Surf smelt (Hypomesus pretiosus) are ecologically and culturally important forage fishes that rely on intertidal beach habitat for spawning. However, the combined effects of rising sea level and human modification (e.g. seawalls, bulkheads, riprap) have put this habitat at risk of coastal squeezing, which could reduce available spawning areas along Puget Sound. This research aims to assess the vulnerability of surf smelt spawning beaches to climate change by combining field data collection with quantitative analysis. We evaluated existing risk assessment methods, such as the Coastal Vulnerability Index (CVI) to determine its applicability to Puget Sound. Additionally, we conducted beach surveys at productive spawning beaches to characterize the beach morphology. Our morphodynamic analysis included measurements of beach slope, sediment composition, pH, and water table depth from the high tide line to the waterline. Our hypothesis suggests that spawning beaches with a lower slope, smaller sediments, and a shallow water table will be more resilient to climate change impacts. Findings from this study will improve our understanding of climate-driven and anthropogenic threats to intertidal ecosystems and provide insight into habitat resilience, supporting conservation efforts for surf smelt populations.

Surf smelt (Hypomesus pretiosus) are an ecologically and economically significant forage fish species that spawn in the intertidal zone of beaches throughout the Salish Sea. Despite their importance to marine food webs, the environmental factors influencing their spawning site selection and seasonal distribution remain poorly understood. This project aims to investigate the morphological characteristics of beaches used for surf smelt spawning during different times of the year, comparing morphological and spatiotemporal variables that influence spawning. In order to study these characteristics, we will record sediment grain size, slope, wave energy, beach temperature and the water chemistry at verified winter as well as summer spawning sites identified by the Washington Department of Fish and Wildlife (WDFW). We will also sample non-productive sites in order to identify key differences between them and further establish parameters that enhance spawning success. Preliminary research suggests that these key characteristics strongly influence surf smelt spawning distribution​​​. Optimal surf smelt spawning beaches appear to consist of mixed sand and gravel substrates, low levels of wave action, high amounts of shading, moderate slopes and moderate temperatures. Habitat alterations such as shoreline armoring along with sea-level rise in response to global warming could lead to a drastic decrease in the upper inner tidal ranges where surf smelt usually spawn. Consequently, we expect beaches heavily influenced by these factors to be poor spawning sites​​. The results of this study will contribute to a deeper understanding of the environmental variables driving spawning site selection, egg survival, and seasonal spawning peaks. This research will be instrumental in informing conservation projects and supporting policy initiatives aimed at preserving surf smelt populations and their critical spawning habitats in the Salish Sea.

Neonatal tracheal intubation (TI) is a high-risk procedure requiring careful coordination to minimize complications and improve outcomes. The Personalized Intubation Neonate Safety (PINS) Bundle was developed to enhance team communication and optimize intubation practices for neonates at risk. The bundle incorporates five key domains: patient risk assessment, treatment threshold for intubation, premedication plan, equipment specification, and provider selection with escalation strategies. At the University of Washington Neonatal Intensive Care Unit, eligibility criteria for the PINS bundle include neonates requiring non-invasive respiratory support with >30% FiO₂, those meeting surfactant administration criteria (≥30% FiO₂ and PEEP 6 on NCPAP), already intubated and mechanically ventilated infants, those with difficult airway diagnoses (e.g., craniofacial anomalies, large tongue, micro/retrognathia), and extremely preterm infants (<1000g or <4 weeks old). We will evaluate the impact of PINS implementation by comparing intubation attempts and adverse events before (January – June 2024) and after (July – December 2024) the bundle’s introduction. Data was adjusted to exclude ineligible patients, ensuring comparable cohorts. Primary outcomes include the number of intubation attempts before success and the incidence of tracheal intubation adverse events (TIAEs). We hypothesize that PINS implementation will be associated with a reduction in intubation attempts and TIAEs, reflecting improved preparation and procedural success by the healthcare team. By standardizing an individualized pre-intubation plan, the PINS bundle aims to enhance neonatal safety and streamline team response during intubation. Findings from this study will inform future clinical protocols and may support the broader adoption of personalized intubation strategies in the NICU. Further assessment of long-term outcomes for infants will strengthen the bundle’s clinical utility.

