VictorJuiz/thesis huggingface dataset:
Transnational Bodies: Audience Performance in Anime and K-pop Media and Theatre Ecologies

The transnational circulation of Asian popular culture has grown exponentially over the last few decades, revealing tensions between concepts of nationality and globality as these media are promoted as national products and simultaneously considered emblematic of neoliberal globalization. How do we study these media without forgetting cultural specificity, but also without retreating to ethnocentrism, which promotes national frameworks? My dissertation Transnational Bodies: Audience Performance in Anime and K-pop Media and Theatre Ecologies enters this conversation by foregrounding the vital role global audiences play in moving and co-creating transnational Asian popular culture, and how fans’ engagement with these media negotiates their own racialized and gendered identities./nThrough specific, historically-situated case studies that span across multiple media and platforms, my research analyzes the worldwide fan communities for K-pop (South Korean pop music) and anime (Japanese animation), and how their interactions form a collective I call “transnational fandom.” Transnational fandom becomes a prime site to uncover tensions within global media surrounding race, gender, and nationality, as fans’ performances demonstrate fraught assumptions about whose body is allowed to co-opt, claim, or otherwise take part in these media’s creation and circulation. In some cases, fan performance promotes bounded notions of identity and shows implicit bias within their own communities, and in other cases, their negotiations with and through K-pop and anime open space for dialogue about complex intertwinings of race and gender vis-à-vis Asian media. Throughout my studies, I argue that fans’ embodied performances are indispensable modes of inquiry to understand how audiences interrogate fixed notions of identity, community, and medium boundaries to form transnational, networked collectives. These collectives point to the uneven, messy, and simultaneous overlaps of transnational identity, but also suggest modes of community building that do not rely on binary constructions or solid borders.

Advisor: De Kosnik, Abigail
A large deviation framework for interacting systems far from equilibrium

It has remained a mystery for the past few decades whether there is a non-equilibrium extension to equilibrium statistical mechanics. Recently, there has been advancements through dynamical relationships between currents and energy dissipation and correspondingly their distributions which comes from a framework called large deviation theory. Within this framework, large deviation functions operate in a similar fashion to the free energy in equilibrium which generates the cumulants for the energy. However, advancements of this theory have been mainly for non-interacting models that are exactly solvable. During my graduate career,I have made advancements towards predicting the fluctuations of interacting systems away from equilibrium. Towards this end, I developed a so-called weighted many body expansion which when combined with an approximate closure allowed for mean-field predictions for the distributions of entropy production and mass current in active matter. The same theory also allowed me to quantify density fluctuations and identify the type of phase transition that occurs in interacting active matter and in a model of 2 dimensional membrane-bound protein condensation. Akin to equilibrium distributions, by quantifying how the large deviation functions scale with system size gives information about the interface. I feel confident that my body of work has progressed the field and has provided a new perspective on a decades old problem.

Advisor: Limmer, David T.
Altruism: Past, Present, Propagation

I intend to examine the question of scalability of altruism and its long term sustainability. Altruism has posed multiple substantial conundrums in different fields, including challenges to its possibility, its efficiency, and its scalability. Multiple accounts of the evolution and dynamics involved in altruistic interaction among humans, institutions, animals and artificial intelligences rely on conflict between entities as the proximal cause of cooperation and altruism within entities. In this examination I go through our knowledge in anthropology, philosophy, neuroscience, evolutionary psychology, and biology to examine in which ways specific properties of humans and human groups, as well as theorized properties of agents in general, can accommodate truly altruistic actions and behaviors. Further I examine the question of where the processes that lead us to the current levels and type of altruism are headed and whether there is a basin of attraction towards which it would be desirable to go from an altruistic perspective in longer timescales. I will examine the limitations and constraints posed by game theory, neuroscience, and the specifics of our evolutionary past, and in so doing I paint a picture of altruism as a valuable and feasible, as well as scalable, strategy, for the foreseeable future. I lastly propose some roads toward achieving these scalable possibilities through a combination of evolutionary and technological nudges according to the current literature.

