VictorJuiz/thesis huggingface dataset:
Spatial ecology of human-wildlife interactions and conflicts

Highly mobile marine megafauna have complex life histories that are often distributed across habitats, regions, and jurisdictional boundaries. Therefore, these life histories, and their potential interactions with an increasingly saturated marine environment in the Anthropocene must be evaluated across relevant spatial and temporal scales. In this dissertation, I explore dimensions of biophysically-driven ecological patterns and resulting human-wildlife interactions. First, I review existing literature on land-dependent marine megafauna and identify commonalities in stressors related to climate change for this clade. I recommend three considerations for quantifying the vulnerability of a land-dependent population, including degree of specialization, intraspecies population-level differences and non-climate anthropogenic stressors, and discuss how the exclusion of these considerations may lead to less successful conservation outcomes. Next, I assess ship strike risk to blue whales (Balaenoptera musculus) in the Southern California Bight and find that it is beneficial to incorporate dynamic, high-resolution information on both anthropogenic activities and species distributions when evaluating the risk of a human-wildlife conflict. Results indicate that coarse or static data inputs can mask important variability in day-to-day co-occurrence. In the last two chapters, I turn to the Pacific blue marlin (Makaira nigricans) and Indo-Pacific sailfish (Istiophorus platypterus) populations in the Eastern Tropical Pacific Ocean as an empirical case study to quantify vertical and horizontal habitat use of two valuable ecological top predators and recreational target species. Blue marlin and sailfish showed similar vertical and horizontal niches but also evidence of habitat partitioning. In both of these studies, I evaluate how dynamic environmental features unique to this ecosystem relate to the variability in vertical and horizontal behavior and potentially influence the catchability of these species. Findings from these studies elucidate how regionally residential these two billfish species may be to this area of their stocks and indicate a need for cooperative management across jurisdictions in Central America. Taken holistically, this dissertation evidentiates the need to consider multiple spatial and temporal scales when surveying human-wildlife interactions in the marine environment and contributes to the development of conservation tools and strategies that can be used to manage vulnerable populations

Keywords: Biology.
Advisor: Crowder Larry B.
Hazen Elliott Lee
Abrahms Briana 
Micheli Fiorenza
Thompson Stuart (Professor of biology)
Spatial, temporal, and dietary niche partitioning of a bat community in northern California

Niche partitioning allows species with similar environmental and resource demands to coexist and is thus an ecological mechanism for producing and maintaining biodiversity. Bats, the second largest group of mammals in terms of species richness, often co-occur with other ecologically similar bat species, as is seen with the multiple insectivorous bat species that reside in the Bay Area. At Jasper Ridge Biological Preserve, ongoing research has used bat echolocation data to understand how the 16 resident bat species partition space and time. However, dietary niche partitioning has not been assessed in these species, and not all the Jasper Ridge species have been represented in previous studies. This study used two different methods to assess niche partitioning patterns among bat species at a local roosting site: 1) DNA sequencing of bat feces that were collected weekly from the roost, and 2) nightly acoustic recordings of ultrasonic bat calls from a bioacoustic recorder. DNA sequencing indicated that the two primary species using the roosting site were Tadarida brasiliensis and Eptesicus fuscus. Echolocation and dietary metabarcoding data suggested that sympatric T. brasiliensis and E. fuscus may be engaging in spatial niche partitioning with several other local bat species detected acoustically, but not observed at the roost. There was also evidence of dietary differences that may be related to subtle temporal partitioning, offering some support to the hypothesis that these co-occurring, ecologically similar species may foster coexistence through temporal and dietary niche partitioning. The dietary differences between the two species may indeed be larger than observed in this study, as analyses were conducted at the level of arthropod families rather than genera or species. Understanding interspecific relationships, between both bat species and their arthropod prey, allows us to predict how such interactions may change under different ecological conditions and to predict the impacts of climate change, habitat loss, and biodiversity loss on these local species. 

Keywords:  Department of Biology
Biology
Ecology
Niche (Ecology)
Bats > Ecology
Insects
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Thesis
Advisor: Hadly Elizabeth
Dirzo Rodolfo
Speaker-Specific Semantic Adaptation in Preschool-Aged Children

