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Transcendentalism and Sam Peckinpah’s Bring Me the Head of Alfredo Garcia
No full textThis essay uses the philosophy of Ralph Waldo Emerson and Henry David
Thoreau to attempt a better understanding of the violence depicted in the film Bring Me
the Head of Alfredo Garcia by Sam Peckinpah. The throughline in the work of these
artists is the belief that the performance of violence degenerates the perception of the
wrongdoer, disconnecting them from nature and enabling further violence. An aim of this
study is to reassess the value of the film under scrutiny as a self-reflexive work where the
director acknowledges and criticizes his own complicity in aggravating the problem of
violence. The thesis examines three essential Transcendentalist concepts associated with
violence: comparative thinking, compensation, and possession. These are examined
through the lens of their political context at the time of their writing since the defining
problem of slavery affected these ideas and is the explicit object of criticism in their
writing, just as the context of the Vietnam War is what informs Peckinpah’s own didactic
efforts against violence. This essay builds on the work of Stephen Prince in particular,
which later scholars ignore, to investigate his insights about Peckinpah’s complete
rejection of violence. An aim of this essay is to dispute the readings of the later scholars,
who maintain Paul Seydor’s framing of Peckinpah’s violence as redemptive
Geometric Templating and Frustration of Two-Dimensional Colloidal Crystals
No full textIn this thesis, I explore how template geometry can assist or frustrate depletion-mediated self-assembly of two-dimensional (2D) colloidal crystals. To understand geometric frustration, it is useful to seed the position and orientation of colloidal crystal nuclei. However, existing experimental methods disrupt crystallization dynamics or do not work on highly curved substrates. Using focused ion beam (FIB) nanofabrication, I deposit seeds that control the position and orientation of 2D colloidal crystals. I show that different nucleation pathways can occur at the seed, while the growth behavior is unaffected by the seed. I use this technique to study geometric frustration on curved surfaces by seeding crystal growth on a thin glass fiber.
Although FIB nanofabrication enables seeding of colloidal crystals on curved templates, FIB is an inherently low throughput process. Therefore, I use simulations to systematically probe how various geometric parameters affect the growth of seeded crystals. I use a greedy algorithm to study how crystals of hard disks grow from a seed placed on a cone. The simulations show that tilt grain boundaries emerge when the crystals wrap around the cone. I find that initially ordered crystals transition into disordered packings near the tip of the cone. Surprisingly, the defect density depends on the circumference only. This finite-size effect appears at small circumferences for both cones and cylinders. In addition, crystals seeded close to the cone tip can temporarily escape the finite-size effect. These findings reveal that cones can frustrate crystal growth, but the frustration can be alleviated by judicious choice of seed placement.
In the absence of a seed, the fiber itself can act as a template. I show experimentally that colloidal crystals growing on conical fibers are geometrically frustrated by the conical closure condition. Whereas crystals on a cylinder can form perfect commensurate bands, crystals on a high-angle cone form a tilt-boundary seam with a predictable grain-boundary angle. At intermediate, near-cylindrical cone angles, crystals can still form perfect commensurate bands, but the widths of these crystalline bands are limited by the emergence of dislocations. The gradient in circumference for conical fibers imposes curvature-induced elastic stress on crystals, and therefore, crystals that reach the critical width incorporate dislocations to release that stress. These dislocations enable the crystal to continue growing beyond the critical width.
Spherical templates and bidisperse suspensions can also geometrically frustrate crystals. Using molecular dynamics simulations, I show that crystallization within a droplet is a competition between heterogeneous nucleation at the interface and homogeneous nucleation in the bulk. I show that crystallization of larger particles is favorable at the droplet interface for short-ranged interactions, resulting in a core-shell structure composed of a shell of larger particles and a core of smaller particles. By increasing the interaction range, I can drive crystallization of the larger particles to occur at the interior of the droplet, resulting in an inverted core-shell structure. In a bidisperse system assembling by depletion interactions, the surface presentation of the droplet can be inverted by simply changing the size of depletants without modifying the particles themselves.
