Silence, Society and Self-hatred: Anti-semitic Female Characters in American Literature: 1863-1947

This dissertation examines anti-semitic female characters in American literature, and how that anti-semitism relates to each of the female characters in the works studied, differs from the male characters, and relates to the period in which it was written. The objective of this study is to investigate the intersectionality of anti-semitism and gender, to show that while female characters are anti-semitic they can be so in their own way, and are not only different from the male characters, but other female characters as well. By focusing on a few specific works I have shown that these characters are given compelling reasons why they are anti-semitic, regardless of wealth, income, occupation or education. This dissertation begins with a discussion of the limited scholarship already done on the subject of anti-semitic female characters in American literature and how existing scholarship focuses mainly on anti-semitic male characters, or anti- semitism in general. This includes the study of authorial intent in writing a novel whose theme is or includes anti-semitism, and why the subject is associated with the literary period in which it was written. The resulting analysis shows that anti-semitic female characters in American literature are just as compelling as male characters, if not more so, and allowing for the expansion of current scholarship and the study of anti-semitism in general

Diversity and Dynamics in Protest Movements: a Comprehensive Analysis of the Citizenship Amendment Act Protests in India

The dissertation analyzes how protester composition and diversity influence contentious political movement dynamics through large-N comparative analysis and case studies. It focuses on protest actions in India, particularly the Citizenship Amendment Act (2019) protest movement. It examines the diversity of participants, motivations, and tactics that characterized the CAA protests, and explores the factors that contributed to this campaign. The second chapter provides an overview of the theoretical and conceptual framework for understanding social movements, with a focus on the CAA protests. It discusses theories related to collective identity, regionalism, economic grievances, and protest strategies and offers a framework called regional identity- based theory of revolution to qualitatively analyze the diversity and dynamics within the CAA protests. The second chapter employs a comprehensive text analysis of over 3,000 English news articles covering the Citizenship Amendment Act (CAA) protests and the Farmers' protests in India. It uses topic modeling to map the underlying narratives, motivations, and fault lines within and across these two protest campaigns. The analysis aims to provide insights into the factors driving the unity and fragmentation of protesters, as well as the complex interplay of factors such as shared identities, grievances, leadership, and framing processes. The fourth chapter introduces a novel approach to measuring protest campaign fragmentation using Google Trends data. By utilizing Google Knowledge Graph, it identifies relevant search queries and topics related to specific protest campaigns. The study offers a behavior-based measure by providing a single score for the campaigns based on their unification and fragmentation. This approach aims to address the limitations of traditional methodologies and provide a scalable and comparable tool for analyzing the internal dynamics of social movements. The dissertation contributes to the literature on social movements and contentious politics by offering a contextualized understanding of protest dynamics in diverse societies across the world

Autonomous Navigation Using Active Visual-semantic SLAM

The use of robots has become increasingly prevalent in nearly every industry, with robots found in not only manufacturing and transport, but also in healthcare and the home. This trend has likewise been accompanied by a demand for greater robot autonomy and the capacity to perform complex tasks unguided. In order to be able to do this, robots require the ability to perceive entities within the environment not only geometrically, but also semantically, as what an object is will dictate how it should be interacted with. Autonomous operation also requires that a robot be able to perform simultaneous localization and mapping (SLAM) within potentially unknown environments. In this thesis, Robot Operating System is used to implement a system which allows a robot to explore a previously unknown environment using a map generated by semantic SLAM. By extracting information from the map, the robot can be directed towards different semantic class instances found within the environment, with new instances found using frontier-based exploration. A custom terrain costmap layer is also created to enable semantics-aware path planning. The efficacy of these contributions are then demonstrated through experiments in a simulated environment

Neural Mechanisms Underlying the Relationship Between Trait Mindfulness, Affect, and Cognitive Performance

