VictorJuiz/thesis huggingface dataset:
Towards Equity and Fairness in Data-Driven Management Systems

This dissertation comprises three lines of work addressing societal challenges related to safe water access, fair incentive design, and secure data sharing, utilizing mathematical modeling to propose comprehensive solutions. These projects collectively advocate for universal resource and information access while prioritizing equity and fairness for marginalized communities. The first project centers on optimizing water storage decisions, considering factors such as cost, water quality, and wastage, with the core objective of promoting equitable access to safe drinking water, particularly for those facing severe water scarcity. In the second project, we address deficiencies in current incentive mechanisms for fairness, introducing quantitative definitions rooted in fairness principles to prevent harm to specific groups and encompass disadvantaged segments of society. Lastly, the third project delves into the intricacies of responsible scientific data sharing, presenting a novel cybersecurity insurance contract to incentivize healthcare providers while safeguarding privacy and livelihoods, especially for vulnerable populations. In sum, this research strives to develop solutions that facilitate equal and inclusive access while mitigating risks, with the goal of addressing cultural and societal issues concerning resource allocation and information sharing for underserved communities.

Advisor: Aswani, Anil
Cooking core spectroscopy with the finest ingredients: Computational recipes based on orbital-optimized references

The development of predictive computational methods to simulate, and thus interpret the phenomena relevant to core spectroscopies is a vibrant and flourishing field. Until recently, computational core spectroscopy was under-developed relative to ground-state and even valence excited-state quantum chemistry. By the appeal of its broad range of modern experimental applications, this emerging sub-field of quantum chemistry is a fertile landscape for research. The work presented here grew in this landscape, and the different findings are bound together by the common theme of using of orbital-optimized references for the description of core excited states. After laying a foundation in Chapter 1, Chapter 2 explores schemes for the use of orbital-optimized references as ingredients for correlated calculations with the aim of providing high quality predictions of the energy required to induce a core excitation. The schemes proposed rely on single-reference coupled-cluster singles and doubles - long lauded for being the most affordable variant within the accurate coupled cluster formalism - and achieves a statistical performance on the order of 0.2 eV for core excitations in small organic molecules. Chapter 3 designs a model constructed within a generalized single-excitation CI framework, relying on orbital-optimized references, to describe the exotic core excited states present in ultra-fast pump-probe core spectroscopy experiments. Specifically, these are core excited states atop valence excited states used to discern the electronic dynamics during photochemical processes. As an efficient yet accurate zeroth order model enjoying explicit spin adaptation, we demonstrate the utility of our model by simulating an ultra-fast time-resolved core absorption spectra of acetylacetone that requires small shifts in energy to align with experiment, and is free from artifacts due to spin contamination. Chapter 5 uses the aforementioned model for an exciting photochemical application on Fe(CO)5, a textbook organometallic compound used to understand metal-ligand bonding in these type of complexes. With our valence-core excited state model, we help uncover for the first time the spectroscopic signatures of the metal-centered excited states of FeCO5 during photodissociation. Finally, Chapter 5 offers some concluding remarks and future outlook.

Advisor: Head-Gordon, Martin
Paleoenvironment and Persistent Places Interwoven at Kharaneh IV, Jordan

This dissertation pairs paleoenvironmental analyses with persistent place theory to better understand human-environment relationships at a large Epipaleolithic hunter-gatherer site in eastern Jordan, Kharaneh IV. I use fecal stanol molecules, gazelle tooth enamel stable isotope values, loss-on-ignition, micro- and macrofossils, geoarchaeological excavation and survey, and sedimentological characterization to reconstruct the paleoenvironmental history of the Kharaneh wetland and understand the qualities of the local environment that contributed to the formation of Kharaneh IV as a persistent place on the Epipaleolithic landscape. Although fecal stanols at the site do not appear to reflect ancient conditions, the analysis identified two major limitations of the method in archaeological studies: 1) stanol molecules appear to be mobile through permeable cultural deposits, suggesting that the method is not viable in dryland sites, and 2) non-human producers of fecal stanols may complicate the interpretations of a site’s history, as herd animals that pass over the site are a likely source of fecal stanol contamination.Gazelle tooth enamel isotope values show little variation between the site’s older Area B and younger Area A occupations, indicating relatively stable conditions over the course of the site’s thousand-year history and supporting notions of Kharaneh IV as a persistent place. However, a -2% excursion in δ18O values suggests a temporary period of enhanced precipitation during the site’s Middle Epipaleolithic occupation. Geoarchaeological excavation and survey identified a permeability gradient between wadi gravels and shallow limestone bedrock surrounding Kharaneh IV that allowed for wetland formation from shallow groundwater flow during the Pleistocene. Loss-on-ignition, micro- and macrofossils, geoarchaeological excavation and survey, and sedimentological characterization data indicate that the wetland fluctuated significantly before and after the site’s occupation, but provided a reliable source of water for Epipaleolithic groups, plants, and prey that in turn encouraged place-making activities to occur and develop Kharaneh IV into a persistent place.

