VictorJuiz/thesis huggingface dataset:
Ethics without moralism : an essay on agency, reason, and responsibility
Keywords: Humanities and Sciences.
Philosophy.

In this dissertation I appeal to a substantive moral ideal of autonomy to defend "constitutivism in ethics", i.e. the view that there are constitutive standards of action which inform the range of morally legitimate answers to the question of how one should live. I first argue that a minimally satisfactory theory of action must recognize the exercise of practical rationality to be constitutive of the exercise of agency, at least for agents who are persons. It follows that there are constitutive standards of action, namely the standards of practical rationality. From here I contextualize contemporary constitutivism within a larger philosophical tradition. According to what I call "the generalized guise of the good thesis", the exercise of person-guided agency constitutively involves the exercise of practical reason. Although it is articulated using different concepts than the previously-established claim - talk of "practical rationality" concerns foremost the guidance of action, but talk of "practical reason" concerns its justification -, to endorse the generalized guise of the good thesis is to hold the distinction to be shallow: both pick out what is fundamentally the same agential capacity, necessarily exercised whenever a person exercises her agency. Finally I argue that the antithesis of constitutivism, a view I call "separatism about agency and practical reason", embroils one in a dubious form of moralism quite at odds with the ideal of autonomy. In particular I argue that the separatist does not do enough to relate her agent-directed moral judgments to the agent's own practical rationality; in this way she repeats the mistake embedded within more concrete forms of moralizing, only at a higher level of abstraction.
Evolved and engineered molecular force sensors in the brain
Keywords: Engineering.
Chemical Engineering.

Mechanical force plays an integral role in biological processes ranging from tissue development to cancer metastasis, but the ways by which forces are transduced remain largely unknown. In particular, force has emerged as a potentially important driver of processes involved in the formation and function of the nervous system and brain. In the first portion of this work, I discuss two ways in which mechanical force can regulate important physiological processes in the brain at the molecular and cellular scales. First, I describe our efforts to characterize the mechanosensitivity of latrophilins, a class of adhesion G-protein coupled receptors (aGPCRs) that are implicated in multiple neuropsychiatric diseases and control excitatory synapse formation. These molecules were hypothesized to function as mechanosensors at the synapse, but the physiological plausibility of such a hypothesis was unknown. Using magnetic tweezers, we demonstrate that forces of 1-10 pN, well within the physiological range of forces, are sufficient to accelerate the rate of a key conformational change in the latrophilin-3 receptor by 10000-fold compared to the rate in the absence of force. Thus, mechanical force may be a driver of latrophilin signaling during synapse formation, suggesting a physiological mechanism by which aGPCRs may mediate mechanically induced signal transduction. As a second example, I discuss our work exploring changes in the force generation capabilities of neural stem cells in the aging brain. ATAC-seq of activated neural stem cells (aNSCs) from mouse brains reveals that chromatin accessibility is enhanced at loci associated with cell-substrate adhesion in older brains compared to younger brains. We use FRET-based force sensors to measure forces associated with cell-ECM adhesion in aNSCs and demonstrate that these adhesive forces are heightened in aNSCs from older brains. In the second portion of this work, I describe a new class of molecular tension sensors that we have engineered to increase the accessibility of force measurements in biological systems. These tension sensors are derived from the human muscle protein titin and can be used in fixed or live cells to provide either fluorescent or bioluminescent readout of the spatiotemporal dynamics of force transmission. We use magnetic tweezers to demonstrate that our sensor responds to forces > 2 pN and apply our sensor to living systems to visualize physiological, cell-generated adhesive forces. These results illustrate the utility of our tools for measuring molecular-scale forces in biological systems, which may facilitate a better understanding of mechanical forces in the brain and in biology more broadly. Taken together, these studies highlight several mechanisms that nature has evolved for force sensing in the brain and outline ways in which force sensors can be engineered to uncover new insights about mechanotransduction.
Exploration and analysis of a blind hydrogen system in western California, USA
Keywords: Earth and Planetary Sciences
Blind hydrogen system
Fairy circles
Serpentine
Ultramafic
Hydrogen
Basin Processes and Subsurface Modeling
Text
Thesis

