VictorJuiz/thesis huggingface dataset:
The War Within: Perceived Legitimacy and Psychological Trauma Among Post-9/11 Veterans
Keywords: War
Veterans
Iraq War (2003-2011)
Afghan War (2001-2021)
War on Terrorism (2001-)
Nation-building
Mental health
Suicide
Moral injuries
Soldiers
Military policy
Counterinsurgency
Veterans > Medical care
Just war doctrine
Text
Thesis

Since the start of the Global War on Terror, over four times as many U.S. soldiers deployed in the conflicts have died by suicide than have been killed in action. Recent studies have established an association between veteran suicide and moral injury (MI), a type of psychological trauma rooted in “perpetrating, failing to prevent, bearing witness to, or learning about acts that transgress deeply held moral beliefs and expectations.” This thesis examines the moral injury element of service member suicide in the wake of the wars in Iraq and Afghanistan, seeking to understand whether veterans’ perception of the legitimacy of war they fought within is related to their sense of moral transgression for participating in that conflict. This study surveyed 54 anonymous U.S. veterans who served in Iraq and/or Afghanistan. I find significant correlation between moral injury and suicidality among participants. The analysis also shows that veterans with lower perceptions of the legitimacy of the conflict(s) they served in tend to have higher scores for moral injury. Finally, I find that perceived legitimacy also acts as a negative moderator on the relationship between MI and suicidality, meaning that the relationship between suicidality and moral injury is stronger when the legitimacy score is lower. These findings empirically support the hypothesis that service members’ mental health is related to their perception of war legitimacy. Through analysis of existing research and interviews with U.S. veterans, this thesis also examines emerging evidence of a causal chain underlying this relationship, indicating that when troops’ experiences in war result in a lessened view of the legitimacy of the conflict, they may be at risk of losing some of the sense of purpose that they had formerly associated with their service. Additionally, I find that political events can impact mental health in the military community by altering perceptions of conflict legitimacy even after one’s service has concluded.
Theory and algorithms for data-centric machine learning
Keywords: Humanities and Sciences.
Mathematics.

Machine learning (ML) and AI have achieved remarkable, super-human performance in a wide variety of domains: computer vision, natural language processing, and protein folding, to name but a few. Until recently, most advancements have taken a model-centric approach, focusing primarily on improved neural network architectures (ConvNets, ResNets, transformers, etc.) and optimization procedures for training these models (batch norm, dropout, neural architecture search, etc.). Relatively less attention has been paid to the data used to train these models, in spite of the well-known fact that ML is critically dependent on high-quality data, captured succinctly with the phrase "garbage in, garbage out." As the returns on ever larger and more complicated models diminish (MT-NLG from Nvidia and Microsoft having 530B parameters), researchers have begun to realize the importance of taking a data-centric approach and developing principled methods for studying the fuel for these models: the data itself. Beyond improved task performance, a data-centric perspective also allows us to take socially critical considerations, such as data privacy, into account. In this thesis, we will take a critical look at several points in the ML data pipeline: before, during, and after model training. Before model training, we will explore the problem of data selection: which data should be used to train the model, and on what type of data should we expect our model to work? As we move forward into model training, we will turn our attention to two issues which can result from the interaction of our ML systems with the environment in which they are deployed. The first issue is that of data privacy: how can we prevent our models from leaking sensitive information about their training data? The second issue concerns the dynamic nature of some modeled populations. Especially when our model is used to make socially impactful decisions (e.g., automated loan approval or recommender systems), the model itself may impact the distribution of the data, leading to degraded performance. Lastly, despite following best practices before and during model training, it may be the case that we want to post-process a model to remove the effects of certain data after training. How can this be achieved in a computationally efficient manner? This thesis covers novel solutions for each of the preceding problems, with an emphasis on the provable guarantees for each of the proposed algorithms. By applying mathematical rigor to challenging real-world problems, we can develop algorithms which are both effective and trustworthy
Therapy without therapists : an ethnographic study of e-mental health in Australia
Keywords: Humanities and Sciences.
Anthropology.

