VictorJuiz/thesis huggingface dataset:
Morphology, stability, and kinetics at the lithium-electrolyte interface

Batteries incorporating a lithium metal anode can reach much higher energy densities than today's dominant lithium-ion battery chemistry, enabling the electrification of high-value transport applications. However, safety and cycle life issues persist due to heterogeneous, high surface area lithium deposits which form at the lithium-electrolyte interface through a complex set of electrochemical, mechanical, and transport-based processes. This dissertation describes work using both theoretical and simulation-based approaches toward better understanding and control of the evolution of this critical interface. First, we developed a coarse-grained Brownian dynamics simulation to model the evolution of lithium morphology during charging in the presence of a thin polymer coating. We created a three-dimensional simulation of lithium deposition incorporating a morphology-dependent electric potential field, a physical effect known to encourage heterogeneous, dendritic morphologies. In accord with experimental findings, we showed that a qualitatively viscoelastic polymer coating, which displays both mechanical strength and flowability, outperformed both purely liquid-like and maximally stiff, solid-like polymers. Next, we extended a field theoretical approach to calculate the free energy landscape for the lithium metal electrodeposition reaction at the electrode-electrolyte interface, accounting for the orientational and electronic polarization of a mixed-solvent electrolyte. Free energy curves for the initial and final states along a reaction coordinate allowed direct evaluation of the reorganization energy and activation free energy which govern the reaction kinetics. Finally, we developed the first linear stability analysis of lithium electrodeposition through a polymer electrolyte to include the coupled effects of ion transport, elastic mechanical response, and Marcus kinetics. This technique determines whether small-scale, randomized disturbances at the lithium-electrolyte interface will grow into largescale heterogeneous morphologies. Our model predicted a novel stability regime for polymer electrolytes with moderate shear modulus and high partial molar volume of lithium ions. This emphasized the underappreciated importance of ionic partial molar volume and can lead to the design of novel electrolyte materials for more stable lithium metal batteries. Control of the lithium-electrolyte interface is crucial for development of reliable, safe lithium metal batteries. In this dissertation, we present several studies which generate novel understanding of interfacial evolution and behavior during charging, which can serve as a guide for design of high-performance electrolytes and coatings for lithium metal batteries

Keywords: Engineering.
Chemical Engineering.
Advisor: Qin Jian (Professor of Chemical Engineering)
Bao Zhenan
Spakowitz Andrew James
The mosaic reef : leveraging genetic differences and local heat resilience for stewardship-based coral conservation

The health of coral reefs and their associated ecosystem services are threatened by compounding anthropogenic impacts including ocean acidification, overfishing, and ocean warming. Passive and active conservation strategies, such as marine protected areas (MPAs), coral aquaculture, and assisted migration, have been employed to protect these priceless ecosystems. Because these actions are relatively recent, guidance is still needed to inform decisions on where to place MPAs, which corals to use in restoration, and how to scale these practices most effectively and equitably. In this dissertation I address these knowledge gaps by examining genetic differences and local heat resilience of coral and their associated endosymbionts to help inform stewardship-centered coral reef conservation. I present visual bleaching scores as a reliable, efficient, and accessible means of assaying individual bleaching phenotype to identify corals for use in conservation and restoration (Chapter 1). I demonstrate that there is strong population structure over short spatial scales within five unique clades of the symbiont genus Cladocopium across the Palauan archipelago and that approximately 10% of corals shift their dominant symbiont clade post-transplantation to match that of their new environment (Chapter 2). In addition, I utilize a two-step, rapid bleaching assay paired with common garden tests to show that thermal tolerance is stable in 75% of heat tolerant colonies when they are moved to new locations (Chapter 3). Finally, I exemplify how and why ecosystem participants can be key players in scaling coral restoration globally and present a framework for scientists, managers, and practitioners to draw on when planning restoration initiatives (Chapter 4). Taken together, these chapters present acute heat stress tests and common garden experiments as methods to scale the identification of thermally tolerant coral holobionts for use in restoration globally and highlight the importance of centering stewardship in reef restoration practices