Serotonin serves a vital role in the regulation of stress responses, and variance in the release of serotonin was found to contribute to various mental illnesses such as anxiety and depression. Current mental health treatments heavily rely on Selective Serotonin Reuptake Inhibitors (SSRIs). While these medications are generally effective, there are patient populations for whom SSRIs show limited efficacy. Recent studies found that in response to stress, the expression of the FKBP5 gene also increases and modulates many neuronal pathways including serotonin. This experiment determined whether manipulating FKBP5 gene expression in the dorsal raphe (DRN) directly correlates with serotonin release in the basolateral amygdala (BLA), an established neural circuit for fear. To manipulate FKBP5 gene expression, an adeno-associated FKBP5-Cre virus was injected into the DRN of Pet1-Cre transgenic mice, causing up or downregulation of FKBP5 in the DRN. To gauge the effects of FKBP5, fiber photometry was used to measure the release of serotonin following optogenetic activation of the DRN-BLA pathway using a 5HT GRAB sensor injected into the BLA. We hypothesize that increased FKBP5 expression in the DRN will increase serotonin release to the BLA, and as FKBP5 expression is decreased, the release of serotonin to the BLA will decrease. Success in modulating serotonin release using FKBP5 gene expression will expand therapeutic targets in mental illness research, mitigating the gap in treatment efficacy for patients who have undergone ineffective SSRI therapy.

Alzheimer’s disease (AD) is a neurodegenerative disease that impacts millions of people and costs billions of dollars annually, with both estimates increasing as our aging population grows. Women are diagnosed with AD at a 2:1 higher rate than men, although the biological drivers of this difference remain elusive. Previous studies have demonstrated that changes to the function of microglia – the brain’s immune cells – observed during AD may be driving disease progression. Furthermore, microglia morphology is related to its function. Thus, we seek to characterize differences in microglia morphology between men and women with and without AD. We hypothesize that microglia from women have, on average, a more disease-associated morphology than those of men, and that differences are exacerbated in individuals with AD. We obtained tissue from the dorsolateral prefrontal cortex of 48 individuals who donated their brains to AD research at UW. We conducted immunohistochemistry (IHC) to stain for microglia markers (IBA1) and two markers of AD pathology (AT8 to stain for phosphorylated Tau and a pan-amyloid β stain). I imaged the samples on a Leica SP8 confocal microscope at multiple depths, which allowed us to compose a 3D rendering of the tissue through an image analysis software called IMARIS. Using IMARIS, I quantitatively measured key aspects of each microglia, such as volume and branching details. Using the data from 12-20 microglia per person, we used multiple regression to test for differences between men and women in both healthy and AD cohorts. We anticipate there are differences in the various measurements of microglial morphology between men and women with AD, which may partially explain the discrepancy in AD rates between sexes. This research is important to better understand the role of sex in AD pathology and help contextualize molecular differences observed in the larger project to which it belongs.

Chronic stress has been associated with maladaptive behaviors in both human and animal research models, but the underlying mechanisms are unclear. In this research study, we sought to define whether stress induces neural inflammation in the ventral tegmental area, the brain region primarily responsible for regulating reward consumption, learning, memory, and addictive behaviors through moderating dopamine release in other brain areas. To do this, male Sprague-Dawley rats were subjected to a chronic intermittent stress paradigm that included stressors such as wet bedding, delayed feedings, social isolation, strobe lights, and forced swims. Following the chronic stress intervention, brain sections were collected from control and experimental groups. Subsequently, immunohistological analysis was performed of microglia and astrocytes, cell types known to mediate inflammatory responses within the brain. By assessing inflammation in the ventral tegmental area through fluorescent microscopy and quantitative morphological analysis of these glial cell types, we will establish whether inflammation in this key brain region regulating motivation may be involved in the harmful behavioral outcomes often associated with chronic stress.

Building on the literature of the importance of strategy, this paper explores the relationships between wealth, strategy, and battle related deaths to find out why we may see unexpected conflict outcomes like Ukraine being able to hold back Russian offensives. This paper argues that wealthy actors often use expensive strategies, like strategic air bombing, that are ultimately ineffective at helping win a war and only cause unnecessary casualties, and that less wealthy actors are forced to be more creative with their strategies and this leads to less casualties. To do this, I analyze the relationships between data on rebel contraband (proxy for non-state actor wealth), GDP, and strategies used in war and their effect on battle related deaths. The paper will also cover the ongoing conflicts in Myanmar and Ukraine as a theoretical supplement to this data. Examining these relationships is increasingly important because wars fought in the modern era often see different sides of varying wealth using different strategies. Implementing the discoveries of this paper may give us opportunities to minimize casualties in conflicts by looking at what strategies are the least lethal at what levels of wealth.

