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(Dis)Connected: Political Polarization, Social Connection, and Social Trust in the United States
No full textThis thesis examines the relationship between political polarization, social connection patterns, and social trust in the United States through a multi-scale quantitative analysis. Using county-level data from the 2016 and 2020 presidential elections, social connection data from Meta, demographic information from the US Census, and data on trust from Gallup surveys, I analyze how these data influence five specific dimensions of polarization: spread, dispersion, divergence, group distinctness, and size parity. My findings reveal that within-county social connectedness is significantly associated with increased dispersion polarization, suggesting that denser social networks support more varied political attitudes. My analysis of cross-county social connections showed that stronger connections between counties slightly decrease overall polarization measures but also increase political similarity between connected counties. These relationships are strongly moderated by geographic and demographic factors, with distance, education, and racial diversity playing particularly important roles. Contrary to expectations, national data (though limited) show that some measures of polarization and all measures of institutional trust increased simultaneously between 2016 and 2020, challenging the hypothesis that polarization necessarily erodes trust. These findings highlight the importance of examining polarization as a multidimensional construct and of considering the multiple scales at which social connections operate to influence political environments.Extension Studie
The evolution of neo-sex chromosomes in Australian honeyeaters (Aves: Meliphagidae)
No full textSex chromosomes display remarkable diversity across the tree of life, including extraordinary variation in their number, size, content, sex determining pathways, and rates of turnover, often even among closely related lineages. In birds, the Z and W sex chromosomes were thought to be stable and immune from evolutionary turnover events because they arose over 140 million years ago and appear to be present in all extant avian lineages. However, discoveries of neo-sex chromosomes, which constitute a type of turnover involving autosomal fusions with ancestral sex chromosomes, have begun to accumulate in various avian lineages. My dissertation focuses on describing the structure and phylogenetic distribution of neo-sex chromosomes in honeyeaters (Aves: Meliphagidae), investigating potential consequences of their formation in the context of gene expression, and finally examining their potential role in climate adaptation. In Chapter 1, I characterize the putative fusion and structure of the neo-Z chromosome with genomic data by creating a high quality long-read genome and comparing it with other avian genomes. In Chapter 2, I integrate cytogenetic data and whole genome resequencing data to validate the fusion and structure of both neo-Z and neo-W chromosomes and resolve the phylogenetic distribution of neo-sex chromosomes in this clade. I also conduct phylogenetic tests to determine the timing and extent of recombination suppression on the neo-W, which is a hallmark of sex chromosome evolution and over time results in degeneration of the W. In Chapter 3, I investigate the evidence for dosage compensation on the neo-sex chromosomes, which is a regulatory mechanism that can evolve in response to degeneration of the neo-W to restore ancestral gene expression levels. I find evidence of incomplete dosage compensation in both the ancestral and added region of the neo-sex chromosomes. In Chapter 4, I conduct genotype-environment association analyses in a honeyeater with neo-sex chromosomes distributed across an aridity gradient in New South Wales. I find the ancestral Z has more significant associations with climate than the added Z and unexpectedly discover a number of large outlier regions on autosomes, including a polymorphic inversion, that are highly associated with climate and likely facilitating local adaptation through recombination modification. Taken together, my dissertation leverages genomic, transcriptomic, and cytogenetic data to shed light on a novel avian sex chromosome system and explore effects of its formation.Biology, Organismic and Evolutionar
Simulating a MethaneAIR Controlled Release Trial using Computational Fluid Dynamics
No full textThe identification and quantification of methane emission sources through remote sensing is a necessary technological innovation towards the mitigation of greenhouse gas emissions. MethaneSAT is a methane tracking satellite that targets point source and diffuse emissions in the oil and gas industry. MethaneAIR, MethaneSAT’s aircraft precursor, acted as a proof-of-concept through its controlled release trials. Due to systematic errors in the imaging spectrometer, such as the assumption of sub grid scale methane concentration homogeneity, the total methane mass in a plume is hypothesized to be underestimated with variation based on spatial resolution. In this paper, a workflow is developed for the simulation and vertical integration of a controlled release plume such that it may be tested and compared with spatial statistics to the MethaneAIR image of that plume. In the context of greenhouse gas emission quantification through satellite altimetry, it is paramount that the sensitivity and detectability of methane by imaging spectrometers is analyzed and quantified relative to comparable data. Computational fluid dynamics simulators can model plumes previously captured by these imaging spectrometers to further the applicability of controlled release data.Engineering Sciences S
EvoAI enables extreme compression and reconstruction of the protein sequence space
No full textDesigning proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.Chemistry and Chemical BiologyAuthor's Origina
Assisting and Evaluating Upper Extremity Movements with Wearables Systems
No full textUpper extremity impairments from injuries and illnesses can result in physical disabilities, medical expenses, and productivity loss in labor intensive occupations. In recent years, wearable sensing and assistive robots have risen as promising tools for general kinematics tracking, injury prevention, and rehabilitation. These wearable options offer a new realm of solutions avoiding issues such as limited clinician availability and expensive infrastructural changes in the workplace. For wearable robotics specifically, soft robots also have the potential for extra comfort, minimal restrictions and harm from joint misalignments as compared to their rigid counterparts. This thesis seeks to bridge the gaps in current wearable assistive and rehabilitative technologies through introducing control and evaluation strategies for a soft inflatable shoulder robot to assist with industrial overhead work and presenting a motor function estimation algorithm with wearable inertial sensors.
