VictorJuiz/thesis huggingface dataset:
Learning to design protein structure and sequence
Keywords: Humanities and Sciences.

Over the last ten years the field of de novo protein design has been revolutionized by new computational methods. Here, I discuss work which illustrates applications of the "traditional" methods of de novo protein design, sampling with MCMC using semi-physical energy functions and heavy manual intervention to design a novel TIM barrel and a stabler and more functional IL-2 cytokine. I will also discuss my work on developing "new" methods based on deep learning which are much more efficient and accurate than traditional methods, and abstract away the need for expert curation. This includes some of the first works to generate NTF2 structures conditioned on secondary and tertiary structure labels, and to co-design protein structures and sequences for all-atom protein modeling. Finally, I briefly conclude and suggest possible future directions for the field to continue improving how we are able to design novel proteins.
Leveraging a cancer drug's off-target effects
Keywords: Medicine.

Red blood cells (erythrocytes, RBCs) are common to almost all vertebrate life on earth. In humans, RBCs circulate for approximately 120 days prior to their phago-cytic destruction by macrophages. RBCs are protected from premature destruction by their expression of the surface protein CD47, which interacts with the macrophage surface receptor SIRPa to inhibit phagocytosis. CD47 is expressed by all cells, and is overexpressed in many cancers. Antibody-mediated blockade of the CD47-SIRPa interaction overcomes this resistance, promoting macrophage-mediated destruction of cancer cells. This strategy works both by disrupting the anti-phagocytic CD47-SIRPa interaction and by engaging pro-phagocytic macrophage-expressed Fc gamma receptors (FcgRs). While a number of CD47-blocking antibodies are now in clinical trials for cancer immunotherapy, one question remains: how are patients able to tolerate CD47 antibody, given that it sensitizes their RBCs to phagocytic destruction? We find that CD47 antibody therapy induces myeloid FcgR-mediated pruning of RBC CD47 in mice, with global concomitant myeloid FcgR loss and splenic myeloid phagocytic inhibition, which protect antibody-bound and CD47-deficient RBCs from phagocytosis. Our findings provide a mechanism for the surprising tolerability of CD47 blocking antibodies and a mechanism by which RBC-binding antibodies may protect against autoimmune destruction of circulating cells like RBCs and platelets.
Leveraging azides in the synthesis of cyclobutenes and the conversion of arenes to pyridines
Keywords: Chemistry.

Four-membered rings are rapidly becoming sought-after scaffolds in pharmaceuticals due to their rigid structure and well-defined exit vectors. Towards this goal, we developed a method to enantioselectively form cyclobutenes from simple olefins and N-sulfonyl-1,2,3-triazoles. While these triazoles are known to act as diazo precursors via ring-chain tautomerization, we recognized them as vicinal dicarbene equivalents. Thus, alkynes are reacted in [3+2] cycloadditions with azides to form triazoles, which are then reacted with alkenes in a formal [2+2] cycloaddition. A host of enantioenriched cyclobutenes were synthesized, several of which were carried on to assemble the carbon skeletons of several natural products. The ability to selectively delete, insert, or exchange atoms in the core scaffolds of molecules is of fundamental interest to synthetic chemists and could be of great use to medicinal chemists seeking to rapidly modulate the parameters of lead compounds. Though atom deletions and insertions have garnered much interest in the form of ring contractions and expansions, atom exchanges have seen considerably less development. One notable exchange that has eluded chemists is the conversion of benzene to pyridine, which is of interest due to the "necessary nitrogen atom" effect, which describes the enhancement of key pharmacological properties when an arene in a lead compound was replaced with a pyridine. To this end, we found that azides serve as effective nitrene precursors to engage arenes in a C to N atom exchange sequence featuring nitrogen atom insertion and carbon atom deletion
Leveraging game structure in modern optimization
Keywords: Engineering.
Management Science and Engineering.

First-order algorithms have risen in prominence in modern optimization, partly due to their successful application to problems in data science and machine learning, especially in settings with large dimensionality and dataset size. In this thesis, we focus on large-scale optimization problems with game structure, either explicitly or implicitly. By uncovering and leveraging such game structure, we design accelerated or randomized first-order algorithms which obtain nearly-linear or sublinear time for a wide range of fundamental decision making tasks. Towards achieving our results we take a modern twist on two classic optimization techniques, acceleration and randomization, demonstrating their versatile utility in modern algorithm design for game-structured optimization tasks.
Leveraging text analytics and large-scale collections of identity artifacts for the culturally-informed classroom : creating teacher resources, gaining student insights, and designing learning experiences
Keywords: Education.