As social media makes it easy for politicians, journalists, pundits, and news broadcasting organizations to deliver information and news directly to the people, scholars have growing concerns regarding the increasing reliance on social media to advance political information and agendas. Social media algorithms have the power to tailor information to people's preferences, issuing content that tends to cover and promote one side of a political narrative. Individual motivations to discover political content on social media, often driven by political ideology, further impact one’s political knowledge and engagement (their level of political sophistication). Bridging social media influences could clarify whether consuming news on social media shapes perceptions of media bias, which may erode trust in media, drive individuals toward ideologically aligned sources, and contribute to increased polarization and shifts in democratic engagement. Expanding on previous research that highlights the role of social media algorithms in shaping partisan bias, this paper examines the interaction of social media consumption with party affiliation and political sophistication to shape perceptions of media bias. I utilize a secondary data set from the American National Election Studies (ANES) to examine this connection between social media consumption and media bias perceptions.

As wealth continues to consolidate among the top 10% of the United States population, investing in quality and accessible education is one of the most explicit ways to increase individuals' median income. However, legislator’s perspective on the best way to support education varies widely which has contributed to the patchwork of inequitable systems throughout the nation. My research aims to test whether legislators’ socioeconomic backgrounds predict their support for and their likelihood of supporting policy to promote access and quality of K-12 public education. A negative relationship between legislators’ socioeconomic status and their voting history could provide evidence to support my hypothesis that upper class legislators are perpetuating barriers to class mobility by inhibiting pro-education legislation throughout the United States. 

Does Universal Basic Income impact educational attainment? Theorists and prior researchers have drawn mixed conclusions on the effectiveness of UBI. While some argue that unconditional cash transfers increase personal goal seeking and human capital investment behavior, increasing educational attainment, others find that UBI negatively impacts educational attainment because it encourages individuals to neglect any investment in their human capital. Despite these arguments, prior research on this topic is extremely limited, which is why it is so important for this paper to investigate these claims. I expect UBI is associated with increased educational attainment because people could use the finances from UBI to support the additional financial and time commitment costs of education. To investigate this puzzle and test my theory, this paper uses Alaska as a case study, as it provides an opportunity to study the effects of UBI through the Permanent Fund Dividend. The Permanent Fund Dividend is a recurring annual payment given to nearly every Alaskan citizen, sourced from the State’s mineral revenue, thus presenting the best large-scale proxy of UBI available to study. This paper will estimate a counterfactual, or synthetic, Alaska without the PFD, which will allow us to infer the impact of PFD on education by comparing real educational attainments with the estimated levels.

This paper explores the significance of U.S. financial assistance to weak democracies and its impact on their political processes, particularly protest movements. In recent history, almost every nation has seen anti-state demonstrations, driven by factors such as war, elections, inflation, or social issues. Domestically, these international conflicts have sparked debate among politicians, scholars, and voters about how U.S. aid should be allocated. While U.S. aid is generally regarded as a stabilizing force that fosters economic growth and democratization, little is known about its influence on political mobilization. Protest as a concept remains underutilized as a mechanism for understanding political dynamics, especially in the context of ongoing global regime changes. This paper examines how U.S. aid shapes protest in weak and transitional democracies. It investigates two competing theories: increased aid either promotes economic stability, discouraging protests, or fosters democratization, which empowers civil society and encourages protests. Using data from transitioning democracies from 1990 to 2020, this research analyzes the frequency of anti-state protests in relation to U.S. economic and military aid allocations.

