VictorJuiz/thesis huggingface dataset:
Shielded Grandeur: A Conversation between Daoism and Frankfurt School in Chen Chuncheng’s Short Stories

Can Daoism serve as a tool in the criticism of modernity and offer an alternative way of living? This thesis intends to put the ideas in Daoism into dialogue with Frankfurt School scholars to analyze four short stories of a contemporary writer Chen Chuncheng 陳春成. In his first collection of short stories published in 2020, Chen juxtaposes a realistic world with a mystic cosmos through natural objects and the practice of crafts. This juxtaposition invokes both Frankfurt School’s criticism of the modern society and a Daoist worldview, both of which yearn for corporeal and experiential connections to a cosmos where every being, whether animated or not, is harmonically integrated into a grand course of the world. Relentlessly writing about the practice of a craft in various socio-historical settings and literary styles, Chen re-writes this motif that links Zhuang Zi’s allegorical tales with Walter Benjamin’s interpretation of the storytelling tradition. He situates this premodern practice in a modern setting to interrogate the efficacy of human language and communicability of experience, comparing the temporality of human society and that of nature.

Keywords:  Stanford Global Studies
Stanford Global Studies
East Asian Studies
Daoism
Ecocriticism
Chinese literature
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Thesis
Advisor: Wang Ban
Shifting Gears: Exploring the Dynamics of China's Energy Market Transition towards Renewable Energy Integration

Climate change is an existential threat to humanity and greenhouse gas (GHG) emissions is the primary driver of such a threat. Reducing GHG emissions has proved to be an intractable problem thus far given that most human productive activities result in GHG emissions. In particular, energy production accounts for ~70% of all GHG emissions globally.
In recent years, China has made several commitments to reducing its GHG emission and increase the share of its renewable energy. Such a position is quite different from its prior commitment and willingness to pursue economic growth regardless of the environmental costs. However, the magnitude of state-led investments and urgency of policy initiatives signal that China is quite serious in its endeavor to reach its climate goals.
Still, China's energy market has long been dominated by fossil fuels. The transition to a renewable driven energy market will inevitably encounter growing pains and obstacles, as evidenced by similar developments in the EU and China.

Keywords: East Asian Studies
China
Renewable Energy
Policy
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Thesis
Advisor: Thurber Mark
Short-term solar forecasting from all-sky images using deep learning

Integration of renewable resources, such as solar photovoltaics (PV), has been recognized as a crucial component in transition to a decarbonized energy system. However, the intermittent nature of solar power has challenged the large-scale deployment of PV. This variability is partly caused by short-term and local cloud events. Ground-based all-sky images captured with high temporal and spatial resolution have shown great promise as a source of input to forecast such fluctuations. In recent years, the development of deep learning has provided powerful tools to extract information from sky images and enhanced short-term solar forecasting capabilities. Despite these advancements, several major challenges have been identified: (1) sky image data are often imbalanced due to the tendency of installing PV systems in sunny locations; (2) cloud dynamics are not well captured by end-to-end deep solar forecasting models and uncertainty of predictions are rarely quantified; and (3) high-quality standardized sky image datasets for solar forecasting method development and benchmark are limited. In this dissertation, we explore ways to address these challenges by focusing on predicting the power output of a 30 kW roof-top PV system up to 15-minute ahead using a locally collected sky image dataset.

Keywords: Sustainability.
Energy Resources Engineering.
Advisor: Brandt Adam
Azevedo Ines
Lobell David
Single cell examination of the human placenta

The placenta, a vital organ for fetal development and species propagation, plays a crucial role in sustaining the fetus by providing nutrients, oxygen, and hormonal support. Despite extensive morphological descriptions, the molecular organization and characterization of cell types within the placenta remain limited. Recent advancements in single-cell RNA sequencing technologies have revealed various trophoblast and fetal cell subtypes, but the open-chromatin regulatory landscape has yet to be described. This dissertation aims to address this knowledge gap by employing a multi-dimensional approach, encompassing single-cell transcriptomics, epigenomics, and copy number variation (CNV) analysis. The study explores placental dynamics across the first trimester and compares them to the third trimester placenta, providing valuable insights into the cellular composition, differentiation trajectories, and regulatory landscape of early placental development. Utilizing single-cell transcriptomics, we identified three distinct syncytiotrophoblast subtypes in the first trimester placenta, each characterized by unique gene expression profiles and marker genes. We further created bulk open chromatin maps to identify active transcription factor motifs within different placental cell types and subtypes. By analyzing genetic variation and CNVs within the placental genome, we also gained insights into the potential influence of structural genomic alterations on the placental regulatory landscape and gene expression patterns. Our findings provide a comprehensive understanding of the modality within the placenta during the late first trimester, as placental cells adeptly respond to the establishment of maternal blood supply, facilitating nutrient and oxygen transfer to the developing fetus. The integration of single-cell transcriptomics, epigenomics, and CNV analysis in this study enhances our understanding of the intricate processes underlying placental development. These findings contribute to the broader knowledge of the placenta's critical role in pregnancy and its implications for maternal and fetal health. Moreover, the identification of specific CNVs and their integration with transcriptional and epigenetic regulation opens avenues for future investigations into the functional consequences of genetic variation, pregnancy complications, and potential therapeutic interventions