Despite widespread consensus in education research that incorporating students' lived experiences in the classroom can improve teaching and learning outcomes, opportunities for students to benefit from such instruction remain scarce. Constraints on teachers, such as lack of time, resources, and peer support, often hinder teachers' ability to design learning environments that are responsive to students' lived experiences. This dissertation proposes and investigates a novel approach to addressing these limitations. Drawing from theoretical and pedagogical frameworks such as Funds of Knowledge and Funds of Identity, a 21-hour online workshop for teachers was developed and piloted. The workshop leverages the analysis of large-scale textual data from a culturally-relevant corpus of student productions to identify recurrent issues that matter to students. This dissertation contends that outputs of such analyses, including lists of topics and associated essays, can serve as an accessible source for teachers to incorporate students' experiences in the classroom. This dissertation further explores how teachers learn from these cultural artifacts and the ways in which they make connections to learners' lived experiences in curriculum units and lesson plans after engaging with them during the workshop. Twelve Brazilian public-school teachers participated in the study, providing valuable insights into the applicability of the proposed approach. The results highlight the potential of such an innovative approach for enhancing culturally-informed teaching and learning environments and justify further research in this direction
Lexi Straube's NSC ePortfolio
Keywords: Communication in science
Human biology
Mind and body > Health aspects
Mixed materials
Image
Portfolio
Software/code
Sound
Text
Video
Book
Essay
Photograph
Podcast
Poster
Sound recording
Story
Thesis
Student project report
Portfolios
Essays
Photographs
Podcasts
Posters
Fiction

This document is an archive of an electronic portfolio (ePortfolio) produced as a capstone requirement for the Notation in Science Communication. In their ePortfolios, NSC students demonstrate how they have met the NSC learning outcomes. These learning portfolios detail students’ growth and development as scientists and science communicators rather than showcasing only their best work. ePortfolios are reviewed and approved by faculty, earning students a special designation on their official Stanford transcript that reflects their science communication acumen.
LIN ZEXU’S SECOND ACT: SETTLEMENT AND DEVELOPMENT OF THE TARIM BASIN 1844–1847
Keywords:  Stanford School of Humanities and Sciences
Lin, Zexu, 1785-1850
林則徐
Daoguang, Emperor of China, 1782-1850
道光帝
Bu-yan-tai, 1791–1880
布彥泰
Mujangga, 1782–1856
穆彰阿
Tarim Basin
Tarim River
Taklamakan Desert
Borderlands
Xinjiang
settlement
migration
oasis
Qing Empire
Text
Thesis

The Qing empire’s early development of its western frontier remains an under-studied area in English and Chinese scholarship. Shortly after the First Opium War (1839–1842), the emperor turned his attention to the looming overpopulation crisis facing the empire. The Taklamakan oases of the Tarim Basin seemed to provide a ready solution: the emperor resolved to settle the landless farmers from the interior provinces in this western borderland, also known as the “Muslim Region.” In time, he argued, the migrants would become “natives,” i.e. people born of the land. When his local administrators rejected the idea, he sent the cashiered official-in-exile Lin Zexu to conduct a fact-finding trip. Drawing on the diaries, letters, and field reports of Lin Zexu, this project uses the history of an individual actor to illuminate Qing’s attempt to assimilate the Taklamakan oases via a settlement policy focused on social structure, water management, and frontier security. The project provides a useful comparison to other empires’ expansion efforts and China’s current development programs in the region.
Lineage & freedom : a quantum computational framework for improvisation
Keywords: Humanities and Sciences.
Music.

Musical improvisation is the spontaneous act of musically communicating and composing with one or more musicians in the moment. However, in the current field of music information retrieval (MIR) there has not been a focus on developing algorithms to better understand the inner workings of improvisation, especially between musicians of different cultures and backgrounds. It is in part, due to the vast and complex space in which improvisation operates. A space with infinite outcomes that could possibly unfold. Because of this, classical computers are not efficient at modeling these types of interactions. Musical improvisation is more aligned with quantum computers, their properties allow us to simultaneously consider and handle this large number of musical possibilities. This dissertation proposes and outlines a new framework for developing music improvisation applications on quantum computers.
Linguistic Indicators of the Growth Mindset
Keywords: Language and education
Computational linguistics
Essays
growth mindset
Mindset (Dweck, Carol S.)
liwc
Text
Capstone
Report
Technical report
Thesis
Student project report

