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Capitola, the Newsboy, as a Story-Paper: Movement, Serialization, and the Rewriting of Domestic Space in E.D.E.N Southworth’s the Hidden Hand
Get PDFE.D.E.N. Southworth’s The Hidden Hand was immensely popular among nineteenth century American readers. These readers would have read the novel in a story-paper before it made its debut in novel form. Similar to a newspaper with the exception being that the content is fiction, readers would rush to purchase a new edition each week. In this thesis, I argue that both the content and print form of The Hidden Hand disrupt the separate gender spheres in nineteenth century America by encouraging a young girl’s movements in public spaces. What I call a separate separate gender sphere allows women and young girls, both in the story and those outside of it, to have the newfound agency to move in public spaces as they please. While the novel’s protagonist, Capitola, prompts more equality between the separate spheres, I argue that her independence also encourages other young girls to devise their own separate separate spheres that afford the many privileges of movement that men are accustomed to
The Impact of Green Credit Ratio on Return on Assets
Get PDFHow does the green credit ratio affect a bank return on assets? This study uses panel data from 2012 to 2019, covering 18 large banks in China, including 6 state-owned banks and major 12 important joint-stock and city commercial banks. I use regression models to measure the effect of the green credit ratio (GCR) on return on assets (ROA) and return on equity (ROE), and we focus on how bank ownership and fixed effects matters.
The results show that the effect of green credit ratio (GCR) on ROA depends on the model design. When bank fixed effects are included, green credit ratio (GCR) does not have a clear effect on ROA. But when fixed effects are not included, green credit ratio (GCR) has a positive and significant effect on ROA, especially in state-owned banks. On the other hand, green credit ratio (GCR) does not have a clear effect on ROE. These results suggest that green credit may not always help short-term profits, and future research should look at long-term effects
Tradespace Exploration With Statistical Modeling Techniques and Immersive Visual Representation in Virtual Environments
No full textStatistical modeling techniques combined with virtual reality (VR) visualization offer powerful new approaches to tradespace exploration in engineering design. The research presented addresses the challenge of analyzing and communicating insights from complex multidimensional datasets, particularly for autonomous ground vehicle systems.
Beginning with a review of statistical methods—including Principal Component Analysis (PCA), Analysis of Variance (ANOVA), and correlation analysis—the study examines their applications in tradespace exploration. Building on this foundation, three distinct visualization pathways connecting MATLAB data to virtual environments are developed and evaluated: VRML representation, STL conversion, and Blender integration. Each approach is assessed for its ability to maintain data integrity, support interactive exploration, and effectively communicate complex relationships.
Findings indicate that while VRML and STL approaches offer basic visualization capabilities, they have significant limitations in representing data relationships and supporting user interaction. The Blender implementation proves superior, providing enhanced visualization quality, richer interaction possibilities, and better preservation of both data structure and context, enabling more intuitive exploration of tradespace relationships.
