VictorJuiz/thesis huggingface dataset:
Building an Intelligent Goal-setting Coach: Transformer-based Evaluation and Suggestion of Written Goals
Keywords: Edtech
Transformers
Goal Setting
Text
Thesis

The structured practice of writing learning goals has been shown to be beneficial for both cognitive and noncognitive skill development (Evans and Hardy, 2013; Ridley et al., 2010). Furthermore, these effects are increased when the goals follow the SMART framework, meaning they are Specific, Measurable, Attainable, Relevant, and Time-bound (Lawlor, 2012). However, the implementation of such programs in schools is challenged by teachers’ lack of availability to provide feedback (Rao, 2021). Therefore, the goal of this project is to use Natural Language Processing to automate two parts of the coaching process– evaluation and suggestion– to save teachers time when implementing a goal-setting program. Firstly, for evaluation, because attainability and relevancy vary based on the writer, I focus on the other three facets, and experiment with four models to evaluate written goals for whether they are Specific, Measurable, and/or Time-bound. Specifically, I experiment with the following systems: one that uses separate vanilla RNNs with linear classification heads for each task, one that uses a single vanilla RNN base that feeds into three task-specific output heads, a system with three separate BERT models with fine-tuned linear classification heads, and finally, a single fine-tuned BERT model base with three output heads, utilizing hard parameter sharing. From these experiments, I conclude that the single BERT base model with three output heads is most advantageous because of its performance and its parameter cost savings and reduced training time. Secondly, as a proof of concept for suggestion, I utilize GPT-3 with few-shot learning and demonstrate the ability for the model to adapt goals to make them Time-bound, with a success rate of 82%. Lastly, I contribute a novel dataset of 1,000 written personal goals, each labeled for whether they are Specific, Measurable, and/or Time-bound. These three pieces hopefully add to the development of automated goal-setting coaching, to expand possibilities for program implementation in schools.
Building cellular maps and dissecting gene regulation of the human body in health and disease
Keywords: Genetics.

The human adult intestinal system is a key and complex organ regulating overall health and homeostasis of the body. The small intestine and colon play many important roles, including promoting digestion, enabling immune surveillance, maintaining symbiotic relationships with microbiota, and supporting overall health. Many diseases, such as inflammatory bowel disease (IBD), affect millions of people worldwide and are a result of disruption of these key processes performed by the gut. Despite the increasing disease burden of gut-related illnesses, our understanding of intestinal organization, function and regulation remains relatively limited. Furthermore, our understanding of healthy gut function enables our study of and ability to treat aberrant states for example in IBD and colorectal cancer. In our three major studies, we map key cell compositions, gene regulatory networks, and spatial organization in both the healthy gut and in early colorectal cancer. In this dissertation, I describe the use of genomic technologies for these three areas of interest, starting with the healthy body and moving towards higher resolution single cell studies of the early onset of cancer. In Chapter 2, we build high resolution cellular maps of the healthy human intestine using single nuclear RNA, open chromatin, and spatial proteomic imaging technologies. Previous studies have mapped cell types using single cell RNA sequencing (scRNA-seq) and have cataloged cell types across the intestine. We extend this work by the spatial mapping of cells and proteins using CODEX (CO-Detection by indEXing) to characterize approximately 1.2 million cells spatially. This study fills major gaps in our existing knowledge of cell types and compositional changes throughout different regions of the intestinal tract and provides a healthy tissue dataset for the community to use to improve our broader understanding of gut pathologies and diseases. In Chapter 3, we investigate molecular changes that drive colorectal cancer formation and subsequent transformation using genomic, transcriptomic, proteomic, metabolomic and lipidomic datasets. In our study, we examine hundreds of heterogeneous precancerous polyps and adenocarcinomas from high-risk patients. Multiomic analyses revealed a dynamic choreography of thousands of molecular and cellular events that occur during early hyperplasia, dysplasia and cancer formation. In Chapter 4, we transition to characterizing cancer formation and progression at the single cell level. We generated single-cell chromatin accessibility profiles and single-nuclear transcriptomes from 1K--10K cells per sample for 48 polyps, 27 normal tissues, and 6 colorectal tumors (CRC) collected from patients with and without germline APC mutations. We observed that a large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from normal to CRC
Bullying & State Law: Examining Associations Between Anti-Bullying Statutes & School Safety Outcomes for Students
Keywords: Public Policy Program
Bullying
Cyberbullying
Anti-Bullying Laws
Bullying in schools > Law and legislation
Anti-Bullying Legal Factors
Bullying > Law and legislation
State Anti-Bullying Laws
State Bullying Laws
Bullying Protective Factors
YRBSS
Stanford University
Humanities and Sciences
Public Policy Program
Text
Thesis