We use data from the synergistic mindsets intervention to find how language in student essays might correlate with self-reported stress levels n= 2000. We use word count based approaches, topic modeling, and word embedding based methods to find the linguistic patterns that correlate with stress levels. Our results show that in comparison to students who cope poorly with stress, those that cope well make greater use of negative over positive emotions, past and present tense over future tense, higher cognitive processing words, and more action over bodily sensation words in their writing. Our text classification models predict stress appraisals with an accuracy of 68 ± 0.4%. However, the length of the text students write is a major confounder in all our results. We discuss the text length as a confounder along with our other qualitative findings in relation to previous linguistic studies of mindfulness and stress.
Literary Reasoning in Large Language Models
Keywords: Large Language Models
Reasoning
Fiction
Text
Thesis

Humans are capable of recognizing similarities not only between single concepts but also between intricate real-world situations that involve multiple entities and relationships. Such analogical reasoning has been considered the hallmark of human cognition. Humans are also able to draw affective inferences from such real-world situations, such as which situations inspire attention and empathy, and to what degree. Large Language Models (LLMs) have shown a variety of human-like content effects in logical reasoning and human-like performance in analogical reasoning in zero-shot and few-shot conditions. This study examines the interaction of LLMs with narratives, with a focus on inferred affect, fictionality, and embedding. In particular, I investigate LLMs’ estimations of affective impact and empathy in response to narrative stimuli presented in one of four different conditions: a fictional story with no embedding,  a fictional story with embedding, a non-fictional story with no embedding, and a non-fictional story with embedding. This study builds upon prior work in narrative psychology and natural language understanding, proposing that LLMs as few-shot and zero-shot learners can differentiate the affective impact of narratives presented in different ways, and demonstrate literary reasoning, in particular, the abilities to 1) draw affective inferences from a story and 2) generate stories analogous to the story in question in mood, form and content.
Lithium ferrite for spin-based spintronics
Keywords: Humanities and Sciences.
Applied Physics.

The realization of more energy efficient nanomagnetic information devices in the field of spintronics relies on the existence of magnetic insulators capable of supporting pure spin currents in the absence of a dissipative charge current. Currently, there is a limited number of thin-film magnetic insulators with low magnetic damping. Li0.5Fe2.5O4 (LFO) is well known to possess the lowest damping among the bulk spinel structure oxides, but, thus far, LFO thin films have not lived up to these expectations. In this work I establish LFO as a promising low damping material in the field of spintronics. First, I demonstrate the first successful synthesis of LFO thin films with bulk-like magnetic properties. With chemical substitution, perpendicular magnetic anisotropy (PMA) was engineered into these LFO films - an additional desirable characteristic for spintronics devices. As a proof-of-concept application I fabricate an LFO-based device and demonstrate spin-orbit-torque switching in LFO films with current densities up to an order of magnitude lower than those observed in similar systems. Furthermore, I demonstrate that LFO can support the transport of pure spin currents over micron length scales, which is moderately large compared to other spinel ferrite insulators. These properties make LFO ideal for efficient spin current applications and highlight LFO's potential to be an all-star material in the field of spintronics.
Living up to the dream? African American school administrator counternarratives about race, leadership and retention
Keywords: Education.

A growing body of research shows that principal turnover is higher among people of racialized backgrounds (Meyer et al, 2020), associated with lower rates of student proficiency (Grissom & Bartanen, 2021) and most often is due to environmental conditions (Levin, Bradley & Scott, 2019). In partnership with the San Francisco Unified School District, I sought to explore the tenure experiences of their Black school leaders. I conducted 20 semi-structured interviews with African American principals and assistant principals. I combine social cognitive framework about administrator career decisions (Fairley-Ripple et al, 2012) with critical organizational theory (Ray, 2019) to demonstrate how SFUSD operates as a racialized organization despite espoused district commitments to African American students, Black educators and antiracist pedagogy. By looking at the district's new leader induction program, I show that there are unintended consequences to their efforts. For example, through helping new principals and assistant principals to name, interrogate and challenge unjust systems, Black leaders are more aware of the ways in which white supremacy culture is negatively impacting their work.
Local thermodynamic probe of correlated electrons in moiré systems
Keywords: Humanities and Sciences.
Applied Physics.

