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Optimal Taxation and Human Capital Policies Across Space
Get PDFIn this senior thesis, I study how the presence of migration affects the optimal taxation and educational investment policies of competing governments seeking to maximize tax revenue. I develop a model that captures both intensive-margin labor supply decisions and extensive-margin migration decisions. Using this framework, I derive elasticity-based formulas for optimal tax rates and public education investment, with and without migration. I show that migration lowers optimal tax rates and distorts education spending policy in the baseline model, particularly in low-productivity regions. I then extend the model to include features such as intergenerational concerns and remittances, where the presence of remittances offers a counterexample in which migration can actually increase the optimal tax and education spending. I prove that the model exhibits spatial sorting and regional inequality, which motivates a role for distortionary central government intervention. I calibrate the model to U.S. Census data and evaluate the main results numerically. Finally, I conclude and suggest future directions of research.Applied Mathematic
Adaptive Innovation in the Octopus Ribosome
No full textThe ribosome is the universal machine for protein synthesis across all life. All ribosomes consist of a conserved core of ribosomal proteins and RNAs (rRNAs) that mediate accurate decoding of mRNAs to synthesize functional proteins. In agreement, biochemical or genetic disruptions to translation fidelity cause cellular death and severe cognitive or aging related defects.
In this thesis, I describe a completely serendipitous discovery, where we find that the 28S rRNA of the octopus contains a novel “break” in the highly conserved catalytic ribosomal RNA (rRNA) core of the ribosome. This rRNA break is unique to octopus species and not found among all analyzed animals, including closely related squid or cuttlefish, or distant mollusks, invertebrates, or vertebrates. By obtaining a cryo-EM structure of the O. bimaculoides ribosome, we find that the octopus rRNA break is found in the E-site near the site of deacylated tRNA binding. We then postulate that octopus rRNA break enhances translation fidelity by allosterically decreasing A-site tRNA binding affinity during decoding.
Later studies focused on how evolution of this break ultimately supports novel traits which emerged in octopuses. We find that the increased accuracy leads to less protein misfolding and aggregation and a reduced basal unfolded protein response in vivo in octopus compared to other cephalopods or mollusks. This advantage for proteostasis supports the expanded nervous systems of the animal. Notably, we also observe that the octopus ribosome innovation contributes to organismal plasticity. Octopus and squid exhibit unusually high levels of ADAR editing, with extensive adenosine-to-inosine recoding in the coding regions of transcripts. Editing increases in response to the environment, and has been hypothesized to contribute to protein recoding. We find that the octopus rRNA break controls how inosines are decoded during mRNA translation. This allows octopus to have higher organismal plasticity and regulation of the proteome than squid upon exposure to changes to environmental conditions such as cold temperature.
In summary, our findings reveal how evolution of the ribosome allows for organismal-specific adaptations to protein synthesis. While much of biology has demonstrated how the genetic code drives evolution, it is less understood how evolution can be driven by adaptations in other components of the central dogma. Here, we discover how the octopus uses modifications in the core protein synthesis machinery to drive biological novelty, a strategy which could support the evolution of unique organismal traits across life.Medical Science
Analyizing Parcel Level Prioritization and Cost Benefit Analysis as Private Land Conservation Tools
No full textPrivate conservation land trusts play a critical role in the attainment of important global climate and biodiversity-related goals, so it is important they make well-informed, strategic decisions about which lands to protect, considering a variety of factors including the ecological, social, and economic. This thesis research evaluated the robustness of a land acquisition prioritization tool designed for Kentucky Natural Lands Trust (KNLT) as an academic exercise by students in a practicum for a Harvard Extension School Land Conservation course. The prioritization tool aimed to guide KNLT’s land acquisition strategy by ranking 23 potential acquisitions (parcels) in the Cumberland Mountain region of Kentucky, USA. The study first conducted a sensitivity analysis of the original prioritization tool by testing the impact of changing importance scores of selection criteria on the parcel rankings. Then parcel level cost analysis was completed using The Nature Conservancy’s Stewardship Calculator to obtain the parcel level cost of acquisition and long-term stewardship. Finally, statistical correlations between parcel rank and cost were examined. Results revealed a robust parcel prioritization tool that experienced minimal changes in rankings despite altering the importance weight of selection criteria. Results also demonstrated a weak, negative correlation between parcel rank and cost, challenging the assumption that the higher-priority parcels would be more costly to protect. These findings underscore the importance of incorporating ecological and economic considerations into conservation planning and provide KNLT with insights to inform actions that can help further protect Cumberland Mountain.Extension Studie
Modeling Perspectives on the Environmental Legacy of Human and Natural Mercury Releases
No full textMercury (Hg) is a naturally occurring heavy metal that has been mined and used by humans since antiquity. Exposure to Hg, particularly its organic form (methylmercury) poses health risks for humans and wildlife globally. This thesis quantitatively explores the natural biogeochemical Hg cycle and the extent of the perturbation from human activity.