This work presents a comprehensive exploration and analysis of a “blind hydrogen system” in Western California. Previous discoveries of natural hydrogen accumulations in various global locations suggest that hydrogen can form in geological settings, often indicated by surface features like "fairy circles". This study pioneers the concept of exploring for "blind hydrogen systems" - areas where geological configurations conducive to hydrogen formation exist, but without surface indications like fairy circles. The hypothesis is that certain geological settings conducive to hydrogen formation exist beyond areas marked by fairy circles. The research involves the assessment of several geological settings, including the presence of ultramafic rocks, aquifers, faults, and serpentinized rocks, to identify potential hydrogen systems. Field studies were conducted in Jasper Ridge Biological Preserve and Portola Valley, California, utilizing soil gas sampling to detect hydrogen presence. Laboratory analyses included measurements of hydrogen, carbon dioxide, methane, and other associated gasses. Results indicated hydrogen concentrations up to 20.32 ppmv in Jasper Ridge and 17.32 ppmv in Portola Valley, with significant seasonal and diurnal variations observed. The study also noted
anomalous concentrations of carbon dioxide and methane, suggesting possible abiotic origins. This work contributes to the understanding of natural hydrogen occurrence and proposes a methodical exploration approach for identifying 'blind hydrogen systems'. It demonstrates the potential for discovering natural hydrogen resources in areas without apparent surficial indicators and underscores the importance of developing systematic methodologies for their identification and exploration.
Exploring connections at the mammalian cell surface
Keywords: Medicine.
Chemical and Systems Biology.

Monoclonal antibodies have become powerful tools for biomedical research and cancer therapy. However, identifying the precise molecular targets of monoclonal antibodies can be challenging. This thesis leverages emerging techniques in proteomics and genome editing to elucidate the targets of two clinically relevant monoclonal antibodies. First, we re-evaluate putative RNA binding by galectin-3 using CRISPR-mediated gene knockouts and endogenous epitope tagging. We demonstrate that previously reported RNA interactions are likely an artifact resulting from cross-reactivity with the RNA-binding protein hnRNPA2B1. Our findings refute direct RNA binding by galectin-3 in HeLa, underscoring the need for stringent controls when characterizing antibody targets. Next, we uncover the molecular identity of the cryptic tumor-associated antigen TAG-72 after decades of uncertainty. We identify the mucin protein MUC2 as a dominant TAG-72 carrier in colon cancer cells. Further analysis defines TAG-72 as aberrantly glycosylated sialyl-Tn pattern on select mucin-like domains. By integrating cutting-edge proteomic and genomic techniques, this thesis provides molecular insight into two clinically important monoclonal antibody targets. Our strategy of leveraging emerging technologies to characterize antibody epitopes could be widely applied to clarify other enigmatic biomarker interactions relevant to medicine and biology.
For the Nations or Against the Nations: Wang Jingwei’s and Kawashima Yoshiko’s Rationales for Collaborating with Japan
Keywords:  Stanford Global Studies
Collaboration
Sino-Japanese War (1937-1945)
Wang, Jingwei, 1883-1944
Kawashima, Yoshiko, 1906?-1948
Resistance
Historiography
Traitor
Nationalism
Transnationalism
Text
Thesis

Traditional mainland Chinese historiography emphasizes Japan’s brutality during World War II and utilizes the “myth of resistance” to attribute political legitimacy to the Chinese Communist government for defeating the Japanese invading forces during the Second Sino-Japanese War (1931–1945). As indicated by the terminology used in China to refer to the conflict, the “War of Resistance against Japanese Aggression,” the prevailing narrative insists that the only acceptable response to Japan was resistance. Collaboration with Japan, viewed as an act of moral failure, is condemned, as collaborators witnessed Japanese atrocities yet chose to assist Japan in exploiting their compatriots. In China, collaborators are labeled as hanjian (traitors to the Han nation) or maiguozei (thieves who sell out their country), implying that they supported Japan in exchange for personal gain at the expense of the Chinese nation’s existence. Through the examination of two case studies of Chinese collaborators—Wang Jingwei (1883–1944) and Kawashima Yoshiko (1906?–1948)—this thesis argues that collaboration and nationalism were not necessarily mutually exclusive. Contrary to being traitors to their nation, they espoused nationalism and even cited it as their rationale to collaborate with Japan.
From rags to riches : cell-free RNA analysis for non-invasive cancer detection and characterization
Keywords: Medicine.

Cell-free RNA (cfRNA) analysis could allow non-invasive tumor gene expression profiling and monitoring of cancers. Here, we describe RARE-Seq (Random priming & Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing), a novel cfRNA profiling platform optimized for the simultaneous noninvasive detection of tissue-derived transcripts and associated somatic mutations. We show that platelet contamination can substantially confound cfRNA analyses and describe a framework to overcome it. In analytical validations, we find RARE-Seq to be ~50-fold more sensitive for detecting tumor-derived transcriptomes than whole transcriptome strategies, corresponding to a limit of detection of 0.05%. To explore the clinical utility of RARE-Seq, we profiled 269 samples from 201 individuals with cancer or non-malignant conditions and controls. Detection of non-small cell lung cancer (NSCLC) expression signatures in cfRNA increased with stage, ranging from 40% in stage I to 87% in stage IV, with driver somatic mutations detectable in cfRNA from 44% of stage IV patients. When applied to EGFR mutant NSCLC patients who developed resistance to tyrosine kinase inhibitors, RARE-Seq detected both histologic transformation and mutation-based resistance mechanisms. Furthermore, RARE-Seq detected other solid tumor types and identified tissue of origin with high accuracy. Lastly, we demonstrate the potential utility of RARE-Seq for assessing benign pulmonary conditions and tracking response to mRNA vaccines. Together, these results highlight the potential value of ultrasensitive cfRNA analysis and provide proof-of-concept for multiple potential clinical applications.
From satellites to stomata : measuring and modeling vegetation responses to water stress at ecosystem scale
Keywords: Sustainability.
Earth System Science.