Bullying has increasingly become recognized as a serious social issue that impacts youth well-being. It has been linked with PTSD and is shown to be a significant risk indicator for suicide attempt. As a result, many state legislatures have addressed this issue through some form of anti-bullying legislation. However, there is wide variability in terms of the types and strength of anti-bullying provisions that are included in each state’s statutes. This study analyzes state statutes for the presence and strength of various anti-bullying legal provisions. It then examines associations between these provisions and the probability of a high school student being bullied, cyberbullied, and missing school due to safety concerns. The study provides a snapshot of the landscape of state anti-bullying laws as of September 2018, as well as some evidence regarding the types of legal provisions that appear most effective in terms of protecting students from bullying and other detrimental outcomes. This study finds that a protective definition of bullying, inclusion of all types of bullying, staff reporting requirements, counseling requirements, prohibitions on retaliation, publicly available data, and training for school staff are significantly associated both with a decreased probability of a student being bullied as well as cyberbullied.
The business of living : socialism at the grassroots in Guangzhou, 1953-1989
Keywords: History.

This dissertation examines the transformation of China's socialist economy at the grassroots, from the implementation of state command in the early 1950s through the first decade of post-Mao reforms in the 1980s. It focuses on food and livelihoods—two of the most important themes of everyday life for ordinary people—in the city of Guangzhou. By examining the interface between local state and society in these two areas over the course of three decades, across the mythical divide of 1978 that marked the start of Reform and Opening, this dissertation seeks to shed light on the relationship between Mao-era command economy and post-Mao reforms, explore the origins and process of 1980s marketization, and understand the political valence and transformation of social contract that accompanied economic change. In doing so, this dissertation seeks to contribute a locally-grounded framework to our understanding of how the China of Mao became the China we know today
By and For Ourselves: Gay Men of Color and the Fight Against HIV/AIDS in San Francisco, 1970-1998
Keywords: Gay activists
AIDS (Disease)
HIV infections > Prevention
California > San Francisco
National Task Force on AIDS Prevention (NTFAP)
National Latino/a Lesbian and Gay Organization (LLEGO)
GAPA Community HIV Project (GCHP)
Black and White Men Together (BWMT)
African American gay men
Hispanic American gay men
Asian American gay men
Native American gay men
Filipino Task Force on AIDS
Comunidad Unida en Respuesta al SIDA (CURAS)
Pomo Afro Homos
Tongues Untied
Racism
Intersectionality (Sociology)
American Indian AIDS Institute (AIAI)
Gay Men of Color Consortium (GMOCC)
Love Like This Theater
Text
Thesis

In the 1980s and 1990s, HIV/AIDS represented an existential threat to the thriving gay community of San Francisco–and particularly for gay men of color, who were being diagnosed with the disease at higher rates than their white counterparts. As mainstream AIDS service organizations like the San Francisco AIDS Foundation—the first and largest in the city—came to serve a primarily white gay clientele, gay AIDS activists of color realized that their racial exclusion from the gay community affected the ability of such mainstream gay organizations to reach gay people of color. The growing threat of AIDS to queer communities of color and the lack of resources for them in these mainstream AIDS groups led to the formation of groups led by and designed for queer men of color in the mid-1980s. Taking into account how both their race and sexual orientation influenced their lives, gay people of color prioritized cultural competence—which emphasized considering the culture and experiences of the group that were trying to reach when developing HIV prevention materials. As the epidemic dragged into the 1990s, these activists created new interventions based in an “empowerment” model that often went beyond HIV prevention to bear witness to their unique experiences as both gay and nonwhite. In this thesis, I add to the nascent scholarship on the AIDS crisis by considering how the intersections of race/ethnicity and sexual orientation influenced the AIDS services that gay men of color created.
CALCOCO2, a positively selected gene in bats has differential effects on host susceptibility to bacterial infection
Keywords: Microbiology and Immunology.