Recent years have seen profound changes to popular understanding of mental health. New discourses emphasize the need to seek support for one's interior struggles, casting "mental health" as a discrete thing which "everyone has." Concurrent with this less pathological conception of the psyche has been a shift towards computerized therapy programs which blur the line between lifestyle adjustment and medical intervention. I conceive of these new digitally mediated programs, which obscure or altogether replace the human therapist, as "therapy without therapists." This ethnography considers the deployment of these e-mental health programs across a variety of contexts in Australia, where they enjoy public funding as part of a broad government campaign to promote mental wellness at the population level. I show that behind these e-mental health programs are real human beings subject to material social conditions and to the powerful forces which reside in the psyche. This dissertation argues for a new approach to the changing politics of mental health, one which is attentive to both realities
'There Will Be Fire': (Re)imagining Vietnamese American Citizenship through Literature
Keywords: American literature > Asian American authors
American literature > Asian American authors > History and criticism
American literature > Vietnamese American authors
Vietnamese Americans in literature
American fiction > Asian American authors > History and criticism
asian american studies
vietnamese american studies
critical refugee studies
Refugees
Vietnamese Americans
southeast asian american studies
vietnamese american literature
Short stories
Short stories, American
Text
Thesis

Informed by the current trend in Asian American studies to question Asian Americans’ and Asian Americanist scholars’ attachments to ‘America,’ this thesis considers how Vietnamese American literature currently contributes to the negotiation and imagination of Vietnamese American citizenship, and the possibilities for this literature to contribute to utopian political projects that imagine a world beyond the U.S. nation-state. In the Introduction, the thesis examines dominant narratives about the Vietnam war to understand Vietnamese American positionality, then analyzes Vietnamese American literature, theorizing that dominant narrative forms (most notably, the ocean-crossing chronotope) have emerged within V.A. literature and problematizing their dominance. The bulk of the thesis is a collection of three original short stories, which are foregrounded with sociopolitical context. The stories explore model minority subject formation and patriarchy, the climate crisis and displacement (and the generic possibility of speculative fiction for Vietnamese American literature), and intergenerational trauma and relationships.
Thin film applications for energy storage
Keywords: Engineering.
Mechanical Engineering.

Renewable technology, a solution to many global warming problems, has been developed in recent decades and progressing rapidly; however, its global adoption rate is still limited mainly because of energy storage sources. To replace fossil fuels, we need to improve the energy and power densities of alternative storage technologies to be competitive. By employing thin film techniques, particularly based on atomic layer deposition (ALD), one can shorten the transport length for improved kinetics and better ability to withstand higher applied electric fields for energy storage devices. First, in this work, a nanoscale protective ALD coating layer for the Li-ion battery cathode to enhance battery durability is introduced. The coating needs not only protect the battery against numerous degradation mechanisms but also exhibit sufficiently high ionic and electronic conductivities. Many ALD-deposited metal oxide films, including Ti, Nb, W, V, Zr, and Li, are explored and ranked according to their conductivities, resulting in Li-V-O coating with minimal Nb-doping as the best candidate. Secondly, an energy storage device with nanoscale thin film in a heterostructure form is often subjected to high applied current or voltage, leading to high thermal loading, which can cause device failure due to thermal expansion mismatch. Therefore, we introduce atomic force microscopy with the harmonic Joules heating method to probe thermal expansion coefficients in nanoscale thin films. We apply such techniques with a varying aspect ratio pillar micropattern to reveal anisotropy in thermal expansion in poly(methyl methacrylate) for the first time. Finally, we explore a new kind of energy storage/transport device by adopting a metal-insulator-semiconductor (MIS) architecture. Guided by density functional theory, the ALD dielectric with high breakdown strength and high aspect ratio structure enable the application of high electric fields, which, in turn, may induce topological electronic states. We observed unconventional current-voltage behavior, including current spikes much larger than the capacitive current at low voltages and an inverse scaling of maximum current densities with area, indicating high energy density behavior. These effects could only be seen in MIS capacitors and not in metal-insulator-metal (normal) capacitors. In addition, simulations indicated that classical bulk and surface leakage currents, as well as tunneling currents, cannot explain the observed behavior. These efforts demonstrate how thin film applications may be crucial for future energy storage technologies
Think globally - act locally : scalable networked artificial intelligence
Keywords: Engineering.
Electrical Engineering.