The meniscus is a crescent-shaped fibrocartilaginous structure in the knee joint that plays a crucial role in weight distribution, shock absorption, and joint stability. Women experience higher rates of meniscal tears when controlled for sport and tend to have worse clinical outcomes following treatment. While surgery remains the standard treatment, regenerative therapies using human meniscal fibrochondrocytes (MFCs) have shown promise in repairing damaged tissue and improving joint stability. However, repeated culture of primary MFCs on tissue culture polystyrene (TCPS) is known to alter cell phenotype, leading to loss of native function. These phenotypic changes remove our ability to accurately model differences that are seen in vivo, such as sex differences. One approach to mitigate phenotypic change is culturing MFCs in a 3D environment, which more closely mimics the native extracellular matrix (ECM) and helps maintain cell phenotype. Little research has been done to assess whether 3D cell culture systems preserve sex-based differences in meniscal tissue. Sodium alginate beads offer a well-characterized, accessible, and cost-effective 3D tissue culture system designed for fibrochondrocytes. These beads are formed via ionic cross-linking between sodium alginate and calcium chloride solution. Studies have demonstrated that sodium alginate can maintain cell phenotype in chondrocytes, making it a promising alternative to TCPS for MFC culture. To address the issue of phenotypic changes, we cultured MFCs in sodium alginate beads and examined their ability to preserve sex differences in vitro. Previous data from our lab indicates that female MFCs express higher levels of decorin (DCN), a key ECM regulator protein, compared to male MFCs. Therefore, to determine whether the 3D structure of sodium alginate beads better supports the native phenotype of MFCs by maintaining sex differences, we analyzed DCN immunostaining. These findings establish an in vitro system that preserves and facilitates the study of sex differences observed in vivo.

As the sensitivity and capabilities of modern synchrotron facilities continue to develop, so does the field of computational material sciences in an effort to meet the demand for analysis of new properties in various systems. 3d transition metals are of special interest due to their wide range of conductive and optical properties. Traditionally, local bonding environments are characterized in terms of group symmetries, but this has limitations in complex systems. Linearly polarized emission of x-rays from these 3d materials can provide information about local anisotropy, and valence-to-core (VtC) x-ray emission spectroscopy (XES) is especially sensitive to oxidation state, ligand environment, and bond length. The purpose of this project is to use local geometric and electronic information to formulate a measure of local anisotropy. This metric is evaluated against real-space Green's function calculations of linearly polarized XES, where we apply a supervised machine learning approach trained on this metric to predict differences in the polarized spectral shapes. Polarized spectroscopy techniques are critical for a wide range of applications including the development of microelectronics, nanostructure characterization, analyzing anisotropy within quantum dots, and studying the polarization sensitivity of non-linear optics. An accurate formulation of this continuous anisotropy parameter will provide researchers with quick and inexpensive computational insight. For the development of new functional materials, this metric can be used for searching databases efficiently, allowing researchers to select the candidates that will provide a more ideal signal of any polarization dependent properties.

Veterans have high rates of early life adversity and mild traumatic brain injury (mTBI), both of which are risk factors for PTSD. Our laboratory has found that common risk factors for stress and PTSD are exacerbated by increased expression of stress-sensitive gene FKBP5. We are testing whether FKBP5 mediates a synergistic interaction between early life adversity and mTBI to produce symptoms associated with PTSD in veterans. A prior study used illness as early life trauma and concussive blast as adult trauma. In our study, the traumas are better specialized to veterans. I'm exposing C57BL/6 mice to limited bedding and nesting (LBN) adversity pre-weaning and concussive blast trauma post-weaning. Post-natal days two-nine, mice undergo LBN using insufficient bedding, reducing maternal care and increasing stress, simulating housing issues and neglect often endured by veterans in childhood. In week 13, I'm using a blast tube to administer a concussive blast to mice similar to that experienced by veterans from improvised explosive devices, resulting in mTBI. LBN, concussive blast, and sex are the variables. In week 17, I'm conducting Open Field Tests and fear conditioning on subjects to test generalized and novel fear responses and anxiety levels. Mice that endured both traumas should have the most generalized fear. If so, we will have shown that there is a synergistic interaction between early life adversity and mild traumatic brain injury that intensifies PTSD associated symptoms. Mice with both traumas are expected to have the highest FKBP5 RNA levels. We’ll analyze FKBP5 to determine how it participates in serotonin pathways resulting in these symptoms, and whether LBN and mTBI synergize to increase FKBP5 expression. We want to exemplify the role of FKBP5 as it has potential to be used in PTSD and other stress disorder treatments.