Bats are the likely reservoirs for many zoonotic pathogens, including Nipah, Marburg, SARS, and Ebola viruses, that can be lethal to humans but cause little disease in bats. Meta-analysis of several genes under positive selection in 18 bat species identified CALCOCO2, an intracellular autophagy receptor that targets invading microbes for destruction. An antimicrobial function of CALCOCO2 during Salmonella Typhimurium infection has been characterized in human epithelial cell lines, leading to our investigation of its effect on infections in bat cells. The objective of this work is to characterize signatures of positive selection in Chiropteran CALCOCO2 sequences, determine its function in bat cell lines, and investigate molecular mechanisms by which it impacts microbial replication. Phylogenetic analyses predict an evolutionary history of CALCOCO2 that implies long-term selective pressure on this gene. In Chapter 2, I analyze the evolution of CALCOCO2 in bats, and determine which regions display signatures of interesting evolution. Our investigation of sequence conservation and divergence highlights hotspots of polymorphism localizing to CALCOCO2 domains and motifs that regulate xenophagy initiation and completion. Chapter 3 investigates the role of CALCOCO2 in the context of Salmonella infection in bats. Depletion of CALCOCO2 via si-RNA and CRISPR-generated CALCOCO2 knockouts cells reveal a surprising pro-bacterial role of CALCOCO2 in cells from two evolutionarily distant bat species. This pro-bacterial role is not due to a differential ability of bat CALCOCO2 to detect Salmonella, and is downstream of bacterial entry. In Chapter 4, I explore the molecular mechanism underlying this pro-bacterial effect by infecting WT and KO cell lines with Salmonella inducing different levels of membrane damage, and monitoring the kinetics of autophagic membrane recruitment to bacteria. Remarkably, CALCOCO2 contributes to early SCV integrity in both human and bat cell lines, and facilitates long-term association of autophagic membranes to Salmonella only in Egyptian fruit bat cell. Collectively, this work provides evidence for microbially-driven positive selection on regulation of selective autophagy in bats, and sheds light on a genetic signature that might enable bats to tolerate dangerous pathogens without succumbing to infection
Calling for the Vote: A Descriptive Analysis of Calls to the Election Protection Hotline During 2020
Keywords: Political Science
Bonica, Adam
Voting Rights Act of 1965 (United States)
Election law
Elections
Text
Thesis

In my thesis, I explore the present-day actualization of voting rights. After the dismantling of the preclearance requirement of the Voting Rights Act of 1965 (VRA) with the Supreme Court’s decision in Shelby County v. Holder (2013), what are the contemporary challenges to accessing the franchise, and do those challenges impact communities unevenly? Do historically marginalized communities experience increased burdens in exercising their rights? Is it more challenging for individuals to vote in counties that were previously subject to preclearance but no longer need approval to alter voting procedures? Utilizing a novel data source, Election Protection Hotline data, I analyze the nearly 200,000 reports of voting challenges and questions that the Lawyers’ Committee for Civil rights received during the calendar year of 2020. With a three-pronged research design, first, I offer a state-level descriptive investigation of calls to the Hotline in ten states that met a threshold based on Google Trends results. Second, I focus specifically on four states to compare county-level census demographic information from the American Communities Survey (ACS) and Hotline call volume by county relative to the population. Specifically, I use regression analysis to see how race, median household income, and unemployment rate affect call volume. Finally, I exploit the pre-Shelby County county-to- county variation in preclearance coverage in North Carolina to compare the frequency of calls in localities that were previously covered by preclearance with places that were not covered, investigating the consequences of the Shelby County majority opinion for voters. My results indicate that counties with a larger Black or African American population reported more voting challenges to the Election Protection Hotline. My research also shows that individuals reported more challenges voting in counties that are no longer constrained by the VRA, suggesting that preclearance remains a vital tool to protect minority voting rights and prevent democratic backsliding.
Caregiver and Child Health Under Lockdown: Impacts of the COVID-19 Pandemic on Caregiver Outcomes, Caregiving Behaviors, and Health Services Utilization in Rural China
Keywords: Rural China
Public health
COVID-19 (Disease)
Health services accessibility
Mental health
China
Infants > Health and hygiene
Infants > Development
Infants > Nutrition
Caregiver and Child Health
Maternal health services
Caregivers > Health and hygiene
Caregivers > Mental health
Text
Thesis

The COVID-19 pandemic has exacerbated societal and health inequities globally. In rural China, in particular, disparities in caregiver and child health already existed and may have shifted, in part due to the uniquely strict lockdown mandates. Caregiver outcomes, caregiving behaviors, and perinatal health services utilization seemingly changed immediately for the many under-resourced communities in rural China. By studying the outcomes and behaviors of families with children born before lockdowns and those with children born during lockdowns, I identify the profound impacts of the COVID-19 pandemic on communities in rural China. I find that paternal but not maternal migration significantly slowed during the pandemic and related lockdowns, which may have contributed to the significantly improved mental health outcomes in caregivers – most often mothers and grandmothers in rural China – through heightened social support. Caregiving behaviors of household and nutrition expenditures and infant feeding practices generally remained the same, other than a significant increase in spending on infant micronutrient supplements. Perinatal health services utilization suffered significantly in some areas, particularly in postnatal care, yet significantly improved in other areas, such as in aspects of prenatal care. This research has implications in public health initiatives and global health policies to improve quality of life for the most vulnerable populations. Contributing knowledge through academic research to the literature on caregiver and child health is essential to promoting equity and transforming lives.
Catalyst layer design and carbonate management for energy efficient electrochemical CO2 reduction to fuels and chemicals
Keywords: Chemistry.