Keywords: Humanities and Sciences.
Biology.
Advisor: Crowder Larry B.
Palumbi Stephen R.
Hadly Elizabeth Anne
Ramos Jorge
Mosquitoes in a warming world : climate adaptation and its consequences for disease transmission

Vector-borne diseases cause over one sixth of all illness worldwide and are emerging and expanding at an increasing rate, due largely to rampant anthropogenic change. Of all human diseases, vector-borne disease systems are uniquely sensitive to environmental change as their transmission involves interactions between multiple species, including ectothermic arthropods. Recognizing this, the potential impacts of climate warming on vector-borne disease transmission have been extensively studied, leading to a general expectation that warming may shift disease burdens towards higher latitudes and altitudes. However, the potential responses of pathogen vectors to warming remain poorly understood -- a knowledge gap my dissertation seeks to fill. In chapter 1, I apply a theoretical framework from conservation biology to synthesize prior information on the potential for mosquito thermal adaptation. Finding that a lack of information on within-species variation in mosquito thermal tolerance currently hinders our understanding of this process, I helped establish Aedes sierrensis as a model system to investigate this empirically in chapter 2. I conduct a common garden experiment measuring Ae. sierrensis thermal tolerance across the species' range—the largest such experiment to date—finding clear, but limited, evidence of current thermal adaptation. Despite this evidence, I find that evolutionary adaptation alone will likely be insufficient to enable persistence under ongoing warming, as the thermal limits of Ae. sierrensis are already frequently exceeded across their distribution. Following on this finding, I investigate the thermal vulnerability of major vector species across their ranges in chapter 3. I find that, when accounting for the ability to access cooler microclimates, most vector species are currently 'thermally safe.' Contrary to the expectation that tropical species are the most vulnerable to climate warming, I find that thermal safety was high around the equator and lowest in the subtropics given the high thermal extremes experienced there. Overall, this dissertation draws on concepts from conservation biology, and combines laboratory experiments with mathematical and statistical modeling, to improve our understanding of the eco-evolutionary responses of mosquito species to warming

Keywords: Humanities and Sciences.
Biology.
Advisor: Mordecai Erin
Exposito-Alonso Moises
Schumer Molly
Mosquitoes in the Anthropocene: A Multi-Decade Study at Jasper Ridge Biological Preserve

Mosquitoes play a critical role in both human and nonhuman community health in the Anthropocene. Global shifts in temperature and precipitation will affect the distribution of many mosquito species and reshape disease risks posed to human population. Simultaneously, the ecosystem services mosquitoes provide have become critically visible as global change disrupts biological communities and their food webs. Understanding mosquito populations over time is critical for developing adaptive management frameworks for present and future community health of both humans and the ecosystems in which we reside.
In this study, I use a rich dataset of mosquito abundances, biocide applications, and climate from 2002 to 2022 in and around Jasper Ridge Biological Preserve to characterize the mosquito community, understand environmental drivers, and assess the impacts of mosquito control efforts. Five species dominate the diverse mosquito community of five genera comprising at least 18 species, which are log-normally distributed. The mosquito community is nested in space, though the relative abundance of species varies between water bodies. However, the community demonstrates significant flux over time, which may suggest competition or differential responses to environmental change. Several species demonstrate significantly different responses to environmental change both within and across the 20 years represented in this study. Though long-term population trends could not be assessed, species abundance patterns correlate to key environmental and physical variables, such as the timing of peak rainfall, temperature, and photoperiod.
No clear evidence indicated biocides impacted mosquitoes, and both increases and decreases in overall abundances were observed in response to control efforts. When mosquito population data were robust enough to detect statistical effects of biocide application, these analyses showed that a few species had a minor response to the application. However, most responses are equivocal.
Mosquito population dynamics at Jasper Ridge Biological Preserve present a unique lens with which to create adaptive frameworks that promote ecological integrity while prioritizing human health. As managers plan for the future of mosquito control in an era of global change, this research demonstrates the importance of statistically grounded effective and ecological approaches to mosquito control, with careful attention to the differences in species responses.