Mindfulness is the ability of an individual to be aware of one’s internal and external experiences, moment-by-moment, with a specific attitude of curious, non-judgmental acceptance. Trait mindfulness refers to the dispositional ability of an individual to practice such awareness with a specific attitude of nonjudgment and acceptance in daily activities. There has been a growing recognition of the beneficial influence of mindfulness on mental health, both cognitive and emotional. It is prescribed for treating and managing disorders in the ill, and improving cognitive, academic and general well-being in the healthy. However, the mechanisms by which mindfulness brings about its salutary effects are not yet understood. In pursuit of understanding mindfulness mechanisms, the current studies examined the behavioral and neural processes associated with trait mindfulness during performance of affective attention tasks. Many psychological and neurocognitive mechanisms have been proposed to underlie the salutary benefits of mindfulness. Two commonly proposed mindfulness mechanisms are complete awareness to moment-by-moment experience, and acceptance. Importantly, behavioral evidence suggests that, in high mindful individuals, there are changes in emotion regulation processes across the time-course of experience that improve subsequent cognitive performance. Specifically, I hypothesized that complete attention to present-moment events initially enhance the emotional experience of an event affecting cognitive performance. This initial processing affords subsequent regulation of the enhanced emotional experience through acceptance strategies which then reduce the emotional influence allowing for better cognitive performance. Results from two behavioral studies provide support for this hypothesis. I then examined the neural bases of these processes using functional magnetic resonance imaging. Such emotional experience and its subsequent regulation would be expected to be reflected in brain activity. Emotional experience in relation to the self is characterized and measured by the extent of activity in emotion generation regions such as the amygdala and insula. The ability to then accept emotions as mere objects of mental experience and not as reflections or representations of the self (i.e., a shift in perspective) may involve higher top-down processing mediated by the prefrontal and cingulate cortices. In the fMRI study, I examined mindful emotion regulation processes, operationalized as specific neural changes occurring in emotion generation and regulation areas, across the duration of an emotional Stroop task. Specifically, I hypothesized that trait mindfulness-related Blood Oxygen Level Dependent (BOLD) signal in emotional generation areas would decrease across the duration of the task, while BOLD signal in emotion regulation areas would increase. Additionally, I hypothesized that such changes would predict both task-related and task- unrelated (i.e., academic and verbal intelligence) performance. Results partially supported my hypotheses and revealed complex time-course changes. Trait-mindfulness related increases and decreases in BOLD signal were observed in both emotion processing and regulation areas, specific to emotional demand. Trait-mindfulness related increases in Left Superior Frontal Gyrus (LSFG) predicted Reaction Time (RT) improvements across the later task runs for negative valence high arousal, compared to low arousal words. Further, trait mindfulness related decreases in Left Superior Medial Gyrus (LSMG) during earlier task runs, in response to negative low arousal compared to positive words, predicted higher academic performance (i.e., GPA). In summary, results partially supported the hypotheses that mindful emotion regulation processes comprise of reductions in emotion processing and increases in emotion regulation activity across the duration of the task. Specific changes in these processes also predicted task-related and task- unrelated performance, providing partial support to the idea that the neural changes indicating mindful awareness and acceptance are related in specific ways to emotional experience and behavioral performance

Calculated Re-vision: Kennedy, Johnson and African American Views of Their Civil Rights Legacies

Since the 1960s, there has been broad scholarly interest in the civil rights legacies of President John Kennedy and his successor, President Lyndon Johnson. Examinations have emerged from a wide range of disciplines, but it has been almost thirty years since the only book-length study of this subject appeared. Mark Stern’s Calculating Visions: Kennedy, Johnson and Civil Rights (1992) argued that neither Kennedy nor Johnson was particularly committed to civil rights when they joined forces on the Democratic Party ticket in 1960, and both were political moderates who eventually succumbed to the pressure applied by civil rights idealists. Stern’s analysis, with its heavy reliance on presidential administration records and former staff members’ memoirs and interviews, overlooked a key question. If both Kennedy and Johnson were viewed as political moderates, why have they been understood so differently by the African American communities most impacted by their civil rights policies? This dissertation addresses that question by focusing on African American responses to the civil rights strategies of Kennedy and Johnson. Mining African American oral histories, memoirs, letters, speeches, telegrams, essays, material culture, newspaper and magazine articles, polling data, song lyrics, visual art, and filmed portrayals, it traces how perceptions about these leaders’ civil rights records developed in the 1960s and continue to circulate today. The resulting analysis highlights the trajectory by which Kennedy emerged as a civil rights hero for black Americans while Johnson became a figure of relative contempt and mistrust. It explores the ways African Americans aligned themselves with Kennedy’s memory over Johnson’s reality as a form of black countermemory, drawing an invisible dividing line between the time many believed integrated, government-led, non-violent social change was possible, and when many no longer maintained that hope. A central component of this research deals with the manner by which John Kennedy has been mourned as a civil rights martyr within the black community. African Americans have imbued Kennedy’s image with a meaning that serves their ongoing, everyday struggle for racial equality, affording him a privileged presence in their homes. The portraits of Kennedy in black households operated as hidden transcripts that communicated his unique value to future generations. Despite Lyndon Johnson’s effort to enact historic civil rights legislation that many African Americans acknowledge went further than anything John Kennedy likely would have supported, Johnson never achieved sustained personal affection from black voters. Although African Americans were vital to Johnson’s landslide reelection victory in 1964, they continued to believe that his support for civil rights was motivated by political self-interest rather than a sincere commitment to racial equality. Representations of Johnson in recent civil rights films perpetuate a narrow view of him as a racist manipulator. The passage of fifty years warrants a calculated re-visioning of these two presidents’ civil rights legacies, and how they have been perceived by African Americans in their own time and since. This effort challenges long-held perceptions of the roles John Kennedy and Lyndon Johnson retain in both the Civil Rights Movement and in the African American imagination