How do state policies in abusive litigation cases within domestic violence law impact state-wide case outcomes? Through this research, I investigate how state legal protections affect case outcomes for defendants in abusive litigation cases within domestic violence law. Abusive litigation, a form of coercive control, allows abusers to exploit the legal system to intimidate and financially drain their victims, perpetuating harm even after separation. While domestic violence laws addressing physical and emotional abuse are well established, their impacts are well understood. In contrast, legal protections against abusive litigation are less common, and little systematic research has explored their effectiveness. In this study, I examine how varying state-level policies—such as vexatious litigant statutes, protective order-linked restrictions, and financial remedies—shape outcomes like dismissal rates, compliance with court orders, and survivor access to justice. By analyzing state-specific legal frameworks and state-wide case data, I aim to demonstrate that robust protections significantly enhance judicial efficiency and equity for defendants. My findings will provide critical insights into the intersection of domestic violence law and procedural justice, offering evidence-based recommendations for policy reform. 

Lentivirus is a well-established gene-editing tool commonly used in cellular research. Recently, its widespread adoption has led to the development of numerous protocols for the transduction of primary human T-cells. However, generating high-titer virus for large vectors remains a challenge, and there is a need for optimized protocols – particularly for creating Base Editor lentivirus for a 15 kb vector. By developing a method to estimate transduction efficiency in primary human T-cells using viral titers, significant reduction to the waste of valuable human samples could be achieved. To address these challenges, we tested various variables—including plasmid concentration, media formulations, and transfection reagents—within infection protocols to optimize lentivirus production and improve T-cell transduction efficiency. By refining the protocol for creating Base Editor lentivirus, we aim to base-edit autoimmune-associated variants in human CD4 T-cells and assess their impact on T-cell effector function. This work is crucial for advancing base editing technologies in the Ray Lab and will contribute to the broader field of immunology.

Cancer remains the second leading cause of death in the United States, with nearly 1.9 million new cases and over 609,000 deaths annually. Research funded by the National Cancer Institute (NCI) plays a key role in advancing cancer treatments, diagnostics, and understanding. This study analyzes 24 years of NCI grant data to uncover funding trends and their broader implications. Using NIH RePORTER, we filtered and analyzed $36.07B of grants from 2000 to 2023. Leveraging BERTopic, a topic modeling algorithm, we clustered grant abstracts based on semantic similarities to identify major research themes. OpenAI’s GPT-4o-mini model was then used to generate topic labels. Our findings reveal key shifts in funding allocation. Total NCI funding has significantly increased since 2000, with notable growth in areas like Epigenetic Modifications in Cancer and P53 Pathways in HCC Liver Cancer, while topics such as Ethics of Cancer Research and Signal Transduction Pathways have seen less emphasis over time. Additionally, emerging areas like Natural Care Approaches for Cancer Patients exhibit high annual growth, reflecting new focuses in patient care. These insights enhance transparency in research funding, informing stakeholders about emerging therapies and underfunded research areas. This work highlights the link between funding and patient outcomes, demonstrating how NCI initiatives drive innovation in cancer care. By presenting trends, we aim to support equitable resource distribution, improve transparency, and enhance knowledge to guide future funding decisions. 

Investigators, funders, and the public desire knowledge on topics and trends in research funded by the federal government. Current efforts to categorize efforts are limited to manual categorization and naming of a few dozen grants at a time. We developed an automated pipeline within BERTopic (a topic modeling and representation technique) to extract and name research topics and applied this to $1.9B of NCI funding over 21 years in the radiological sciences to determine micro- and macro-scale research topics and funding trends. In our prior work by Nguyen et al., we used Word2Vec-based embeddings to represent grants, hierarchical/K-means clustering to group them, and iterative topic naming by humans to label them. Our current study builds on this with updated embedding, clustering, and generative-AI-driven naming methods. We mapped out 9202 grant abstracts from 2000-2020 using PubMedBERT-base embeddings, then clustered them into 60 clusters with HDBScan, and visualized them in two dimensions using UMAP to aid in interpretation. We employed a chaining strategy comparing c-TF-IDF and topic distributions to reduce cluster outliers. The resultant clusters were named via OpenAI's GPT-3.5 model. We used prompt tuning methods (role prompting, directive commanding) through three reinforcement phases to generate topic labels based on the most representative documents of each cluster. The three largest topics in descending order are related to PET/CT imaging, tumor cell imaging, and breast cancer computer-aided detection. We believe these results may (1) demonstrate the feasibility of using topic modeling to help funders and the public understand funding patterns in the field of radiation oncology (2) provide updated clustering and representation methodology which increases accuracy and decreases reliance on manual human validation.

