Bioculture Journal
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Examining the Human Experience of Moral Distress: A Narrative Inquiry
No full textDoctor of Educational Leadership (EdD)Abstract Background: Evidence suggests that one in three nurses will experience moral distress, which has been associated with intent to leave, depersonalization of the patient and disengagement with work at some point in their career. Purpose: The purpose of this narrative inquiry was to identify nurses that have experienced a morally distressing experience in practice and give them the opportunity to share their lived experience and share the impact of their experience. This study provided a better understanding of the complexities of moral distress. Method: Convenience sampling was used to select the female registered nurse participants. Narrative inquiry was used to collect the experiences of moral distress. Results: Twelve nurses wrote narratives for this study. Two themes (the voices behind the experience and outcomes of moral distress) and five subthemes were identified. All the participants mentioned that not being heard and silencing of self, contributed to moral distress. Participants also discussed strategies for growth after a morally distressing incident. Implications for practice: Nurses in many different settings have the potential to experience moral distress. This finding suggests that interventions for moral distress should be considered in any setting. This study also identified the potential to learn and grow from morally distressing experiences. Conclusions: The impact of self-silencing and the practice of being dismissed should be further explored to truly identify stronger and more effective interventions
Challenging Normative Gender Within the Domestic Sphere
No full textTSOC 455 Sociology of GenderThis informational pamphlet explores the ways in which socialization drives behavior and normative gender standards in early childhood
Bless Me Anyway- A Solo Performance of My Own Design
No full textThesis (Master's)--University of Washington, 2019The fight against HIV/AIDS is not over. Since the beginning of the epidemic over 39 million people have lost their lives due to HIV/AIDS related complications. And yet, HIV/AIDS continues to disproportionately affect marginalized populations. Stigma, fear and discrimination run high and force those affected into isolation. Access to medication is difficult and expensive. Under the current administration, Trump proposed diverting money away from HIV/AIDS research to fund detention centers for undocumented children. This crisis is not over. A personal, political, historical call to action, Bless Me Anyway, harkens back to the beginning of the ACT UP Movement: to Stand Up. Fight Back. Fight AIDS
Predicting maternal-fetal cannabinoid exposure during pregnancy using physiologically-based pharmacokinetic modeling and simulation
No full textThesis (Ph.D.)--University of Washington, 2019Maternal marijuana (cannabis) use during pregnancy is associated with reduced fetal growth and subtle but persistent neurodevelopmental effects. It is not possible to establish the independent risk associated with maternal cannabis use via prospective clinical studies due to ethical considerations. In vitro and animal studies identified (-)-Δ9-tetrahydrocannabinol (THC), the psychotropic component of cannabis, and its active hydroxy metabolite, 11-OH-THC, as potential perpetrators of fetal developmental risk. The observed toxicity to THC and 11-OH-THC may not be translated from preclinical studies to humans without knowing the exposure of these cannabinoids during pregnancy. As such, maternal-fetal cannabinoid (hereafter cannabinoid refers to THC and 11-OH-THC) exposure needs to be determined. However, sampling maternal and fetal cannabinoid plasma concentrations during pregnancy is logistically difficult or unethical. Physiological-based pharmacokinetic (PBPK) modeling and simulation can be used to predict drug exposure in silico. PBPK modeling incorporates physiological data, such as tissue composition and blood flows, with drug specific pharmacokinetic (PK) parameters, such as metabolism and transport, to mechanistically predict in vivo PK of a drug. We hypothesize that we can predict maternal and fetal THC and 11-OH-THC exposure using maternal-fetal-PBPK (m-f-PBPK) modeling and simulation. To do so, we first quantified the pertinent mechanistic drug parameters in vitro, which included the identification of enzymes, their contribution, and kinetics relevant to maternal THC/11-OH-THC hepatic disposition. Next, we extrapolated the in vitro mechanistic information to in vivo and built a THC/11-OH-THC PBPK model in nonpregnant women using PBPK software Simcyp®, and verified using observed data. Lastly, we incorporated the gestational-age dependent physiological changes via the m-f-PBPK model to predict THC and 11-OH-THC exposure in the maternal-fetal pair. By bridging cannabinoid disposition data with m-f-PBPK modeling, this project translated in vitro PK mechanistic information into predictions of maternal and fetal pharmacologically relevant cannabinoid exposure following THC consumption. The predicted THC and 11-OH-THC concentrations during pregnancy can then be used in preclinical studies to establish the toxicity of THC exposure during pregnancy
Effect of habitat cues on the swimming behavior of pre-competent Lacuna vincta larvae from Friday Harbor, WA, USA
No full textSwimming behavior in planktonic larvae has been suggested to affect their dispersal and
recruitment. Behavioral regulation of vertical distribution can affect the extent to which larvae
may accumulate in or escape from vertically sheared flows or fronts. Competent larvae of many
invertebrate species are known to respond to various settlement cues in the environment by
regulating their behavior in order to facilitate settling in suitable habitats. The behavioral
responses of pre-competent larvae to cues from the adult habitat could have implications for
retention, however such responses have not been investigated. In this project we have studied the
swimming behavior in pre-competent larvae from the gastropod Lacuna vincta in the laboratory
with the objective of determining whether behavioral changes in response to potential settlement
cues are present in larvae at that earlier developmental stage. Potential settlement cues included
in this study are eelgrass (Zostera marina), the kelp Agarum fimbriatum, and adult L. vincta, in
addition to a control of filtered seawater. Pre-competent L.vincta larvae were recorded swimming
in water columns containing water in which these various cues had been soaked, and their
behaviors were compared across treatments. Videos were analyzed for mean upward swimming
speed, mean swimming speed along the path of travel, mean oscillatory speed, and mean axial
speed for each treatment. For all metrics, there were no significant differences between all four
treatments and the control. The sample size of larvae was consistently low in the kelp cue as
larvae remained on the bottom of the column, possibly due to high viscosity of that cue water.