Advisor: Deacon, Terrence
Application of Tyrosinase-Mediated Oxidative Coupling to Site-Selective Surface Bioconjugation

Bioconjugation is key to enabling the diverse applications that biomolecules are capable of mediating. While strategies for solution-phase bioconjugation are of critical importance, many applications of biomolecules require surface immobilization. Thus, efficient surface bioconjugation strategies are required in order to enable the full potential of biomolecules, particularly proteins. Many current immobilization methods are not site-specific. Although non-site-specific methods are sometimes effective, such as the new approach for tyrosinase immobilization provided herein, site-specificity is often critical to maintaining protein activity once immobilized. This work focuses on a new method for surface bioconjugation that employs an enzymatic oxidative coupling strategy. The method was optimized on gold nanoparticles, and it was demonstrated that phenol functional groups on gold nanoparticle surfaces can be directly oxidized by the enzyme tyrosinase to enable subsequent site-selective bioconjugation of proteins, including multivalent protein assemblies, and DNA. Cellulose was also explored as a solid support, and small molecule oxidative coupling is described. Appropriate optimization may allow the oxidative coupling approach to be efficient for biomolecule immobilization on cellulose substrates. Progress was also made toward oxidative coupling of proteins on gold chips, with the goal of generating reversible Surface Plasmon Resonance sensor chips to study biomolecule interactions. Overall, the work herein offers a new route for protein immobilization on a range of surfaces, which expands the toolbox of surface bioconjugation and may improve or enable a variety of devices, diagnostics, and other systems that require efficient protein immobilization strategies.

Advisor: Francis, Matthew B
GI Jazz: African Americans as Artists and Occupiers in Post-World War II Germany

Abstract/nGI JAZZ: African Americans as Artists and Occupiers in Post-World War II Germanyby Kim Rene Nalley Doctor of Philosophy in History University of California, Berkeley Professor Waldo E. Martin, Jr. Chair/n‘GI JAZZ: African Americans as Artists and Occupiers in Post-World War II Germany,’ examines the lives of African American Jazz musicians living in and around German military bases after 1945 until 1970. Despite Truman’s Executive Order desegregating the armed forces, the military continued to have problematic pockets of discrimination. Off base, social segregation was also persistent and its effect on the lives of these GIs is examined. The proliferation of military bases in Germany after World War II and the longevity of these occupied presences in the wake of the Cold War resulted in a proliferation of service clubs designed to entertain African American GIs. German Jazz clubs and bars sprang up around military bases that provided off-base havens for Black GIs because despite the military being desegregated officially, socially the races often were segregated. These clubs and the relatively freer conditions in Germany for African Americans compared to segregation in the United States led many African Americans to settle as expatriates, furthering our understanding of the African diaspora through the transnational history of African Americans in the United States and Europe. The political-cultural impact of Jazz GIs as artists is examined utilizing new archival documents and artifacts.This work also examines both the soft and hard power Jazz GIs had, interracial relationships between Black GIs and Fräuleins, and offers a glimpse into African American women’s reaction to male Black GIs’ new freedom to engage in interracial relationships with less fear of reprisal. Given that the United States was still segregated, the dichotomy of African Americans’ status as military occupiers of a vanquished country, or a privileged minority, while still being an oppressed minority in the United States is explored.

Advisor: Martin, Waldo
Circuits and Control for High-Performance Grid-tied Ac-Dc Conversion Systems

Ac-dc (and dc-ac) power converters are the interfaces between the electrical grid and thesystems for emerging applications such as electric vehicle (EV) charging, renewable energy source integration, data center power delivery, consumer electronics and numerous other applications. In this dissertation, new circuit topologies and control techniques to improve the performance for both single-phase and three-phase grid-tied converters are explored for three major conversion scenarios: high power bidirectional single-phase ac-dc converters for EV charging and data center applications, low power single-phase ac-dc converters for consumer electronics, and high power three-phase ac-dc converters. For single-phase conversion, the challenge of twice-line frequency energy buering is addressed with active buering techniques that can signicantly reduce the required capacitor size compared to conventional solutions. Through the development of active buers with systematic multi-objective optimization methods and associated advanced digital control, the energy utilization ratios of the passive components are much improved, and the system losses are optimized. For threephase conversion, control and modulation techniques to reduce computational complexity and inductor current ripple are proposed and validated. The proposed circuit topologies and control techniques for both single-phase and three-phase are all validated with high performance hardware demonstrations. Some of the highlighted ones in this dissertation are: a 6 kW, 400 Vdc single-phase liquid-cooled EV charger with optimized series-stacked buer, achieving record power density; a 6 kW 400 Vdc three-phase multilevel rectier with advanced digital control techniques; an active single-phase buer with the smallest reported capacitor size for 2 kW, 400 Vdc inverters; a compact active buer for 65 W USB-C charger.