Keywords: Medicine.
Genetics.
Advisor: Baker Julie (Professor of genetics)
Boettiger Alistair
Kundaje Anshul
Lipsick Joseph Steven
Situating neural function within a biologically plausible optimization framework

There is a promise at the heart of neuroscientific research: understanding the brain will provide insights that improve health and well being. To fulfill this promise, our theories of neural function must be able to operate 'at scale'---i.e., generalize to naturalistic environments. However, even in well-controlled experimental settings, neuroscientific theories often fail to replicate, much less generalize. Recent advances in computer science have created computational frameworks which can operate at scale and necessarily generalize across experiments. But leveraging these methods to understand neural function beyond canonical visual cortex has had limited success. In this dissertation I demonstrate how these methods can be used to formalize and evaluate theories of neural function downstream of canonical sensory cortex. First, I review the historical challenges in understanding perirhinal cortex (PRC), including a longstanding debate over PRC involvement in perception (chapter 1). To formalize and evaluate PRC involvement in visual object perception, I situate lesion, electrophysiological, and behavioural data within a deep learning computational framework. This work resolves decades of apparent inconsistencies in the experimental literature by integrating results from human (chapter 2) and monkey (chapter 3) experimental data within a 'stimulus-computable' modeling framework. I extend this work to better isolate and characterize PRC contributions to visual object perception (chapter 4). Finally, I synthesize neuroscientific findings from multiple species to provide an account of PRC involvement in visual perception (chapter 5). Taken together, these data suggest that PRC supports visual object perception by integrating over the sequential outputs of canonical visual cortices. I conclude by describing how, to further understand how PRC supports these behaviors, this neuroscientific data can be situated within a biologically plausible optimization framework: we are well-positioned to understand perirhinal function using optimization approaches from computer science, constrained to reflect what we know about the underlying biology. This approach promises not only to formalize the relationship between experimental variables and PRC function, but to instantiate our theories of neural function in a way that is designed to operate at scale

Keywords: Humanities and Sciences.
Psychology.
Advisor: Wagner Anthony David 
Yamins Daniel
Gardner Justin
McClelland James L.
Slow and fast atoms : modeling strong field effects on Yb for slowing and quantum imaging of magnetic fields

Known for the ultra-stable clock transition, ytterbium atoms are one of the leading candidates for atomic clocks and qubits for quantum computing. This thesis tells two untold stories of ytterbium atoms, slow and fast. The first half of the thesis covers an alternative laser slowing method using only the narrow 1S0-3P1 cooling transition that utilizes amplitude-modulated light to induce a series of stimulated emissions. This slowing method shows promise as a starting point for many cold-atom experiments. I present a numerical model of this process and how it can help engineer optical forces on ytterbium and other alkaline earth-like atoms. In the second half, I show how a combination of fast ytterbium atoms and a similar laser setup enables visual imaging of magnetic field gradients and contours. Based on Autler-Townes splitting and the Hanle effect, this unique magnetometer can measure both magnitude and direction of the magnetic fields based on understanding of dark striped patterns in the atomic fluorescence. Both aspects of this thesis bring to light the unique features of the narrow 1S0-3P1 transition in ytterbium with potential to advance quantum sensing.