Our results indicated no response to adult habitat cues when larvae are pre-competent
The Amazing Adventures of Bewbs the Clown: a solo performance of my own design
No full textThesis (Master's)--University of Washington, 2019The Amazing Adventures of Bewbs the Clown is a solo performance of my own design in which a topless, opera-singing, feminist clown embarks on the absurdly impossible journey of finding something appropriate to wear. In creating this theatre piece, I sought to use the artistic tools I have gathered in my three years at the University of Washington School of Drama in order to explore the ways in which women are sexualized and oppressed by what society instructs them to wear. This thesis documents my inspirations behind creating this character and telling this story, my process in developing the piece, and my personal reflections on living as a woman with a body in a man’s world. What happens when a woman stops listening to “the Man,” or society, and reclaims ownership of her own body
Developing Metacognitive Competence for Governing Self-Influence on Learning To Improve Collaborative STEM Learning
No full textThesis (Ph.D.)--University of Washington, 2019Abstract Developing Meta-Cognitive Competence for Governing Self-Influence on Learning To Improve Collaborative STEM Learning Derya B. Sunkel Chair of the Supervisory Committee: Associate Professor Min Li Measurement & Statistics This dissertation examines an instructional approach aimed at developing co-empowered learning communities through self-empowered individual leaders, particularly in STEM fields, becoming metacognitively competent in governing their Self-Influence on Learning (SIL), while simultaneously educating them in the importance of co-empowered learning. I conducted the research at an after school, on-site-training environment. The goal of this approach is to train students to STEM learning Program, which provides year-long STEM enrichment to underserved children of color in Grades 1-8, using a project-based learning model with advanced technology tools. Twenty-three students in Grades 3-5 participated in the study during 2011-2012. I designed a systematic model, the Metacognitive Coaching Model (MCM), to guide each stage of the project and support assessment of student performance. The findings reveal that following the four-month MCM intervention, students demonstrated shifted understanding and practices in which they developed leveraged awareness and self-responsibility at an individual level. Furthermore, findings indicate an association between the MCM practices and students’ increased dedication to self-empowerment and to co-empowering their learning communities through their improved academic and social strengths. Results also showed that the practices gained through the MCM principles not only helped students develop SIL capacities but also generated a synergistic learning community in which members demonstrated care about each other’s learning. Four months after the conclusion of the MCM intervention, analysis of students’ verbal teamwork report revealed that they were more focused and efficient, and their actions were more thought-out when working hand-in-hand with their peers. Specifically, they were more attentive of the task at hand, were more fluent in their explanations, and demonstrated a more collaborative approach while sharing their learning progress. The results show that it is possible for students to acquire comprehensive metacognitive competence skills on SIL when provided opportunities to acknowledge and act on their individual and collaborative learning responsibilities. By helping students connect meta-emotional regulation components with metacognitive strategies, the MCM not only offers students a deeper awareness of their learning processes, but also helps them to develop their metacognitive thinking capacity to become better learners, team participants, and citizens
Rapid modulation of dynamics and computation in neural systems
No full textThesis (Ph.D.)--University of Washington, 2019A central goal in theoretical neuroscience is to understand how neural systems perform computations over the continuum of timescales that underlie behavior. In particular, what are the algorithms and mechanisms enabling single-neuron membrane voltage fluctuations, which occur over milliseconds, to produce the dynamics and information processing in behavior that unfold over hours to years? Notably, while the core ionic processes of membrane voltage fluctuations have been largely elucidated and while extensive theories and evidence exist to explain how slow modulation of neural network structures might underlie learning, almost nothing is known about the liminal regime of seconds to minutes that bridges these two timescales. In the work that follows I address three questions in three different systems, each of which centers around neural computations occurring over the timescales of seconds to minutes. I first investigate the navigational decisions made by flying insects during odor tracking, where I show that fruit flies and mosquitoes exhibit a history dependence in their odor-triggered turning responses that is qualitatively similar to an information-maximizing tracking strategy, but not to others. Next, in collaboration with Ari Zolin, Raphael Cohn, and Vanessa Ruta, I analyze the dynamics of dopaminergic neuromodulation of a short-term memory circuit in the fruit fly mushroom body, where we suggest that the fly dopamine system encodes multiplexed representations of a wide diversity of sensory, motor, and