Every year, thousands of cancer research abstracts are presented at the ASTRO Annual Meeting. As biomedical literature continues to grow, there is a need to better understand trends in this large corpus of unstructured text data to aid conference organizers and attendees. This study examines the effectiveness of natural language processing (NLP) techniques to organize and present conference research. We analyzed a dataset of 9,770 abstracts accepted to the ASTRO Annual Meeting conference from 2019 to 2023. Using the BERTopic Python package, we converted abstracts into PubMedBERT embeddings and clustered the embeddings into 100 topics with HDBScan clustering. We experimented with c-TF-IDF scores, centroid distance, or HDBScan probabilities as various distance metrics to identify representative documents of each topic. To generate topic names, we input representative documents and BERTopic-extracted keywords into OpenAI’s GPT-3.5 model, applying role prompting and directive commanding strategies across three reinforcement phases of prompt tuning. Manual validation of GPT-generated names was performed through surveys assessing quantitative agreement and comments. Our approach combining BERTopic with a PubMedBERT transformer model and HDBScan clustering successfully categorized 91% of ASTRO abstracts. The three largest topics encompassed thoracic malignancies, head and neck cancer radiation therapy, and prostate cancer, while the smallest topics centered around radiation oncology education and brain tumor treatments. Two-dimensional interactive visualization using the Altair package also uncovered meta-topics such as Education and Basic Science. GPT-generated names, obtained using 20 representative documents selected by c-TF-IDF scores and three prompt tuning stages, were preferred in validation over human-generated categories. These results demonstrate the potential of combining representative models and generative models to derive topics from abstracts that are more preferred than human-generated categories. Our methods for optimizing clustering and prompt tuning to produce the best organization and naming of biomedical text may also be applied to automated conference organization.

Publications are constantly being released as scientists and doctors continue to conduct new research. Keeping track of all publications released, even if narrow to a specific field, is onerous, requiring dedication of extensive time and resources. Our project uses LLMs (Large Language Models) to automate this process so that investigation of publication trends over decades is easily accessible to help inform future research. We extracted 4277 abstracts published from 2013 to 2023 from the International Journal of Radiation Oncology, Biology, and Physics. We leveraged the BERTopic (Bidirectional Encoder Representations from Transformers) framework, to cluster publications into a hundred topics based on PubMed pre-trained embeddings. In addition, we explored the parameter space of HDBSCAN (Hierarchical Density-Based Spatial Clustering of Applications with Noise), our chosen clustering method, in order to maximize the number of relevant topics and minimize the number of outliers. However, an outlier group that contained 18% of our abstracts still remained. To address this, we further processed abstracts in this group and assigned each of them to a topic using c-TF-IDF (class-based Term Frequency-Inverse Document Frequency) with more relaxed matching thresholds. We applied three different threshold levels and manually reviewed 30 randomly chosen outlier abstracts and graded them as strongly, moderately, or poorly aligned to the assigned topic. We found on our lowest threshold 76% of the abstracts were sorted to relevant topics. The verification we conduct on reduction helps ensure the quality of the clusters we produced and thus the accuracy of future analysis on underlying trends.

Senate Republicans are no longer supporting environmental policy, breaking a longstanding history of tacit support for such legislation. This occurrence is drastically highlighted in former President Joe Biden’s Inflation Reduction Act (IRA) of 2022. While policy stance change is not an atypical occurrence in Congressional behavior, it usually coalesces with legislation that fails to advance a party’s given agenda. This stipulation was not present within the IRA; it championed the Republican Party’s desires for domestic American manufacturing and industry, while simultaneously investing in US-based technologies. Why are Republicans no longer supporting legislation that reflects their historical and modern values? This study will test whether the level of polarized messaging within official Republican Party Platforms impacts the frequency of Congressional opposition towards ecological policy. I theorize that Republican Senators downvoted the IRA bill of 2022 to demonstrate ideological compliance with the 2024 GOP Party Platform. As dictated by the platform, it is in these representative’s electoral interest to oppose any ‘liberal agenda’ (even while sacrificing advancement of Republican domestic manufacturing goals) due to the increase of anti-left rhetoric and blame purported by the Republican Party. I hypothesize that increased polarization rhetoric within such documents will produce increased levels of opposing votes towards ecological policy from Republican Senators. I will first conduct a sentiment analysis of GOP and Democratic Platforms spanning from 1988 through 2024 to establish a metric of polarization level per document. Then, the roll call votes of all Senators for the 63 relevant bills will be used to conduct a regression analysis, determining whether higher polarized party documents produced higher levels of opposing votes.

