Application for Prediction of Heart Failure; the Next Step in Machine Learning for Healthcare

Heart failure (HF) is a serious medical condition affecting approximately 6.7 million U.S. adults and is expected to impact 8.5 million Americans by 2030 [1]. Heart failure is a complicated clinical ailment and characterizes the final course of numerous heart diseases [2]. This paper introduces a machine-learning-based application that utilizes Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and XGBoost models, implemented through the Python Flask framework, to predict HF risk using clinical data. The results indicate high model performance, with precision and recall metrics underscoring the application’s reliability in identifying at-risk patients. By providing real-time, accessible insights, this tool aims to enhance diagnostic accuracy and support early intervention, withparticular value for underserved populations. The study also discusses limitations related to data access, privacy concerns, and model generalizability, recommending future research to address these challenges for broader clinical adoption

The Theology of Home: Cultivating Faith and Belonging Through Community and Hospitality as a Reflection of God’s Presence in the Community and Church

This dissertation examines the essential human need for belonging and its theological significance in shaping faith, identity, and community. Drawing on biblical texts, historical theological perspectives, and contemporary ecclesiological discourse, this study explores the church as a spiritual home—a sacred space of belonging where relationships foster deeper engagement with God and one another. This study contends that the modern church is in decline, and to revitalize it, we must reclaim the ecclesial essence of home. Rather than relying on institutional structures or programming strategies, churches must prioritize relational engagement and radical hospitality and cultivate authentic communities. Organizations like Mission Waco exemplify this transformative approach, alleviating homelessness through the incarnational presence of Christ in intentional community and service. By integrating theological reflection with practical insights for church renewal, this dissertation contends gathering and hospitality are not merely components of the church’s mission but central to its identity. Faith communities flourish when they embody God’s love through radical welcome and genuine fellowship, inviting individuals to experience spiritual transformation and communal belonging. Ultimately, this study calls for a renewed ecclesiology that values relational depth over institutional formality, reclaiming the church as a living, welcoming home for all. While this study aims to develop a comprehensive theological vision of the church as a spiritual home, its primary focus is on the essence and characteristics of such a faith community rather than offering a detailed practical guide for implementation

Lobbying by Brief: Unveiling the Dominance of Amicus Lobbying in the Development of Business Law

This Article uncovers the pervasive and significant impact of business law amicus lobbying, a strategic tactic whereby lobby groups have commandeered the amicus curiae filing process in state courts to shape business law according to their interests. This Article makes three primary contributions to the literature. First, it presents the only comprehensive dataset of amicus curiae filings in business law cases. This hand-collected dataset encompasses nearly all business law amicus curiae filings from 2005 to 2022 in the key jurisdictions of New York, California, Delaware, Texas, and Nevada. Second, it reveals a striking empirical finding: lobby groups account for 67% of all amicus curiae filings in the dataset, with a high rate of success in persuading courts to adopt their positions. Finally, the Article provides a normative assessment of amicus lobbying in business law and proposes policy recommendations designed to ensure a more balanced representation of stakeholder interests. By shedding light on this understudied phenomenon, this Article aims to stimulate critical discourse on the intersection of lobbying, judicial decisionmaking, and business law formation. It offers valuable insights for scholars, practitioners, and policymakers engaged in the ongoing debate over the appropriate role and influence of interest groups in shaping legal doctrine

From Clusters to Frameworks: Synthesis, Engineering, and Application of Sub-2-Nanometer Nanoclusters and Microporous Covalent Organic Frameworks

In this dissertation, we have investigated the complex interplay of atomic composition, structural modifications in covalent organic frameworks (COFs), and atomic-level designs in bimetallic chiral nanoclusters (NCs). By synthesizing COFs and bimetallic NCs, we elucidated how these elements govern their exceptional catalytic, optical, and electronic properties. Our work demonstrates that precise atomic adjustments, tailored pore engineering in COFs, and the strategic use of chiral ligands in NCs enable fine-tuned reactivity and stability. These advancements were applied to enhance photocatalytic performance, optimize iodine adsorption, and facilitate asymmetric A3 coupling reactions, laying a robust foundation for practical applications and future innovations in materials science

Using Object Density to Modulate Tension Responses

This thesis investigates the connection between object density and player tension in video games. Expanding on Canny Yuan’s work, “Using Spatial Composition to Influence Player Tension”, the researcher introduced a quantitative approach to measuring room density and posits that increased navigable space can lower player tension. To test this hypothesis, the researcher developed a custom single-player level, “Veylmoor”, in The Elder Scrolls V: Skyrim. The level is composed of rooms with systematically varied spatial layouts and navigable areas, allowing for controlled analysis of spatial density. The researcher quantified room density using four methodologies implemented through custom C# scripts. The researcher also assessed player tension through heart rate data and a post-playtest survey, enabling a comprehensive evaluation of the proposed methodologies

Topology Optimization Based on Micropolar Elasticity and Enhanced by Machine Learning: Structure Generation and Material Design