Keywords:  Department of Biology
California > Jasper Ridge Biological Preserve
Mosquitoes
Biology
Ecology
Text
Thesis
Advisor: Hadly Elizabeth
Dirzo Rodolfo
mother, daughter—Toward a Greater Understanding of Southeast Asian Refugee Experiences Across Generations

This paper explores relationships between Southeast Asian refugee families, with particular interests in the function of care on both a state and interpersonal level. By engaging with personal memories from myself, my mother, and my grandmother, my project affirms various means for care-building amongst multigenerational families.

Keywords: Southeast Asian American families
Generational trauma
Asian Americans
Memory
Oral history
Text
Thesis
Mother of demons and Dharma protector : tracing Hārītī's worship in East Asia

This dissertation is a study of the worship of the Buddhist goddess Hārītī in China and Japan from the fourth century CE to modern times. Hārītī was originally a child-eating demoness who roamed the Indian city of Rājagṛha with her army of demonic children, feasting on the flesh of babies. Eventually, the Buddha kidnapped her youngest son to make her realize how much suffering she had inflicted upon countless families. In this way, Hārītī was converted and became a Buddhist deity with many personas: a fertility goddess, a protector, a healer, and a wish-fulfilling deity. In my dissertation I explore the different aspects Hārītī can assume, the various forms of her worship, and what she meant, and still means, to different groups of people. Focusing on Hārītī's ambiguity and transgressive nature (as an ex-demoness), I argue that her worship in East Asia is the result of a constant process of domestication and accommodation. Because her past as a child-eating demoness is hard to accept, Buddhists have continuously transformed Hārītī to reconcile her demonic past with Buddhist ideas of what a goddess is supposed to be: on one hand, she was transformed into a decorous fertility deity; on the other hand, Buddhists drew on her demonic powers to protect their community. As a result, the goddess is, above anything else, a powerful protector who can watch over women, children, ill devotees, monastics practicing austerities, and many more

Keywords: Humanities and Sciences.
Religious Studies.
Advisor: Kieschnick John
Gentry James Duncan
Harrison Paul M. (Paul Maxwell)
Rambelli Fabio
Motives as the heart of ethics and agency

This work situates motives at the heart of a number of longstanding themes for ethics and agency. I begin by advancing the thesis that motives have intrinsic significance independent of outcomes: while one moral standard of rightness assesses acts according to their outcomes, a second standard assesses acts according to the motives underlying them. The dualism of being for what matters and bringing about what matters is central to ethics. I also argue that agents directly control their motives. Whereas many philosophers think that we can control our motives only indirectly, by acting on them, I hold to the contrary that this basic control over motives is what facilitates control over actions in the first place. My position implies that morality might place daunting demands on motivational capacities, an extreme example being that you ought to love your enemy. Given that your enemy may merit hate, however, the grounds for such love must lie in your own background experiences with unmerited love

Keywords: Humanities and Sciences.
Philosophy.
Advisor: Wenar Leif
Bobonich Christopher
Dannenberg Jorah
Hussain Nadeem J. Z.
Maguire Barry
MRI-driven evaluation of passive myocardial stiffness