Advisor: Pilawa-Podgurski, Robert R.PP
Single-cell and single-molecule methods for mapping protein-DNA interactions

The same two meters of DNA is carefully packed into the nucleus of nearly every cell in a human’s body, where it encodes essentially all of the complex information required to build a complete human being. However, DNA by itself cannot give rise to life; it must be decoded and maintained by specialized macromolecules, including proteins that read, regulate, replicate, recombine, and repair DNA. Mapping where and how these life-giving proteins interact with DNA can provide key insights into how they function or malfunction in healthy and diseased cells./nHigh-throughput DNA sequencing technologies form the basis of several powerful methods for mapping protein-DNA interactions across the genome, but they often require researchers to blend together many thousands or millions of cells to provide enough material to make an accurate measurement. Due to this blending, these bulk methods cannot capture the dynamic and heterogeneous nature of protein-DNA interactions as they regulate the genome in individual cells. While newer methods are beginning to enable protein-DNA mapping in single cells, they are incompatible with high-resolution microscopy, which can provide rich orthogonal information about nuclear organization and other complex phenotypes in single cells. Furthermore, existing protein-DNA mapping approaches fail almost completely within highly repetitive DNA sequences, which constitute roughly 5-10% of the human genome and play indispensable roles in maintaining genome stability./nIn this body of work, I have developed two new technologies to address each of these limitations in turn. Firstly, I designed an integrated microfluidic platform (μDamID) that combines high-resolution imaging and sequencing information in the same single cells, allowing for the joint analysis of the nuclear localization, sequence identity, and variability of protein-DNA interactions in single cells. Secondly, I worked collaboratively to develop DiMeLo-seq (Directed Methylation with Long-read sequencing), which uses cutting-edge DNA sequencing technologies to map protein-DNA interactions on long, single molecules of DNA that retain endogenous DNA methylation marks and can be mapped to highly repetitive regions of the genome. Together, these new methods expand the toolkit available to researchers to study the fundamental processes that regulate the genome, with the potential to enhance our understanding of embryo development, stem cell differentiation, and diseases resulting from genome misregulation.

Advisor: Streets, Aaron
Making Sense of Number, Bit-by-Bit

Numerosity perception has been studied for at least 150 years and its psychophysics have been well characterized by experimental work. However, the origins of many of its key properties remain obscure. For instance, people estimate the numerosity of small sets (up to four) much more rapidly and accurately than larger sets; people tend to underestimate larger numerosities; estimation precision and accuracy increase with exposure duration. Standard models of numerical estimation do not account for these wide ranging phenomena, with large number estimation typically characterized as a draw from Gaussian(n, w * n) where w is a person's "Weber fraction," and exact small number perception characterized separately, the result of an independent object-file system. Furthermore, the inherently perceptual nature of estimation is largely ignored in many accounts of individual differences, which are often considered evidence of disparities in innate mathematical cognition. In my dissertation, I present studies of human behavior and computational models aimed at clarifying the visual mechanisms underlying numerical estimation. Our findings help to understand, and unify, key properties of number psychophysics which have previously been explained in terms of independent mechanisms or with ad hoc modifications to existing theories. For instance, we show how the psychophysics of both small and large number estimation can be unified into a single framework with a common mechanistic origin, and in fact how myriad properties of both (including estimation precision, bias, effects of time) can be understood as downstream consequences of bounded-optimal perceptual inference.

Advisor: Piantadosi, Steven T.
K\"ahler Geometry of non-Compact Toric Manifolds

Toric manifolds and toric varieties have played an important and particularly illuminating role in algebraic, symplectic, and K\"ahler geometry going back at least to the 1970's. The high degree of symmetry in many cases allows one to reduce the complexity of a given geometric question, giving the impression that we can really ``see'' the structure. A notable example of this in the K\"ahler setting is Donaldson's classic paper [27]./nUntil relatively recently, this has been mostly confined to the setting of compact manifolds (complete varieties). Both the algebraic and the symplectic perspectives have come to be fairly well understood individually in the non-compact case, but there has been little application of the intersection of the two theories, which naturally comprises toric K\"ahler geometry. The notable exception to this rule is the case of toric K\"ahler cones [56, 55, 39, 17, 16]. These non-compact manifolds inherit a great deal of structure from their compact \emph{link}, which are interesting spaces in their own right. However, these manifolds are (typically) highly singular at precisely one point./nIn this dissertation, we describe a procedure for the study of K\"ahler geometry on smooth non-compact toric manifolds. This involves tying together the algebraic and symplectic perspectives. We study a class of toric manifolds and show that here we can apply a non-compact version of the classical Delzant classification together with its application to K\"ahler geometry [4, 41, 24, 42]. We apply this to non-compact shrinking K\"ahler-Ricci solitons, where we propose a useful class of complete K\"ahler metrics, and ultimately prove a general uniqueness theorem for shrinking K\"ahler-Ricci solitons on non-compact toric manifolds.

