VictorJuiz/thesis huggingface dataset:
Learning with fishing families : how worldviews and lived experience shape fisher livelihoods and marine conservation

This dissertation takes an embedded approach to examine how understanding the worldviews and lived experience of Indigenous small-scale fishers, including how marine resources contribute to their well-being, can move toward more productive and inclusive resource management in Central Sulawesi, Indonesia, which sits at the heart of the Coral Triangle. My first chapter reviews how visual participatory methods can facilitate nuanced understandings of stakeholder perceptions of social-ecological systems, as well as reconcile disparate worldviews toward locally relevant conservation outcomes. In my second chapter, I employ participatory photography to explore how Indigenous fishing families experience time and how evolving time perception influences resource use. My third chapter dives deeper into one fishery, the global aquarium trade, and how it enhances the resilience of fisher livelihoods. In my fourth chapter, I examine what motivates and sustains use of 'destructive' fishing practices and whose knowledge is privileged when labeling certain practices as destructive. Across the latter three empirical chapters, I show how local weather patterns influence resource use and well-being and argue for conservation approaches that are more attentive to these cycles. In sum, this work provides empirical evidence of how fisher ontology (ways of being) and epistemology (ways of knowing) influence marine resource use, as well as how the aquarium trade contributes to fisher livelihoods. These findings inform recommendations for including fisher worldviews and lived experience in conservation efforts. .

Advisor: Ardoin Nicole M. (Nicole Michele)
Crowder Larry B.
Durham William H.
Pauwelussen Annet
Leaving Brussels for Moscow: Examining External Factors in Yerevan’s Decision to Forgo the 2013 EU-Armenia Association Agreement

On September 3rd 2013, President Serzh Sargsyan announced that Armenia would abandon its proposed Association Agreement with the European Union after years of negotiations. In place of this agreement, Armenia would pursue full membership in the Russian-led Eurasian Economic Union (EAEU). Although this abrupt decision came as a surprise to Armenian political actors and many western observers, this development was the product of years of political maneuvering by Moscow towards Armenia as part of the creation of an alternative model of regional integration within the former Soviet Union. Considering that the European Union and Russia held relative parity with one another as trading partners of Armenia and both Brussels and Moscow held close diplomatic ties with Yerevan this begs the question: what specifically allowed Russia to pry Armenia away from its path of European Integration and secure Yerevan’s membership in the EAEU? In exploring Sargsyan’s decision, this paper will investigate the elements differentiating Russia and Europe’s trading relationship with Armenia, differences between Brussels’ and Moscow’s ability to act as an energy provider to Armenia, and Moscow’s role as a guarantor of security to Yerevan.

Keywords: Eurasian Union
EAEU
Eurasian Economic Union
Eastern Partnership
Armenia
European Union
South Caucasus
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Thesis
Advisor: Crews Robert
McFaul Michael
Legacy Media Coverage of Russia’s Activities in the Arctic

The changing conditions in the Arctic have sparked interest for stakeholders across the globe. The melting ice sheets create both opportunities and challenges. New transport routes are opening up that would shorten delivery times to both Europe and Asia significantly. Oil and gas exploration is of interest to many. Warmer temperatures threaten biodiversity and the communities dependent thereupon. Geopolitical and security issues are of concern and actors such as China and the EU are vying for position. With the largest Arctic coastline of all the Arctic states, Russia has by far the most dominating presence in the region.
For decades, Russia’s motivations, both generally and in the Arctic, have been an enigma for Western audiences to decipher, which leaves room for various interpretations and the potential for misunderstanding. The media plays a significant role when it comes to informing the public by drawing insights from current developments. The media has the power to shape and influence the public’s opinion, whether rightly or wrongly.
This study incorporates a content analysis of legacy news media outlets from a multi-national perspective. Key themes and narratives from the US, Germany, Norway and Iceland are evaluated and compared as these states all have a claim in the Arctic and yet have a unique relationship with Russia.
From a multi-national perspective, the media coverage in this study has revealed the Arctic’s distinctive duality of cooperation and tension. The coverage, as expected, reflects the differing national stances towards Russia whereby the distinctive interests of each state are seen in the reporting. These discrepancies are indicative of the respective government’s commitment to and policy in the region in the future. As we have witnessed in the wake of Russia’s invasion into Ukraine, each state’s relationship with Russia and the subsequent reporting of relations can and will change in accordance with world events. Such changes in dynamics provide ample material for a future study.