Chapter 1 focuses on the natural Hg cycle. Volcanism is the largest natural source of Hg to the biosphere. However, past Hg emission estimates have varied by three orders of magnitude. Here, we present an updated central estimate and interquartile range (232 Mg a−1; IQR: 170 - 336 Mg a−1) for modern volcanic Hg emissions based on advances in satellite remote sensing of sulfur dioxide (SO2) and an improved method for considering uncertainty in Hg:SO2 emissions ratios. Atmospheric modeling shows the influence of volcanic Hg on surface atmospheric concentrations in the extratropical Northern Hemisphere is 1.8 times higher than in the Southern Hemisphere. Spatiotemporal variability in volcanic Hg emissions may obscure atmospheric trends forced by anthropogenic emissions at some locations. This should be considered when selecting monitoring sites to inform global regulatory actions. Volcanic emission estimates from this work suggest the pre-anthropogenic global atmospheric Hg reservoir was 580 Mg, 7-fold lower than in 2015 (4000 Mg).
Chapter 2 focuses on the future anthropogenic perturbation to the global mercury cycle. Mercury (Hg) is a naturally occurring element that has been greatly enriched in the environment by human activities like mining and fossil fuel combustion. Despite commonalities in some carbon dioxide (CO2) and Hg emission sources, the implications of long-range climate scenarios for anthropogenic Hg emissions have yet to be explored. Here, we present comprehensive projections of anthropogenic Hg emissions up to 2300 and evaluate impacts on global atmospheric Hg deposition. Projections are based on four Shared Socioeconomic Pathways (SSPs) ranging from sustainable reductions in resource and energy intensity to rapid economic growth driven by abundant fossil fuel exploitation. There is a greater than two-fold difference in cumulative anthropogenic Hg emissions between the lower-bound (110 Gg) and upper-bound (235 Gg) scenarios. Hg releases to land and water are approximately six times those of direct emissions to air (600 - 1470 Gg). At their peak, anthropogenic Hg emissions reach 2200 - 2600 Mg a−1 sometime between 2010 (baseline) and 2030, depending on the SSP scenario. Coal combustion is the largest determinant of differences in Hg emissions among scenarios. Decoupling of Hg and CO2 emission sources occurs under low- to mid-range scenarios, though contributions from artisanal and small-scale gold mining remain uncertain. Future Hg emissions may have lower gaseous elemental Hg (Hg0) and higher divalent Hg (HgII), resulting in a higher fraction of locally sourced Hg deposition. Projected reemissions of previously deposited anthropogenic Hg follow a similar temporal trajectory to primary emissions, amplifying the benefits of primary Hg emission reductions under the most stringent mitigation scenarios.
