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America’s Social Disconnection Problem: Rebuilding Social Capital Within the Framework of Liberal Neutrality
No full textThis thesis explores the decline of social capital in the United States, its implications for society, and the compatibility of social capital-promoting policies with the principles of liberal neutrality. It begins by defining social capital through Robert Putnam\u27s concepts of bonding and bridging social capital and highlighting its significance for individual well-being, community efficiency, and democratic governance. The research then examines the historical decline in social capital, driven by economic inequality, suburban sprawl, technological shifts, and cultural changes.
Central to the analysis is the application of various liberal theories, particularly liberal neutrality, to evaluate whether the state can justify policies aimed at enhancing social capital. While Gaus\u27s restrictive framework poses challenges to state intervention, Mang\u27s reinterpretation of liberal neutrality through qualified judgments provides a more practical approach. This framework balances respect for individual autonomy with the promotion of public welfare by justifying indirectly coercive measures, such as funding community programs, while avoiding direct coercion.
The thesis concludes with actionable policy recommendations, such as supporting recreational sports, third spaces, and bridging initiatives, which align with liberal neutrality while addressing the structural barriers to social connection. Ultimately, it argues that revitalizing social capital is essential for fostering a cohesive, democratic society and can be achieved without compromising liberal principles
Hispanic Participant Perspectives on the Impact of Patient Navigation Strategies on Enrollment in NonHodgkin Lymphoma Clinical Trials
No full textThis study examines the barriers and supports influencing Hispanic patients\u27 enrollment in oncology clinical trials at a well-resourced academic center, highlighting the need to address healthcare disparities and improve accessibility.
To assess patient considerations regarding participation in therapeutic clinical trials, including perceived barriers, potential resources to facilitate participation, and willingness to engage in various trial scenarios, we developed a 52-item questionnaire available in both English and Spanish. Eligible patients treated in the Texas Medical Center at the University of Texas MD Anderson Cancer Center, who self-identified as Hispanic or Non-Hispanic White, were aged 18 years or older, and had a histologically confirmed diagnosis of non-Hodgkin lymphoma, were invited to participate. Surveys were offered in paper form, on tablets, or via email to accommodate patient preferences, and data collected included demographics, perceived barriers, and potential facilitators for trial participation.
Hispanic participants were younger (median age 60 vs. 66 years), less likely male (54% vs. 66%), less educated (38% vs. 50.5% with a bachelor’s degree), and less likely to have discussed (49% vs. 70.9%) or participated in clinical trials (28% vs. 51.5%). Common concerns included trial costs (34% H, 22.3% NHW), distance to treatment (32%, 13.6%), and contact frequency with care teams (26%, 14.6%). Facilitators like written materials (69% H, 60.2% NHW), insurance aid, and videos were widely endorsed. Participants prioritized treatments that improved quality of life, such as reducing pain or enhancing activity levels.