Advisor: Maher, Lisa A
Optimized Receive Frontend Hardware for Magnetic Particle Imaging, Characterization Tools, and Biosensors

Magnetic Particle Imaging (MPI) is an emerging medical imaging modality that detects the strong magnetization of superparamagnetic iron oxide nanoparticle tracers. MPI has proven applications in angiography, stroke, stem cell tracking, white blood cell tracking, lung perfusion, traumatic brain injury, and gastrointestinal bleed imaging among many other highly critical medical imaging applications. However, MPI receive frontend hardware suffers from direct feedthrough interference as a result of simultaneous transmit and receive and is currently not optimized for higher resolution tracers that require a ten-fold wider bandwidth. In this dissertation I will discuss my PhD work that introduces methods to optimize for signal-to-noise ratio and suppress feedthrough interference for inductive sensors used in MPI, specifically for benchtop magnetic particle sensing systems./nThe first part will discuss design methodologies for the preamplifier and receive coil. The preamplifier can be designed for another ten-fold lower noise over a five-fold wider bandwidth despite the challenge of broadband noise matching for inductive sensors. The receive coil can be designed for a ten-fold higher sensitivity per volume and lower inductance with microcoils./nThe second part will discuss methods to suppress feedthrough interference with passive and active cancellation. Passive cancellation is done using gradiometric coils designed with linear programming to achieve better mechanical shimming tolerance, cancelling feedthrough by three orders of magnitude. Active cancellation using an adaptive feedforward scheme reduces feedthrough by another two orders of magnitude.

Advisor: Conolly, Steve
Investigation of Small Molecule Dynamics Using Fast Beam Photofragment Spectroscopy and Flat Liquid Jet Scattering

Molecular dynamics is the sub-field of chemistry interested in studying the microscopic movements of molecules and their partitioning of energy. Through molecular dynamics, a higher level of understanding of both reactive and non-reactive chemical processes can be achieved. In these works, two separate techniques are used to investigate the molecular dynamics of three different chemical systems. The first technique, fast beam photodissociation spectroscopy utilizes a combination of anion photoelectron spectroscopy and fast beam free radical dissociation to study the photodissociation dynamics of free radical species. The free radical species investigated in these works are the methyl phenoxy radical and isoprene hydroxy radical both of which are relevant to atmospheric and combustion chemistry. Insights are obtained for the different dissociation products which can be formed from these two radicals, the branching ratios of each dissociation channel, and the dissociation mechanisms responsible for each channel. The second technique, flat liquid jet scattering is used to investigate the gas-liquid interface of ND3 and dodecane. Flat liquid jet scattering is a relatively new technique which utilizes a flat liquid sheet and molecular beam to uncover mechanistic details of gas-liquid interactions. The dynamics uncovered in these works specifically investigate ND3 scattered from the relatively high vapor pressure liquid dodecane, and provide a proof of concept for the flat liquid jet technique being used on more volatile liquids such as water.

Advisor: Neumark, Daniel M
How Everyday Language Shapes the Development of Stereotypes

Stereotypes are powerful. They not only influence our perceptions and interactions but also shape individual identities and societal structures. Crucially, stereotypes emerge early, shaping children’s understanding of the world and their place in it. The early emergence is particularly concerning as it underpins the perpetuation of social inequities, such as racial and gender disparities. This dissertation explores the development of stereotypes, focusing on the linguistic factors that contribute to their formation. By examining how language–both in terms of what is said about and to social groups–influences children’s stereotypes, this research highlights the subtle yet powerful ways that everyday language can shape social cognition./nChapter 1 examines the emergence of racial stereotypes in early childhood, revealing that by age 7, children start attributing competence and warmth differently across racial groups. This finding suggests these stereotypes are not due to mere in-group preferences, but rather, mirror broader societal beliefs. By shedding light on the developmental trajectory of stereotypes, this chapter serves as a foundation for further exploration into the mechanisms underlying this development./nChapter 2 shifts the focus to pragmatic inferences, investigating how children and adults “read between the lines” of what a speaker says to form judgments about social groups. The chapter illustrates the powerful role of indirect language cues in stereotype formation and the nuanced ways language impacts social cognition./nChapter 3 demonstrates that the manner of addressing social groups affects perceptions of their competence. The research reveals that both children and adults perceive individuals addressed with simplified language or information as less competent. This novel perspective expands our understanding of linguistic factors in stereotype formation, moving beyond the traditional focus on the content of speech about social groups, and highlights the significance of how speech is directed at them./nCollectively, this dissertation presents a unique perspective on the development of stereotypes, emphasizing the significant role of linguistic cues from childhood through adulthood. This work contributes to academic discourse and offers valuable insights for developing educational and policy interventions aimed at dismantling harmful stereotypes.