Chapter 3 explores the cumulative impact of historical and future Hg releases on the global cycle. Humans have intentionally mined and released Hg from the Earth’s lithosphere over millennia. Here, we synthesize past, present, and future anthropogenic releases of Hg and explore its fate using a global geochemical box model. Future growth trajectories are based on the Shared Socioeconomic Pathways (SSPs). Results suggest that the upper bound for future anthropogenic Hg releases (SSP5-8.5) between 2010 and 2300 (1.7 Tg) could surpass historical anthropogenic releases over the past half millennium (1.5 Tg). In contrast, lower bound releases (SSP1-2.6; 0.7 Tg) highlight substantial effects of mitigation. We estimate that cumulative future (2010 - 2300) Hg releases from coal combustion will be ∼12 times higher under SSP5-8.5 than under SSP1-2.6. Observational constraints on global modeling suggest that most Hg released to land and water prior to 2010 remains sequestered at contaminated sites. Substantial oceanic enrichment by anthropogenic Hg (270%) has been driven mainly by atmospheric emissions, which totaled 0.36 Tg between antiquity and 2010. In the future, about 6-times more Hg is expected to be released to land and water than to the atmosphere. This pattern of Hg releases may result in localized Hg contamination issues but is unlikely to substantially impact Hg pollution in the ocean unless legacy Hg waste pools are mobilized by climate change. Modeling results suggest that by 2100 atmospheric Hg concentrations will be similar to present levels if society follows SSP5-8.5. Declines in the surface ocean (-19%) and atmosphere (-45%) are expected under SSP1-2.6, emphasizing the benefits of stringent regulatory controls on future Hg releases.
The chapters presented in this work: (1) leverage satellite observations to reduce uncertainty in natural Hg emissions, (2) quantify the drivers of future anthropogenic Hg emissions, and (3) provide a framework for combining simple and complex models to gain new insight into the environmental fate of Hg following release. Together, these studies advance understanding of the key sources of Hg, the processes mediating its redistribution, and the timescales of its removal.Engineering and Applied Sciences - Engineering Science
Characterization of metabolism in human gut Coriobacteriia using a newly developed genetic toolkit
No full textThe human gastrointestinal tract is colonized by trillions of microorganisms that greatly impact health and disease. Among these organisms are Coriobacteriia, a class of prevalent human gut Actinobacteria implicated in drug and dietary phytochemical metabolism and associated with multiple human diseases. Gaining a mechanistic understanding of Coriobacteriia metabolic activities and their regulation could better inform efforts to modulate gut microbial activities to improve human health. However, the whole Coriobacteriia taxon, including Eggerthella lenta, is currently genetically intractable. This thesis describes our efforts to develop a comprehensive genetic toolkit for Coriobacteriia and our application of these tools to characterize biochemical activities of human gut Coriobacteriia and their genetic regulation.
Chapter 2 describes our efforts to develop a genetic toolkit for Coriobacteriia. We construct shuttle vectors and develop methods to transform E. lenta, Gordonibacter urolithinfaciens, and other Coriobacteriia. With these tools, we characterize endogenous E. lenta constitutive and inducible promoters using a reporter system and construct inducible expression systems, enabling tunable gene regulation. We also achieve genome editing by harnessing an endogenous type I-C CRISPR-Cas system. We further create a transposon mutagenesis library for E. lenta and G. urolithinfaciens by engineering a native transposable element. By greatly expanding our ability to study and engineer gut Coriobacteriia, these tools will reveal mechanistic details of host-microbe interactions and provide a roadmap for genetic manipulation of other understudied human gut bacteria.
Chapter 3 details our work characterizing Coriobacteriia enzymes involved in polyphenol metabolism. Polyphenols are an important group of phytochemicals known for their antioxidant and anti-inflammatory properties. These dietary compounds are greatly impacted by gut bacterial metabolism, which changes their bioactivity and bioavailability. A prominent reaction in polyphenol metabolism is the removal of para-hydroxyl groups from catechols by molybdenum-dependent catechol dehydroxylases encoded in Coriobacteriia. However, the substrates of most putative catechol dehydroxylases remain unidentified due to the challenges of obtaining these enzymes from standard heterologous expression systems. To solve this problem, we establish G. urolithinfaciens as a versatile bacterial host to express active catechol dehydroxylases. The heterologous expression system allows us to streamline the catechol dehydroxylase discovery process and rapidly deorphanize twelve previously uncharacterized gut bacterial catechol dehydroxylases that selectively dehydroxylate intermediates in the gut bacterial metabolism of plant-derived catechins and lignans. Unexpectedly, we discover multiple instances of distinct catechol dehydroxylases that selectively metabolize individual substrate enantiomers, setting the stage for future efforts to elucidate the mechanisms and evolution of these enantiocomplementary dehydroxylases. Altogether, these findings greatly increase our knowledge of these metalloenzymes and provide a more comprehensive understanding of phytochemical metabolism relevant to human health.