The response of plants to water stress is a first-order control on the water and carbon cycles, and plays a key role in wildfire, crop productivity, and forest mortality. While water stress response has been studied extensively in individual plants, ecosystem-scale data and models are largely missing, limiting our ability to understand plant water stress effects at large spatial scales. This dissertation helps address that gap. In Chapter 2, I present the first field experiment directly testing the sensitivity of microwave radiometry (a type of remote sensing) to plant water potential in a forest. I show that vegetation optical depth derived from radiometry mirrors diurnal and seasonal changes in tree leaf water potential. In Chapter 3, I use a simulation experiment to investigate how plant traits describing water stress response could be estimated with microwave radiometry from satellites in various orbits combined with a land surface model. Encouragingly, using two satellites similar to those already in Sun-synchronous orbits yields similar accuracy to using a geostationary satellite observing at all hours of the day, which has been proposed but would be much more expensive in practice. In Chapter 4, I focus on one key mechanism of water stress: the closing and opening of stomata on plant leaves. I introduce a new model of stomatal response to water stress, I empirically estimate the time scales that stomatal responses to water stress appear to be optimized for in a range of ecosystems, and I relate those time scales to ecosystem climate characteristics. Overall, the results presented in my dissertation can help see the forest for the trees - that is, help understand how water stress affects entire ecosystems. In the future, this work could be extended to predict vegetation responses to the increased stresses of climate change and identify hot spots of vulnerability or resilience, among other applications.
The genetic manipulation of non-model flatworms and its applications
Keywords: Engineering.
Bioengineering.

Regeneration is a dynamic biological process that allows organisms to restore lost or injured tissues. Among flatworms, whole-body regeneration is common and has been studied extensively in the planarian Schmidtea mediterranea. However, despite interest in understanding their regenerative capacities, genetic manipulations and live imaging remain challenging. Here, I discuss advances made in the genetic manipulation and live imaging of two highly regenerative flatworm systems, Schmidtea mediterranea and Macrostomum lignano. First, I describe how we developed a novel method of transient mRNA-based expression in S. mediterranea. By leveraging nanostraws, an array of minuscule hypodermic needles, to deliver mRNA encoding nanoluciferase, an extremely bright luminescent enzyme, we observed the first instance of transgene expression in planarian cells. With a positive control for delivery, we identified additional chemical-based transfection methods that functioned both in vitro and in vivo. Using this, we identified post-transcriptional regulators of gene expression and explored sites of translation initiation using synthetic mRNAs. Finally, we constructed a specialized microscope capable of detecting the faint signals emitted by luminescing cells, enabling the quantification of transfection kinetics and permitting live imaging of animals transfected in vivo, thus paving the way for future studies dedicated towards developing longer-term DNA-based expression. Second, I introduce a comprehensive toolkit for live imaging of whole-body regeneration in the flatworm Macrostomum lignano, including a high throughput cloning pipeline, a refined injection protocol, and several advanced microscopy techniques. By driving tissue-specific reporter expression, we examine how various structures regenerate. Using a genetically encoded toxin, we ablate specific cell types to study their functions during regeneration. Through a custom luminescence/fluorescence microscope, we monitor the nervous system after cellular ablation and find it necessary for wound healing post-injury. Finally, we built a tracking microscope to continuously image freely moving animals for over a week, quantifying kinetics of wound healing, nerve cord repair, body regeneration, growth, and behavioral recovery. Notably, our findings suggest that nerve cord reconnection operates independently from primary body axis re-specification and other downstream processes of regeneration. Together, these results demonstrate how expanding the reach of our technological tools to non-model organisms can reveal new insights into their unique biology.
Greenhouse gas detection in the energy system : an integration of remote sensing and GIS database
Keywords: Sustainability.
Energy Resources Engineering.