My work demonstrates how geometric parameters can affect the grain orientation, defect structure, and crystal morphology of self-assembled colloidal crystals. In addition, focused ion beam methods can directly template particles for experiments requiring high spatial control. These results enable future fundamental studies in geometric frustration and applied studies in crystal and defect engineering at the colloidal scale
Discovery and biosynthesis of α-diazocarbonyl-containing natural products
No full textMicrobes perform a variety of complex and synthetically challenging chemical transformations under environmentally benign conditions, including the production of structurally unusual natural products. Discovery and biosynthetic characterization of enzymes involved in microbial natural product biosynthesis may enable new biocatalytic and metabolic engineering approaches to overcome limitations in synthetic chemistry. In addition, identification of new biosynthetic enzymes facilitates genome mining approaches to discover novel natural products with potentially interesting biological activity. A rare subset of natural products contains a highly reactive diazo functional group which is synthetically attractive and often confers potent biological activity. Despite the biological and synthetic utility of diazo-containing metabolites, their biosynthesis remains poorly understood. In this work we discovered new biosynthetic logic for diazo formation which we leveraged to discover diazo-containing molecules through genome mining and reactivity-based screening. Elucidation of the biosynthesis of these molecules revealed an unprecedented diazo-forming metalloenzyme with promising biocatalytic applications.
Chapter 2 describes the discovery and characterization of the azaserine biosynthetic gene cluster which encodes biological production of the synthetically enabling ⍺-diazoester functional group. Characterization of the azaserine biosynthetic pathway revealed a novel strategy for diazo production through iterative hydrazine oxidation. Further, our collaborator Dr. Jing Huang (Keasling and Hartwig labs) engineered a biosynthetic pathway for unnatural carbene transfer which utilized the azaserine biosynthetic gene cluster to biologically generate the key ⍺-diazoester carbene donor.
Chapter 3 describes the development of a reactivity-based screening workflow using strained cyclooctynes to discover new diazo-containing natural products. Genome mining for iterative hydrazine oxidation machinery revealed putative diazo-producing organisms which were prioritized for reactivity-based screening. This approach revealed two previously unappreciated ⍺-diazoketones, 4-diazo-3-oxobutanoic acid (DOBA) and diazoacetone (DAC), from pathogenic Nocardia with potentially interesting biological roles.
Finally, Chapter 4 describes the discovery and characterization of the DOBA and DAC biosynthetic gene cluster. Biochemical characterization confirmed iterative hydrazine oxidation logic and revealed a novel diazo-forming metalloenzyme that catalyzes a biologically unprecedented hydrazone N-oxidation with significant biocatalytic potential. Additionally, discovery of this biosynthetic gene cluster now enables biological production of the known carbene transfer reagent diazoacetone which expands the potential scope of engineered biosynthetic pathways for carbene transfer
Is the Swedish Model of Gender Equality in Decline?
No full textAbstract
Gender equality and women’s rights are being challenged in many Western countries. Sweden is one such country. Although other nations have long admired and tried to emulate Sweden’s gender equality, in recent years the country’s model of gender parity has begun to decline. The decline is a result of complex dynamics with many contributory factors, and some Swedish women even challenge the very notion that Sweden ever reached a higher level of gender parity in the first place; these women believe that the perception of Sweden as a gender utopia is a nice façade but is not representative of reality. In this thesis, the decline of gender equality is discussed through analysis of Sweden’s abandonment of its feminist foreign policy, decreasing rates of male participation in parental leave, low rates of female participation in high-paying managerial or leadership roles, low level of female entrepreneurship, high rates of female employment in low-paying jobs (such as childcare and healthcare), persistent sexist cultural norms, and increased violence against women.
Sweden’s government is a large contributing factor in these issues. In 2022, Sweden decided to abandon its feminist foreign policy, which was the first of its kind in the world when it was adopted in 2014. Abandoning a feminist foreign policy contradicts the ambition to challenge gendered institutions and power hierarchies and stands in opposition to the advancement and protection of women’s rights. Sweden’s new government also includes a coalition with the rapidly growing Sweden Democrats (SD)—a right-wing populist party, who have publicly denounced feminism and measures of gender equality over the years—and they currently hold 20% of Sweden’s vote. In addition, Sweden joining the European Union (EU) and adhering to the EU’s laws and regulations has in some ways reversed gender equality in Sweden, although Sweden may have helped to further gender equality for other EU countries.