Chapter 4 illustrates our work to elucidate the function and mechanism of a unique class of transmembrane transcriptional regulators in Coriobacteriia. Aiming to address the molecular details underlying the regulation of catechol dehydroxylase expression, we identify a previously unappreciated family of transcriptional regulators comprised of a 12-transmebrane helix domain and a LuxR-type DNA-binding domain, which are referred to here as 12-TM LuxR. Bioinformatic analyses show their high diversification and wide distribution in Coriobacteriia. We confirm that 12-TM LuxRs sense specific compounds and upregulate cognate metabolic enzymes. We further combine genetic and biochemical approaches to characterize the mechanism underlying 12-TM LuxR regulation. We show that 12-TM LuxRs are one-component systems that directly bind to their inducers. The 12-TM domains structurally resemble major facilitator superfamily (MFS) transporters, and we show these domains determine inducer specificity. Lastly, we show that inducer binding likely promotes 12-TM LuxR dimerization/oligomerization, which activates the regulator. Our findings suggest that Coriobacteriia evolved MFS-like domains for metabolic regulation, representing a new mechanism for bacterial nutrient sensing and signal transduction.Chemistry and Chemical Biolog
Privacy in Online Social Networks: Theory and Practice
No full textAt the heart of online social networks (OSNs) lies a fundamental tension between user welfare and business profitability. Despite outwardly expressing a commitment to user safety, OSNs continue to grapple with persistent privacy leakages that threaten to disrupt people’s lives in catastrophic ways and bely their professed dedication to putting users first. The inability of privacy laws to adequately prevent violations motivates us to take an ethical lens to the data practices of social networks. Under the framework of contextual integrity, we prove that current data practices fall short of ethical standards because they undermine user interests for profit-oriented goals. It is necessary to appropriately recalibrate current practices to social values and user needs.
We first attempt to find a more conservative solution that would preserve the underlying structures of OSN business models. Current protections involve de-identifying user data (removing personal identifiers), but researchers have shown that de-identified data is susceptible to privacy attacks. We employ a local differential privacy model to directly privatize user survey data with the Gaussian mechanism and randomized response. We found that when the underlying population is normally distributed and follows the probit model, we can recover the original non-private probit regression techniques by conditioning on the observed noisy data. However, our method produces an inconsistent maximum likelihood estimator, suggesting that direct perturbation of data might be incompatible with prediction utility.
We then analyze the normative implications of the privacy-utility tradeoff and argue that it continues to allow profitability to be prioritized over social values and quality. Thus, differential privacy is not a sufficient guarantee of privacy in the context of OSNs. We advocate for a reimagined relationship between users and OSNs, emphasizing the need for enhanced transparency, accountability, and user-centric data practices.Computer Scienc
Group Symmetries in Diffusion Models: Formulation, Generalization, and Enforcement
No full textGroup symmetries are fundamental structures in many real-world datasets, and lever- aging them is crucial for building robust and data-efficient machine learning models. Diffusion models have achieved state-of-the-art performance in generative tasks but typically rely on standard neural network architectures for score estimation. This thesis investigates whether such standard configurations enable diffusion models to implicitly learn and generalize underlying data symmetries purely from examples, particularly when data is partially observed. Drawing motivation from Neural Tangent Kernel (NTK) theory, which suggests limitations in the ability of standard supervised networks to generalize symmetries beyond local data structure, we hypothesize and empirically demonstrate that score networks in diffusion models exhibit similar constraints. Using a 2D toy dataset with inherent SO(2) rotational symmetry, we show a consistent failure of standard models trained on incomplete data (interpolation and extrapolation settings) to generalize symmetry, exhibiting significant score field distortions in unobserved regions. To address this limitation, we propose and evaluate a novel per-timestep symmetry loss that regularizes the denoising process to encourage approximate equivariance. Empirical results on both the toy dataset and higher-dimensional MNIST data confirm that this loss significantly enhances symmetry generalization even in standard architectures, yielding geometrically consistent results comparable to extensive data augmentation. This work highlights a critical limitation in standard diffusion models and underscores the importance of incorporating explicit geometric biases, via architecture or regularization, for reliable generative modeling on structured data.Computer Scienc
Formation, integration, and control of semiconductor spin-defects in electronic and photonic devices
No full textCan we identify new techniques to better create, control, and understand quantum systems? This is the central question of my thesis, which I explore by focusing on a particular class of quantum system--semiconductor-hosted spin-defects, namely the silicon monovacancy in silicon carbide, and the G center and T center in silicon. In this thesis, I investigate laser-mediated local defect formation in nanophotonics (create - Ch. 3), electrical manipulation of telecom defects in a silicon lateral PIN-diode (control - Ch. 4), and defect-enabled mapping of carrier phase transitions revealing negative differential resistance in silicon (understand - Ch. 5). Together, these results underpin the wealth of insight to be probed at the intersection of semiconductor physics and quantum science, as decades-old solid-state theories can be rediscovered in emergent quantum networking candidates.