Lyapunov-Based Nonlinear Control Strategies for Manipulation of Particles and Biomolecules Using Optical Tweezers

Tweezers-based nanorobots, optical tweezers in particular, are renowned for their exceptional precision, and among their biomedical applications are cellular manipulation, unzipping DNAs, and elongating polypeptide chains. This thesis introduces a series of Lyapunov-based feedback control frameworks that address both stability and controlled instability for biological manipulation, applied within the context of optical tweezers. At the core of this work are novel controllers that stabilize or destabilize specific molecular configurations, enabling fine manipulation of particles like polystyrene beads and tethered polymers under focused laser beams. Chapter 1 covers the foundational principles and surveys existing literature on the modeling and control of optical tweezers, emphasizing gaps in the stability and instability control of molecular systems. Chapter 2 presents a robust Control Lyapunov Function (CLF) approach, designed to stabilize spherical particles under optical trapping. By formulating a smooth, norm-bounded feedback controller, we achieve lateral stabilization despite external disturbances, using a real-time, static nonlinear programming (NLP) solution. Simulations verify the effectiveness of this CLF framework, even with significant initial displacements from the laser focus and under thermal forces modeled as a white Gaussian noise. Chapter 3 addresses controlled instability through a Control Chetaev Function (CCF) framework, specifically targeting protein unfolding applications. Linearization with respect to the control input facilitates the application of destabilizing universal controls for affine- in-control system dynamics. The resulting CCF-based norm-bounded feedback controller induces system instability by laterally extending the trapped DNA handle, thereby increasing the molecular extension and providing insights into protein denaturation and unfolding pathways. This controller is robust to stochastic thermal forces and optimized for real-time computational efficiency. These Lyapunov and Chetaev-based control designs collectively expand the capabilities of optical tweezers, advancing single-molecule manipulation under both stable and unstable conditions. These findings advance precision nanomanipulation, opening new avenues for exploring the molecular mechanics of protein unfolding and DNA elasticity

Advanced Approaches in NLP and Security: Addressing Catastrophic Forgetting Through Continual Learning and Resolving Data Imbalance in Semi-supervised Settings

In the rapidly evolving field of machine learning, particularly in applications demanding continual or sequential learning, the phenomenon of catastrophic forgetting poses a significant challenge. This issue occurs when a model, trained on new tasks, inadvertently loses information related to earlier learned tasks. Several innovative methodologies have been developed to address this problem without relying on traditional methods that often require additional memory or compromise privacy. One such approach is the introduction of calibration techniques that adjust both parameters and output logits to balance the preservation of old knowledge with the acquisition of new concepts, as exemplified in frameworks that incorporate Logits Calibration (LC) and Parameter Calibration (PC). These techniques ensure the retention of previously learned parameters while integrating new information, thereby maintaining performance across a variety of tasks, such as those in the General Language Understanding Evaluation (GLUE) benchmark. Another promising method involves the use of Energy-Based Models (EBMs), which associate an energy value with each input and allow the sampling of data points from previous tasks during new task training. This method has been adapted in different solutions, with the latter combining EBMs with Dynamic Prompt Tuning (DPT) to adaptively adjust prompt parameters for each task, efficiently generating training samples from past tasks and thus mitigating the effects of catastrophic forgetting. In the realm of cybersecurity, particularly in analyzing imbalanced, tabular data sets such as those encountered in industrial control systems and cybersecurity monitoring, semi- supervised learning techniques have been employed. These methods leverage a mix of labeled and unlabeled data and utilize novel data augmentation techniques triplet mixup to overcome the challenges posed by limited labeled data and the loss of contextual information. These approaches have demonstrated effectiveness in detecting vulnerabilities and attacks within cyber-physical systems, highlighting their potential in sectors where high stakes and high data imbalance are common. Across these diverse applications, the overarching goal remains consistent: to develop machine learning models capable of continual learning without sacrificing previously acquired knowledge. By harnessing innovative strategies such as parameter calibration, energy-based sampling, and semi-supervised learning with data augmentation, we are setting new benchmarks in the field, ensuring that models not only retain old knowledge but also seamlessly integrate new information, thereby paving the way for more robust, adaptive machine learning applications