Keywords: Arctic Regions
Geopolitics
Russia
Militarization
Journalists
Press coverage
Reporters and reporting
Mass media > Political aspects
Climatic changes > Government policy
Climatic changes > Political aspects
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Capstone
Thesis
Student project report
Advisor: Berman Russell
Weiner Amir
Lesen und erleben : Zugänge zum heiligen land in deutschsprachigen pilgertexten des 15. jahrhunderts

In the late medieval German speaking lands, texts, objects, and images that sought to make the spatially distant Holy Land and the temporally distant Biblical events present were widespread. To these media belonged late medieval pilgrimage texts, which often incorporated images, offered modes of reception that allowed to imaginatively approach the spatially distant Holy Land as well as the temporally distant events of salvation history that took place there without going on a journey to the Levante. In my dissertation, I closely analyze three 15th century pilgrimage texts written in the German vernacular: Felix Fabri's Die Sionpilger, Hans Tucher's Reise ins Gelobte Land and Arnold of Harff's Die Pilgerfahrt des Ritters Arnold von Harff. Late medieval pilgrimage texts, I argue in the dissertation, aim at a wide spectrum of reader response. They invite their readers to recreate, share and understand the shared and lived experiences of late medieval pilgrimages to Jerusalem from afar. To this end, they develop a set of literary, medial and material strategies. As I show in the four chapters of my dissertation, pilgrimage texts allow for different degrees of involvement and participation in the narrated experiences of travelling to the Holy Land. In some cases, the audience is confined to the role of a passive observer who can gain an abstract understanding of pilgrimage by reading. Other modes allow for an active participation from afar or even evoke imaginary lived experiences of pilgrimage. I show that late medieval German pilgrimage texts do far more than just giving accounts of completed pilgrimages. I propose to rather understand pilgrimage accounts as texts which cater to the wishes of their readership to experience the faraway places of salvation -- even if only by means of reading. In so doing, these texts offer to their readers options to build experiences of pilgrimage without travelling. Even though their contemporary readers might have never set foot in the Holy Land, they thus could still engage with the loca sancta and hope for their salvific effects by engaging with words, images, and objects

Keywords: German Studies.
Advisor: Griffiths Fiona J.
Starkey Kathryn
Backes Martina
Beebe Kathryne
Eshel Amir
Leveraging deepfakes to close the domain gap between real and synthetic images in facial capture pipelines

From a technical standpoint, this thesis presents a framework for personalized appearance and motion capture that utilizes unsupervised deep learning in the form of deepfake technology. Notably, only a minimal amount of person-specific in-the-wild imagery is required to drive these pipelines, as we were able to effectively leverage synthetically created "ground truth" data during network training. Such personalized facial capture pipelines bypass issues with data diversity and bias that plague large-scale data collection and large pre-trained monolithic models, and has potential benefits beyond appearance/motion capture and retargeting. From a more general standpoint, our method's reliance on only subject-specific in-the-wild data could be leveraged to parametrize and analyze the facial motion present in videos, and be subsequently used to detect frame based video forgery (e.g. as created by deepfakes, ) which is actually the original motivation for this line of research. To paint a more complete picture of this research, I present technical details of our methodology and results, but also provide some more high-level context on deepfake detection, on our initial efforts on this work, and on some brief musings on ``lean AI'' as an alternative to large networks trained on massive datasets

Advisor: Fedkiw Ronald P.
Liu Cheng-Yun Karen
Yeung Serena
Leveraging near-term quantum computing for spin chemistry and combinatorial optimization

Quantum computing offers computational tools and speed-ups beyond the reach of classical computers in the long run, yet demonstrating the computational advantage of small-scale near-term quantum devices remains a challenge today. In this thesis, I introduce two applications of near-term quantum computers from the fields of spin chemistry and combinatorial optimization. In the first part of my thesis, I discuss the quantum beats phenomena that occur in spin chemistry when geminate radical pairs go through singlet-to-triplet conversions under hyperfine coupling interactions and an external magnetic field. I demonstrate that both the coherent time evolution and the thermal relaxation of these radical pair systems can be efficiently simulated on a quantum computer, both hardware and simulator. I introduce the first Hamiltonian simulation method on a quantum computer that can simulate the quantum beats phenomenon for radical pair systems with nontrivial hyperfine interactions under an arbitrary magnetic field, by utilizing Hamiltonian partitioning strategies. The second part of my thesis focuses on the open-pit mining problem, where the optimal mine digging pattern that maximizes the profit is searched for, while obeying slope constraints. This optimization is traditionally solved as a maximum closure problem. Our algorithm formulates this task as a Hamiltonian ground state search in order to map it to a quantum computer, and utilizes VQE as a subroutine to find the optimal solution. I show that the Hamiltonian can be decomposed into smaller, classically correlated partitions that can each be iteratively optimized. This will allow us to make use of near-term quantum hardware for larger scale optimization problems

Keywords: Electrical Engineering.
Advisor: Weissman Tsachy
Bouland Adam 
Jones Barbara (Barbara A.)
Leveraging prior knowledge and structure for data-efficient machine learning