Detailed:
In the recent decade, the ideas of quantum information science (QIS) have begun to become realized through the rapid development of technology which directly rely upon the principles of quantum mechanics such as superposition and entanglement. Computing, sensing, and communications are the three principal modalities which quantum technology is re-imagining, enabling enhanced capabilities unrivaled by their classical counterparts such as information theoretic security and efficient simulation of quantum phenomena. Fundamentally, a quantum technology platform is constituted by an isolated quantum two-level system (qubit) in which information can be controllably stored, manipulated, and accessed. However, each candidate offers vastly different advantages and challenges toward experimental implementation. The great promise of these technologies has motivated an intense study of quantum engineering to realize platforms ideally suited to their respective QIS task. While atoms, ions, superconducting Josephson-junctions, and photons are all compelling candidate qubits, a class of quantum systems known as solid-state spin-defects (color centers) are particularly exciting due to their natural environmental coupling (quantum sensing) and inherent spin-photon interface with facile deployment in nanofabricated devices which enhance their performance (quantum communications and networking).
Spin-defects are imperfections in an otherwise perfect crystal lattice, whereby an electronic structure is localized in the bandgap via the removal or addition of atoms in the crystal, leaving behind some isolated electron system. While imperfections exist in every crystal, their utility toward quantum technology varies drastically--reliant on features such as their possession of: microwave-controllable spin, optically-active charge state, robust spin-photon interface, and host material quality. Considering all of these traits, the current leading solid-state spin defect qubits are the Silicon Vacancy (SiV) and Nitrogen Vacancy (NV) in diamond. However more recently, there has been great interest in evaluating emergent spin defects which may exist in other crystal hosts and offer inherent unique benefits not possessed by these leading diamond candidates. For instance, quantum-grade diamond is highly-specialized and hard to fabricate, the NV and SiV visible-photon emission exhibits tremendous loss in conventional telecom fiber, and the SiV spin requires milliKelvin temperatures to utilize.
In contrast, silicon (Si) and silicon carbide (SiC) are ubiquitous commercial semiconductors with nearly a century of development in growth, material purity, and nanofabrication techniques--therefore, quantum technology stands to benefit greatly by leveraging the wealth of research and development of semicondcutor hosts. Furthermore, a class of carbon-related color centers in Si have been recently re-discovered which emit photons in the low propagation loss (0.3dB/km) telecommuncations O-Band (1260-1360nm) of the optical fiber which circles the globe for classical internet, and which possess an optically-addressable spin. The immense practical advantages of material host and emission frequency for these semiconductor spin-defects renders them exciting candidates for scalable quantum networking, however their nascency requires significant investigation to compete with existing leading systems in diamond.
