American Crow (Corvus brachyrhynchos) calls vary considerably in their acoustic structure and timing, but the function of this variation is still not fully understood. Learning how crows use their ‘caw’ vocalizations to relay information will enrich our ability to more fully comprehend complex communication across species. We examined differences between crow vocalizations made in two contexts with frequent calling. We used a parabolic microphone to record calls both passively at pre-roost aggregations and actively by placing a model owl in a tree while playing back a 75 second recording of crow distress calls to induce predator mobbing responses. We analyzed 75 seconds of audio in each recording for differences in the duration of silence between multisyllabic calls, the duration of silence between caw syllables, the number of caws, the average fundamental frequency of the caws, and the harshness of the caws. We measured harshness as the difference between the atonal, non-harmonic signal existing within caws and random background noise. Preliminary evidence suggests that calls given during mobbing are harsher than those given during pre-roosting. We are currently developing and refining our analyses methods in order to verify our results, which may be useful in future research of avian vocal communication.

I, along with advisor Dr. Simpkins and student peer Katie Ward conducted research on integrating disability studies in their classrooms, by surveying faculty and students who self-describe as having a disability across an extensive tri-campus state school system. With an emphasis on intersectionality, interdisciplinarity, and interrogating diversity, the team researchers, including myself, will offer tools for bringing disability studies into conversation with existing curricula. In spending the past two quarters on this project, I have extensively read about disability, intersectionality, and interdisciplinarity. I have since utilized these readings to correctly write the surveys the team used for collecting data, being a significant contributor to our paper, and being a significant contributor to the term reference collection and academic resource collection. At the symposium, I will outlay the progress our team has made thus far, including writing the survey, sending them out to all three University of Washington campuses, and receiving the data back to analyze it and make conclusive understandings. I will also present the disability term book and resource collection that we compiled for faculty, staff, and students to access utilizing disability curriculum content. The rest of the team and I will then address our future hopes for implementing a disability curriculum and the concerns of both groups with integrating disability studies in classrooms across the curriculum. I will also describe their use of Pressbooks to publish an open-source resource that collects their findings; this resource offers suggested materials, teaching strategies, and research guides to support instructors who are less familiar with disability culture and disability studies to bring disability-related content into their teaching. 

Autosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder that affects people who have mutations in the PKD1 or PKD2 genes. The prominent feature of this disease is the formation of cysts in the kidneys. Despite ADPKD being genetically heterozygous, cystic tissue from patients with ADPKD also contains cells with homozygous mutations. This causes speculation within the PKD community about whether heterozygous mutations with one mutated copy of the PKD1 or PKD2 gene are sufficient to induce cystogenesis or if two mutated copies are needed. This concept is referred to as the two-hit hypothesis, a somatic mutation (second hit) occurs during the lifetime of the kidney and gives rise to clonal populations of cells that give rise to cysts. The goal of my project is to investigate the two-hit hypothesis and determine if there is cyst formation in the heterozygous organoids. To do so, I use patient-derived hSPC lines modified using CRISPR to express PKD1 or PKD2 mutations. I follow a 21 day differentiation process to produce PKD organoids. I then pick individual organoids to place in suspension for 14 days and track cyst growth by area and amount. If cysts form in heterozygous PKD organoid models at the same rate as the control, it would suggest that heterozygous mutants are unlikely to cause cyst formation, indicating the two-hit hypothesis applies to PKD. Current data collected on mutations in PKD2 have shown heterozygous organoids do not form cysts, however more data is needed to test the PKD1 site. Future applications involve inducing cyst formation in heterozygous mutants using forskolin, an agonist of adenylyl cyclase shown to induce cyst growth. Establishing if heterozygous mutant organoids form cysts has significant implications in ADPKD research by potentially creating a better representation of the disease process, which has been difficult to study in other models.

An invertible matrix is called a Perron similarity if one of its columns and the corresponding row of its inverse are both nonnegative or both nonpositive, a definition introduced in a previous work by Johnson and Paparella (2016). For a given matrix S, the spectracone is a polyhedral cone formed by the vectors that produce nonnegative matrices when multiplied on the left by S and the right by S-inverse. The spectratope is a set defined similarly, with the added condition that the included vectors have an infinity norm of one. This work identifies previously unknown relationships between Perron similarities and their Kronecker products. First, if two matrices are Perron similarities, their Kronecker product is also a Perron similarity. Second, the Kronecker product of spectracones (spectratopes) is a subset of the spectracone (spectratope) of the Kronecker product. In addition, if two matrices are Perron similarities with dimensions greater than 1, then the Kronecker product of the spectracones (spectratopes) is properly contained in the spectracone (spectratope) of the Kronecker product. Another significant result is if S is a Perron similarity, then the ray through the all-ones vector is properly contained in the spectracone of S, but the converse is not true. One reason this work is relevant is that Perron similarities were previously defined to have a necessary and sufficient condition that the ray through the all-ones vector is properly contained in the spectracone. With the publication of this article, the condition was found to only be necessary, and the definition was corrected. Perron similarities are important when examining the nonnegative inverse eigenvalue problem, or NIEP, which is concerned with the spectrum of nonnegative matrices. This research expands on previous work related to the NIEP by examining relationships between Perron similarities and their Kronecker products.