Essays on Investigating the Revelation of Information Content

This dissertation consists of three essays on corporate finance. The first essay studies the differential information content on a firm’s fundamentals of top executives’ insider trades. It is well understood that a CEO and a CFO have played very different roles in achieving the goal of a firm. A CEO manages a firm largely from a strategic perspective, while a CFO focuses more on the tactical aspect. However, it is very difficult to assess their economic contributions separately because we only observe their joint action and overall firm performance on the firm level. As a novel approach, we analysis their insider trading activities and the firm’s following fundamentals changes in this study to understand their different roles in affecting the firm as a nature experiment. Our results suggests that a CEO have large impact on a firm’s long term persistent performance while a CFO affects the firm’s short-term cyclical performance. Moreover CEOs also tend to be more conservative in investment after additional purchase. This finding is consistent with the fact that they have different responsibilities in managing the firm. The second essay, included in Chapter 2, also deals with the topic of information content on executives’ insider trading activities. Instead of concentrating on purchases, we study whether the executive’s insider sales also reflect firm’s fundenmentals and compare the information content contained in CEOs’ and CFOs’ trades. This study highlights the nuanced differences in trading behaviors between CEOs and CFOs and underscores the importance of sales trades as indicators of future firm events and the firm’s fundamentals. These insights contribute to the broader understanding of insider trading dynamics and their implications for market efficiency. The third essay, included in Chapter 3, is ”The Real Effects of Cybersecurity Breaches on Firms and Managers’ Attentiveness”. This study explores the adverse impact of information breaches and the impact of managers’ attentiveness, measured by the time managers need to identify the breaches. We find that the time lag from when the breach is identified to when the announcement is made affects the market reaction and the firm’s operating performance. The time lag has a quadratic relationship with the cumulative abnormal return in the short term and with earnings in the long term. Also, the firms tend to react quickly to security breaches (14.5 days early) when they have a technical-related chief officer

Lighthouse: A Compendium of the Visual Development Process

Lighthouse: A Compendium of the Visual Development Process delineates an approach of developing a narrative for an animated film beyond the initial visual exploration. This paper establishes the current methodology of commercial productions within the customary phase of pre-production, where the project is grounded in visual research and preliminary conceptual design based on a screenplay or narrative brief. The author will demonstrate the strata of pre- production stages utilizing an original project created in 2018 to provide a broad overview of the process of taking the written word through the stages of research and design to create a visual framework for the remaining production phases to build upon. There will not be specific disclosure of tools used in the creation of this project unless they have direct relevance to the process. The focus remains primarily on the methodology of the execution of the thesis. Drawing from three decades of industry experience the author will also touch upon a possible landscape where the design process continues throughout the production pipeline and how the methodology may be valuable in assisting the evolution the project narrative

Digital Spill: Black Data and Meaning-making in New Social Media

Digital practitioners from Black Twitter are trying new social media platforms in the wake of Twitter’s platform collapse. In this thesis, I examine one of those platforms, SPILL, to understand the interface, practices, and beliefs and perceptions of the app as it functions in its introductory period. Toward that end, I utilize critical technocultural discourse analysis in this thesis. I argue that SPILL has inconsistent messaging and non-user perceptions that mark it as undesirable, which could spell its future demise. On the other hand, I argue SPILL is redeemable in its aims for a cultivated, safe experience and a popular live audio-visual option. However, I argue it is inconclusive whether SPILL can supplant the vital discursive publics of Black Twitter and the SPILL team should be careful of its many pitfalls