Are nations holding true to their commitments to address climate change, and why or why not? On November 4th, 2016, the Paris Agreement (PA) went into force, creating a legally binding international treaty on climate change with the overall goal of limiting the increase of the global average temperature from 2 degrees Celsius above pre-industrial levels. This agreement is unique from others in that countries can build their own goals, dubbed Nationally Determined Contributions (NDCs). These NDCs refer to national climate action plans that each country made for itself under the PA, outlining how it plans to reduce greenhouse gas emissions (GHGs) to meet the 2 degrees Celsius goal. Many countries have created ambitious targets, and some have even been credible in following through on their commitments. However, there is great variation across countries in levels of ambition, and therefore in progress and implementation of NDCs. While 195 countries have signed the PA, we are still on track to surpass 2 degrees of warming early- to mid-century. It is thus crucial to investigate what drives environmental action and inaction, especially on a domestic level. In my work, I address the question “what domestic factors impede or bolster the implementation of climate action in regard to NDCs?” using regression analysis to systematically test the impact of domestic factors on nations’ progress towards meeting their self-imposed CO2 emission reduction goals.

Children of immigrants are uniquely situated in the United States. They share parts of both their American identity and upbringing, along with that of their parents’ and relatives’ homeland(s). Previous research has shown that because of these identities, children of immigrants are more civically engaged than any other group of young people. However, more research is needed to understand what is most effective for this population along with broader implications for these individuals. Utilizing the Youth-Parent Socialization Panel Study of 1965-1997 from the Inter-University Consortium for Political and Social Research, I examine different civic engagement methods including civic education and community involvement and the effect on children of minority groups as opposed to their majority group counterparts. Furthermore I predict that these methods have a positive long term impact on measures of civic engagement, while also having a stronger effect on minority groups.

This study investigates the mechanical behavior and fracture mechanisms of 3D-printed continuous carbon fiber/polymer matrix unidirectional composite materials as potential alternatives to conventionally processed laminate samples of similar geometry and constituents. A Markforged Mark Two 3D-printer is used for printing test samples using a proprietary nylon based, Onyx matrix-reinforced with C particulate and pure C fiber filament. 3D-printed samples and laminate samples will be evaluated through tensile and flexural tests to quantify mechanical properties to include strength, modulus of elasticity, and percent elongation. Hardness and sample densities will also be compared. Printing limitations of the Markforged printer will also be investigated. Fracture surfaces of both 3D printed samples and laminates will be examined with both stereomicroscopy and scanning electron microscopy to investigate differences in fracture morphologies involving fiber and matrix.

The Tait graph, an undirected graph with signed edges derived from a knot diagram, is fundamental to knot theory and algebraic topology, enabling the study of knot invariants and topological properties. Despite its importance, widely-used software packages like SageMath and SnapPy lack native functionality for Tait graph construction and manipulation. Our research addresses this gap by presenting an efficient algorithm to construct the signed Tait graph and its associated dual graph from a knot's Planar Diagram Code (PD-Code). We validated our algorithm by comparing the reduced weighted Laplacian matrices of our constructed graphs with those of nearly 3,000 classified knots up to 12 crossings. Future work will extend our implementation to support additional functionalities such as Reidemeister moves, Jones polynomial calculations, and directed edge representations. By deploying our code on SageMath, we aim to provide a valuable tool for researchers in knot theory and related fields.