How flexible are children’s semantic representations? It is unknown whether they understand
that others may have semantic boundaries that are different from their own. Adults update their
expectations about how a speaker uses quantifiers after exposure to the speaker (Yildirim,
Degen, Tanenhaus, & Jaeger, 2016). Here, we explore whether this ability is present in
preschool-aged children. In Experiment 1, we show that preschoolers have adult-like
expectations about how a generic speaker would use the quantifiers some and many. They prefer
some for proportions less than 50% and many for proportions above 50%. In Experiment 2, forty
4 and 5-year-olds (mean = 4.6) were exposed to a speaker who was biased to either prefer using
some or many in a situation when describing a proportion of 50%. After exposure, participants
updated their expectations about the use of some and many, such that they aligned better with the
exposure speaker’s usage, suggesting that preschoolers are able to engage in semantic adaptation.
Experiment 3 replicates the results of Experiment 2 with sixty participants (mean = 4.8) while
reducing potential confounds. Experiment 4 investigates whether preschoolers can adapt to two
different speakers, one who is biased to use some and one who is biased to use many, at the same
time. We find that they do update their expectations about both speakers but that this is not a
long-lasting effect. Taken together, these results suggest that preschoolers engage in
speaker-specific adaptation and that they can use their prior exposure to a speaker’s utterances in
order to predict their future speech patterns, which demonstrates that children are attentive to
their conversational partners even at a very subtle level.

Keywords: Child development
Linguistics
Psychology
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Thesis
A spectrum apart : Chinese and Japanese American republicans and conservatives, 1920-1990

Although Asian Americans today are the fastest-growing racial group in the US electorate, historians of Asian American politics have generally neglected the electoral realm in favor of studying labor, culture, and revolutionary or anti-colonial diasporic and transnational activism. After all, many Asians were disenfranchised until race-based bans on their naturalization were lifted piece by piece from 1943 to 1952. Yet a small and influential cohort of Chinese and Japanese Americans in California with birthright citizenship set the tone of Asian American politics from the 1930s to 1970s. Drawing on archival collections, newspapers, and oral histories and interviews, this dissertation analyzes their experiences to offer the first history of Asian American electoral politics. It argues that Chinese and Japanese American voters carefully operated within the limits of acceptable political expression set by geopolitical dynamics and racial norms. They sought to soften the impacts of racial subordination by working within established political structures, framing their goals with conservative arguments, and cooperating with the Republicans who dominated California politics to carefully create piecemeal change without threatening the status quo. However, the constructions of race and ethnicity that Asian Americans developed to become legible political constituents also limited their potential arguments and allies, with pivotal implications for their participation in both liberal and conservative political movements. Together, race and ethnicity refracted the left-right spectrum of mainstream American politics into distinct experiences, interpretations, and choices. By integrating insights and questions from scholarship on modern conservatism, multiracial civil rights struggles, and transpacific Cold War-era transformations in the US racial order, this work underscores the diversity of Asian American political thought and experience.

Keywords: History.
Advisor: Chang Gordon H.
Burns Jennifer
Carson Clayborne
Spies in the Public Eye: A Comparative Community Analysis of Nuclear Sleuths and Government Intelligence Agencies

The advent of the internet and technological advancements in remote sensing, artificial intelligence, and machine learning have generated an explosion of open-source information. As the quantity of public data has grown, a new community of non-government open-source intelligence (NG OSINT) analysts has emerged, exploiting public information to provide insights on the most guarded of programs: the pursuit of nuclear weapons. Coined “nuclear sleuths,” the nuclear NG OSINT community democratizes secrets through analysis, redefining the divide between public knowledge and government intelligence. Despite operating in a high-stakes and influential environment, nuclear sleuths remain understudied. In recent years, news media has covered the findings of nuclear OSINT practitioners but not how or why they operate. Academic studies have compared nuclear sleuths to government intelligence agencies but have not yet offered comprehensive data about who operates in this space, what backgrounds they have, or what tools they use. This thesis seeks to fill the gap, unearthing how and why the nuclear NG OSINT community is different from U.S. government intelligence agencies. The thesis draws from a novel and thorough dataset of 66 individuals, 44 organizations, and 100 publications that systematically identifies and tracks the expertise, methods, and technologies leveraged in the nuclear sleuth community. The thesis also reviews government threat assessments, intelligence guidebooks, and declassified nuclear intelligence reports from 1966-1991. Interviews with 13 intelligence practitioners from both communities offer insights on perceptions of each group. The thesis finds that the nuclear sleuth community is diverse, collaborative, and responsive. However, nuclear NG OSINT analysts have limited intelligence training and informal peer-review processes, which create higher risks for the spread of misinformation. Conversely, government intelligence agencies maintain a highly structured and refined analytical environment, but bureaucratic processes often hinder internal innovation, technological experimentation, and interagency cooperation. The thesis offers 10 novel insights on the nuclear sleuth and government intelligence communities related to practitioners’ publication habits, technical assets, and motivations for research. Conclusively, the thesis calls for increased collaboration between the two communities and presents strategies to refine analytical methods in each group. The comparative analysis of non-government and government intelligence communities provides crucial understanding of and preparation for the future of 21st-century intelligence.