Advisor: Sun, Song
Perceiving 3D Humans and Objects in Motion

We exist in a 3D world, where we accomplish everyday tasks by perceiving and interacting with other people and objects in dynamic scenes. Could we develop a perception system to understand such rich interactions? This is crucial for future intelligent systems to collaborate with humans and to create immersive AR/VR experiences. While great progress has been achieved in the individual perception tasks of 3D humans, objects, and scenes, the connections between these components have not been explored much. In this thesis, we attempt to build the connections between these three components to understand their rich interactions. We start by bridging the scene and object component in Chapter 2, where we present an end-to-end learning system to perceive the 3D scene and independent object motions. We next show how 3D scenes influence human motion in Chapter 3, where we design a framework to predict future 3D human motion considering the scene context. In Chapter 4, we study the interaction between human hands and objects, where we introduce an optimization-based method to reconstruct the interaction in the wild. Finally, we conclude with several interesting future directions.

Advisor: Malik, Jitendra
Leveraging paleo, historical, and modern records to understand the effects of management and fire on forest carbon biomass

My dissertation weaves together paleo-ecological data, archival records, historical evidence, and modern inventories to understand the long-term impacts of fire disturbance on forest carbon dynamics in Six Rivers National Forest, California. Over three chapters, I use my results to evaluate the consequences of management activities, namely anthropogenic manipulation of fire, on aboveground live forest biomass. In the first chapter, I present a reconstruction of forest structure and composition during the 1880s and compare it to modern forests conditions. I found that modern forests are considerably denser and increasingly favor shade-tolerant taxa, likely due to twentieth century fire suppression. In the second chapter, I focus on developing an emerging fossil pollen analysis technique as the first step in quantitative reconstruction of past vegetation biomass. By modeling the relationship between modern pollen influx and modern biomass, I demonstrated that calibrated pollen influx-biomass relationships provide a robust means to infer changes in past plant biomass. My third chapter concludes with the application of the models I developed in the previous chapter to 3000 years of pollen influx data. These models allowed me to estimate aboveground biomass in a mixed conifer forest over the late Holocene. Taking a trans-disciplinary approach in this chapter, I integrate empirical datasets about biomass and fire with Native oral history to illustrate the significant and important role that Indigenous peoples played pre-contact in shaping the forest ecosystems of northwestern California. With this dissertation, I document forest dynamics at different spatial scales over three millennia and provide a practical benchmark for land managers by indicating the scale of intervention needed to move California forests closer to their long-term historical conditions.

Advisor: Battles, John J
Potts, Matthew D
Machine Learning Augmented Nuclear Data Evaluations

With the fast increase in computational power over the last decade, including the development of better Graphical Processing Units (GPUs), the field of Machine Learning (ML) and Artificial Intelligence (AI) has improved drastically since its inception in the 1980s. With more efficient algorithms and faster training times, the prominence of ML/AI throughout business and technology sectors has only grown. However, its extension to Nuclear Physics and Engineering remains limited to date. In this work, we explore the possible roles of ML in the Nuclear Data Evaluation pipeline including the development of (1) NucML and (2) an ML-based solution for neutron-induced evaluations. To catalyze future development in the area, NucML, the first end-to-end ML-augmented nuclear data evaluation pipeline was developed. This Python toolbox contains various capabilities ranging from loading ML-ready datasets to automatic validation of trained models using an in-house developed criticality benchmark public repository. It allows any user to focus on model development, in addition, to quickly navigating each step of the proposed enhanced pipeline in a modular easy-to-use fashion. Using the ML-enhanced framework and the newly developed code, several proof-of-concept ML models including Decision Tree, K-Nearest-Neighbor, and Gradient Boosting Machines were fitted to nuclear data from the EXFOR database to infer neutron-induce reaction cross sections. All models were used to predict nuclear data for several well-characterized isotopes in literature including Pu-239, U-238, U-235, and U-233. Afterward, data for several isotopes of interest including Cl-35, a less studied but important nuclide for advanced nuclear reactors, was generated. The predicted values for several of these isotopes were used to create an evaluation and tested using various benchmarks using SERPENT2 including the U-233 Jezebel and U-235-reflected U-233 spheres. Results for these proof-of-concept models in some cases outperforming the current release of the ENDF library by up to 200%. Once the models were validated, they were used to predict the Cl-35(n,p)S-35 at the same energy points as the new LBNL/UCB measurements. The predicted values described the cross sections 150% more accurately than any of the evaluated data libraries, which overestimate experimental results by up to a factor of five. The proof-of-concept models explored in this work, reliant on learning underlying patterns of cross section data from other radionuclides, demonstrate evidence that ML models can aid traditional physics-guided models and have a role to play in nuclear data evaluations. Furthermore, incorporating ML models in the nuclear data pipeline can allow evaluators to make faster human-bias-free decisions in areas of uncertainty as well as better inform future data measurement campaigns on areas of greatest sensitivity in EXFOR.

Advisor: Fratoni, Massimiliano