VictorJuiz/thesis huggingface dataset:
Linking heat stress resistance and recovery in reef-building corals

Organisms are facing more intense and frequent stress events in their environments due to climate change impacts, and resilience capacity plays a vital role in survival and persistence through generations. Two important components of stress resilience are the ability to resist and recover from stress. Yet, there is limited understanding of how mechanisms of an individual's resistance and recovery ability contribute to overall resilience, how resistance and recovery may be linked, and whether there are other physiological tradeoffs associated with resistance and recovery. Reef-building corals are the foundational taxa of highly diverse and productive marine ecosystems, and ocean warming represents one of the biggest threats facing corals currently and under future climate change scenarios. Yet, experiments on coral resilience research focuses primarily on identifying and bottling those corals that are predicted to excel at bleaching resistance. However, as our oceans continue to warm, even the most bleaching resistant corals will be at a high risk of bleaching. Therefore, it is valuable to shift focus toward comprehensively evaluating the interconnectedness of other stress resilience factors, like heat stress resistance and recovery. In this dissertation, I characterize patterns of individual heat stress resistance and recovery ability in the tabletop coral Acropora hyacinthus. I show that mortality after short-term heat stress occurs rapidly and is positively correlated with bleaching severity, bleaching state is stable after heat stress, and there is a high likelihood of longer-term recovery if corals survive the first week post-stress. I also show that moderately resistant corals exhibit higher skeletal growth than low and high resistant corals by four months post-heat stress, and that there is significant differential gene expression between low, moderate, and high resistant corals at pre- and post-heat stress timepoints that may illuminate underlying mechanisms of individual resistance and recovery. These results provide insight into putative links between coral heat stress resistance and recovery, and fitness tradeoffs associated with resilience capacity

Keywords: Biology.
Advisor: Palumbi Stephen R.
Grottoli Andréa G.
Hadly Elizabeth Anne
Pringle John R.
Long-distance compensatory lengthening

Compensatory lengthening (henceforth, CL) is the phenomenon wherein one segment in a word is deleted or shortened, and another is lengthened to make up for it. Traditionally, the two segments involved have always been adjacent to one another, or in adjacent syllables and separated by only a single consonant. As such, previous accounts of CL have assumed (either tacitly or explicitly) that these were the only possibilities. In this thesis, I present evidence from Slovak and Estonian that the two sounds can in fact be separated by any distance. In Slovak, the deletion or shortening of one vowel can cause another vowel two syllables away to lengthen. In Estonian, the deletion of a vowel anywhere in the word can cause the first syllable to lengthen. The existence of such patterns warrants a new theoretical account of CL, which is exactly what this thesis will provide. I will argue that CL amounts to the movement of a mora from one segment to another, and that moras are required to move as little as possible in this way. This is enforced via the proposed constraint M(ULTI)T(IER)-LIN(EARITY), which is an expanded version of LIN that punishes the inversion of precedence relations between any two nodes in the prosodic hierarchy---including moras and segments. It is violated more the further a mora moves from its original position, and therefore assigns a greater number of violations to long-distance CL than local CL. If this constraint is highly-ranked, CL will be purely local. If it is dominated by other markedness constraints, CL can be forced into being long-distance if such is necessary in order to avoid violations of those markedness constraints

Keywords: Linguistics.
Advisor: Kiparsky Paul
Anttila Arto
Leben William Ronald
Ryan Kevin M. (Professor of linguistics)
Long-term intertidal community change following mass mortality of Pisaster ochraceus, a keystone marine predator

Beginning in 2013, a Sea Star Wasting Disease epidemic caused a mass mortality event for the ochre sea star (Pisaster ochraceus) and several other sea star species across their entire range of distribution in the California Current region. Because Pisaster ochraceus is a keystone species in rocky intertidal communities and has been shown to control California mussel (Mytilus californianus) populations and prevent their competitive dominance under several settings, thereby maintaining intertidal community diversity, sudden sea star population declines are expected to cause cascading changes on the community. This study tests this prediction and investigates how the natural removal of keystone predation affects the rocky intertidal community in the long term. Previous studies conducted at Hopkins Marine Station, in Monterey Bay, California, in 2014 and 2015 found a limited and spatially heterogeneous expansion of M. californianus following the sea star demise. Field surveys of 18 mussel plots at two sites at Hopkins Marine Station conducted three times a year between 2014 and 2021 show that mussel cover has been increasing since 2014, when there was a peak in mussel recruitment in the area, and that the lower limit of mussel beds has been shifting to lower tidal heights, supporting the hypothesized mussel expansion following predator mass mortality. However, long-term monitoring of the P. ochraceus population at Hopkins Marine Station shows that sea star abundance has been declining since long before 2013. It is therefore likely that changes in M. californianus abundance and distribution are driven by other factors, such as recruitment variability and extreme events in addition to predation pressure. As more mass mortality events are expected under warming conditions in the coming decades, the results of this study, and of future research addressing the impact of multiple stressors on intertidal communities can inform predictions about how the community will change when these events occur.

