VictorJuiz/thesis huggingface dataset:
Information Warfare: Russian Cyber Strategy Abroad and Future Policy Recommendations

Since the early days of the Soviet Union, the Russian government has been using information warfare in order to sow distrust in adversaries. For Russia, “information warfare” is a broad and inclusive term that covers hostile activities using information as a tool, a target, or a domain of operations. A fundamental difference between Russian and Western conceptions of information activities is that it is not a Russian concept to believe Computer Network Operations or other activities in cyberspace to be a separate domain. Information warfare for Russians covers a broad array of tactics, including hacking, distributed denial of services, and disinformation campaigns. These campaigns have altered throughout the 2010s but were most prevalent in the 2014 invasion of Crimea, the 2016 U.S. election, and are now frequently used in the 2022 Russian invasion of Ukraine. Throughout this paper, I will analyze recent Russian information warfare events and information operations, while defining the various tactics they use and their relative efficacy. I will also follow up this analysis with a short policy recommendation for Western legislators and social media platforms. In this paper, I will argue that information warfare has been and will continue to be used by Russia as a method of hybrid warfare in order to attain strategic victories. These tactics were seen before the collapse of the Soviet Union and have transformed with the digital age. NATO, the EU, and other Western alliances must adopt certain policies in order to mitigate Russian information operations and ensure that Western ideology and democratic institutions are protected.

Keywords: Information warfare
Disinformation
Russia
National security
War
Cyberspace operations (Military science)
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Thesis
Advisor: Weiner Amir
Gottemoeller Rose
The inner court and politics in the Han empire

In traditional Chinese historiography, the inner court—usually consisting of the palace women, imperial affines, eunuchs, and the emperor's favorites—is often depicted as the cause of political decay and blamed for the fall of dynasties. This narrative shows empathy with the bureaucrats who were in constant tension with the inner court in their attempt to exert more political influence. Using both transmitted texts and archaeological sources, this project examines the roles of the inner court in the politics of the Han empire (202 BC--220 AD) from the angles of space, gender, family, ideology, social networks, institution, and historical memory. It argues that the inner court, who exerted political influence because of their spatial and emotional closeness to the ruler, served as the ruler's personal power base against the outer court bureaucracy. While previous research has largely treated the inner court as an institution, this research shows that the inner court was primarily a space and individuals who were close to the ruler prior to its institutionalization. Decentering the literati's rhetoric, this research illuminates the political significance of gender, family, and social networks in Han politics. It thus revises the current paradigm of Chinese political history that highlights the bureaucracy and downgrades the inner court, presenting a picture of competing ideas of legitimacy and dynamic interactions among different groups. Its relational approach to imperial power also contributes to the comparative study of empires in world history

Keywords: History.
Advisor: Lewis Mark Edward
Lewis Martin W.
Sommer Matthew Harvey
Zhou Yiqun
An integrated framework for production data analysis using machine learning and wavelets

This work introduces a framework for generating full data-driven well models that combine machine and deep learning algorithms with wavelet-based decompositions. The research shows that applying the Maximum Overlap Discrete Wavelet Transform Multiresolution Analysis (MODWT-MRA) to pressure and flow rate data from a well results in a decomposition analogous to a set of superposed wells in space and time. Two specific applications are presented in the work, capturing a well's pressure response from flow rate data, and reconstructing the flow rate history. The methodology increased model accuracy and noise filtering as well as allowed for the use of incomplete datasets with minimum loss of performance

Keywords: Energy Resources Engineering.
Advisor: Horne Roland N.
Mukerji Tapan
Tartakovsky Daniel
Interface design to enable efficient data curation for machine learning