The thesis begins with the development of a kinematics-based state machine controller for a soft inflatable shoulder wearable robot for industrial work. The controller is aimed to provide assistance to the shoulder quickly and accurately when needed during overhead industrial work. The state machine was designed to classify user intent using shoulder and trunk kinematics estimated with body-worn inertial measurement units. Through human subject experiments, we evaluated the controller’s intent classification accuracy and response times, by using the users’ reactions to cues as their ground truth intentions. On average, we found that the kinematics controller had 99% classification accuracy, and responded 0.8 seconds after the users reacted to the cue to begin work and 0.5 seconds after the users reacted to a cue to stop the task. In addition, we implemented an EMG-based controller for comparison, with state transitions determined by EMG-based thresholds instead of kinematics. Compared to the EMG controller, the kinematics controller required similar time to detect the users’ intentions to stop overhead work but an additional 0.17 seconds on average for detecting users’ intentions to begin. We also implemented an online adaptive tuning algorithm for the kinematics controller to speed up
response time while ensuring accuracy during offset transitions.
Post assessment of the controller, we evaluated the robot’s performance with this controller with
a portable system. The updated portable robot is worn like a shirt with integrated textile pneumatic actuators, inertial measurement units (IMUs), and a portable actuation unit. It can provide up to 6.6 newton-meters of torque to support the shoulder and cycle assistance on and off at six times per minute. From human participant evaluations during simulated industrial tasks, the robot reduced agonist muscle activities (anterior, middle, and posterior deltoids and biceps brachii) by up to 40% with slight changes in joint angles of less than 7% range of motion while not increasing antagonistic muscle activity (latissimus dorsi) in the current sample size. Comparison of controller parameters further highlighted that higher assistance magnitude and earlier assistance timing resulted in statistically significant muscle activity reductions. During a task circuit with dynamic transitions among the tasks, the kinematics-based controller of the robot showed more robustness to misinflations (96% true negative rate and 91% true positive rate), indicating minimal disturbances to the user when assistance was not required. A preliminary evaluation of a pressure modulation profile also highlighted a trade-off between user perception and hardware demands. Finally, five automotive factory workers used the robot in a pilot manufacturing area and provided feedback.
Building upon the robot controller and biomechanics evaluation, we aimed to improve the adaptability of the robot through developing a dynamic controller with the purpose of providing assistance during quasi-static motion and allowing for minimal restrictions during fast movements. Furthermore, we designed an on-body measurement tool to enable direct measurements of elevation torque during unconstrained tasks for the first time. With the development of these tools, we evaluated the effect of various support types on user biomechanics and perception. We found that the improved robot can provide 7.3 newton-meters of elevation torque with controller gains being effective in modulating the absolute torque delivered. The robot reduced muscle activity in the agonist muscles without affecting the antagonist ones during controlled and functional activities. Comparing the amount of support
delivered to the biomechanical outcomes, we observed a pseudo-linear relationship between the percentage of support to the user and the percentage of muscle activation reduction. Finally, the users were able to perceive the differences among the assistance types, in terms of perceived robot support, transparency and precision, with a main preference for sufficient support during loaded conditions.
In addition to control and evaluation methods for assistive robots, this thesis aims to contribute to wearable sensing algorithms. In a final demonstration of an application of wearable sensing, we present an estimation algorithm for estimating upper extremity Fugl-Meyer Assessment (FMA-UE) scores, a well-accepted post-stroke recovery metric for motor function assessments. To address the need for simplified automated FMA-UE assessments, we present an estimator which can make score predictions for a subset of the full assessment using data from inertial measurement units placed on the hands, arms and the trunk from a minimal number of volitional reaching motions representative of functional daily activities. To develop the estimator, we collected a dataset of eleven stroke participants performing a key subset of FMA-UE motions, and three reaching motions. The FMA-UE of each participant was assessed by an occupational therapist providing the labeled score for the training data. The estimator was trained on windowed data during FMA-UE motions and was able to make score estimates from reaching motions. Through leave-one-subject-out cross validation, the estimator achieved a normalized RMSE of 7%, which is comparable to or below the established minimal clinically important difference and minimal detectable change of FMA-UE for individuals with chronic stroke. Comparison experiments of various model designs also revealed the importance of trunk-based features inspired by compensation strategies common post stroke and features extracted from the hand sensor.