Building high-performing end-to-end machine learning systems primarily consists of developing the machine learning model and gathering high-quality training data for the application of interest, assuming one has access to the right hardware. Although machine learning models are getting increasingly commoditized in the last few years with the rise of open-sourced platforms, curating high-quality labeled training datasets is still either costly or not feasible for many real-world applications. Hence, we mainly focus on data in this thesis, specifically how to (1) reduce dependence on labeled data with data-efficient machine learning methods through either injecting domain-specific prior knowledge or leveraging existing software systems and datasets that have initially been created for different tasks, (2) effectively manage training data and build associated tooling in order to maximize the utility of the data, and (3) improve the quality of the data representations achieved by embeddings by matching the structure of the data to the geometry of the embedding space. We start by describing our works on building data-efficient machine learning methods for accelerated magnetic resonance imaging (MRI) reconstruction through physics-driven augmentations for consistency training, scale-equivariant unrolled neural networks, and weak supervision using untrained neural networks. Then, we describe our works on building data-efficient machine learning methods for natural language understanding. In particular, we discuss a supervised contrastive learning approach for pre-trained language model fine-tuning and a large-scale data augmentation method to retrieve in-domain data. Related to effectively managing training data, we discuss our proposed information extraction system for form-like documents Glean and focus on the often overlooked aspects of training data management and associated tooling. We highlight the importance of effectively managing training data by showing that it is at least as critical as the machine learning model advances in terms of downstream extraction performance on a real-world dataset. Finally, to improve embedding representations for a variety of types of data, we investigate spaces with heterogeneous curvature. We demonstrate mixed-curvature representations provide higher quality representations both for graphs and for word embeddings. Also, we investigate integrating entity embeddings from Wikidata knowledge graph to an abstractive text summarization model to enhance factuality

Keywords: Electrical Engineering.
Advisor: Pauly John (John M.)
Chaudhari Akshay (Akshay S.) 
Pilanci Mert
Vasanawala Shreyas
Life in the Margins: Minor Characters in Katherine Mansfield’s Short Stories

Many of Mansfield’s stories are lauded for their layered depictions of major characters’ interiority. As central as these are to her work and her exploration of character, this focus only on perspective characters can minimize the importance of minor characters in her more crowded stories like “At the Bay,” “Bliss,” and “The Garden Party.” These characters, despite their places in the margins of their stories, fill a large part of these stories’ character-systems and play off of one another and off of the major characters to create a complex web of meaning that enhances and adds to the many interpretations that the stories offer. They are also a ground for modernist experimentation as much as plot or structure are, and Mansfield uses them to explore and discover new roles for minorness in fiction. The women Mansfield wrote about resembled her in many ways, and she drew on her own experience as a marginalized writer to depict them. This marginalization also contributed to the long-standing perception of her as a minor writer, pushed aside in the narrative of the development of literary modernism just as the (often marginalized) minor characters are in her stories. Yet Mansfield’s minor characters are not solely defined by their minorness, instead presenting avenues for exploration of sexuality, class, colonialism, and gender.

Keywords: English
minor character
Character
Women in literature
queer women in literature
Marginality, Social, in literature
Short story
Short stories, English
Queer theory
British colonies
New Zealand
Mansfield, Katherine, 1888-1923
Short stories (Mansfield, Katherine)
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Thesis
Advisor: Stavely Alice
McGurl Mark
Lighthouse: Combatting Disinformation On Encrypted Messaging Services

With the advent of social media as a crucial news source for the average smartphone owner, the spread of disinformation, and curated fake news, as a tool for political propaganda on encrypted messaging services is becoming an expanding threat to the public’s perception of news and journalis- tic accuracy. While several systems are in place to detect fake news on public networking platforms, the availability of encrypted messaging has made disinformation notoriously easy to disseminate but challenging to detect in the quest to alert users of fallacious information. Based on previous research that found that increasing awareness of fake news can noticeably reduce its spread, we designed Lighthouse, a standalone application that makes use of notifications from WhatsApp to detect links that have been professionally flagged as disinformation, and alerts users to potentially spurious news articles that have been sent to them. Lighthouse uses the NewsGuard disinformation database as a truth source with the intention of increasing accuracy awareness in the context of fake news as a method to fight the further spread of disinformation. The current implementation of the app serves as a starting point for the further study of disinformation dissemination and intervention methods aimed at addressing curated fake news on platforms protected by end-to-end encryption. It was used by 10 university students over one-week periods to test for database relevance and was found to positively influence the ability to identify disinformation and demonstrated the potential to alter sharing habits.