Keywords: Center for International Security and Cooperation
Open source intelligence
Nuclear intelligence
Nuclear sleuths
Community analysis and assessment
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Thesis
Advisor: Gottemoeller Rose
Zegart Amy
State expansion, social science, and schooling in the United Kingdom, 1800 to 1914

This dissertation is grounded in an empirical puzzle: at the beginning of the nineteenth century, few states compelled a national education through state schooling; yet by its end, states that schooled were nearly ubiquitous across North America and Western Europe. Why? Why did states with vastly different histories, material resources, and political traditions converge on this specific social welfare policy? I theorize that the ongoing development and institutionalization of the social sciences during the nineteenth century constituted a powerful, transnational force of cultural construction that made new kinds of state intervention newly conceivable. What I term social scientization, this epistemic movement elaborated state-centric functionalist social theory that centered on rationalized societal progress via state schooling; reified this theory with new varieties and volumes of social data and quantification; and diffused these theories translocally within and via state apparatuses as well as civil society organizations. The chapters of this chapter set out (Chapter 1) and test this argument with quantitative and computational techniques, highlighting scientization's role in expanding political notions of the schooling state (Chapter 2), in intensifying the rationalization of welfare and education policy discourse (Chapter 3), in diffusing functionalist theories of societal progress via state schooling in normative political debate (Chapter 4), and in progressively intensifying the state's intervention in education through formal legislative acts (Chapter 5). Together, this dissertation offers a computational historical-sociological case study of state expansion while demonstrating empirically how the expansive cultural content of the nascent nineteenth-century social sciences fundamentally and indelibly shaped the politics of education in the modern era

Keywords: Education.
Advisor: Bromley Patricia
Meyer John
McFarland Daniel
Stationary models for prophet inequality and matching problems

Individuals and companies are increasingly faced with the challenge of making decisions with only partial information about the future. This is only further complicated when decision makers care less about immediate gains than long-term outcomes. With this motivation, in this thesis, we study online algorithms, where inputs are revealed over time and must be responded to immediately and irrevocably. In particular, we consider two continuous-time, infinite time horizon counterparts of classic online matching problems, which we refer to as the stationary prophet inequality problem and the dynamic spatial matching problem. In both problems, we investigate the performance of simple and natural algorithms, with the main challenge being how to (approximately) characterize the stationary distributions under these algorithms. We take two different approaches. For the stationary prophet inequality problem, we use a linear program benchmark and techniques from queueing theory. For the dynamic spatial matching problem, we provide a novel reduction to an instance of a Coagulation-Fragmentation Process (CFP), which we indirectly analyze via a simpler CFP and recently developed techniques for the study of their equilibrium solutions

Advisor: Saberi Amin
Ashlagi Itai
Lo Irene (Management science professor)
Statistical and algorithmic approaches for health policy and fairness

Advances in statistics, econometrics, and computer science have the potential to facilitate data-driven decision making in improving the health of populations. However, adapting modern data science methods to eliminate health disparities remains challenging because interventions based singularly on health data do not fully address health issues borne from structural, upstream inequities. A multi-level approach that integrates social and health data to characterize how specific social systems perpetuate health inequities provides opportunities to create more tailored health and social policies. I will discuss examples of addressing health inequity through data science in three contexts: (1) mass incarceration in relationship to public health policies, (2) equity for structurally vulnerable populations in public health and social policies, and (3) methods for "small data" in precision health. An underlying theme is the importance of statistical methodology and study design informed by a holistic understanding of the interplay between social and health systems

Keywords: Medicine. Department of Biomedical Data Science
Advisor: Hastie Trevor
Andrews Jason Randolph
The statistics of RNA splicing in single cells

Although the amount of single-cell RNA-sequencing (scRNA-seq) data has exponentially increased in recent years, analysis of RNA splicing in these datasets remains virtually nonexistent, largely due to the sparsity and bias of the data. In this thesis, we introduce a new method of analyzing differential splicing at the single-cell level and apply this method to make new biological discoveries. We start by introducing the SpliZ, which quantifies the alternative splicing of each gene in a single number for each cell in the dataset. We verify the validity of the SpliZ through simulation, comparison with existing methods, and re-discovery of known true positives in the human lung. Next, we apply the SpliZ to over 200,000 cells from human, mouse, and mouse lemur to create a comprehensive atlas of cell-type-resolved alternative splicing, with experimental validation of two examples. We discover that unsupervised clustering of cells based only on the SpliZ scores of RPS24 and ATP5F1C accurately recapitulates division into stromal, immune, and epithelial compartments. Correlation of the SpliZ with developmental time reveals previously unknown conserved splicing changes throughout spermatogenesis. Finally, we apply the SpliZ to spatial transcriptomics data to discover spatially-resolved RNA splicing patterns in the mouse brain, which are more significantly localized than gene expression for Myl6 and Gng13. The SpliZ opens the door to widespread analysis of alternative splicing in scRNA-seq data