Controlled and untethered Micro Aerial Vehicles (MAVs) near 1 gram offer transformative potential in applications like disaster response, inventory inspection, and precision agriculture, offering reduced costs and minimal hazards compared to larger drones. However, MAVs of this size face significant challenges in achieving both flight stability and maneuverability, particularly due to difficulties in generating sufficient lift and controlling multiple degrees of freedom mid-flight. While recent advancements have addressed various aspects of untethered flight, there has yet to be a MAV near 1 g that has also demonstrated stable hover and autonomous navigation. We introduce Coin-copter, a dual-rotor helicopter designed to overcome these limitations. We present three Coin-copter sizes, ranging from 0.8 g, to 1.1 g, and 1.8 g that leverage a foldable flybar-propeller mechanism for achieving passive stability and a feedback-controlled tail motor for yaw-axis control. Our prototypes achieve free-flight stabilization with payload capacities of up to 0.3 g, 2 g, and 5 g respectively, and evaluate the operational efficiency of each design to determine the optimal Coin-copter size for maximizing duty cycled flight time under practical energy harvesting scenarios.

Developing solutions to address social risk factors (SRF) in low- and middle- income countries (LMIC) can be difficult as many SRFs are a result of lacking financial support. SRFs are adverse living conditions that may impact the physical or mental well-being of an individual or community. Addressing SRFs in LMICs can increase implementation of evidence-based practices aimed at improving mental health outcomes. In this study, we focused on who is involved in proposed solutions that address SRFs and what specific roles those individuals undertake. Understanding what persons and roles are involved in a solution can help organize and facilitate action. We conducted a secondary inductive thematic analysis on qualitative data from a parent NIMH-funded study which aimed to develop strategies to address SRFs alongside a culturally adapted form of trauma-focused cognitive behavioral therapy (TF-CBT) for children who experienced parental death in Western Kenya. In the parent study, clinical supervisors conducted a workshop and training for TF-CBT lay-counselors to co-develop strategies to address SRFs. Most suggested strategies supported economic empowerment and a worksheet was designed to aid implementation of the strategies. This study uses data from worksheets filled out at 10 different schools in which lay-counselors designed economic empowerment strategies. The primary solutions included poultry rearing, vegetable gardening, and tree nurseries. Preliminary results show that most solutions tend to require school administration, teachers, children, for whom the solutions are for, and their guardians. Administrative roles tended to supply land required for solutions, teachers and guardians mostly supplied resources, while children were tasked with implementation of the solutions. Knowing who executes what roles can help inform what resources, skills, or knowledge a person can contribute to a solution, which may facilitate transferability between solutions. This can help researchers and communities individualize strategies to address SRFs where certain persons may be unavailable.

Protein Kinase Inhibitors (PKIs) are a family of heat stable, high-affinity inhibitors of the catalytic subunit of Protein Kinase A (PKAc). In the presence of Mg-ATP, the three isoforms—PKIα, PKIβ, and PKIγ—bind to PKAc with very low dissociation constants: 0.758nm, 1.875nm, and 0.4142nm respectively. In vitro studies have shown that PKIs can translocate PKAc from the nucleus to the cytoplasm, suggesting a role for PKIs in terminating nuclear cAMP-driven PKA activity. Previous research, including studies from our lab, has found that dysregulated PKAc mutants play a significant role in Cushing’s syndrome, a rare and potentially fatal metabolic disorder caused by excessive cortisol production. Building on these findings, we hypothesized that increasing PKI expression could counteract the hyperactivity of PKAc mutants and reduce cortisol production. To test this, we expressed each PKI isoform in adrenal cell lines and assessed their steroidogenic capacity using biochemical assays such as western blots, RNA-seq, qPCR, and ELISA-based cortisol assays. We observed that PKIα and PKIγ led to a general suppression of steroidogenic associated proteins such as StAR, Cyp11a1 and SF1. This altered proteome was accompanied by significantly suppressed cortisol synthesis only in the PKIα and PKIγ expressing cells. The difference between PKIα/γ and PKIβ was surprising given that all PKI isoforms are postulated to potently inhibit PKAc. Thus, we questioned whether PKIα/γ effects are mediated through PKAc. To answer this, we have cloned mutant PKI isoforms that do not bind PKAc, and confirmed the mutant PKIs do not inhibit PKAc through kinase assays. Our next step is to express the mutant PKI isoforms in adrenal cells and assess their effect on steroidogenic capacity of the cells. Our findings suggest that PKIα and PKIγ play key roles in cortisol regulation and may have broader implications for gene regulation in adrenal cells.