Advisor: Srinivasan, Mahesh
Magical Realism on Cuban Landscapes: A Distant Reading of Regional Development Through Satellite Data

Our awareness of detrimental changes to all environmental systems has forced us to project into the uncertain future to determine how to live in the present. The United Nations (UN) is currently holding the global conversation on climate change by incorporating ‘sustainability’ in poverty reduction goals. After decades of scientists failing to work with other core disciplines to mobilize our society, those outside of the discipline have started to write about the inevitability of societal collapse to express urgency in a way that connects with popular culture (Bendell, 2018). This is a process tracing case study to understand the development trajectories captured in public datasets of the Republic of Cuba since the Special Period began. During this time, the island nation was able to avoid a major collapse and begin to shift towards a circular economy, a central tenet of the UN’s Sustainable Development Goals (SDG). A noted weakness of public global development data is the lack of intranational resolution. While satellite imagery has limitations, it can give insight into regional conditions. Assuming unique milieus have produced varying change to the Cuban landscapes across regions, this research attempts to capture that variance using global public datasets. Measuring intranational variance is a key part of the UN’s development goals that necessitates data at local scales. The lack of consistently produced global datasets severely constrain the ability to use them for time series analysis or local level adaptation planning. Cuba’s ability to educate its citizens makes it possible to examine the role of human capital accumulation on ‘sustainable’ regional economic adaptation and poverty reduction. The political climate of the country also helps us discuss the balance needed between strong governance and individual freedoms as the nation underwent a multisector decentralization effort.

Advisor: Hill, Kristina
From Voronoi Cells to Algebraic Statistics

Algebraic statistics is a relatively young field, which explores how algebra and statistics interact, thus fostering a meaningful dialogue between theory and applications. Many statistical models are naturally made up of distributions whose coordinates satisfy polynomial equations. Viewing these models as algebraic varieties, we may use tools from algebraic geometry to gain additional insight into their properties. Alternatively, we may revisit familiar algebraic and geometric objects in the setting of probability distributions./nIn the first part of this thesis, I develop the theory of logarithmic Voronoi cells. These are convex sets used to divide experimental data based on which point in the model each sample most likely came from. For finite models, linear models, toric models, and models of maximum likelihood degree one, I prove that these sets are polytopes and characterize them combinatorially. I then use their structure to maximize information divergence to linear and toric models. For the latter family, I present a new algorithm for computing maximizers using vertices of logarithmic Voronoi polytopes. For non-polytopal logarithmic Voronoi cells, I develop a method to compute them via the framework of numerical algebraic geometry./nThe second and third parts of this dissertation focus on conditional independence. In the second part, I study context-specific independence and introduce the family of decomposable CSmodels. I prove that these models mirror many of the algebraic and combinatorial properties that characterize decomposable graphical models, and hence they are good candidates for decomposable models in the context-specific setting. I give the strongest possible algebraic characterization of decomposable CSmodels by describing their prime ideals. In the third part, I focus on nonparametric algebraic statistics. I study dimensions, defining polynomials, and degrees of the moment varieties of conditionally independent mixture distributions. The last chapter features both symbolic and numerical computational methods.

Advisor: Sturmfels, Bernd
Hosten, Serkan
Controlling Long-Form Large Language Model Outputs

As large language models have greatly increased in capability in recent years, it becomes increasingly important to improve our ability to exert control over their outputs. In this thesis, I discuss several such control schemes I have developed, ranging from pure inference-time control to finetuning-based alignment methods. I will first discuss highly general methods that apply to unstructured natural language generation, including both an inference-time control scheme called FUDGE as well as a reinforcement-learning based finetuning approach called RLCD. I will next discuss more specialized methods that can be used for control in more structured domains such as molecule design, program synthesis, and semantic parsing. Finally, I will show how many of these ideas can be used in conjunction with structured planning via prompting to extend our control to much longer outputs—in the range of thousands of words—in an automatic story generation application.