Advisor: Salzman Julia
Hastie Trevor
Sabatti Chiara
Stem cell and machine learning approaches for understanding heart field development

During embryogenesis, the heart is derived from two major progenitor populations known as the first and second heart fields that give rise to the left and right ventricles, respectively. While these cell lineages have been extensively studied in mice, the lack of access to early human embryonic tissue has largely limited the study of these cell populations to animal models. Here, we present a novel TBX5/MYL2 lineage tracing reporter system and machine learning prediction pipeline for elucidating the identity of heart field lineages during a human induced pluripotent stem cell (hiPSC) cardiac development. Using our lineage tracing reporter system, we reveal the unexpected predominance of FHF differentiation using a well published cardiac differentiation protocol. We conduct a detailed single cell RNA sequencing time course where we confirm the FHF differentiation trajectory of our hiPSC cardiac differentiations and establish an atlas of human left ventricular development. Moreover, we developed a machine learning algorithm, devCellPy, to allow for the automated annotation of single cell RNA-seq datasets across a complex hierarchy of annotation layers. Using our algorithm, we trained the algorithm on a large murine cardiac developmental cell atlas and apply the cardiac prediction algorithm to conduct a cross-species identification of hiPSC-derived cardiomyocytes. Concordant with our lineage tracing data, devCellPy predicted a predominance of left ventricular differentiation, effectively demonstrating the power of the algorithm at identifying human cell types using a murine embryonic reference dataset. Lastly, we applied our devCellPy cardiac prediction algorithm to hiPSC cardiomyocytes derived from patients with a single ventricle congenital heart disease known as Hypoplastic Left Heart Syndrome. Using our algorithm, we discovered a predominance of left ventricular differentiation and reveal impairments in contractile force generation and metabolic activity within the disease lines. In summary, our work provides two powerful new tools for the study heart field development and provides a transcriptional reference of human first heart field development

Keywords: Stem Cell Biology and Regenerative Medicine.
Advisor: Wu Sean F.
Mercola Mark
Rabinovitch Marlene
Storing analog data with an analog memory system

Data stored in the cloud or on mobile devices reside in physical memory systems with finite sizes. Today, huge amounts of analog data, e.g. images and videos, are first digitized and then algorithmically compressed (e.g., using the JPEG standard) to minimize the amount of physical storage required. However, the conventional approach to analog data storage is inefficient in accommodating the continuing exponential increase of data (most of the data are in analog form) in the era of artificial intelligence. Emerging non-volatile-memory technologies (e.g., phase change memory (PCM), resistive random access memory (RRAM)) provide the possibility to store information in an analog fashion to enhance memory use efficiency. This dissertation introduces a new concept of directly storing analog data in a compressed format into analog-valued memory. Taking a multi-disciplinary approach combining joint source channel coding (JSCC) from information theory, neural network, along with the use of emerging non-volatile memories that can directly store analog values as a set of analog electrical properties (e.g., resistances), we develop and demonstrate with experiments a novel image compression and storage scheme using analog-valued non-volatile memories (NVM), with PCM and RRAM arrays as examples. This scheme simultaneously delivers competitive performance for storing analog images compared with conventional image compression and storage with digital memory, resilience to the PCM and RRAM device technology non-idealities (e.g., defective cells, device variability, resistance drift, and relaxation), and adaptivity to different NVM characteristics. This work opens up new opportunities for addressing pressing demands for the storage of analog data

Keywords: Electrical Engineering.
Advisor: Wong Hon-Sum Philip
Pop Eric
Wong S. Simon
Strongly nonlinear axion dynamics

Axions and axion-like particles are well-motivated candidates for Beyond-the-Standard-Model (BSM) physics. While the present-day dynamics of axions are typically well approximated as nearly-free massive particles, their production in the early universe via the misalignment mechanism can allow them to access strong self-interactions. This thesis focuses on the consequences of these strong self-interactions for astrophysics and cosmology. In the first part of this thesis, we consider the dynamics of quasi-bound states called oscillons, and construct a new formalism to calculate their structure and properties. We use this formalism to construct a family of scalar field theories whose oscillons are cosmologically long-lived and can lead to present-day astrophysical signatures. The second part of this thesis focuses on coupled axion systems, and we show how the kinds of potentials that naturally arise in models of the axiverse can lead to a new kind of resonant energy transfer between axions. This resonance causes energy to flow from the axions with larger decay constants to those with smaller decay constants, generically enhancing direct detection signatures. Further, this resonance enhances density perturbations, leading to the formation of dense galactic substructure and oscillons. We explore the possible signatures of this resonance in direct detection experiments such as ADMX and DM Radio, as well as astrophysical signatures in astrometric and photometric probes of galactic substructure

Keywords: Physics.
Advisor: Dimopoulos Savas
Graham Peter (Peter Wickelgren)
Wagoner R. H. (Robert H.)