Machine learning (ML) models achieve performance on par with or exceeding human capabilities on benchmark tasks across numerous applications spanning object detection, language modeling, question answering, and more. Unfortunately, translating the success of these models from benchmark datasets to real-world deployments is often bottlenecked by the curation of high-quality, domain-specific training datasets. It can take a domain expert weeks to months (if ever) to curate a labeled training dataset to train a model for tasks solving a specific business need. This poses a major scalability challenge as a company's typical ML deployment can consist of hundreds of tasks, spanning different data modalities that address several distinct, yet overlapping, business needs. Without training data of sufficient quality to input to the ML training procedure, the resulting models fail to perform well in practice. This dissertation argues that a key opportunity for optimization is to leverage shared information across tasks to expedite the data curation process—while companies deploy models for many tasks, they are often related, and overlapping information can bootstrap data curation for new tasks. We demonstrate how defining and systemizing new abstractions for practitioners enables them to more efficiently curate datasets across a varying number of datasets, schemas, and modalities for fixed classes of downstream ML tasks. We consider the problem of data curation across four regimes: a single data source, multiple data sources of the same schema and data modality, multiple data sources with heterogeneous schemas, and multiple data sources with more than one data modality. For each regime, we present our findings from designing and developing interfaces for efficient data curation for a specific class of downstream workload. Concretely, we show how to: (1) Perform whole-workload optimization to pre-process a single training dataset; (2) Automatically enrich datasets with additional data sources both of the same and heterogeneous schema; (3) Transfer and reuse labels across modalities to save data curation overhead by up to several weeks at scale

Keywords: Electrical Engineering.
Advisor: Ré Christopher
Bailis Peter
Olukotun Oyekunle Ayinde
Interfacial degradation of ceramic solid electrolytes in high energy density batteries

As rechargeable batteries seek higher energy densities, new chemistries are constantly being explored. A general trend in batteries is that reactions with higher degrees of transformation (phase changes, volume expansion, ect.) result in higher energy density systems. These are sometimes termed "conversion" reactions. However, the higher degree of transformation also results in systems which are morphologically unstable, leading to crossover between electrodes of the battery. Solid electrolytes are an attractive option for helping to stabilize conversion reactions in batteries because of their high mechanical stiffness and chemical stability. This work highlights the complex degradation processes which occur when ceramic solid electrolytes are incorporated into full battery systems. Specifically we examine ion exchange, chemical reactions, and mechanical fracture processes in a variety of solid electrolytes. Specifically, we examine the effect of hydronium ion exchange on K-beta'' alumina, (electro)chemical reactions between molten lithium and LLZO, and mechanical fracture processes driven by lithium intrusions in Li3PS4 (LPS) and LLZO via operando X-ray computed tomography (XCT) and operando scanning electron microscopy, respectively

Keywords: Materials Science and Engineering.
Advisor: Chueh William
Dauskardt R. H. (Reinhold H.)
Reed Evan J.
Interfacial spin wave phenomena in thin film oxide heterostructures

Spintronics, based on the use of the spin degree of freedom of electrons, has attracted much attention as an avenue for creating energy-efficient memory storage and electronic devices. A pure spin current, where spin angular momentum is transferred without any charge current, is desirable to realize low-loss devices due to the lack of heat dissipation associated with moving charge. Low-damping magnetic insulator thin films that can propagate spin currents with minimal dissipation are essential for this purpose. At the same time, magnetic insulators are also useful to stabilize novel ground states in neighboring materials. We have identified a class of spinel ferrite magnetic insulators which have desirable properties for these applications. I will present results on spin-to-charge and charge-to-spin conversion in low-damping MgAl0.5Fe1.5O4 (MAFO) and Li0.5Al1Fe1.5O4 (LAFO) thin films, which show ideal properties for pure spin current applications. Further, I will discuss MAFO/Bi2Se3 bilayers in the context of inducing a magnetic proximity effect in a topological insulator, and I will show that common techniques currently used to detect magnetic proximity effects are insufficient. Finally, I will characterize LaTiO3 thin films for charge-to-spin conversion in bilayers with CoFeB. These results highlight both the promise and challenges associated with building magnetic heterostructures for novel, energy-efficient devices