The research contributes a methodological framework for transforming statistical analyses into immersive VR environments, carefully addressing data fidelity concerns throughout the visualization process. These findings provide practical insights for engineering design and systems engineering professionals looking to leverage immersive technologies for more effective decision-making
Environmental Concern and Its Relationship to Community Attachment and Satisfaction in Southern West Virginia
Get PDFExtractive industries, especially coal, in the Appalachia region, have contributed to severe environmental challenges. Over the past years, residents in these areas faced increased health risks and damage to natural landscapes, impacting on how connected they are attached to their communities and overall satisfaction with their quality of life. Previous studies have examined these issues but with a focus on amenity-rich rural west, low amenities, urban-suburban, tourist-dependent and Great Lakes regions; this study looks at southern West Virginia, a coal-dependent region. And as such fills that gap by exploring how environmental concerns - combined with a longstanding reliance on coal - shape community attachment and satisfaction. This study explores how environmental concerns affect people’s attachment to and satisfaction with their communities. Findings indicated that there was no statistically significant relationship between environmental concern and community attachment, while the relationship between environmental concern and community satisfaction was statistically significant. Long-term residents tend to develop strong attachments to their community. However, research is limited to some extent considering the demographic skew of its sample, which is predominantly white and elderly. It is recommended to combine environmental remediation with economic development to enhance community resilience and environmental sustainability in southern West Virginia. Also, efforts on staying alert to policies that prioritize environmental sustainability and community engagement
Developing Reduced Order Models for Gas Bubble Formation in Irradiated Metals Using Integrated Phase Field Modeling and Koopman Operator Theory
Get PDFIrradiation damage in materials is prevalent in nuclear components, posing significant risks in the safety and reliability of nuclear reactors. Phase field models offer a versatile framework for modeling irradiation damage in materials at mesoscales. Such high fidelity method has been used to model the formation of fission gas bubbles superlattice, a microstructure array occurs at certain irradiation conditions (dose, dose-rate, and temperature). To overcome the high computational cost of phase field modeling, Koopman operator theory is applied to create reduced order models, allowing for instantaneous simulations of fission gas bubble behaviors. These low fidelity models are integrated into machine learning methods to predict the formation window of gas bubble superlattice, and then validated by the high fidelity phase field models and experiments. In this thesis, phase field models of irradiation damage along with dynamic mode decomposition (DMD) method were developed in reducing the computational costs of high fidelity simulations
Graph Based Deep Reinforcement Learning Aided by Transformers for Multi-Agent Cooperation
Get PDFMission planning for a fleet of cooperative autonomous drones in applications that involve serving distributed target points, such as disaster response, environmental monitoring, and surveil- lance, is challenging, especially under partial observability, limited communication range, and uncertain environments. Traditional path-planning algorithms struggle in these scenarios, particu- larly when prior information is not available. To address these challenges, I propose an innovative framework that integrates Graph Neural Networks (GNNs), Deep Reinforcement Learning (DRL), and transformer-based mechanisms for enhanced multi-agent coordination and collective task ex- ecution. My approach leverages GNNs to model agent-agent and agent-goal interactions through adaptive graph construction, enabling efficient information aggregation and decision-making un- der constrained communication. A transformer-based message-passing mechanism, augmented with edge-feature-enhanced attention, captures complex interaction patterns, while a Double Deep Q-Network (Double DQN) with prioritized experience replay optimizes agent policies in partially observable environments. This integration is carefully designed to address specific requirements of multi-agent navigation, such as scalability, adaptability, and efficient task execution. Experi- mental results demonstrate superior performance, with 90% service provisioning and 100% grid coverage (node discovery), while reducing the average steps per episode to 200, compared to 600 for benchmark methods such as particle swarm optimization (PSO), greedy algorithms and DQN. My framework establishes a robust solution for cooperative Unmanned Aerial Vehicle (UAV) path planning in challenging operational scenarios
Untethered and Unraveled: Isolated Motherhood in the Liminal Stage
No full textIn examining Kate Chopin’s The Awakening alongside anthropologic theories of liminality, this paper examines the becoming women traverse as they transition between various social roles: girl, woman, mother. Edna is a maternal character attempting to unweave herself from her roles as mother and wife, and she finds this desire to go backwards to the freedom she experienced as a girl is proven to be impossible. The unmooring of her psyche and her subsequent suicide is indicative of a failure, not of her own accord, but in the social preparation and support she receives within her new identity. Social anthropologists further direct towards the concept of liminality as a result of extended periods of social isolation and rejection, and the term becomes necessary in the conversation of motherhood, as it notes these in-betweens as sites of tension, opening up conversations about the expectations of motherhood and how they are felt: socially, physically, and politically.