Keywords: Computer Science
Disinformation
Encrypted Messaging Services
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Thesis
Advisor: Bernstein Michael
Hancock Jeff
Seering Joseph
Likelihood ratio testing in critically-spiked wigner models

Spiked random matrix models are widely used to model data in which a low-rank signal exists alongside high-dimensional noise. When the eigenvalues of this signal, known as spikes, are either above or below a certain critical threshold, the corresponding models have been widely studied and are well understood. However, the behavior of models with spikes at the critical threshold is more difficult to study, and has often remained elusive, despite the existence of data that is not well-explained by either sub- or supercritical models. This thesis contains the results of series of projects that investigate the likelihood ratios for Gaussian models with critical spikes. It includes rigorous results illustrating the transition between the qualitatively different sub- and supercritical regimes, which has applications not only in statistics, but also in the statistical physics of the SSK model for magnetism. It also contains edge universality results, demonstrating how the quantities crucial for understanding the likelihood of critically-spiked Gaussian random matrices can be extended to their Wigner counterparts. The thesis concludes with a presentation of results about phenomena occurring exactly at the critical threshold, determining the contiguous set of alternatives for testing a critical spike and providing the first description of the limiting likelihood ratio for such tests

Keywords: Statistics.
Advisor: Johnstone Iain
Dembo Amir
Owen Art B.
Linear periodically time-varying circuits for the Internet of Everything

As the Internet of Everything (IoE) ushers in an age with tens of billions of connected devices, there is a persistent demand for radio receivers to join this ever-growing network. In particular, low power consumption is a critical requirement in order to enable remote deployments and battery-powered operation while receiver linearity specifications are only moderate. With this in mind, the passive mixer-first receiver is an attractive option for the IoE because it requires no external components and offers baseband-controlled impedance matching, high-Q filtering, and RF input range over a decade or more; however, it requires high power to achieve low noise figure due to the lack of gain at RF. Recent work has demonstrated that a transformer--mixer cascade can facilitate significant power savings at the cost of increased area and restricted RF input range. In this dissertation, we propose a low-power passive N-path harmonic-rejection transformer-mixer for narrowband IoE applications. Composed of only switches and capacitors, this circuit integrates the behavior of a transformer and harmonic recombination into the passive mixer itself, providing voltage gain, harmonic-rejection, and high-Q filtering before any active components and while supporting a wide RF input range. We also propose a single-transistor amplifier with back-gate feedback for high power efficiency in the receiver baseband while maintaining sufficient linearity at low supply voltages. Prototype amplifier measurements in 22-nm FD-SOI demonstrate that back-gate feedback improves linearity by 6--20 dB and reduces device-to-device gain variation by 5--10× compared to a conventional design. Finally, we present measurements of a prototype receiver with an N-path harmonic-rejection transformer-mixer at its core and with back-gate feedback employed in the baseband amplifiers. The receiver occupies just 0.064 mm² in a 22-nm FD-SOI technology and consumes 0.6-1.8 mW across the operating range of 0.3--3.0 GHz. It achieves 3.4--4.8-dB NF, 14--18-dBm OB-IIP3, -5--0-dBm OB-B1dB, -8/-3-dBm H3/H5-B1dB, and < 1-dB NF degradation with a -15-dBm OB blocker, demonstrating that the proposed techniques enable power and area savings while achieving performance suitable for the IoE

Keywords: Electrical Engineering.
Advisor: Murmann Boris
Arbabian Amin
Lee Thomas H.
Lingering Effects: An Analysis of the Teacher Incentive Fund

The ability to predictably increase student outcomes has clear value to primary and secondary education. The methods by which that is achieved, however, are less clear. Throughout the past few decades, several government programs and plans have been put forth to improve these outcomes. The Teacher Incentive Fund “TIF” is a unique government grant program that specifically targets teacher and administrator professional development. Using data from the Texas Education Agency, I seek to determine the effect of the TIF on 5th grade standardized test scores as well as SAT scores and participation rate. The grants studied last only 5 years, raising the additional question of whether or not such a short-term grant can have longer-term effects at a school. I look for these “lingering” effects as well as effects during the 5-year grant period using a set of difference in differences regressions using both synthetic and non-synthetic control groups. The non-synthetic results yield inconclusive or no evidence for each hypothesis tested. The synthetic-control regressions provide 1) weak evidence for a positive effect on SAT participation rate and negative effect on SAT scores during the active grant period in large cities; 2) weak evidence for positive active-grant and lingering effects on 5th grade standardized math scores in Austin ISD but no evidence of effects on reading or either reading or math in other regions tested (state-wide and Houston ISD).

Keywords: Lingering Effects
Teacher Incentive Fund
Standardized Test Outcomes
Texas
Department of Economics
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Thesis
Advisor: Hoxby Caroline