To expand my experience with the human brain beyond dissections, I worked in the Intelligent Networks Laboratory (INL) in UW Bothell’s Computing and Software System (CSS) Division to simulate activity in a biological neural network. INL has a computer software system called “Graphitti” that allows users to run simulations of large biological neural networks. The specific simulations I analyzed were of growth and development in cultures of initially dissociated cortical neurons, which produce bursts of activity that propagate as waves across the network. Networks were grown over 28 simulated days on a 100 by 100 neuron grid, producing 500,000 synaptic connections. Two previous student papers suggest that this bursting activity is stable with 10% inhibitory neurons distributed across the simulated culture. With the original raw data stored in Matlab software (www.mathworks.com), I ran other code to pull burst location, speed, and distance from four simulations with different neuron firing rates and percentage of inhibitory neurons. In one simulation, burst origin locations were scattered across the network, indicating bursting behavior throughout the network. Two other simulations had a few, stable origin locations, suggesting a discernible pattern in bursting behavior. The burst propagation speed graphs for each network demonstrated growth and stabilization of activity by the end of the simulations. Working with this neural network has provided me with a fresh and "live" perspective on the connectivity of neurons. By understanding the dynamics of the network under these conditions, the data inspires further research investigating the connectivity effects of neurodegenerative diseases such as Parkinson's Disease.

Machine learning is a powerful tool that allows us to use data to make predictions and decisions about the world, but it requires expensive centralized hardware and data, is prone to algorithmic biases, and has privacy concerns surrounding the use of required data. In contrast, Federated Learning (FL) allows users to collaboratively train a shared model under a central server while keeping personal data on their devices. This ability potentially addresses problems of traditional machine learning by using widely available mobile devices to increase accessibility to mainstream users and leverages decentralized user data and computational resources to train machine learning models more efficiently. However, this emerging field requires established processes for training and measuring the efficiency of FL models on edge devices. This research provides an inclusive framework to federatively train models on Android devices and analyze their computational and energy efficiency. On the mobile devices, I leveraged a terminal application to install dependencies and natively train FL models on the device. Then, I analyzed the device’s efficiency by measuring the computational, energy, and network resources through terminal applications. This flexible framework can deploy diverse machine learning models and datasets for training on Android devices. In preliminary experiments, I used this framework to measure efficiency for a PyTorch obstacle detection model and a Tensorflow abnormal heartbeat detection algorithm. These experiments showed that federatively training machine learning models on mobile phones makes efficient use of CPU, memory, and bandwidth, and it uses minimal energy consumption compared to centralized machine learning systems. With little to no examples of FL on Android devices, this framework provides a novel plug-and-play solution for native FL on mobile devices. Applications of this research will also demonstrate using FL techniques to address topics of accessibility, privacy, algorithmic bias, and hardware limitations for the machine learning domain.

The IEEE 754 standard, established in 1985, provides the most widely used formats for real number arithmetic. These formats use a floating radix point, and therefore they support a wide range of real numbers. However, these formats require greater computational complexity and hardware circuit area than the integer format. Many modern applications, such as multimedia signal processing and machine learning, are tolerant of approximate calculations. Thus, many custom hardware designs have been proposed for approximate arithmetic, especially for real number multiplication, that can calculate faster and with higher area efficiency at the cost of accuracy. This research is based on an existing approximate multiplier hardware architecture for 32-bit single-precision floating-point numbers. As this architecture uses an iterative approach, it has great advantages in reducing the circuit area. We extend the architecture to be used for the 64-bit double-precision floating-point number format and the recently devised Posit number format. The proposed approximate multiplier hardware designs are then applied to real-world applications, such as histogram stretching. Applications are developed on a hardware/software codesign platform, which has been optimized for cooperation between hardware and software components. In particular, real number multiplications are processed by the proposed hardware designs, and the rest is processed by an ARM processor on the platform.