The emergence of "moiré materials", heterostructures formed by twisting and stacking atomically thin layers, has inaugurated a new era for investigating correlated electronic systems. They offer unprecedented tunability over band structure, electronic interactions and topology. In this dissertation, I will present my works on the use of a specialized scanning probe microscope, a scanning single-electron transistor (SET), to locally investigate correlated states in a diverse array of moiré systems. The SET probes the local compressibility and chemical potential of an electronic system with unparalleled resolution, enabling access to the delicate interaction-driven incompressible (insulating) phases and their phase transitions. In this dissertation, I will first summarize instrumentation efforts to set up two different scanning SET systems at Stanford University, which were used to carry out scientific projects described in this dissertation. I will then describe measurements on a selection of representative examples from two distinct classes of moiré materials. In magic-angle twisted bilayer graphene, I explore both the interacting Chern and Hofstadter physics in the high magnetic field regime, as well as the enigmatic correlated insulators found at low magnetic fields. In a semiconductor moiré heterobilayer WSe2/MoSe2, I describe measurements that reveal the coexistence of flat and dispersive moiré bands that leads to intricate competitions between Hofstadter and unconventional charge-ordered states. In a twisted double bilayer WSe2 system, I discuss how the introduction of Γ−valley moiré bands leads to new correlated ground states and charge excitations. Through these measurements, I will demonstrate how the local thermodynamic sensing capabilities of scanning SET synergize with the high tunability of moiré materials in uncovering novel correlated electronic phases
Locating legacies of environmental racism in park-going : a study of urban nature, race, and spatial interactions
Keywords: Humanities and Sciences.
Sociology.

Environmental justice research has highlighted how contemporary patterns of provision and accessibility of urban parks reflect a long legacy of environmental racism and injustice. However, the limited availability of large-scale data on trips to parks has precluded examining whether the legacy of environmental racism in park allocation manifests in park use behavior. This three-paper dissertation leverages SafeGraph cell-phone mobility data of trips to parks in America's ten most populous cities as of 2019 to understand whether patterns of park-going replicate the racial inequality in the provision of nature in urban areas. Paper 1 relies upon mixed effects regression models of park trips to assess explanations provided by leisure scholars for racial differences in park use. Paper 2 uses spatial regression analysis to test Jane Jacobs' theory that social diversity in the residential neighborhood of a park is critical for attracting high rates of foot-traffic to the park. Paper 3 leverages an Infomap network clustering algorithm to quantify the level of socio-spatial homophily in park-going and the tendency for whiter and affluent neighborhoods to use different types of parks than residents in neighborhoods of color. Collectively, the papers suggest that park use is less geographically constrained and less racially segregated for park-goers in neighborhoods of color than prior research has presumed.
Long horizon planning in the real world
Keywords: Engineering.

Enabling robots to perform everyday tasks such as cooking a meal or doing laundry requires giving them the ability to plan future actions over long horizons. Task and Motion Planning (TAMP) seeks to achieve this by combining high-level symbolic reasoning with low-level geometric reasoning to produce long horizon plans that are grounded with actionable motor commands. However, prior TAMP works have largely been limited to simulation due to their computational complexity and brittleness to perception and control noise. This thesis presents the first full-stack TAMP system designed to handle the unpredictability of the real world in real time. We demonstrate the ability to perform TAMP on a real robot with real-time reactive behavior and planning times no longer than several seconds. This system includes a symbolic perception pipeline that enables robust closed-loop task planning, efficient TAMP algorithms that are faster than previous state-of-the-art by an order of magnitude, and a method for integrating TAMP planning with reactive controllers that can adapt to unexpected environmental changes in real time. This thesis also addresses the challenge of scaling TAMP to large domains by proposing an alternative framework that can perform TAMP with a library of learned skills
Long-horizon prediction for human-robot collaboration
Keywords: Engineering.
Mechanical Engineering.

Robots are mainly seen as tools that offer passive assistance to humans or operate independently in close proximity to them. However, we are still far from witnessing robots that can collaborate with humans on tasks wherein both agents' actions and dynamics are interdependent and achieve synergistic results. As an example, and one that serves as the central motivation of my work, robots carrying a table towards a goal location and avoiding obstacles must be able to predict their partners' actions and mutually adapt to changing strategies during collaboration. Key challenges have been accounting for diverse, multimodal human behaviors over both short and long horizons, and producing joint actions that are temporally consistent. To address these issues, I leverage generative modeling for accurate sequence prediction of human-like motion and behaviors. I focus on two approaches to model interaction: first, by predicting team subgoals and executing cooperative actions; and second, by predicting partner actions and executing collaborative actions that would account for the partner's efforts. In the first part of this thesis, I develop a Variational Recurrent Neural Network-based planner trained with human-human demonstrations that learns to sample sequences of future waypoints autoregressively to achieve successful synergy with a human-in-the-loop on the table-carrying task. Next, I show that mixture density models can capture multimodality in human-human demonstrations, but fail to predict action sequences accurately for the cooperative carrying task. Finally, I show that a co-policy developed with a Transformer-based diffusion model conditioning on past human actions can not only plan action sequences with real humans-in-the-loop to achieve high success rates, but also display compelling collaborative behaviors in novel, out-of-training-distribution settings