Keywords: Applied Physics.
Advisor: Suzuki Yuri (Applied physicist)
Hwang Harold Yoonsung
Wang Shan X.
Intersectionality at work : penalties and rewards for breaking or adhering to gender norms across race

Gender is highly influential in social and organizational life. In recent years, research has shown that race often interacts with gender to produce different outcomes for women of different races. However, extant work has largely focused solely on the racial group membership of the target woman. In my dissertation, I expand upon prior work by shifting the focus to include both the perceiver and the target, and by extension, the psychological relationship between the two. Drawing from a social constructionist perspective on gender, I argue that racial groups represent the social communities within which gender is constructed, conferred, and enacted, and explore this proposition in a few different ways. In Chapter 1, I explore the basic psychology of this understanding of gender, demonstrating that people primarily associate the construct of womanhood with racial in-group members, more so than racial out-group members. I find that this effect generalizes across samples of White (Study 1) and Asian (Study 2) perceivers, suggesting that, broadly speaking, when people think of women, they primarily think of racial in-group women. In Chapters 2 and 3, I explore an important downstream consequence of the tendency to ascribe womanhood more to racial in-group members than racial out-group members—gender-norm enforcement. In Chapter 2, I examine penalties that women suffer in response to gender-norm violation (i.e., backlash). Across five studies, I find that White (Studies 1, 3, and 4), Black (Study 2), and Asian (Study 5) perceivers all penalize racial in-group women who violate gender norms more than racial out-group women for the same behavior. In Chapter 3, I turn to the flip side of gender-norm enforcement—rewards that women may receive for conforming to gender norms. In two studies, I find that White men extend benevolence and aid to gender-norm conforming women primarily when these women are White, rather than Black or Asian. Across nine studies, I find evidence that people construct, confer, and enforce gender within their respective racial groups. I establish that people hold a basic, cognitive link between racial in-group members and the construct of womanhood. I further demonstrate that this way of understanding gender is linked to important outcomes. Both penalties for gender-norm violation and rewards for gender-norm adherence are primarily meted out towards racial in-group women, rather than racial out-group women. Broadly speaking, my dissertation suggests that people may understand gender primarily in the context of their racial in-groups

Keywords: Business.
Advisor: Lowery Brian
Flynn Francis J.
Martin Ashley
Investigating gamma-secretase in human neurons reveals connections between cholesterol metabolism and synaptic function

Alzheimer's Disease (AD) is characterized by memory loss and dementia, with underlying synapse loss and synaptic dysfunction. While the strongest risk gene for late-onset AD is APOE, early-onset forms of AD are mainly caused by familial mutations of presenilins, the catalytic subunit of the protease gamma-secretase. Mutations in gamma-secretase are thought to cleave the amyloid precursor protein (APP), leading to toxic Aβ oligomers associated with synapse loss. However, evidence from non-neuronal cells and murine models suggests that gamma-secretase may cleave over 90 transmembrane proteins, including synaptic signaling, scaffolding, and adhesion proteins. The resulting intracellular fragments following cleavage can exert transcriptional control in the nucleus. We hypothesized that gamma-secretase plays an important role in regulating synaptic function. In this study, we address the current knowledge gap on the physiological role of gamma-secretase in maintaining the proper functioning of human synapses. Here, we show an unexpected role of cholesterol metabolism in the regulation of synaptic function by gamma-secretase. Using patch-clamp electrophysiology, we demonstrate that gamma-secretase is required for presynaptic release and postsynaptic response in human induced neurons (iN). With RNA-seq and qPCR, we find that gamma-secretase modulates cholesterol synthesis gene expression and immediate early gene expression. Total cholesterol levels were reduced in human iN following gamma-secretase inhibition, when measured by confocal imaging and spectroscopy. Treatment of human iN with statins revealed novel insight on pre- and postsynaptic function regulated by cellular cholesterol levels. Our data shows, for the first time, a connection between cholesterol metabolism and synaptic function that is modulated by gamma-secretase activity in human excitatory neurons. These findings provide insight into the effects of proteolytic cleavage by gamma-secretase on the synapse. Our work highlights the need to further understand cholesterol metabolism pathways and synaptic dysfunction in early- and late-onset AD pathophysiology