Machine learning aims to relegate many decision-making processes to agents (machines). In applications like autonomous vehicles, communication networks, and robotics, the agents interact in a networked environment, where the decisions of one agent affect the other agents and their learning. As game theory predicts, this interaction can lead to inefficient outcomes for all agents involved. However, machines follow programmatic objectives and protocols that, unlike humans, are not limited by selfish interests but by information and resources. This modern paradigm calls for new tools to design efficient multiagent protocols for distributed and cooperative agents, which is the subject of this thesis. First, we present a distributed learning algorithm that can maximize the sum of rewards in a general game (for a concave objective), based on reward values alone (i.e., "bandit feedback") and limited communication. We then show that in special cases, we can design algorithms that use less (or no) coordination by leveraging the structure of the application. This is done by targeting the Nash Equilibrium (NE) of the game instead of the optimal actions directly. For distributed energy allocation, we show that although poor NE may exist, best-response dynamics (BRD) converge with high probability to an asymptotically optimal NE (in the size of the network). The idea is to look at a random game (i.e., network) rather than the worst-case one. When poor NE are unavoidable, we propose a manager that can learn to steer the inefficient NE toward an efficient point. This game control offers another tool to design efficient and mostly distributed multiagent systems since the manager does not need to know the game and only observes high-level feedback. Finally, we take a step towards dynamic multiagent optimization by considering the accumulated players' rewards over time instead of a static objective. With such a dynamic objective, players can learn to share resources over time, which can significantly increase their average reward
Three essays on administrative law, artificial intelligence, and disparate impact
Keywords: Humanities and Sciences.
Philosophy.

The rise of artificial intelligence raises many questions for lawyers and ethicists. Novel algorithmic tools create challenges that span multiple areas: in the private sphere, where companies have adopted pricing algorithms that can personalize prices for different customers; to the public sphere, where government agencies have adopted algorithmic tools that can predict regulatory violations or speed the processing of agency adjudications. Algorithmic tools hold great promise, but they also raise concerns about disparate impact, privacy, and the proper role of government regulation. This dissertation explores some topics in administrative law and artificial intelligence ethics and regulation.
Three essays on causal inference
Keywords: Humanities and Sciences.
Statistics.

This thesis describes three research projects in causal inference, all related to the problem of contrasting the average counterfactual outcomes on two sides of a binary decision. In the first project, we discuss estimation of the average causal effect in a randomized control trial. Here, we find that statisticians find themselves in a kind of statistical paradise: a simple model-based procedure delivers correct confidence intervals even if the experimental participants are not randomly sampled and mis-specified models are used. In the second project, we consider the problem of testing for a treatment effect using observational data with no hidden confounders. Conceptually, this is no different from a rather complicated RCT, and one might expect that a return to statistical paradise is possible. Unfortunately, this is not the case: we show that even intuitively reasonable uses of correct models may still yield misleading conclusions. The final project looks at observational data with unobserved confounding and gives methods for computing bounds on average causal effects. Here, we discover some never-before-seen robustness properties unique to the partially-identified setting.
Through thick and thin : improved transcranial focused ultrasound transmission estimates with acoustic simulation and magnetic resonance imaging
Keywords: Engineering.
Electrical Engineering.

Transcranial focused ultrasound is a promising technique for non-invasively treating brain disorders. During treatments, acoustic energy is focused through the intact skull to a millimeter-sized target. This can result in a variety of effects on tissue, ranging from mechanical perturbations to necrosis, depending on the duration, pulsing scheme, and intensity of the sonications. However, the skull is a substantial obstacle to safe and effective treatments. It is highly attenuative, absorbing and scattering the majority of the transmitted ultrasound due to its strongly heterogeneous composition. The consequence of this could be an aberrated focal spot which might be shifted from the intended target. In this dissertation, we demonstrate the necessity for accurate estimates of acoustic intensity delivered into the brain for transcranial focused ultrasound treatments, such as ultrasound-mediated blood-brain barrier opening. We discuss and propose improvements to two promising approaches for estimating in situ acoustic intensity, one using magnetic resonance imaging and another using acoustic simulation. Magnetic resonance acoustic radiation force imaging is a phase-contrast imaging technique where motion-encoding gradients are applied to encode tissue displacement induced by the acoustic radiation force in the phase of the image, enabling localization of the focal spot. As the acoustic radiation force is proportional to the applied acoustic intensity, measured displacements could potentially be used to estimate the acoustic intensity at the target. However, variable brain stiffness remains an obstacle. We demonstrate that viscoelasticity information from magnetic resonance elastography could be used in combination with displacement estimates to more accurately predict the delivered acoustic intensity. Finally, another approach for estimating acoustic transmission through the skull is by simulating acoustic propagation using the hybrid angular spectrum method. While this method is computationally efficient, its assumptions of normal incidence and weak heterogeneity in the medium may not be suitable for transcranial applications. We demonstrate the limitations of this method using a set of numerical benchmarks, and we propose adapting it toward transcranial applications by extending the implementation of acoustic attenuation into the spatial-frequency domain. The improvements presented here have the potential to enable clinicians and researchers to more accurately determine how much acoustic energy is being delivered to which regions of the brain, allowing them to focus on exploring the treatment parameter space rather than being uncertain about whether ultrasound is even reaching the intended target at power levels relevant for therapy. We hope that this work moves the field towards safer and more effective transcranial focused ultrasound therapies
TinyML computer vision using coarsely-quantized log-gradient input images
Keywords: Engineering.
Electrical Engineering.