Addressing systemic barriers such as cost, transportation, and communication gaps between healthcare providers and patients and implementing tailored interventions to address these barriers and supports are essential steps toward improving Hispanic representation and participation in lymphoma clinical trials
Ethnomathematics Projects for Projective Geometry in Distance Learning
Get PDFThis article reports on an ethnomathematics project we developed and implemented in an online learning environment to connect with students’ cultural backgrounds and to highlight the links between their environment, culture, and mathematics. The project is based on Simple House Theory, a framework that involves the application of projective geometry in the design of traditional houses and building numbers. Our results show that this approach fostered active participation and engagement despite the standard constraints and challenges of distance learning
The Operator Algebras Mentor Network: Impact of Community-Based Mentoring
Get PDFThe Operator Algebras Mentor Network (OAMN) is an international mentoring initiative that offers support in small groups to women and minority genders in the particularly male-dominated field of operator algebras (OA) in mathematics. Expected advantages of membership include raising awareness of the lack of gender diversity in this field, providing advice to mentees by mentors (e.g., pertaining to career or work/life balance), broadening one’s network in OA, etc. In this project, we set out to determine if membership within the OAMN is beneficial to its members. To this end we sent a questionnaire to OAMN members and a control group of non-members at similar institutions and similar positions to collect their experience with the mentoring initiative and perception of gender dynamics within the OA discipline, together with basic demographics. The initial analysis of the data we collected shows that mentoring directed towards junior women and other minority genders in the area has a positive effect on mentees’ networking ability, self-promotion, and raising awareness of gender issues within OA as a whole
For Chow Variety Try This New Dessert Recipe
Get PDFA positive addition to any dinner table or social function, this baked good can be served plane or à la mode
Investigating the Immunometabolism of Macrophages and Invading Microbes in Polymicrobial Infections
No full textSeveral studies have pioneered the discovery of immunometabolic shifts occurring during microbial infections; however, little work has been done at observing these shifts occurring in polymicrobial infections or occurring in vivo. Here we propose expanding this field by first observing dynamic immunometabolic changes occurring in macrophages when challenged with both Candida albicans and Escherichia coli, first in vitro via RNA-seq and RT-qPCR, and then in vivo while measuring changes in diet and metabolite concentration by utilizing advancements in magnetic resonance spectroscopy and RT-qPCR. We expect to find that when challenged with C. albicans and E. coli, macrophages will undergo Warburg metabolism in an effort to quickly generate energy to fight the infecting microbes. We expect that C. albicans will escape phagocytosis from macrophages and outcompete them for glucose by also upregulating glycolytic genes. While E. coli also prefers glucose as its main source of energy, the competition for glucose will cause E. coli to change its carbon catabolite repression to preferentially utilize more available secondary carbon energy sources, such as utilizing acetate through the glyoxylate cycle. The dual attack of these microbes utilizing different metabolic resources would allow for them to mount a stronger attack on macrophages due to less competition between each other for metabolic resources, causing macrophage death to occur at a faster rate. The discovery of potential synergistic and opposing effect in polymicrobial infections and their dynamic metabolic changes will give us greater insight into the mechanisms utilized by these invading microbes, the immune system’s metabolic response to these threats, and future directions for potential targets of therapeutic intervention
The Garden of pDYN: The impact of pDYN gene deletion on ethanol self-administration and reinforcement in female mice
Get PDFDebilitating over-consumption of alcohol, often culminating into a prevalent psychiatric disorder known as alcohol use disorder (AUD), stands as one of the United States’ most expensive societal battles to face (Harwood et al., 1998). Consequently, the public’s desire and scientists’ motivation to develop novel pharmacological solutions to treat it is high. Recent and ongoing research presents new insights into the role of the dynorphin/kappa opioid receptor (DYN/KOR) system as an inhibitor of dopamine release and a regulator of the negative affective states that come with alcohol withdrawal (Karkhanis et al., 2017). However, this growing body of literature is predominantly conducted using male subjects, highlighting a sex-related gap in our knowledge of the DYN/KOR system in females. As such, we focused our current study to investigate the influence of the deletion of the gene encoding for prodynorphin (pDYN) in alcohol reinforcement and self-administration in female mice. We utilized an operant conditioning paradigm, an established model of drug self-administration/reinforcement (Guttlein et al., 2021). At the start of our experiment, we consistently used a fixed ratio (FR1) reinforcement schedule, testing different ethanol concentrations (2%, 4%, and 8%). Afterwards, we stayed at 8% ethanol, but transitioned to a fixed ratio (FR3) schedule before incrementally increasing our schedule by 3 (FR6 and FR9). However, we did not observe any significant changes in alcohol intake or active lever presses using the FR1 or the progressive ratio of three schedules of reinforcements between mice lacking the pDYN gene and their wildtype controls, suggesting that the pDYN gene deletion did not impact alcohol self-administration or reinforcement in female mice