Keywords: Humanities and Sciences.
Physics.
Advisor: Hollberg Leo
Hogan Jason
Simon Jon
So that it might be different for you : the intersection of adolescents/ce, legal culture, and sexual violence in young adult literature

This dissertation investigates the question of how--and to what end--law is represented in contemporary young adult literature ("YA Lit") and graphic narratives. With a focus on laws surrounding sexual violence, it investigates these works' unique expression of law as part of an adolescent legal culture--via the inclusion of legal actors, spaces, procedures, and the language of and references to laws themselves--to adolescent readers, who are not taught law in school, though remain subject to it. By contextualizing law as it relates to adolescents, and specifically adolescent sexual violence, I argue that these works mediate the transitional gap space of adolescence, filling a necessary educative niche by providing vital insight for young people into the complex legal structure governing the United States, particularly as it relates to individual and sexual rights. Thus, these works function not only as entertainment, but as important tools for necessary intergenerational conversations on sexual violence specifically, and law more generally. The result is an unprecedented space for young people to ask questions of and engage in conversations for which there currently is no clear, consistent space in the school or home. In this way, this dissertation argues, the counterpublics stemming from these YA Lit narratives provide a unique and unprecedented space for adolescents to ask tough questions, to have difficult conversations, to talk about what the issues of the day may mean, and to provide each other support and guidance, thereby encouraging an essential, broadscale, adolescent-focused space for deliberative democracy, critical citizenship, and participatory politics.

Keywords: Humanities and Sciences.
Modern Thought and Literature.
Advisor: Meyler Bernadette
Greif Mark
Wolf Jennifer Lynn
Social media sensitivity : probing heterogeneity across people, places, platforms, types of use and time

Recent research suggests that the relationship between social media use and wellbeing is heterogeneous and multifaceted. This dissertation examines five potential sources of this heterogeneity: user's psychological dispositions (e.g., tendency for psychological vulnerability), the physical and social context of use (e.g., where and around whom use is occurring), the platform that is being used (e.g., Instagram, YouTube), the type of use that is occurring (e.g., passive active) and time domains (e.g., hours, weeks and months). I deploy random-slope multilevel models to analyze two large corpuses of experience sampling data collected from young adults (N=3,233; Observations= 219,027). Results reveal small but persistent associations between social media use and wellbeing outcomes that are moderated by a range of variables. Psychologically vulnerable people tend to feel worse after using social media as compared to psychologically healthy people. Using social media in social locations and around others is associated with negative wellbeing outcomes, but these results differ across platforms. Both passive and active social media use is associated with increased wellbeing outcomes at the within-person level but decreased wellbeing outcomes at the between-person level. Lastly, some evidence suggests that social media's effects on wellbeing accumulate steadily over time instead of "drenching" users in the moments after use has occurred. Theoretically, my dissertation provides empirical support for three key theories -- Digital Wellbeing as a Dynamic Construct, Differential Susceptibility to Media Effects Model and The Complementarity-Interference Framework. More broadly, results from dissertation suggest that blanket legislation on social media companies might be less effective than promoting tools that bolsters' users agency over their social media use.

Keywords: Humanities and Sciences.
Communication.
Advisor: Harari Gabriella
Hancock Jeff
Matz Sandra C.
Ram Nilam
Reeves Byron
Social Network Optimization to Reduce Opinion Polarization Using a Graph Pooling Policy Network

In recent years there has been a substantial increase in sociopolitical polarization—it is clear that our society does not agree on issues in politics, healthcare, education, and beyond. Evidence of polarization in politics has been found in the increasingly partisan voting patterns of the members of Congress (Poole and Rosenthal (1984), Poole and Rosenthal (1991)) and widespread partisan sorting (Baldassarri and Gelman (2008)). Indeed, McCarty et al. (2016) claim via rigorous analysis that America is polarized in terms of political attitudes and beliefs.Drawing on the computational sociology approach presented by Macy and Willer (2002), this research operationalizes a sociotechnical perspective where agent-based modeling assists in simulating the social dynamics underpinning observed trends. The study incorporates the interplay of individual actors within the social network structure, moving beyond conventional statistical analyses to an agent-centered understanding of polarization phenomena.Empirical studies have argued that that homophily, i.e., greater interaction between like-minded individuals, results in polarization (Gilbert et al. (2009), Baron et al. (1996), Sunstein (2002)). Butas Dandekar et al. (2013) show, homophily alone, without biased assimilation, is not sufficient to polarize society. Indeed, research has shown that biases lead to more network homophily and, overtime, more homophily leads to actions that put more weight on biases and less weight on expert opinion (Hakobyan and Koulovatianos (2019)). This interplay between homophily plus confirmation and assimilation bias result in opinion polarization.Counterintuitively, the increase polarization has been accompanied by the growth of social media platforms where individuals are sharing more information more than ever before and are able to connect with others across a wider range of communities (Silver et al. (2019)). Despite the ability to connect with a greater diversity of people, individual’s beliefs have become more ideologically constrained and extreme in some areas (Kozlowski and Murphy (2021)). Research into social networks and the role of bias, as well as “echo chambers,” have indicated that the structure of social networks can make consensus harder to reach, potentially preventing exposure to other opinions,even despite increases in the total number of connections in a network. As such, modifications to asocial network through purposeful addition of edges may enable less polarization.