Altered myocardial mechanical behavior is a component of maladaptive cardiac remodeling implicated in the etiology of heart failure. However, the specific underlying mechanisms and the extent to which the changes contribute to the progression of heart failure are poorly understood. Biophysical modeling of the heart has opened up significant possibilities for thoroughly investigating cardiac mechanics and could be a useful tool for further elucidating the mechanisms of cardiac dysfunction associated with heart failure. This thesis focuses on using a magnetic resonance imaging (MRI) approach combined with finite element modeling (FEM) to evaluate passive myocardial stiffness. This thesis contributes to the field in two specific ways: validating MRI-based passive myocardial stiffness estimation and using in vivo MRI to characterize healthy passive cardiac mechanics. In order to validate an approach to passive myocardial stiffness estimation that combines MRI and FEM, we developed an experimental setup which incorporates synthetic heart phantoms with realistic cardiac geometry, as well as tunable heart-like stiffness and MRI relaxation properties. Using the setup, we evaluated the degree of accuracy with which an MRI and FEM-based framework could identify the stiffness of heart phantoms of varying geometry and stiffness. Comparison of the simulated results to ground-truth stiffness values obtained independently through benchtop tensile testing, revealed errors that ranged from 1% to 6% across all models, thereby demonstrating the feasibility of highly accurate passive myocardial material stiffness estimation using MRI and FEM. Regarding characterizing healthy passive cardiac mechanics using in vivo MRI, we established a tractable pipeline for developing personalized cardiac computational mechanics models. The pipeline combines MRI methods capable of estimating high-resolution cardiac geometry, in vivo microstructure, dynamic motion and local deformation kinematics over the cardiac cycle. The in vivo passive myocardial stiffness estimation method was tested in healthy subjects in order to establish normal reference values for passive myocardial stiffness. Furthermore, we evaluated the sensitivity of passive mechanics to microstructural configuration. This kind of personalized biomechanical modeling, when extended to patients with heart failure, can provide new insights regarding the remodeling occurring in the disease. Such estimates of passive myocardial stiffness could help inform diagnosis and improve management of patients with a failing heart.

Keywords: Engineering.
Mechanical Engineering.
Advisor: Ennis Daniel B.
Kuhl Ellen
Levenston Marc Elliot
Multi-modal analyses for the identification of immune characteristics in viral infections and associated human disease

Viruses are ubiquitous pathogens responsible for a substantial disease burden globally. Refining our strategies in managing viral infections and their related pathologies requires us to have a comprehensive understanding of the host response in these diseases. Here, we identify immunological elements evoked in viral infections and associated host-virus interactions, focusing on two contrasting aspects: emerging viral infections, and lymphoid malignancies causally linked to the oncogenic Epstein-Barr virus (EBV), an ancient human pathogen. Our group has repeatedly shown that integrating heterogeneous data cohorts yields biological findings that are more consistently generalizable to downstream therapeutic applications. Firstly, we applied this integrated multi-cohort analysis framework in a disease context where our understanding is still lacking, as a tool for robust discovery to instruct further multi-omics studies for the elucidation of immune features characteristic to EBV(+) and EBV(-) B cell lymphomas. We identified gene signatures that implicate CD300a as a potential therapeutic target and provide evidence for the manipulation of the tumor microenvironment by EBV(+) B cell lymphomas. Secondly, in the context of emerging infections, we applied our multi-cohort analysis framework to identify conserved elements of the host response to viral infections across 16 different viral pathogens as a stepping stone for the development of a triage strategy to prioritize medical resources to patients more likely to develop severe disease outcomes in the event of another pandemic

Keywords: Medicine.
Advisor: Khatri Purvesh
Martinez Olivia
Bendall Sean
Krams Sheri Michele 
Robinson William (William Hewitt)
Multimode squeezing and quantum correlations of dissipative Kerr solitons in optical microresonators

Kerr soliton microcombs are phase-locked frequency combs generated in a microresonator via a third-order optical nonlinearity. Since their first demonstration, soliton microcombs have found applications in spectroscopy, LiDAR, communications, and convolutional processing. Experimental studies of soliton microcombs have also revealed a wealth of interesting nonlinear dynamics, and fundamental research on the classical dynamics continues to-date. This thesis is divided into two parts: (I) the modeling and experimental observation of quantum processes in multimode nonlinear photonics; and (II) the engineering of silicon carbide-on-insulator (SiCOI) integrated photonics for nonlinear and quantum technologies. Part I is general to all Kerr integrated photonics platforms. However, in experimental realizations, the choice of photonics platform matters, not only because of a variation among materials in the raw strength of the nonlinearity but also because of additional properties that influence device engineering and ultimate performance. The development of the SiCOI nonlinear photonics platform enabled the experimental quantum optics demonstrations of this thesis, and will be the focus of Part II.