Together, this thesis contributes to control and evaluation methods for wearable systems for both healthy and clinical populations targeting the use cases of injury reduction and rehabilitation progress tracking respectively.Engineering and Applied Sciences - Computer Scienc
AIlice in Numberland: Comparing numerical understanding in language models and humans through multilingual reasoning puzzles
No full textNumbers in language constitute an extraordinary human cultural innovation. When counting, languages around the world use diverse mathematical strategies to construct and combine their numbers. People learn how to use these systems of numbers despite this diversity. But while large language models (LLMs) appear to independently excel at linguistic and mathematical tasks, they are unable to solve linguistic-mathematical puzzles about systems of numbers in different languages, which humans can learn to solve successfully. This thesis presents a detailed investigation into why this task is difficult for language models.
We design a series of experiments that untangle the linguistic and mathematical aspects of numbers in language, probing at how individual parameters of numeral construction and combination affect model performance. Our experiments establish the novel finding that while individual mathematical features do not hinder the solving ability of current large language models, LLMs are unable to infer the compositional structure of numerals in these problems like humans can. LLMs cannot consistently solve such problems unless the mathematical operations in the problems are explicitly marked using known symbols (+, ×, etc.). Humans are able to use their understanding of numbers in language to make inferences about the implicit compositional structure of numerals — language models seem to lack this notion of numeral structure. We conclude that flexible, adaptive cross-domain use of language appears to remain a challenge for current language models.Computer Scienc
Judicial Bias and Religious Assumptions in U.S. Asylum Adjudication
No full textThis paper examines how religious and cultural assumptions held by immigration judges in the United States can profoundly influence the adjudication of asylum claims. Through detailed analysis of three appellate cases—Yan v. Gonzales, Pavlova v. INS, and Fiadjoe v. Attorney General—the study reveals how judicial decisions are often shaped by unconscious biases rooted in American religious norms and colonialist understandings of non-Western traditions. These biases distort the evaluation of asylum criteria, leading to unjust denials. The paper further explores the historical and ideological roots of these assumptions in U.S. immigration law and proposes concrete legal strategies—including expert testimony and culturally informed legal advocacy—to counteract bias and promote more equitable asylum adjudication.Author's Origina
Boundary construction and education: un/belonging among Somali refugee students in Addis Ababa, Ethiopia
No full textThis study analyzes how un/belonging is experienced by Somali refugee students in public primary schools in the Bole Michael area of Addis Ababa. Drawing on data from interviews and focus group discussions, we place these micro-level experiences of un/belonging in conversation with the current Ethiopian policy for the inclusion of refugees in the national education system. While the inclusion of refugees is now the status quo for large refugee-hosting countries in the Global South, we find that this policy often ignores the specificities of refugees’ educational experiences in particular places. Somali refugees describe public primary schools as ‘difficult’ and ‘alien’ to their culture, while school authorities and teachers characterize Somali learners as ‘others’ who should, but fail to, assimilate. Our findings indicate the need for policies and practices to engage in negotiations between refugees and public schools to move beyond foundational efforts of providing access to schools to goals of learning and belonging.Accepted Manuscrip
Disentangling sex differences in PTSD risk factors
No full textDespite extensive research on sex/gender differences in posttraumatic stress disorder (PTSD), underlying mechanisms are still not fully understood. Here we present a systematic overview of three sex/gender-related risk pathways. We assessed 16 risk factors as well as 3-month PTSD severity in a prospective cohort study (n=2924) of acutely traumatized individuals and investigated potential mediators in the pathway between sex assigned at birth and PTSD severity using multiple mediation analysis with regularization. Six risk factors were more prevalent/severe in women, and none were more pronounced in men. Analyses showed that acute stress disorder, neuroticism, lifetime sexual assault exposure, anxiety sensitivity, and pre-trauma anxiety symptoms fully mediated and uniquely contributed to the relationship between sex assigned at birth and PTSD severity. Our results demonstrate different risk mechanisms for women and men. Such knowledge can inform targeted interventions. Our systematic approach to differential risk pathways can be transferred to other mental disorders to guide sex- and gender-sensitive mental health research.Accepted Manuscrip