Keywords: sociopolitical polarization, polarization, computational sociology, social networks
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Thesis
Advisor: Willer Robb
The social structure of knowledge innovation, diffusion, and practice

In this dissertation, I ask how social structure--patterned regularity and configuration of social life--shape the production and dissemination of knowledge and practice in society. Just as social structures permeate social life at every conceivable level of analysis, from the macroscopic array of institutions and fields to the microscopic units of turns in everyday conversation, this dissertation spans a similarly diverse array of contexts such as political speeches, judicial decisions, quarterly earnings calls, and labor markets. I integrate recent methodological advances in natural language processing and deep learning with rich sociological theories to demonstrate the inseparability of social structure and knowledge

Keywords: Business.
Advisor: Goldberg Amir
McFarland Daniel (Daniel A.)
Rao Hayagreeva
Some algorithms and hardness results for the planted clique problem

One fascinating aspect of trying to solve modern high-dimensional statistical tasks is the rich interplay between the twin requirements of computational as well as statistical tractability. The planted clique problem is a prototypical task that exhibits this interplay. As such, it has become a testbed for theoretical computer scientists interested in developing tools to understand and predict the computational intractability of statistically feasible problems. In this thesis, we discuss some algorithmic and hardness results for the planted clique problem, particularly using the lens of sublinear-time algorithms, query complexity, and memory complexity.

Keywords: Engineering.
Electrical Engineering.
Advisor: Weissman Tsachy
Valiant Gregory
Wootters Mary
Some results in high dimensional statistics : iterative algorithms and regression with missing data

We study two problems at the interface between statistics and computation. In the first part of this thesis, we consider the problem of fitting a model to data by applying an iterative algorithm to perform empirical risk minimization. While the choice of iterative algorithm determines both the speed with which a fitted model is produced as well as the statistical quality of the produced model, the process of algorithm selection is often performed in a heuristic manner: via either expensive trial-and-error or appeal to (potentially) conservative worst case efficiency estimates. Motivated by this, we develop a framework---based on Gaussian comparison inequalities---to rigorously compare and contrast different iterative procedures to perform empirical risk minimization in an average case setting. In turn, we use this framework to demonstrate concrete separations in the convergence behavior of several iterative algorithms as well as to reveal some nonstandard convergence phenomena. In the second part of this thesis, we turn to studying parametric models with missing data in high dimensions. While this problem is well understood in the classical fixed dimension and infinite sample scaling, the situation changes drastically when the data is high dimensional. First, the high dimensional nature of the problem---which ensures that most samples contain missing entries---removes a complete case analysis from the statistician's toolbox. Second, the log-likelihood may be nonconcave in which case maximum likelihood estimation may prove computationally infeasible. Motivated by these issues, we study imputation-based methodology. In particular, we show that conditional mean imputation followed by a complete data method yields minimax optimal estimators in the linear model. We then show that the situation is quite different in the logistic model: in a stylized setting, conditional mean imputation can yield inconsistent estimators which nonetheless match the (Bayes) optimal prediction error

Keywords: Engineering.
Electrical Engineering.
Advisor: Montanari Andrea
Duchi John
Wootters Mary
Some variations of Khovanov homology for null homologous links in RP³

Asaeda, Przytycki and Sikora extended Khovanov homology to links in I-bundles over surface. In particular, their construction works for links in the real projective space RP³. In this thesis, we will present two variations of their construction for null homologous links in RP³. First, we introduce Khovanov-type homologies which depend on an extra algebraic input [alpha] = (V₀, V₁, f, g), consisting of two graded vectors spaces and two maps between them. With some specific choice of [alpha] = [alpha] [subscript APS], we recover a reduced version of the Asaeda-Przytycki-Sikora construction. With another choice of [alpha] = [alpha] [subscript HF], we construct a spectral sequence from our theory converging to the Heegaard Floer homology of the even branched double cover of RP³, extending the usual Ozsváth-Szabó spectral sequence for links in S³. Second, we introduce Bar-Natan homology for null homologous links in RP³ over the field of two elements. It is a deformation of the Asaeda-Przytycki-Sikora construction, in the sense that the associated graded complex with respect to the quantum grading gives their chain complex. We also define an s-invariant from this deformation following the same recipe as for links in S³, and establish certain genus bounds based on its properties

Keywords: Humanities and Sciences.
Mathematics.
Advisor: Manolescu Ciprian
Eliashberg Y.
Li Zhenkun (Mathematician)