The oil and gas (O&G) system significantly contributes to global anthropogenic greenhouse gas emissions (GHGs). The rapid development of remote sensing technologies enables direct measuring of point-source GHGs within the O&G system. These technologies, known as "top-down" methods, demonstrated their capabilities in measuring methane, carbon dioxide, and gas flaring by collecting radiance in the shortwave infrared using airborne or spaceborne remote sensors. This study aims to enhance our understanding of GHGs in the O&G system using remote sensing and geographic information system (GIS) techniques. We first estimated field-level gas flaring volumes using the satellite gas flaring data and a global O&G field GIS database. We then introduced an improved method for detecting and quantifying methane emissions based on Sentinel-2 satellite imagery. Finally, we applied imaging spectroscopy methods to measure carbon dioxide emissions within the liquefied natural gas (LNG) supply chain, with a particular focus on LNG terminals.
Higher-order approximation manifolds for more efficient nonlinear projection-based model order reduction
Keywords: Engineering.
Mechanical Engineering.

Solving large-scale parameterized dynamical systems, which may be obtained through, for example, the discretization of partial differential equations, is foundationally important to many fields, including engineering. Oftentimes, these high-dimensional models are expensive to evaluate due, in part, to their large size; this expense may be exacerbated by repeated evaluations in a large-dimensional parameter space. Projection-based model order reduction is a framework that allows us to solve these high-dimensional models at a much lower cost in terms of computational resources. This is accomplished by collecting prior solutions associated with different parameter values obtained by exercising the high-dimensional model and forming a lower-dimensional subspace. Using this subspace, we can compute a new solution associated with an unsampled parameter value at (ideally) a much lower cost. This computational efficiency has significant implications for applications in simulation-driven design, optimal control, and uncertainty quantification, among others, all of which would be impractical, if not impossible, for truly large-scale problems without resorting to some form of surrogate modeling. In practice, however, projection-based reduced order models sometimes struggle to achieve this level of performance in problems that exhibit the well-known Kolmogorov barrier as is often encountered in first-order hyperbolic partial differential equations, e.g., Navier-Stokes equations. This dissertation presents dimension reduction techniques, the problem of the Kolmogorov barrier, why it remains a challenge for model reduction today, and discusses methods to solve it. Among these methods are two novel approaches presented in this dissertation: a data-driven quadratic approximation manifold as well as an arbitrarily nonlinear approximation manifold using artificial neural networks. With no sacrifice in accuracy, both achieve an order of magnitude improvement in wall clock time compared to the current state-of-the-art in projection-based model order reduction for industrial-grade flow problems.
Impact of climate variability on landslide hazard in the western United States
Keywords: Sustainability.
Earth System Science.

Landslides broadly include debris flows, rock falls, avalanches, mudslides, and any other down-gradient movement of soil, rock, or debris under the direct influence of gravity. Although landslides occur over a broad range of lithologies, climatologies, hydrological regimes, and land use types, the majority are caused by precipitation. However, for most precipitation-triggered landslides, other complex atmospheric, surface, and subsurface conditions also play a role in predisposing a slope to landslides by increasing the effects of down-gradient forces and/or reducing the strength of the underlying slope. While there is "high confidence" that climate change will affect landslide hazard in some regions, several limitations persist in attributing the unique influence of a climate variable — like precipitation — to a given inventory of landslides. Key challenges broadly include: the short length of the landslide record, geographic reporting bias, and the complexity of the physical system. This dissertation develops strategies for overcoming these attribution challenges, while enhancing fundamental understanding of landslide response climate variability. Chapter 1 applies panel regression with fixed effects to quantify the impact of daily, ten-day, and thirty-day precipitation accumulation on landslide hazard in urbanized and non-urbanized areas. Chapter 2 evaluates the effect of wildfire severity on precipitation-triggered landslide hazard across the western United States. In addition to developing empirical frameworks for analyzing causal relationships between land use, climate variability, and landslides, the chapters enhance fundamental understanding of landslide response to climate variability.
Improving access to untranscribed speech corpora using AI
Keywords: Humanities and Sciences.
Linguistics.

How easily speech corpora can be indexed and searched has a direct impact on how effectively its contents can be used by many interested parties — from linguists, to language teachers, to community members. As transcribing speech is much more time consuming than recording it, large parts of speech corpora typically remain untranscribed, making it difficult to index and search these sub-parts. While searchable transcriptions can be automatically derived using a speech-to-text system for major languages like English, such technologies are typically unavailable for smaller languages, especially those typical in language documentation work. For documentation projects, this difficulty creates a bottleneck for creating language learning materials for language revitalisation and maintenance as well as linguistic analyses. In this dissertation, I propose four approaches to widen this bottleneck to enable some form of search or indexing, or accelerate the time-consuming process of transcription. Each chapter addresses a common but distinct scenario within language documentation projects according to the types and amounts of available data. For each scenario, I propose a context-appropriate, data-efficient solution that leverages AI speech models as well as external resources where appropriate.