Enduring Wisdom for Leaders: Bringing a Biblical Worldview to Leadership and Management
Get PDFLeadership is fundamental to human relations and society but involves many mysteries. Based on the premise that human nature has been consistent over time, this study investigates an ancient text, the most published book in history, with three research questions: What are key insights for leaders from a biblical worldview? How do those insights align with current scholarship? How do they add to our understanding to help current leaders? Key points were drawn from all 66 books of the Bible. Using inductive research methods, 310 key points were comparatively analyzed, grouped into common themes, and organized into a conceptual model, with 9 topics, under 3 domains. Elements of the model were compared with recent scholarship, noting the unique emphases from a biblical perspective. Implications and applications of the model were considered, highlighting the interactions between the elements that enable the conceptual model to be utilized as a wholistic perspective on leadership and management. Recommendations for future study are proposed, building on the three research questions. The study seems to validate the initial thesis: The Bible lays a foundation for effective leadership and management that has stood the test of time and provides helpful insights and guidance for today’s leaders
DeepGridMCLP: A Deep Reinforcement Learning Approach to Solve the Maximal Covering Location Problem with Facilities in Continuous Regions
Get PDFThe Maximal Covering Location Problem (MCLP) is a classic Combinatorial Optimization Problem (COP) in spatial optimization and operations research, predominatnly used for strategic public facility placement. The model’s objective is to determine the optimal locations for a fixed number of facilities in order to serve the largest possible demands within a desired service distance. In its original form, the MCLP model is formulated with discrete facility candidate points. However, in many practical situations, the facilities can be positioned anywhere in a continuous region. For example, in environmental planning or wireless network design, the prospective facility placements may be established in open areas rather than predetermined spots. This continuous variant, known as the Continuous MCLP (C-MCLP) or Planar Maximal Covering Location Problem (PMCLP), presents unique computational challenges. In this thesis, I propose a novel hybrid approach that combines a custom Candidate Location Set (CLS) generation technique with a Deep Reinforcement Learning (DRL) model to address the C-MCLP. Unlike previous studies that apply DRL to the discrete MCLP, my approach offers a streamlined solution by discretizing the problem model and making sequential decisions on facility placement within a given convex continuous region, while maximizing the total covered demand. The model’s architecture explicitly accounts for complex spatial interactions between facility locations and demand points, enabling it to optimize placement decisions through iterative training. The proposed method was evaluated by comparing with the solutions based on a commercial solver (CPLEX) and a heuristic method (Genetic Algorithm). Results demonstrate that my DRL model effectively solves the C-MCLP; it exhibits advantages in identifying better solutions compared to the GA-based heuristic model\, and achieves faster computation time compared to the solver-based (CPLEX) solution. This work advances the application of deep reinforcement learning in spatial optimization and offers a new perspective on solving location covering problems in continuous spaces. The primary contribution of this dissertation include the development of a novel methodology for solving a variant of a well-known combinatorial optimization problem, providing both theoretical advancement in spatial optimization and practical implications for urban planning, emergency management, and various domains where optimal location decision is crucial. Future research directions include investigating DRL applications to other MCLP variants and spatial optimization models, mainly focusing on addressing dynamic constraints and uncertainty in real-world scenarios
Enhancement of Mechanical, Structural, and Electrical Properties in Advanced Composites and Vat Photopolymerized 3D Printing Nanocomposites
Get PDFAdvanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the broader adoption of advanced composites. Critical issues include enhancing the delamination resistance and electrical conductivity of FRP composites, as well as improving the mechanical performance of 3D-printed materials while reducing weight and material waste. This research seeks to address these challenges through innovative solutions: (1) reducing carbon fiber-reinforced polymer (CFRP) delamination and enhancing electrical conductivity by incorporating polyamide (PA) and carbon non-woven veils; (2) improving the mechanical properties of digital light processing (DLP) 3D-printed materials via the addition of graphite nanoparticles; and (3) applying a novel, machine learning-aided analysis and printing method to reduce structural weight and material usage without compromising necessary mechanical integrity. The anticipated outcomes of this study aim to advance the design, performance, and application of advanced composites across these critical sectors, addressing current limitations and unlocking new possibilities for innovation