This work presents a novel topology optimization (TO) framework that integrates the micropolar elasticity theory with machine learning (ML) techniques to design high-performance structures and metamaterials. Traditional TO approaches rooted in classical elasticity neglect microstructural effects such as size-dependent behaviors and microrotations, which limits their accuracy for advanced materials (e.g., composites and metamaterials). To address this limitation, a new TO model based on micropolar (Cosserat) elasticity is developed, which introduces the rotational degrees of freedom and the associated couple stresses to more accurately capture microstructure-dependent mechanical responses. The framework is further enhanced with ML algorithms – including feedforward neural networks (FFNN), convolutional neural networks (CNN), and generative adversarial networks (GAN) – to accelerate the optimization process. By training these models on intermediate designs from iterative TO, the ML-assisted approach can predict near-optimal material layouts with greatly reduced computational effort. Compared to conventional methods, the integrated approach achieves an 80–85% reduction in iteration count, about 80% faster convergence, and approximately 70% lower computational energy consumption, while maintaining a high level of accuracy (with a root-mean-square error ≤ 0.007). The proposed methodology is validated through both 2D and 3D structural examples under diverse loading conditions. Results show that incorporating micropolar parameters (such as a coupling coefficient and a characteristic length) into the TO significantly enhances structural stiffness – improvements of up to 18.5% are observed – by enabling better load distribution and increased bending resistance. For mechanical metamaterials, the framework optimizes periodic structures for target properties (e.g., bulk or shear modulus and micropolar coupling effects), with the ML models effectively capturing design trends under periodic boundary conditions. In case studies, the deep learning-based predictors (CNN and GAN) outperformed the FFNN in accurately generating spatially complex optimal topologies. Overall, this work bridges advanced continuum mechanics with data-driven optimization techniques, offering a robust tool for designing next-generation materials and lightweight structures in fields such as aerospace, automotive, and biomedical engineering. The findings demonstrate the potential of combining physics-based modeling with machine learning to efficiently solve high-resolution topology optimization problems that were previously computationally prohibitive

Commercial Development Utilizing Faith and Business Innovation

In the evolving landscape of business and commerce, the intersection of faith and business innovation has become a topic of debate, particularly in a world that increasingly values efficiency, scalability, and profit. This dissertation examines the role of spirituality in business leadership. We will explore how Christian values, servant leadership, and heart-mind coherence contribute to a more sustainable, ethical, and community-driven business model. Through the lens of my family’s business, Sam Moon Group, I will explore how faith-based leadership can coexist with success and serve as its very foundation. The early journey of Sam Moon Trading Company, from a small family-run retail business to a diversified real estate and hospitality enterprise, will be studied and analyzed. I hope to provide a meaningful model for others seeking to merge faith and commerce while maintaining ethical integrity and a commitment to the community

Rulemaking Behind Closed Doors: Governor Abbott’s Secret Rulemaking. Worse Yet, All State Agencies Are Colluding with the Governor

In 2019, the Texas Legislature granted the Governor new powers to review the rulemaking process for certain state agencies. Since then, the Governor has apparently extended this authority of review over the rulemaking process to more agencies than he was authorized to. Some journalists and scholars, including this Author, have attempted to access the proposals and comments submitted to the rulemaking process by the Governor’s Office—and yet the records are withheld by the Texas Attorney General under claimed exceptions to the Texas Public Information Act. Despite the Attorney General’s claims, this Author and others maintain that any records of these submissions to agencies’ rulemaking processes by the Governor should be publicly available as a matter of law. This Article lays out the recent history of the Governor’s “Secret Rulemaking Division,” and ultimately explains why, under the Texas Administrative Procedure Act, any and all comments, suggestions, or changes made by the Governor to state agencies’ rulemaking processes must be released as public information

The Role of Executive Functioning in the Suppression-Induced Forgetting of Reactivated Negative Memories

This study investigated the effectiveness of direct suppression in reducing negative versus neutral memories and examined whether these effects persisted over a 48-hour delay through memory reactivation and reconsolidation. Additionally, the role of executive functioning in moderating suppression-induced forgetting was examined to determine whether these effects depend on individual differences, as proposed by the executive deficit hypothesis. 142 participants participated in a 3-day memory reconsolidation paradigm that utilized the Think/No Think Task as an intervention to disrupt reconsolidation. Results indicated that while reactivated, neutral memories in the No-Think condition were reduced, negative memories remained resistant to this process. Contrary to expectations, executive functioning did not moderate these effects; however, exploratory analyses revealed that individuals with lower inhibitory control exhibited greater suppression effects for neutral memories and an unintentional faciliatory effect on negative memories when attempting to directly suppress reactivated memories. These findings offer preliminary support for direct suppression as a potential intervention to disrupt memory reconsolidation and suggest that individuals with lower inhibitory control may benefit more from such approaches; however, this may not be an effective intervention for negative emotional memories