Keywords:  Department of Biology
Biology
Keystone species
Pisaster ochraceus
Mytilus californianus
Mussels
Sea Star Wasting Disease
Marine ecology
Predation
Recruitment
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Thesis
Advisor: Micheli Fiorenza
Fukami Tadashi
Crowder Larry
Look Who’s Talking: Examining the role of racialized beliefs in language processing and speaker judgments

We heavily depend on information about who is talking, as well as our prior beliefs about the world, to construct meaning. However, there exists little empirical research on the role of preconceived notions and stereotypes in how we process utterances and judge their speakers. In a series of three experiments, I examine how racialized ideologies affect both language comprehension and listeners’ judgments of different speakers. I first investigate whether racialized stereotypes and beliefs affect comprehension using a series of self-paced reading tasks (Experiments 1 & 2), and then ask whether racial (and gendered) biases affect the degree to which listeners penalize speakers for interrupting (Experiment 3). Experiments 1 and 2 provided no evidence for the activation of racialized stereotypes. The findings from Experiment 3 suggest that race and gender significantly affect how a speaker is judged. When interrupting, female speakers were judged to be less prosocial, more aggressive, and less intelligent than male speakers. And when interrupting, Black speakers were judged to be less prosocial, and more aggressive than White speakers. These results suggest that the perceived race and gender of a speaker — and the implicit biases associated with race and gender — affect how harshly a listener penalizes that speaker for interrupting. This penalization has broader consequences in larger societal systems including the courtroom and classroom.

Keywords: language and race
linguistic discrimination
language processing
race and perception
speaker perception
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Thesis
Low power techniques for wireless MRI receiver arrays

A longtime goal of the MRI community has been the development of conformal wireless receiver arrays as an alternative to their bulky, rigid, and often uncomfortable standard implementations. Current MR receive channels require high power consumption to enable the stringent Noise Figure, Gain, and Dynamic Range necessary for clinically relevant data. Combined with high channel counts (32 to 96), power consumption is a major challenge when translating to the wireless use case. As the pre-amplifier is the receiver element that determines many performance metrics and can consume over 200mW it is a prime candidate for re-evaluation. In this work, I will present an alternative SiGe HBT based MRI pre-amplifier with power con- sumption up to 28x less than current HEMT-based devices. Its potential for integration is first evaluated through behavioral modeling alongside a real image dataset. Following initial simulated results, its impact on imaging performance is evaluated via benchtop evaluation with MR-relevant receiver components. Alongside this pre-amplifier I propose a semi-blind calibration and compensa- tion framework that can be integrated into the existing pre-scan period for dynamic range expansion, as this amplifier features reduced linearity relative to MR standards. The application of this cali- bration method is able to reduce errors stemming from non-linear distortion to levels comparable to industry reference amplifiers. This is followed by preliminary work integrating this amplifier and calibration method into a 1.5T system demonstrating example calibration experiments and phantom images. The presented calibration method is applied to these images recovering image quality and illustrating the potential for the utility of the presented amplifier and calibration method. This concludes in a discussion regarding system level integration considerations for such a method in high-channel count arrays

Keywords: Electrical Engineering.
Advisor: Pauly John (John M.)
Rivas-Davila Juan
Scott Greig Cameron
Machine learning and crowdsourcing for digital behavioral phenotyping

Early childhood is the most potent opportunity to impact long-term health and learning. However, there are major bottlenecks to care, with a massive shortage of clinicians for diagnosis and treatment, disproportionately affecting underserved populations. This thesis centers around developing a streamlined system for continuously phenotyping children with potential developmental delays by leveraging distributed non-expert crowdworkers in conjunction with machine learning algorithms. This work involves collecting diagnostically rich information from children and their parents in a secure and trustworthy manner, curating a reliable and capable crowd workforce for labeling behavioral features, and training behavioral computer vision classifiers for detection of neurodevelopmental concerns

Keywords: Bioengineering.
Advisor: Wall Dennis Paul
Altman Russ 
Liphardt Jan
Machine learning for clinical trials and precision medicine