Also, welfare states such as Sweden tend to have female populations that are more likely to work compared to those in non-welfare states. In Sweden’s case, the large female workforce is the result of a government that has encouraged the dual earner/ dual carer model since the 1970s. However, economists have concluded that women are still less likely to end up in high-paying managerial positions in Sweden. Mothers’ careers are thwarted not only by parental leave but also by a gendered workforce, unpaid work, part-time work, and a persistent wage gap.
Women have also been impacted by the fact that attention to refugee issues have often taken precedence over gender issues in Swedish politics since 2015. Moreover, most refugees in Sweden are from Muslim countries and patriarchal societies, and they often bring the gender stereotypes of their home countries with them. According to Swedish data, an increase in sexual violence against women has coincided with the increase in immigration. Overall, in the framework of Women, Peace and Security (WPS), it is recognized that women must be critical actors in all facets of society in order for countries to achieve sustainable peace and security; in particular, women must have a voice in government and leadership. Through deeper analysis of these topics, this thesis demonstrates the decrease in gender equality in Sweden and suggests that the dual earner/carer model has not progressed sufficiently to allow women the opportunity to participate in the workforce equally
Myeloid Cell-based Immunotherapies for the Treatment of Cancer
No full textA key question in cancer immunotherapy is which features dictate therapeutic response versus non-response. Therapeutic responses to checkpoint blockade immunotherapies still hover around 15-20% across most cancers. Critical barriers to therapeutic response include the immune suppressive tumor microenvironment (TME), which is predominated by tumor-associated macrophages (TAMs). These TAMs generally promote tumor growth, invasion, metastasis, and resistance to treatment. Due to their high plasticity, TAMs can exhibit various phenotypes. Recent studies have revealed that some TAMs actually stimulate the immune response, challenging their traditional view as purely immunosuppressive. While prior approaches have been made to therapeutically target TAMs using antibodies binding cell surface proteins or growth factor pathways, these approaches have had limited clinical success. A possible reason why these approaches failed is that they targeted macrophages without identifying an immunological direction. Here, we show that systematic identification of stimuli to induce interleukin-12 (IL-12), a strongly anti-tumor cytokine produced by macrophages, provides novel combination therapies to induce IL-12 production natively within TAMs. We combine a high-throughput molecular screen for IL-12-inducing compounds with a cyclodextrin-based nanoparticle to create a Highly Active Myeloid Therapy (HAMT) that can complex small molecule immune modulatory drugs for simultaneous delivery into macrophages. By employing this simultaneous delivery strategy, we overcome the challenges of the uneven drug distribution that often results from differing pharmacokinetics in separate administrations to modulate macrophage more effectively.
We hypothesized that a novel TAM-targeted nanoparticle, encapsulated with triple small-molecule drugs targeting the Janus Tyrosine Kinase (JAK1/2), the non-canonical nuclear factor kappa light chain enhancer of activated B cells (NF-κB), and toll-like receptor (TLR) pathways, would trigger native macrophage production of IL-12 to mitigate the immune suppressive microenvironment within tumors. To test the mechanism further, we applied intravital microscopy and flow cytometry to confirm that most nanoparticle uptake was into TAMs but not tumor cells or lymphocytes. We also demonstrate that HAMT treatment cohorts showed fewer terminally exhausted T cells compared to the control groups. Finally, we performed RNA sequencing on HAMT-stimulated bone marrow-derived macrophages, which characterized a novel TAM phenotype by an over-expression of IL-12, MARCO, DC-SIGN, and SIGNR7 and the absence of ISG, which includes the inhibitory factors PDL1 and IDO1/2
Designing Efficient Domain-Specific Architectures for Autonomous Systems
No full textThe rapid development of deep learning models is driving a remarkable expansion in capabilities for a wide array of real-world applications, from smart sensors to autonomous systems like self-driving cars and aerial robots. These innovations bring the promise of unparalleled intelligence and autonomy. Yet, efficiently implementing these AI models in autonomous systems poses a significant challenge, a key to unlocking their full potential in practical applications. As Moore's Law begins to plateau, computer architects are increasingly focusing on domain-specific architectures to meet the evolving performance demands of these complex domains.