Advisor: Südhof Thomas C.
Chen Lu (Professor of neurosurgery)
Wernig Marius
Wyss-Coray Anton
Investigating Prodromal Spine Density in an Alzheimer’s Disease Mouse Model

Alzheimer’s disease (AD), a progressive neurodegenerative disorder, is characterized clinically by a decline in cognitive function and memory and at the neuropathological level by extracellular deposits of beta amyloid (Aβ) and intercellular neurofibrillary tau tangles. Although Alzheimer’s disease is thought of as a disease of old age, the failure of treatments administered after clinical presentation, as well as research uncovering early neural plasticity changes in mouse models of AD, has ignited interest in understanding prodromal Alzheimer’s disease. APP/PS1 Alzheimer’s disease model mice have deficient ocular dominance plasticity at 30 days of age, which can be prevented if PirB, an innate immune system receptor present in the brain, is knocked out. In addition, synaptic changes correlate with and appear to underlie cognitive dysfunction and behavioral deficits in AD; however, current spine density analyses have focused on aging mice that already have plaques, spine and synapse loss, and significant cognitive deficits. In this project, dendritic spines on layer 5 cortical pyramidal neurons were counted in APP/PS1 mice at one and six months of age to assess the impact of Aβ oligomers early in prodromal Alzheimer’s disease. At 30 days of age, we did not anticipate changes in spine density, as ocular dominance plasticity is the only known plasticity perturbation at this age. At 180 days, we expected to see a decrease in spine density, since plaques begin to form around 6 months of age and deficits in cognition and memory emerge following the appearance of widespread plaques. At 30 days of age, we observed a trend towards lower spine density in PirBWT APP/PS1(+) animals as compared to their APP/PS1(-) counterparts, consistent with their deficient ocular dominance plasticity. Results also indicated that spine density was not greater in PirB knock out (KO) mice as compared to PirBWT mice at 30 days of age. This was unexpected given the previous research indicating that knocking out PirB increases spine density in a variety of ages and may have resulted from low quality images. At 180 days, spine density was greater in PirBKO animals as compared to PirBWT, the expected phenotype. In addition, there was a trend towards greater spine density in the PirBWT APP/PS1(+) animals vs APP/PS1(-) animals. This result was unexpected but could coincide with observations of increased spine turnover and excitability in APP/PS1 mice around 3-6 months of age. Although these results are promising, the inability to replicate expected results at P30 call for further investigation in a full cohort of re-imaged mice at higher resolution, especially at P30, in order to draw firm conclusions about spine density in APP/PS1 mice in the context of PirB.

Keywords:  Department of Biology
Biology
Alzheimer’s Disease
PirB
prodromal
spine density
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Thesis
Advisor: Shatz Carla J.
Heller H. Craig
Investigating the composition and architecture of insoluble polysaccharide systems and protein interactions

Polysaccharides are essential macromolecules found across all life forms. However, they can pose a challenge to solution-based analytical methods due to insolubility, high molecular weight, and close interactions with other biomolecules including proteins. To study these diverse polysaccharides and heterogeneous composites, we leverage solid-state nuclear magnetic resonance (ssNMR) to quantify and compare polysaccharide modifications, to determine the composition ratio of protein-polysaccharide mixtures, and to assign novel gene function. Additionally, we develop methods to enable cryogenic electron microscopy (cryo-EM) visualization of the architecture of these biologically complex systems. Here we report on studies of three systems: exopolysaccharides produced by S. meliloti, amyloid-polysaccharide biofilms formed by E. coli and S. Typhimurium, and chrysalides of the Monarch and Swallowtail butterfly. First, we demonstrate how two types of fibers in the bacterial extracellular matrix assemble into an impressive "basket-like" architecture and detail our specialized cryo-EM approaches optimized for the unique characteristics of the biofilm. After "unraveling" the biofilm baskets, we weave them back together by reconstituting robust biofilms with inter- and intra- species complementation between E. coli and S. Typhimurium. Next, we identify a novel pyruvyltransferase using ssNMR to analyze rhizobial exopolysaccharides. Finally, we perform a comparative analysis of a much larger yet comparable structure to the biofilm extracellular matrix - the butterfly chrysalis - detailing the chitin-rich framework and proteomic analysis of Monarch and Swallowtail chrysalides