These social, physical and political implications of motherhood and female-driven community are complicated with the incorporation of creative nonfiction sections. The distance that is maintained in ethnographic and literary analysis is complicated by the experiential, and the intimacies of the mother-daughter relationship construct another in-between. The expectations of a mother under a Western patriarchal social structure are upheld to alienate and exploit, and yet, they have the power to maintain certain connections between women across various divides
Cloud-Native MUCAD for Design Reviews
No full textThis research explores the potential of a cloud-native multi-user computer-aided design (MUCAD) system to improve communication and efficiency during engineering design reviews and shorten the design timeline for military tools. First, a literature review is used to generate a list of thirty-five collaboration-oriented requirements that aim to ensure concurrency, annotations, heterogeneity, security, IP protection, version control, and viewing within a MUCAD system. A comparative evaluation of existing collaborative CAD system architectures, including cloud-native, cloud-enabled, and a single-user system with external file sharing, is conducted to determine how well each system architecture fulfills the generated collaboration-oriented requirements. Following this, a survey with thirty-six participants is used to evaluate the usefulness of the generated collaboration requirements and elicit personal experience and opinions from both industry and academic personnel regarding CAD, MUCAD, and design reviews. Eleven participants from the survey were involved in one-on-one interviews diving deeper into personal experiences and opinions regarding the topics. While participants generally expressed caution, many participants believed that real-time collaborative features could streamline feedback, accelerate the design process, and improve design work. Overall, the findings from this research indicate that a cloud-native MUCAD platform, equipped with the generated collaboration requirements and a user-friendly interface can significantly enhance distributed design reviews. This thesis recommends the implementation of cloud-native MUCAD systems within engineering design environments, particularly within government and defense contexts
Essential Components for a UAS Standard Operating Procedure Manual for State Departments of Transportation
No full textThe integration of Unmanned Aircraft Systems (UAS) within state Departments of Transportation (DOTs) has become increasingly essential for improving efficiency, safety, and regulatory compliance in transportation operations. However, the lack of a standardized approach to UAS program management has resulted in variability in policies, procedures, and implementation strategies across state agencies. This study examines how state DOTs incorporate the Association of Unscrewed Vehicle Systems International (AUVSI) Organizational Implementation Guide (OIG) 35 essential components into their UAS Standard Operating Procedures (SOPs) and identifies 13 additional components that address agency-specific operational, regulatory, and administrative needs. Through an analysis of publicly available SOPs and survey responses, the research explores areas of alignment, variation, and gaps in standardization among state UAS programs. Findings indicate that while FAA regulatory compliance components—such as Part 107 licensing, aircraft registration, and mission planning—are widely implemented, significant inconsistencies exist in areas such as training requirements, maintenance programs, safety protocols, and record-keeping policies. Additionally, state DOTs have adopted non-OIG components, including procurement policies, data security measures, inter-agency collaboration frameworks, and emergency response planning, to address evolving UAS applications. Given the unique regulatory and operational contexts of each state, the study recommends a flexible best-practices approach rather than rigid standardization, ensuring that all agencies maintain core safety and compliance principles while adapting their UAS programs to their specific needs. These findings contribute to the growing discourse on UAS governance and provide a foundation for enhancing policy frameworks, fostering inter-agency cooperation, and strengthening the overall effectiveness of UAS integration within state DOTs
Healthy Dietary Patterns’ Impact on Depressive Symptoms: A Meta-Analysis of Randomized Controlled Trials
Get PDFAs the search for innovative mental health treatments expands, dietary interventions have emerged as a promising approach for alleviating depressive symptoms. This thesis presents a meta-analysis of randomized controlled trials (RCTs) examining the efficacy of whole-of-diet nutritional interventions in reducing depression symptoms among adults. Grounded in Bronfenbrenner’s Bioecological Model and Engel’s Biopsychosocial Model, this study explores the intersection of biological, psychological, and social factors that influence mental health outcomes. A systematic review identified six eligible RCTs assessing the impact of healthy dietary patterns, including the Mediterranean diet and other plant-based interventions, on depression symptoms. A random-effects meta-analysis revealed a significant overall effect (Cohen’s d = -1.32, 95% CI: -2.11 to -0.52, p = 0.0011), indicating that dietary interventions are associated with large reductions in depressive symptoms. These findings highlight the potential of dietary interventions as clinically meaningful complementary strategies to traditional mental health treatments. The study contributes to growing evidence supporting nutrition-based approaches in psychiatric care and underscores the need for further research to refine dietary guidelines for mental health. Implications for clinical practice, public health policy, and culturally adaptive interventions will be discussed, emphasizing the importance of holistic and accessible approaches to mental health care