Designing domain-specific architectures for autonomous systems presents unique challenges. These systems are complex, involving multiple critical components such as compute systems, sensors, controllers, and physical limitations like size, weight, and power. This complexity is exacerbated by two main factors. First, current methodologies in designing domain-specific architectures often result in inefficiencies, as they focus narrowly on compute-centric metrics, neglecting the autonomous system's holistic performance needs. Second, the evolving landscape of AI models and the diversity of autonomous systems call for domain-specific architectures that are not only efficient in a holistic sense but also flexible enough to adapt to rapidly changing AI model landscape. This scenario underscores the necessity to develop methodologies and tools that span from efficient training of AI models to their characterization and the creation of automated design methodologies for domain-specific architectures, for the effective deployment of these models in autonomous systems.
This thesis presents systematic methodologies and tools for designing domain-specific architectures. It introduces a holistic framework specifically crafted for training AI models for autonomous systems. It leverages deep reinforcement learning combined with domain randomization and hardware-in-the-loop techniques to validate AI models across various deployment scenarios. These methods ensure that the models are not only functional in simulations but also effective in revealing system-level bottlenecks when deployed on aerial robots. Furthermore, the thesis introduces tailored performance bottleneck tools like roofline models, designed for autonomous aerial robots. These tools are instrumental in identifying and addressing computational bottlenecks, while also considering sensor and physical characteristics unique to autonomous systems, thus optimizing system performance.
Moreover, much of the research focuses on creating custom domain-specific architectures, employing machine learning as a tool to automate their design for autonomous systems. The thesis demonstrates that a cross-stack approach in designing hardware and software is critical for optimizing the safety and performance of autonomous systems. By integrating components such as sensors, compute elements, and controllers, this comprehensive strategy ensures that the domain-specific architectures are efficient and balanced, maximizing mission-level performance. Additionally, the thesis acknowledges the vast design space involved in creating domain-specific architectures and proposes standardized interfaces to apply machine learning automatic design space exploration. This approach streamlines the process, efficiently navigating and pinpointing optimal solutions, thereby significantly reducing the complexity and time required in the design process.
In conclusion, the thesis contributes by providing a comprehensive methodologies, performance models and tools for the design and optimization of domain-specific architectures. These contributions not only address the current challenges in the field but also pave the way for future advancements in the deployment and efficiency of AI models in autonomous systems, ensuring their practical and effective application in a rapidly evolving technological landscape
Algorithms for Political Methodology in the Information Age
No full textContemporary politics is bound to an unprecedented volume of online information, and to the algorithms and social networks that deliver it. From millions of online campaign ads to billions of fake news social media posts, these novel phenomena are a vital frontier for political science, yet we require new methodological tools to understand them. Specifically, we require new methods that allow us to understand the content of these massive and exciting data sources, as well as methods that allow us to understand their fundamental strategic and behavioral dimensions. This dissertation comprises four papers that each offer a new method for these problems.
The first paper introduces a new means to obtain solutions to LDA topic models that summarize the content of large text datasets in a manner that is provably better fitted to the text data, more interpretable, faster, and more amenable to causal inference than the current state of the art. This solves a set of open methodological problems that have been extremely well-studied since the popularization of topic models two decades ago. It also provides researchers with a first practical means to run topic models with provable guarantees and interpretability properties similar to those of linear regression and other workhorse methods in the political methodology toolkit. I demonstrate the advantages of this method by applying it to several well-studied datasets, as well as an original dataset of every text-based online political campaign ad on Google in the run-up to the 2020 US Presidential Election.
The second and third papers describe the results of an academic research/data collaboration with Facebook, which yielded the first-ever academic access to Facebook's internal data on the billions of fake social media accounts that introduce and spread fake news across the social network. These papers show that despite the oft-changing content and effects of fake news, there exist fundamental and persistent strategic dynamics that characterize how campaigns of fake-news-sharing social media accounts strategically connect to a social network. In addition to their theoretical contributions, our models also contributed to the removal of billions of malicious fake Facebook accounts over the last year. The fact that these simple models consistently achieve state-of-the-art performance in an oft-changing setting dominated by far more complex machine learning algorithms suggests that the social interactions they capture are central to the strategic environment in which fake news propagates.