This thesis studies the merits of applying log-gradient input images to convolutional neural networks (CNNs) for tinyML computer vision (CV). We show that log gradients enable: (i) aggressive 1-bit quantization of first-layer inputs, (ii) potential CNN resource reductions, (iii) inherent insensitivity to illumination changes (1.7% accuracy loss across 2^{-5}...2^3 brightness variation vs. up to 10% for JPEG), (iv) robustness to adversarial attacks (> 10% higher accuracy than JPEG-trained models), and (v) and insensitivity thresholds for quantization that confirms hardware implementability. We establish these results using the PASCAL RAW image data set and through a combination of experiments using quantization threshold search, neural architecture search, and a fixed three-layer network. The latter reveal that training on log-gradient images leads to higher filter similarity, making the CNN more prunable. The combined benefits of aggressive first-layer quantization, CNN resource reductions, and operation without tight exposure control and image signal processing (ISP) are helpful for pushing tinyML CV toward its ultimate efficiency limits. Dataset related issues currently prevailing in machine-centered vision tasks are reviewed and analyzed, with a focus on RAW image datasets. By approximating RAW data, our proposed method shows potential to generalize to larger datasets. Taken together, we demonstrate an energy efficient and robust tinyML computer vision system approach using coarsely-quantized log-gradient input images
To make a christian of Andrew Jackson : religious politics at the rise of American democracy
Keywords: Humanities and Sciences.
Religious Studies.

This dissertation identifies the mid- to late-1820s as uniquely inaugurating a new and permanent kind of religious politicking at the presidential level. Whereas in almost all previous elections, religion had been a personal matter, the elections of 1824 and 1828 saw a surge in interest concerning religious matters. Competing for votes was Andrew Jackson against John Quincy Adams, and both had their theological convictions, spiritual habits, denominational preferences, and religious biographies utilized and scrutinized in ways never seen before in American politics. But it was among Jackson's supporters that a collection of energized voters and savvy political organizers saw in him not only the people's choice, but also God's choice. In speeches, newspapers, and art, these religiously motivated operatives (as well as their more cynical allies) smoothed out Jackson's rough edges, downplayed his faults, exaggerated his spiritual qualities, and exploited his Christian orthodoxy. As in so many other ways, these Jacksonians transformed presidential religious politics and, in the process, made religion an unavoidable issue in American democratic politics.
To rise from the ashes : frontiers in the age of civil wars
Keywords: Humanities and Sciences.
History.

This dissertation seeks to answer how and why frontiers of empires remained an integral part of empire-building and maintenance during periods of civil wars. In doing so, it will also address the following questions: How different were frontier policies in these periods from those during times of imperial stability? How did rival factions exploit frontiers, and how did these acts of exploitation allow these factions to further their political struggles in the interior? Why were minority groups often the target of exploitation? Did these minority peoples form some ethnic consciousness (ethnogenesis), or did regionalization and profession serve as dominant forces of group cohesion instead? Finally, why was the mismanagement of frontier affairs so dangerous for these potential claimants to the throne? Using primary literary sources and archaeological evidence, this dissertation examines the military, political, and economic aspects of frontiers in the age of civil wars to fully understand the centrality of frontiers in the power of empires and emperors. Frontiers of the late Eastern Han Empire and the late Roman Empire underwent significant changes during civil wars when unified imperial authority over the empires had broken down, and rival claimants to the throne were vying to establish dynastic control over the lands. By comparing these periods of civil disorder, it is possible to look past the traditional narratives that focus heavily on political developments at the imperial center and instead understand how frontiers played a vital role in the deconstruction and reconstruction of imperial power. Even during civil wars, there was a direct symbiotic relationship between the organization of frontiers and imperial stability at the core of empires. In these times of civil conflict, imperial authority and immediate control over the lands degenerated as rival claimants to power fought for control over the empire. For these rival powers, the frontiers became sources of opportunity and threats to their political fortunes. Inspired by existing Western scholarship on the concept of ethnogenesis and regionalism, this dissertation will also examine how the movement of peoples from different parts of both empires gradually created ethnic identification, which was closely linked to their locale and their military service. As these people settled at the frontiers (voluntarily or coerced), they were exploited for their labor and military service. As a result, they took on new markers of identity