Advisor: Klein, Dan
JUN mRNA Translation Regulation is Mediated by 5’ Untranslated Region (5’ UTR) Features and Multiple Translation Initiation Factors

mRNA translation regulation by eukaryotic initiation factors (eIFs) is crucial for cell survival. In humans, eIF3 stimulates translation of the JUN mRNA which encodes the transcription factor JUN, an oncogenic transcription factor that is involved in cell cycle progression, apoptosis, and cell proliferation. Previous studies revealed that eIF3 activates translation of the JUN mRNA by interacting with a stem loop in the 5′ untranslated region (5′ UTR) and with the 5′ -7-methylguanosine cap structure. In addition to its interaction site with eIF3, the JUN 5′ UTR has a longer than average length, a high degree of secondary structure, high GC content, and an upstream start codon (uAUG). This motivated us to explore the complexity of JUN mRNA translation regulation in human cells. Chapter 2 describes our findings on the contributions of multiple 5’ UTR and start codon features in JUN translation regulation. We find that JUN translation is regulated in a sequence and structure-dependent manner in regions adjacent to the eIF3-interacting site in the JUN 5′ UTR. Furthermore, we identify contributions of an additional initiation factor, eIF4A, in JUN regulation. We show that enhancing the interaction of eIF4A with JUN by using the compound Rocaglamide A (RocA) represses JUN translation. We also find that both the upstream AUG (uAUG) and the main AUG (mAUG) contribute to JUN translation and that they are conserved throughout vertebrates. Work presented in this chapter demonstrates additional layers of regulation for JUN translation. Chapter 3 describes isolation of a translation initiation multifactor complex (MFC) from in vitro translation reactions of a JUN 5’UTR reporter mRNA in human cell extracts. The yeast MFC is composed of eIF1, eIF2, eIF3, eIF5 and the initiator methionyl-tRNA (Met-tRNAi) and has been well-characterized. However, knowledge about the human MFC is limited and isolation of the endogenous complex from human cells hasn’t been achieved. By using the JUN mRNA as a platform for MFC binding, we present the first instance of isolation of an mRNA-bound human MFC. We also present in-depth protocol optimization and propose next steps for complex validation. Work presented in this chapter provides strong evidence for the formation of a human MFC with the presence of novel initiation factors such as eIF4A and eIF4G. Together these findings demonstrate the complexity of JUN translation regulation and establish JUN’s potential as a model transcript for understanding multiple interacting modes of translation regulation.

Advisor: Cate, Jamie H.D.
Quantum metrology with trapped ions

We present the results of an experiment that used the quantized motion of an ion trappedin a harmonic pseudopotential to test for nonlinear extensions of quantum mechanics. This test was motivated by the development of a recent, consistent theory of nonlinear quantum mechanics that, in contrast to previous frameworks, also preserves causality. This experiment represents the first test of this new theory in a fully quantum system and improved the bounds on potential nonlinear effects in quantum mechanics inferred from previous experimental results by an estimated eight orders of magnitude./nWe also present the results of an experiment that used two entangled ions to test for localviolations of Lorentz invariance and which tightened the bound on such hypothetical violations by about half of an order of magnitude. In particular, this experiment used a special entangled state of the ions, residing within a decoherence free subspace, which is immune to the dominant source of noise. By comparing our results against a similar experiment, performed with two non-entangled ions, we verify the expected factor-of-two improvement in the signal-to-noise ratio predicted by theory. This improvement can be directly attributed to the use of entanglement and, thus, this work provides a case study of how entanglement can be leveraged as a resource to fundamentally enhance the performance of spectroscopic measurements

Advisor: Haeffner, Hartmut
Magnetoelasticity for Integration of Quantum Defects

Integration of atomic-defect spin qubits into memory or computing remains a challengingtask due to a range of engineering problems, including microwave power delivery and material compatibility. While approaches exploiting spin-wave dipolar coupling have been explored in the past, they are reliant on Yttrium Iron Garnet (YIG), a model magnetic material which displays long spin coherence length, but cannot be integrated on-chip except under relatively restrictive conditions. Therefore, despite a growth in research interest in recent years, such hybrid quantum magnonic systems currently remain confined to laboratory conditions./nIn this thesis, I will present a method by which surface acoustic wave (SAW) driven magne-toelastic waves can be used as an effective near-field antenna for interfacing with spin qubits. Beginning with a set of experiments on resonant coupling of acoustic waves to magnetic dy- namics, we will show that the magnetoelastic interaction acts as linear method of conversion of acoustic waves into magnetic dynamics at high microwave power levels. Following this, experimental results demonstrating a dipolar coupling to the nitrogen-vacancy center in di- amond will be shown, along with a set of conditions under which this dipolar coupling is dominant over incoherent off-resonant coupling mechanisms. With these conditions iden- tified, we implement them and demonstrate the phase-coherent coupling of acoustic waves to nitrogen-vacancy dynamics mediated by a magnetoelasticity in a ferromagnet. This ap- proach is in theory applicable across a wide range of materials, and offers the capability to integrate atomic qubits in a more power efficient manner compatible with commercial nanofabrication.

Advisor: Salahuddin, Sayeef