The fourth dissertation paper leverages the content of online news to develop a novel measure of security dilemma dynamics. Specifically, we assemble a dataset of the full texts of virtually every online English-language article published about China, and we use plagiarism analysis to reconstruct the network of inter-media and government-media influences responsible for the spread of popular news `meme' characterizations of Chinese politics over time. We show how this approach constitutes a novel means to theorize the process by which security narratives emerge in international relations
Five-Year Vision for Stewardship of Born-Digital Content at Harvard Library
No full textWith the proliferation of born-digital content, Harvard Library (HL) is at an inflection point. If the Library does not implement robust stewardship practices for these materials, it will be unable to honor commitments to donors and records creators, researchers, and students. Moreover, the Library could incur significant institutional and reputational risk from its inability to manage, preserve, and provide access over time to Harvard's institutional records and to the research, pedagogic, and cultural heritage assets acquired by Library units.
In 2021, HL charged a Born-Digital Stewardship Working Group (BDSWG) to develop and implement strategy and an initiative for the stewardship of born-digital content managed by Harvard’s libraries. This content includes research and licensed data; digital scholarship output; special collections and archival materials; institutional records; course materials; and student and institute publications.
The BDSWG collaborated across Harvard schools, departments, and library units to develop the Five-Year Vision for Stewardship of Born-Digital Content at Harvard Library. With this roadmap, HL can achieve a state of sustainable, programmatic stewardship of born-digital content by expanding the capabilities of its staff, systems, policies, and strategies for managing, acquiring, preserving, and providing access to born-digital content and records. Through these efforts, HL ensures that the born-digital content it stewards becomes—and remains—available for access and use by the Harvard and global communities.Version of Recor
Mixed Ownership and Alternatives to Privatization in India
No full textThis paper conducts two empirical investigations concerning state-owned enterprises (SOEs) in India. The first follows existing methods proposed by Ben-Nasr et al. (2012) and OECD (2019b) to estimate the cost of equity for publicly-traded Indian SOEs with mixed ownership (owned by both the state and private individuals). I argue that Indian SOEs not only face higher costs of equity than private firms, but are less likely to have exceeded ex-ante cost of equity estimates with subsequent realized returns on equity. The second study evaluates the effectiveness of an Indian government program designed to reward well-performing firms with enhanced corporate autonomy. Analysis of the timing of performance gains suggests that improvements to financial performance are exogenous to the program itself. This paper responds to the recent rise in state-led capitalism and continuing development of capital markets in regions with large SOE sectors
Engineering chitosan-silk fibroin laminates for use as strong, tough, and biodegradable alternatives to plastic packaging
No full textPlastics are strong, resilient, and lightweight materials that have become essential to modern life. However, the mass production of plastic has also generated 6.3 billion metric tons of plastic waste, with devastating effects on wildlife, natural ecosystems, and even human health. Thus a need exists for biodegradable plastic substitutes that perform like conventional plastics. This study fabricates, characterizes, and optimizes chitosan-silk fibroin laminate films (termed “Shrilk”) for use as biodegradable alternatives to plastic packaging, which makes up 40% of all plastic waste. Shrilk—a portmanteau of the two words, “shrimp” (because chitosan is often isolated from shrimp shells) and “silk” (from silk fibroin)—demonstrated optical clarity and tensile properties comparable to common plastic packaging materials. The laminate structure resulted in higher tensile strength than both pure and blended films. Raman spectroscopy indicated a region of chitosan-silk fibroin overlap at the interface, suggesting that the laminar arrangement enables chitosan and silk fibroin to interact in an organized form of mechanical entanglement. Shrilk films were confirmed to be biodegradable, losing 84% of their total mass after four weeks in simulated landfill conditions. Casein, collagen, and keratin were investigated as potential substitutes for silk fibroin, but were unable to reproduce the adhesion, flexibility, and strength found in Shrilk films. The molecular weight of chitosan, thickness of films, number of laminate layers, and amount of glycerol were varied in order to alter Shrilk’s mechanical properties, but generally had little effect. However, covering Shrilk films with a hydrophobic coating effectively prevented Shrilk from completely losing its mechanical properties when wet, and even suggested that a moderate amount of water could act as a plasticizer to increase the films’ toughness and elongation at break. Overall, this work presents a strong foundation for future research into chitosan-protein laminates as a potential solution to plastic pollution