valence signals, some of which predict behavior several seconds in the future. Third, I develop a spiking neural network model capable of storing and replaying sequential activity patterns using a heterosynaptic and fast-acting biological plasticity rule, and which reconstructs sequences through the existing recurrent network structure. Collectively, these results elucidate the computational capacities of three distinct systems and shed new light on short-term information processing in neural computations from three novel angles. Finally, in collaboration with Sid Henriksen and Mark Wronkiewicz, I describe a simple network-growth model reproducing several statistical features of mouse brain network connectivity at the mesoscale; while this work does not explicitly address short-term computations, simplified statistical network models will be crucial to eventually understanding how such computations occur within large scale distributed brain networks
Quantifying and Modeling Subgrid Scale Snow Depth Variability in Forested Areas Throughout Multiple Climates in the Western United States
No full textThesis (Ph.D.)--University of Washington, 2019The mountain snowpack provides natural storage of freshwater. This natural storage far exceeds the extent of manmade reservoirs. Furthermore, watersheds throughout the western United States can be predominantly covered in forests. Forests decrease atmospheric winds, alter the amount of incoming radiation, and intercept snowfall, leading to significant variation in snow depth throughout the forest. Snow depth variability influences the magnitude, timing, and temperature of streamflow. Additionally, snow depth variability can drive ecological processes and affect the energy exchanged between the land and the atmosphere. To quantify snow depth variability in forests, spatially continuous, high-resolution (1-3 m) observations are needed at watershed extents. Chapter I of this dissertation evaluates the ability for airborne lidar to derive snow depth underneath the canopy by comparing airborne lidar to terrestrial lidar and snow depth probe transects from NASA’s 2017 SnowEx campaign. Differences between gridded airborne lidar and ground-based observations did not increase underneath the canopy. Airborne lidar observations were therefore used in Chapter 2 to examine forest snow depth variability in four different snow climates throughout the western United States. In the Jemez Mountains, NM and in Tuolumne, CA, snow depth differences between north and south-facing sides of the canopy were statistically significant and greater than or equal to the difference between areas underneath the canopy and in the open. To account for this variability, a tiling parameterization, was incorporated into the Distributed Hydrologic and Soil Vegetation Model (DHSVM). The tiling parameterization explicitly simulates radiation differences within the forest and accounts for horizontal forest structure by using classifications from high-resolution vegetation maps. The tile parameterization therefore tested the impact of explicit forest representation on simulated snow water equivalent (SWE) and streamflow compared to the original implicit representation in three watersheds throughout the western United States. In Jemez, NM, where forests were relatively sparse and trees were 10.2 m tall, the tile model’s grid-cell average snow disappearance date (SDD) was 12 days earlier and peak streamflow occurred 20-days earlier than the original model. In the Chiwawa, WA, where forests were dense and 17.2 m tall, SDD was 11 days later and late-season streamflow increased up to 11-13%. Despite statistically different snow depth distributions, forest edges had a relatively small effect on simulated streamflow (2-6%). However, grid cell average ablation rates and streamflow were primarily impacted by tiled grid cells, which only contained exposed and forested areas. The contrasting responses between the Jemez and Chiwawa were primarily controlled by the grid cells average fractional forest cover and the forest’s radiation attenuation, which is a function of tree height and the sun’s elevation angle. Ultimately, DHSVM’s tile parameterization is a tool that more realistically represents forest radiation and while forest-edge contributions were relatively small within the existing forest structure, going forward, forest managers could use the tile parameterization to better understand how changes in the forest structure (e.g. maximizing forest shading) affect streamflow
Street Vitality: A Socio-Spatial Analysis of S Jackson St
No full textThesis (Master's)--University of Washington, 2019Vital streets are important to urban environments; they support the various activities that make up the “mixed life” of cities (Francis 2011). In order to understand its significance, this thesis discusses the role of the street as a public space and the concept of “street vitality”. It identifies some built-environmental characteristics that affect street vitality and provides methods to evaluate them, using South Jackson St in Seattle as a case study to demonstrate both real-world observation of street activity and environment, combined with GIS-enabled data analysis. Findings suggest several ways to improve street vitality, such as increasing building façade transparency, adding outdoor extensions and encouraging small and diverse developments. This study does not intend to change street conditions in the near future, but to provide ideas for analysis and design, and to provide inspirations for future development