Machine learning (ML) has been wildly applied in biomedicine and healthcare. The growing abundance of medical data and the advance of biological technologies (e.g. next-generation sequencing) have offered great opportunities for using ML in computational biology and health. In this thesis, I present my works contributing to this emerging field in three aspects --- using large-scale datasets to advance medical studies, developing algorithms to solve biological challenges, and building analysis tools for new technologies. In the first part, I present two works of applying ML on large-scale real-world data: one for clinical trial design and one for precision medicine. Overly restrictive eligibility criteria has been a key barrier for clinical trials. In the thesis, I introduce a powerful computational framework, Trial Pathfinder, which enables inclusive criteria and data valuation for clinical trials. A critical goal for precision medicine is to characterize how patients with specific genetic mutations respond to therapies. In the thesis, I present systematic pan-cancer analysis of mutation-treatment interactions using large real-world clinico-genomics data. In the second part, I introduce my work on developing algorithms to solve biological challenge --- aligning multiple datasets with subset correspondence information. In many biological and medical applications, we have multiple related datasets from different sources or domains, and learning efficient computational mappings between these datasets is an important problem. In the thesis, I present an end-to-end optimal transport framework that effectively leverages side information to align datasets. Finally, I present my work on developing analysis tools for new technologies --- spatial transcriptomics and RNA velocity. Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In the thesis, I describe a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. Recent development in inferring RNA velocity from single-cell RNA-seq opens up exciting new vista into developmental lineage and cellular dynamics. In the thesis, I introduce a principled computational framework that extends RNA velocity to quantify systems level dynamics and improve single-cell data analysis

Keywords: Electrical Engineering.
Advisor: Zou James
Soh H. Tom
Tse David
Machine learning for seismic event detection : a story in three parts: earthquakes, microseismic events, and tectonic tremors

As new seismic acquisition methods arise, growing data volumes call for automated processing methods to extract full value out of the recorded data. Herein, we develop an end-to-end machine learning framework for seismic event detection and identification on continuous data. We illustrate our methodology through three field-data use cases. Firstly, we perform earthquake detection using fiber-optic cables in the telecommunication conduits under the Stanford University campus. We identify new uncataloged small-magnitude local earthquakes by analyzing more than three years of continuous recordings. We demonstrate that fiber-optic cables can complement sparse seismometer networks. We then tackle microseismic event detection in fiber-optic data acquired inside an unconventional reservoir. Our methodology identifies more than 100,000 events over ten hydraulic stimulation stages, allowing the reconstruction of the spatio-temporal fracture development far more accurately and efficiently than would have been feasible by traditional methods. Finally, we explore tectonic tremor identification using a catalog of more than 1 million events detected along the central San Andreas Fault over a period of 15 years. Tectonic tremors are composed of hundreds of repeating low-frequency earthquakes (LFEs). These LFEs are near the noise level and are thus usually found via a multichannel matched-filter search using carefully curated waveform templates. We demonstrate that our methodology can successfully detect new LFEs with low signal amplitude without a prior template

Keywords: Geophysics.
Advisor: Biondi Biondo
Beroza Gregory C. (Gregory Christian)
Clapp Robert G. (Robert Graham)
Macroporous hydrogel sponges for enhancing stem cell transplantation and skeletal muscle regeneration following traumatic injury

Volumetric muscle loss (VML), characterized by an irreversible loss of skeletal muscle due to trauma or surgery, is accompanied by severe functional impairment and long-term disability. Tissue engineering strategies combining stem cells and biomaterials hold great promise for skeletal muscle regeneration. However, scaffolds, including decellularized extracellular matrix, hydrogels, and electrospun fibers, used for VML applications generally lack macroporosity. As a result, the aforementioned scaffolds typically delay host cell infiltration, transplanted cell proliferation, and new tissue formation. In this dissertation, I will present our work on engineering macroporous hydrogel scaffolds to enhance stem cell treatment of VML. We show that scaffold macroporosity improved muscle stem cell proliferation in vitro and in vivo. In addition, scaffold macroporosity promoted early scaffold cellularization, endothelialization, and establishment of a pro-regenerative immune microenvironment in a mouse VML model. Moreover, we found that the macroporous hydrogels enhanced muscle tissue regeneration and recovery of muscle function four weeks after implantation. Finally, we demonstrated the scalability of our approach, with respect to scaffold fabrication and therapeutic efficacy, using a rat VML model. Together, our results validate macroporous hydrogels as novel scaffolds for VML treatment and skeletal muscle regeneration

Keywords: Bioengineering.
Advisor: Rando Thomas A.
Chaudhuri Ovijit
Cochran Jennifer R.
Heilshorn Sarah
Making and measuring race, ethnicity, and language : South Asian racialization across community contexts