Asthma, a chronic disease of the lungs, affects approximately 262 million people and caused 461,000 deaths worldwide, just in 2019. Asthma can result in frequent emergency department visits, hospitalizations, and premature deaths. To effectively manage their condition, asthma patients need to accurately track their medication usage. But it is a manual task, prone to human error. To improve the lives of asthma patients, we built a smart asthma-inhaler system to automatically record patients' use of medication. Our system is made of a Bluetooth-enabled inhaler, a smartphone app, and a Bluetooth-enabled wearable sensor. The inhaler records when the patients took their medications and sends the data to the smartphone app. The app retrieves weather information including temperature, humidity, and Air quality index from the web. The wearable sensor measures the particulate matter in the air surrounding the patient when the inhaler was used. This system should allow patients to accurately record when and why they used their inhalers. Physicians can then use this information to better diagnose and treat asthma. We hope to marketize this system to mitigate the damages of asthma.

In a world where the pace of change is increasing drastically, it has become less feasible to complete tasks alone. The skill of being able to communicate and work in a team has become valuable, if not necessary. Working with others, however, can be challenging for many reasons. One reason, which affects project teams across all fields, is when one team member worries that the deadline is close (e.g., “the deadline is only a week away!”), while another team member believes the deadline is further out (“we still have an entire week to work on it!”). This disparity occurs because the team members have different Temporal Distance Perceptions (TDP) of the deadline. This project seeks to analyze how these individual differences in team members’ TDP affects the team’s performance. Evaluating divergent TDP can improve team project planning, helping them work better together. In this project, I contacted faculty members from University of Washington Bothell’s School of Business to gather data from 11 undergraduate classroom teams, working on a quarter-long team project in their courses. The duration of this task allows them to establish their own perception of the deadline’s temporal distance. I disseminated a survey, comprised of only validated scales, to the project teams one week before the project’s due date. The procedures used for data collection, which included a consent form that implied use of their performance on the project, were submitted for review and approved by the Institutional Review Board prior to survey dissemination. I compared an individual team member’s TDP with the rest of the team’s individual TDP to determine the team’s collective TDP. Then I compared this collective TDP with their performance, determined by the team’s grade earned. I expect to find a positive correlation between collective TDP and output performance.

Stereotypes around femininity, as presented to young Women, have historically not been inclusive. Often consisting of single-story one-dimensional white male ideals of femininity. Young Women could either lean into the stereotype or turn away, the dismissal often created new stereotypes due to a lack of strong feminist representation like the “I’m not like other girls” trope. The exposure to these white feminine stereotypes created cracks in a young Woman’s relationship with femininity and what it means to be girl. Causing a shift to anti-feminist and sexist thought while developing internalized misogyny. This presented externally as Women hating behavior that supported the learned mindsets of white men on the sexualization, degradation, and general treatment of other Women. The patriarchal system influenced this young Woman and others across the country in their homes, in their classrooms, each night on television, reinforced on the covers of teen magazines, through the eyes of their fathers and actions of their mothers. This young Woman functioned as a monument to the Patriarchy. Acting for the best interest of the heteronormative white male experience. I was the monument. With a lack of strong feminist representation, I instead turned into a living, breathing, and sometimes ‘preaching’ monument to the patriarchy. Through autoethnography and research of pop culture from the 1990s and 2000s, friends, family, members, and television shows. I will analyze my own experience to identify and understand my journey from anti-feminist to feminist. Answer how I was manipulated by the heteropatriarchy and colonialism to be antifeminist, to hate other Women, and actively cause harm to others based on their expression of femininity. Understanding the way in which I was once an image fighting for feminine oppression to help others unlearn too.