Keywords: Humanities and Sciences.
Applied Physics.
Advisor: Vuckovic Jelena
Fejer Martin
Safavi-Naeini Amir
Multi-omics studies of aging and neurodegenerative disease in human cohorts

Aging is the number one risk factor for everything from heart disease to cancer to broken bones to neurodegeneration. The molecular details of how aging drives such diverse disease processes are still largely unknown. A critical limitation to such study in humans is the lack of reliable molecular biomarkers of aging in different organs. This is a particularly severe problem for the brain and the study of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, the two most common forms of neurodegeneration, where damage is thought to accumulate silently for many years before symptoms emerge. This dissertation is focused on the question of biomarkers for aging generally and on early biomarkers of neurodegenerative disease in particular. Here, I take a data-driven approach to the discovery of new biomarkers using biofluid proteomics, the quantitative analysis of thousands of proteins in plasma, cerebral spinal fluid, and urine. In Chapter 1, I give a general overview of the fields of biomarkers for aging and neurodegeneration, with a focus on data-driven and machine-learning approaches. Chapter 2 presents a machine-learning approach to the development of organ-specific biomarkers of aging using plasma proteomics from thousands of people across the adult lifespan. We create biomarkers for 11 different organs which can be used to predict future health and disease outcomes, and we do a deep dive into how the aging of different organs contributes to Alzheimer's disease onset, progression, and general cognitive decline. Chapter 3 presents the discovery and characterization of a new molecular biomarker of Parkinson's disease using cerebrospinal fluid, plasma, and urine proteomics. This biomarker, AADC, can predict disease onset before symptoms appear and can predict future disease progression, two urgently unmet needs in the field of Parkinson's disease research and clinical care. Together, these studies demonstrate the power of data-driven proteomics for biomarker research in aging and neurodegeneration, and provide analytical frameworks and large resources of human data for future study.

Keywords: Medicine.
Genetics.
Advisor: Montgomery Stephen
Wyss-Coray Anton
Jerby Livnat
Snyder Michael
Multi-task learning for object understanding

Understanding the physical and semantic properties of objects is a major goal of computer vision. These include shape, materials, weight, position, orientation, object class, and affordances. Given the multitude of properties involved, object understanding is an inherently multi-task problem. In this thesis, we present three contributions that advance object understanding by capitalizing on multi-task learning. First, we focus on estimating an object's shape and weight from its image, proposing a model that performs this prediction effectively. We also investigate and characterize human performance on this task through a human study. Next, we explore multi-task learning more directly, addressing object class, position, and orientation. We find that incorporating all tasks within a single multi-task network typically yields poor results. To overcome this limitation, we propose a method that strategically groups tasks together to be learned by multiple smaller models, achieving improved performance using the same compute resources. Finally, we present EMMa, a massive multi-modal object dataset comprising product listing text and images for nearly 3 million objects. EMMa includes labels for materials, price, weight, and category, among other attributes. We apply multi-task learning and expectation-maximization to fill in missing data, ensuring that every object possesses a label for each attribute. Moreover, we introduce smart-labeling, an innovative technique for rapidly adding custom properties to every object in EMMa with minimal human labeling effort. Taken together, these contributions effectively utilize multi-task learning to address a significant portion of the object understanding landscape, paving the way for more efficient and accurate computer vision models

Keywords: Engineering.
Advisor: Savarese Silvio
Wu Jiajun (Computer scientist)
Koyejo Oluwasanmi