Mainstream approaches to understanding ethnoracial categories such as Asian American presuppose them to be pre-existing, self-evident empirical phenomena that can be objectively perceived and measured according to stereotypical signs thereof. Rather than such approaches for granted, I demonstrate, how, under the guise of (neo)liberal multiculturalism, the presupposition of stereotypical signs of Asianness portend the techniques of government that motivate demographic projections and the perceived reconstitution of Americanness, necessitating modes of governance for managing difference. Building off scholars' examination of liberal multiculturalism as a political technology for (re)producing difference embodied as societal abjection, I am in dialogue with theorizations of racialized populations' positionality that are located in a relation between (neo)liberal multiculturalism and a politics of "post-multiculturalism". That is, this dissertation explores the interplay between the liberal democratic politics of inclusion/production of difference and the positioning of difference as a legitimate object of liberal democratic exclusion as it plays out in South Asian American serving community-based organizations in the Chicagoland area. Through analyzing the relationship between historical, institutional, and interactional negotiations of the English as a Second Language (ESL) intake process, diversity discourses, and securitization processes, I ask (1) How are colonially constituted and institutionally sanctioned modes of categorization and measurement, particularly in relation to South Asian Americans, understood, (re)produced, and negotiated across scales in the Chicagoland area?; and (2) In what ways can we conceptually rethink pragmatic approaches to educational and societal stratification and attendant inequities by attending to how racializing histories constitute contemporary material relations? Through the deployment of qualitative methods, including over a year-long ethnographic engagement with South Asian American communities entailing participant observation, structured interviews, archival inquiry, and critical discourse analysis, I focus on the ways South Asians are recruited to occupy circumscribed political subjectivities, identities, and modes of expressivity rooted in the settler colonial and imperialist formation that is the US. This racializing histories approach to contemporary material relations helps to fundamentally rethink the nature of educational and societal inequities

Keywords: Education.
Advisor: Rosa Jonathan
Inoue Miyako
Martínez Ramón
Making every day Earth Day : family environmental learning in the home context

Environmental learning is an important avenue to more sustainable environmental behavior; prior research focuses heavily on formal and informal environmental education programs. Equally important, however, is understanding how children and caretakers learn in everyday life contexts, such as within the home, and how we can support environmental learning in that context. Using a learning ecology framework, I conducted a remote, two-week diary study with 58 diverse adult caretakers, asking them to engage in environmental learning moments at home with their children. Following the diary study, I also conducted semi-structured interviews with 13 caretakers to gain a deeper understanding of their perspectives, experiences, and identities. The qualitative and quantitative data from the diary study and interviews were analyzed using three different lenses, each of which are presented in individual papers. In the first paper, I present an analysis which reveals the types of activities, discussions, topics, and resources with which families engage, as well as differences by demographic groups. In the second paper, I focus the analysis on the learning moments to understand what resources parents leverage and why, how technologies can enhance exploration in the world, and how families react to two pre-selected educational climate change-related videos. In the third paper, I explore how parents themselves generate ideas about climate change and sustainability, and in particular, the role of identities, attitudes, and beliefs. At the end, I discuss methodological and theoretical contributions to the literature as well as relevant implications for designers, educators, policymakers, and researchers to support family environmental learning in the home and everyday life context

Keywords: Education.
Advisor: Ardoin Nicole M. (Nicole Michele)
Blikstein Paulo
Barron Brigid
Making Sense of a Nonsensical World

Artist Gunner Dongieux speaks to the thematic underpinnings of his expansive 25-painting installation in OK Corpse, the 2022 Art Practice Undergraduate Honors Thesis Exhibition. Describing paintings rich in absurdist humor and pop-cultural puns, Dongieux ponders how one makes sense of a nonsensical world, exploring the tension between his desire to form logic through depiction, and his subject’s inherent absurdity.

Keywords: Absurdism, Humor, figurative painting, painting, pop-culture, absurdist humor, airbrush, puns
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Thesis
Mallows permutation model : sampling algorithms and probabilistic properties

Introduced by Mallows in statistical ranking theory, Mallows permutation model is a class of non-uniform probability measures on permutations. The general model depends on a distance metric that can be chosen from a host of metrics on permutations. This thesis studies Mallows permutation models with L1 and L2 distances, respectively known as Spearman's footrule and Spearman's rank correlation in the statistics literature. We focus on two aspects of these Mallows models--sampling algorithms and probabilistic properties. For sampling algorithms, we investigate hit and run algorithms for sampling from the two Mallows models. Hit and run algorithms are a broad class of Markov chain Monte Carlo algorithms that includes the celebrated Swendsen-Wang algorithm for sampling from the Ising model. These algorithms are usually non-local and fast mixing in practice. In this thesis, we show that the hit and run algorithms for sampling from Mallows permutation models with L1 and L2 distances mix extremely fast. For probabilistic properties, we consider the following question: Picking a random permutation from either of the two Mallows models, what does it "look like"? This may involve various features of the permutation. In this thesis, we focus on the distribution of the points in the graphical representation of the permutation. We show that most of these points are concentrated in a band around the diagonal of the plane with high probability, and obtain precise limit theorems regarding the distribution of the points and their band structure. The proofs of these results are based on multi-scale analysis and the use of the hit and run algorithm as a proof technique

Keywords: Statistics.
Advisor: Diaconis Persi
Dembo Amir
Siegmund David