Chronic wounds affect 20 million people worldwide and are a silent epidemic often occurring with a comorbid condition such as diabetes. Most often, these wounds are treated with wound dressings, topical formulations, and antibiotics; however, their effectiveness is hampered by the presence of biofilms. We have shown that hypochlorous acid (HOCl) is effective against chronic wound biofilms, in particular against Pseudomonas aeruginosa, one of the most persistent Gram-negative bacteria present in most chronic wounds. However, the mechanism of action of HOCl against P. aeruginosa remains unknown. Given the unique behavior of HOCl with P. aeruginosa survival, we hypothesized that the quorum sensing compounds and virulence factors would lose functionality after reacting with certain concentrations of HOCl. Here, we tested the effects of HOCl against elastase and N-3-oxo-dodecanoyl homoserine lactone (AHL), a virulence factor and quorum sensing molecule, respectively, that are excreted for P. aeruginosa survival in biofilms. Our primary aim was to study how hypochlorous acid interferes with elastase activity and modifies the AHL structure. The activity of elastase was monitored by UV-Visible spectroscopy and the effects of HOCl on the AHL was monitored by High-Performance Liquid Chromatography (HPLC). Elastase enzyme activity showed a dose response to various concentrations of HOCl. Simultaneously, we developed a successful method for monitoring modifications of the AHL. Our results suggest that HOCl can act to modulate communication signals used by P. aeruginosa. This opens up further opportunities to understand the mechanism of action of HOCl against quorum sensing compounds and virulence factors and provides useful clinical information for treating chronic wounds.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by communication and social impairments deficits. I am investigating alpha power, EEG activity between 8 and 12 Hz, which is found present during quietly resting with greater power (amplitude squared) when the individual's eyes are closed rather than when their eyes are open. This is thought to reflect increased cortical activation (decreased power) when eyes are open in preparation for attention and cognition. Previous research shows lower alpha power in individuals with ASD as compared to typically developing (TD) and has been associated with attention and cognition and social understanding and imitation in individuals with ASD. I plan to evaluate the association between eyes-closed EEG resting-state alpha power and social responsiveness in youth with and without ASD by gender and diagnosis. We collected data from 152 youth (ASD = 76) ages 8-17 years from an NIH-funded study investigating sex and gender differences in youth with ASD. The youth sat with their eyes closed while we collected high-density EEG data. A fast fourier transformation (FFT) was applied to artifact-free EEG data to extract alpha power for central and posterior electrodes. I calculated the Regions of interest (ROIs) for alpha power over: left frontal, mid frontal, right frontal, left central, left posterior, mid central, mid posterior, right central, and right posterior. Parents of children completed the Social Responsiveness Scale-2 (SRS-2), a 65-item rating scale measuring autism traits. I conducted a series of one-way ANOVAs, and correlations to evaluate the differences in frontal, central, and posterior alpha power x group (ASD/TD), gender (male/female), and associations with social responsiveness. Preliminary results comparing alpha power and social responsiveness show significant group differences. This research is important since it helps individuals currently affected with ASD and helps understand the larger class of neurodevelopmental disorders.

Quasars are the most luminous of active galactic nuclei; because of this we can study them at high redshifts to gain more insight of galactic evolution within our own universe. I am presenting a survey of extremely-high-velocity outflow (EHVOs) quasars. These are quasars whose outflows reach relativistic speeds (10-20% the speed of light). Our research group is in the process of compiling the largest catalog of EHVOs to date, which we have done by designing a series of Python modules to automate the search for EHVO quasars in the sixteenth data release from the Sloan Digital Sky Survey catalog. I was in charge of adjusting the absorption algorithm and performing the final visual inspection of EHVO candidates. The latter is performed using plots and key spectral features, which are outputs of the code I co-wrote. I also led the team to document all the programs for a future public release. I also present the analysis of the EHVO we have found in the spectrum of the most luminous quasar found to date, SMSS-J2157-3602, which was observed using Keck/NIRES and VLT/X-shooter. This result emphasizes how these outflows are likely powered by the quasar radiative luminosity, as well as allows us to adapt our codes mentioned above to other non-SDSS quasar spectra. Studies of quasars with EHVOs, especially our survey that will include information of black holes masses and quasar luminosities, are key to understanding how quasar outflows are launched and accelerated away from the central region of galaxies, as they represent some of the most extreme cases.

Carbapenem-resistant Enterobacteriaceae (CRE), usually belonging to the bacterial species E. coli or Klebsiella pneumoniae, are resistant to carbapenem antibiotics, which are often used as a last resort in treating infections. CRE is a growing public health concern as it spreads rapidly within certain settings like hospitals. Currently, limited research assessing the presence of CRE within environmental samples is available. Without this research, the abundance of CRE and therefore its threat to public health remains unclear, making mitigation strategies challenging. This study seeks to identify if CRE resides in the protected wetlands at the University of Washington Bothell campus. Because crows, specifically Corvus brachyrhynchos, provide an impeccable habitat for Enterobacter species, and because of the large crow population in this area, we want to find out if crows are bringing in any CRE strains to the wetland. To answer this question, samples of both wetland water and crow feces have been collected from strategic locations, and using selective plating potential CRE strains have been isolated. The isolated Enterobacter species have undergone a modified Hodge test with both meropenem and ertapenem. Isolates suspected to have resistance to either antibiotic are undergoing PCR with primers specific to the genes bla_KPC, bla_NDM, and bla_OXA, genes which are common culprits of carbapenem resistance. We plan to perform multidrug resistance testing to determine if our isolated strains are resistant to other antibiotics. After conclusion of this project, we will be able to say if crows could be responsible for bringing these antibiotic-resistant bacteria of clinical importance to the Bothell Wetlands, and what health risks they pose to the community.