In this thesis, I present work on the investigation and device engineering of semiconductor-hosted spin-defects, focusing on the silicon monovacancy (VSi) in silicon carbide (SiC) and the G and T centers in silicon. I first introduce the relevant background information to support this thesis in Chapter 1, from QIS theory to the varied platforms which enable it. In Chapter 2 I introduce solid-state spin defects, analyze the leading host materials and defect qubit trade-offs, then describe the intersection of defect integration with quanutum photonics, electronics, acoustics, and nanofabrication techniques. At the conclusion of this section I detail the thin-film SiC platform our group has developed for device nanofabrication of SiC defects. In Chapter 3 I develop a laser-based approach for controllably forming silicon vacancy defects (VSi) within these fabricated nanophotonic crystal cavities in SiC. Chapters 4 and 5 then focus on electrical integration, characterization, and control of silicon color centers in lateral PIN-diodes. Using these principles, chapter 4 presents stark tuning and optical charge state control of a G center ensemble, and chapter 5 reports direct optical observation of carrier phase transitions characteristic of negative differential resistance through the coupling of electrical nonlinearities to a T center ensemble. Finally Chapter 6 describes the outlook for semiconductor spin-defects, detailing the remaining challenges faced by VSi, G centers, and T centers, and discussing exciting new opportunities with color centers such as Vanadium.Engineering and Applied Sciences - Applied Physic
Mutable Ghosts: A Collection of Short Stories
No full textMutable Ghosts is a collection of three short stories that feature unreliable narrators in the first person. These works explore the fickle nature of the self and its ability to create its own reality. They are in some way, a study of solipsism. Each narrator resides intensely in his or her own reality. These stories investigate the conditions needed to either expand or contract a person's understanding of themselves and likewise a person's understanding of their intrinsic responsibility to those around them. These stories explore a host of conditions that affect these insular worlds. Among them include personal hauntings, that is the people and experiences that bedevil us, as well as place and environment. These stories offer a tour of the Eastern Seaboard from Massachusetts to West Virginia to Florida. I am inspired by the cast of unreliable narrators that have defined my experience of fiction; from the Underground Man to Humbert Humbert and Nick Carraway, from Holden Clawfield and Richard Papin to Ava Bigtree and Amy Elliot Dunne. I am consistently moved by fiction that finds the universal truth in the utterly untrue; that which holds authentic in even the most skewed and insular of human spirits. I have always taken solace in fiction that acknowledges the subjectivity of every human being and so too, the remarkable sameness of the human experience. I hope these works are, in some small way, an addition to that project.Extension Studie
The United States and Industrial Policy: A Look Inside the CHIPS Program Office
No full textThe “Creating Helpful Incentives to Produce Semiconductors” (CHIPS) and Science Act of 2022 represents the United States’ most significant industrial policy initiative in recent decades, allocating $52.7 billion to revitalize domestic semiconductor manufacturing. This thesis examines the implementation of the CHIPS Program Office (CPO), analyzing how the American approach to industrial policy creates opportunities and challenges. Via an evaluation of the CPO’s organizational structure, funding mechanisms, and application processes, this research identifies key tensions in the program’s execution.
The study finds that, despite the CPO’s efforts to align with commercial and industry growth objectives, substantial challenges remain. The root causes of these execution challenges can be traced to the dual objectives of the program: improving supply chain resilience and advancing social policy goals within the constraints of a very low tolerance for risk in the context of protecting taxpayer dollars. These elements, not clearly aligned with economic interests, complicate the program’s execution. The significant attrition rate—marked by over 640 initial Statements of Interest but fewer than 200 sustained applications—highlights tensions between the program’s broad scope and its regulatory demands. Key obstacles include compliance with the retroactive Davis-Bacon Act, National Environmental Policy Act requirements, and rigid milestone-based funding structures, which may hinder flexibility in adapting to rapidly changing market conditions.
This research also contrasts the CPO’s expansive approach with more targeted strategies employed in East Asia. While East Asian countries tend to focus their efforts more narrowly, the American approach simultaneously seeks to expand manufacturing capacity, develop the workforce, protect the environment, and pursue social policy goals. The thesis concludes that this broad scope, while commendable, may dilute the program’s effectiveness in achieving its primary goal of strengthening supply chain resilience and enhancing national and economic security. Ultimately, policymakers must strike a balance between the social policy goals included to gain support for the bill and the practical economic realities involved in its implementation. Some key considerations include the adaptability of regulatory frameworks, the need for focused objectives, and the overall design of government intervention in industrial development. Indeed, the findings have significant implications for American industrial policy and global semiconductor manufacturing competitiveness.Extension Studie