Keywords: Structural Biology.
Advisor: Cegelski Lynette
Puglisi Joseph D.
Chiu Wah
Long Sharon R.
Investigating the Effects of FDA-approved Drugs in a Cortical Organoid Model of Neurodevelopment

The effects of many FDA-approved drugs on the development of the human brain are still poorly understood. Despite an extensive review process, verification of drug safety is often carried out in animal models, and later clinical trials tend to exclude pregnant women. For these reasons, new ways of evaluating the effects of drugs on early neurodevelopment in human cells are needed. Neural organoids derived from pluripotent stem cells present an excellent model system for studying brain development and dysfunction in human cells, but large-scale organoid culture has been difficult to maintain. In this study, I used a biocompatible polymer co-culture approach, which allows many organoids to be cultured simultaneously, to perform a screen investigating the effects of 298 drugs including FDA-approved compounds and teratogens on early cortical development in over 2,400 cortical organoids. Examining organoid growth over time, cytotoxicity, and distribution of a key neurodevelopmental marker allowed identification of a known teratogen affecting cortical organoid growth and development. I also found an intriguing result regarding the effect of a class of serotonin receptor agonists known as triptans on organoid growth. Taken together, the results of this study provide an evaluation of the effects of a wide variety of FDA-approved drugs on early cortical development and demonstrate the utility of cortical organoids for large-scale drug screens in the future.

Keywords:  Department of Biology
Biology
Organoid
High throughput screening (Drug development)
Neurodevelopment
Serotonin > Agonists
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Thesis
Advisor: Pașca Sergiu
Chen Xiaoke
Investigating the Effects of Stanniocalcin 2 in an in vitro Stroke Model

The investigation of neuroprotective agents against ischemic injury is impeded by the lack of appropriate in vitro models. An in vitro model of ischemic stroke was developed using PC12 and induced pluripotent stem cell (iPSC) derived neuronal cell cultures exposed to oxygen-glucose deprivation (OGD) followed by reoxygenation (24 hours) under atmospheric oxygen levels. Stanniocalcin 2 (STC2) is a protein expressed in the brain and has been shown to play a key role in calcium regulation. This property, along with evidence supporting STC2’s cytoprotective role in cells facing oxidative stress, has suggested it may have a neuroprotective effect during ischemic insult. Live-dead staining from initial experiments showed that iPSC-derived neuronal cells were resistant to cell death under 4, 6, and 8-hour hypoxia at 0.2 - 0.3% oxygen. However, PC12 cells plated on collagen I and collagen IV experienced significant death after OGD relative to control cells. STC2 administration at different doses (4 ng, 20 ng, and 40 ng) yielded no difference in PC12 cell viability between the OGD group and OGD groups supplemented with protein as measured by a fluorometric LDH assay. However, with an increasing dose of STC2, fewer PC12 cells died, suggesting a significant difference in cell survival may occur with the administration of a sufficient dose of STC2. Future experiments will need to assess the effects of higher concentrations of recombinant STC2 administered during OGD and reoxygenation. Stem cell resistance to ischemia-reperfusion injury, cell variability, and lifting of cells after live-dead staining may capture the lack of significant cell death seen in experiments with iPSC-derived neurons. Thus, a more robust neuron differentiation protocol will be followed in the future to produce cells with neuronal properties and less variability.

Keywords:  Department of Biology
Biology, Stroke, PC12 cells, iPSC-derived neurons, Oxygen and glucose deprivation
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Thesis
Advisor: George Paul
Dixon Scott
Long Sharon