Reducing anthropogenic CO2 emissions will be critical for mitigating the harmful effects of climate change on the environment. The ability to cost-effectively capture CO2 from point sources and utilize it as a chemical feedstock would allow several industrial processes to become carbon neutral. CO2 reduction (CO2R) powered by renewable electricity is a promising strategy for converting CO2 into valuable fuels and chemicals such as ethylene, ethanol, propanol, and acetate. To advance this technology for commercial applications, its operational costs must be reduced by improving energy and carbon efficiencies. Unfortunately, performing CO2R at low cell voltages at steady state is extremely challenging. Alkaline electrolytes minimize the cell voltage of CO2R, but CO2 rapidly reacts with OH-- to form (bi)carbonate (HCO3-- and CO32--), which drives the pH to 8 at steady state where the cell voltages are much higher. One approach to avoid (bi)carbonate formation is to use a two-stage electrolysis system, which consists of a CO2R step to generate CO, followed by CO reduction (COR) to multicarbon products in a separate electrolyzer. Solid oxide electrolysis cells can convert CO2 into high-purity CO streams at very high energy efficiency. Moreover, CO reacts with OH-- very slowly, which allows alkaline conditions to be maintained at steady state, thereby enabling low COR cell voltages. Both direct CO2R and the two-step process are being explored, but the energy efficiencies of both systems are still far too low. Improving cathode performance, developing ideas for managing (bi)carbonate formation, and constructing innovative cell designs will be necessary to advance these technologies towards commercialization. In this dissertation, we work towards improving the energy efficiency of CO2R and COR in several ways. We first provide a strategy for lowering the cathode overpotential for COR. We find that using a thick catalyst layer with percolated networks of hydrophobic pores and 5 µm Cu domains enables a high catalyst loading, which reduces cathode overpotentials. Such layers achieve a steady state COR cell voltage of 2.13 V at 200 mA cm--2, which is the lowest reported cell voltage for COR or CO2R at high current density. We then present an approach for mitigating CO2 uptake in direct CO2R by using highly concentrated (bi)carbonate electrolytes. This works towards maintaining alkaline conditions at steady state, which reduces operational cell voltages. Finally, we provide a platform for prototyping flow fields with 3D printing, which will be beneficial for scaling up CO2 and CO electrolyzers.
Causal aggregation of heterogeneous datasets and stabilization of feature selection procedures
Keywords: Statistics.

Variable selection is increasingly becoming a key step in any data analysis pipeline. Identifying true relationships between a large number of covariates and a response of interest is a challenging problem that often requires strong modeling assumptions. In this thesis we develop new variable selection methodologies in two different directions. Our contributions build on the recently developed knockoff procedure as well as the causal invariance framework. We show how to aggregate data originating from heterogeneous datasets generated through different experimental settings to estimate causal effects and identify the relevant covariates in a causal sense. Our methodology efficiently uses all available information, and we propose an extension to high dimensions where the number of samples available per environment is small. Finally, we develop a Causal Boosting algorithm that efficiently recovers non-linear causal response functions from multiple datasets where different subsets of covariates are randomized. On a different topic, we propose some improvements on the knockoff procedure by extending the scope of datasets where such methodology can be applied. Going beyond Gaussian distributions, we propose a Bayesian Network knockoff sampling procedure that fits a much larger class of distributions. Also, we identify sources of instability in the procedure and devise an entropy based multi-knockoff procedure to mitigate the variability of the selected set of variables induced by the randomized nature of the procedure
Causal and selective inference in complex statistical models
Keywords: Statistics.

During the past decades, advances in technology have led to a rapid growth of data in many fields. This abundance of data brings great opportunities as well as great challenges to data analysis: Datasets often measure hundreds of thousands of variables with complex dependence structures, which results in difficulties for statistical inference. For example, in a social network, each individual's behavior can be significantly influenced by the behavior of many others in complicated ways. Thus one cannot assume independence when analyzing the data. Similarly, in genetics, a trait could be associated with a large number of genetic variants, the relationship among which cannot be efficiently summarized by simple models. In both examples and many other real-world problems, datasets have dependence structures that standard statistical methods have difficulty dealing with. It is thus of interest to develop tools to conduct statistical inference under such complex dependence structures. This dissertation contributes to the toolbox of causal and selective inference in complex statistical models. One topic of interest is to develop methods to answer various causal questions in situations where individual subjects are interdependent. Chapter 2 and 3 develop statistical theory and methodology for treatment effect estimation under interference. Another interesting topic is to identify important dependency structures among many seemingly promising ones from a dataset. In settings where a specific variable is of scientific interest and many explanatory variables are potentially related to that variable, the goal is to build tools to select with confidence which of the variables are important for explaining the variable of interest. Chapter 4 and 5 tackle the problem of variable selection with false discovery rate control