replication and provides a foundation for the discovery of new antiviral drugs that target this essential replicative step