21794 research outputs found
Sort by
Studies Towards High Surface Area Porous Polymers Via Cross-Coupling Methodology
Get PDFPorous polymers, known for their high internal surface area and robust chemical stability, are promising candidates for applications in gas storage, water purification, energy storage, and catalysis. The Yamamoto-type Ullmann reaction, known for yielding high porosity polymers, serves as a benchmark in this study. However, its limitations as a homocoupling reaction restricts the synthesis of ordered A-B type copolymers. This research addresses this challenge by investigating the use of cross-coupling reactions, particularly the Negishi reaction, to synthesize A-B type copolymers with reduced defectivity and enhanced surface area. The synthesis of fully-metalated intermediates and their subsequent polymerization are discussed in detail. The results demonstrate that fully transmetalation-active nucleophilic monomers can potentially lead to higher porosity in cross-coupled polymers. Additionally, we explore the Eglinton coupling methodology for alkyne-alkyne polymerization, aiming to further reduce defectivity in porous polymers via fully pre-metalated monomers. The findings indicate significant potential for the development of highly porous polymers through optimized cross-coupling techniques, though challenges remain in achieving the theoretical maximum surface areas
Determinants Of Fertility In The United States
No full textThis study analyzes the determinants of fertility among women aged 15–50 in the United States, using data from the June Current Population Survey (CPS) for 2010 and 2016. The study aims to understand how various socioeconomic and demographic factors, including family income, education level, female share of household earnings, marital status, age, race, and ethnicity, influence the likelihood of having children and the total number of children ever born. We employ three different regression models—Logit regression, zero-inflated Poisson regression, and Poisson regression—to examine these relationships and identify any significant changes in fertility determinants over the six years. For the ANYBORN outcome, we use a Logit regression to estimate how the probability of having at least one child is affected by determinants of fertility. Our second and third regressions use zero-inflated Poisson regression and Poisson regression to analyze the TOTBORN outcome, which is the number of total births a female has, using the same independent variables. Our main findings are as follows: First, the logistic regression models for 2010 and 2016 revealed that females with no high school diploma were more likely to have at least one child. Women with a high school diploma also showed an increased likelihood. The coefficients were positive for females with some college education but decreased slightly over time. Conversely, females with graduate degrees were less likely to have children. Family income negatively impacted the probability of having children, while the female shares of household earnings increased the likelihood, though its effect decreased over time. Marital status remained a strong predictor, with married females more likely to have children while never-married females were less likely. Age significantly influenced childbirth probability, with a stronger impact observed in 2010 compared to 2016. Racial and ethnic differences indicated that Black non-Hispanic and Hispanic foreign-born females had increased probabilities of having children, while White non-Hispanic and non-Hispanic foreign-born females showed decreased probabilities, though the negative impact lessened over time. These findings suggest evolving societal and economic factors influencing fertility decisions between 2010 and 2016. Second, both the zero-inflated Poisson regression and Poisson regression analyses for 2010 and 2016 reveal significant associations between various demographic factors and the number of total births for females. Key findings include a positive relationship between lower educational attainment and higher birth rates, while higher education is associated with lower birth rates. Family income negatively impacted birth rates, and the female share of household income positively influenced birth rates, though this influence slightly decreased over time. Marital status showed substantial effects, with married females having higher birth rates and never-married females having lower birth rates. Age significantly affected birth rates, with its influence declining over time. Ethnicity and birthplace also played a role, with White non-Hispanic US-born females consistently having lower birth rates and Black non-Hispanic US-born females having higher rates, although these effects declined over time. These findings highlight evolving relationships between demographic factors and fertility, reflecting broader socio-economic shifts and changing family planning behaviors over the years
Novel Safety Analysis For Heterogenous Roadways: Integrating Crash Data, Crash Surrogates, And Intelligent Transportation Systems
No full textRoad traffic crashes are a major global issue, causing over 1.19 million fatalities worldwide, with vulnerable road users (VRU) such as pedestrians, bicyclists, and motorcyclists accounting for more than half of the fatalities. The recent trends in VRU crashes in the United States reveal a significant increase in pedestrian and bicyclist fatalities. These increasing traffic crashes affect the individuals involved, their families, communities, and the entire country physically, psychologically, and financially. Examining the contributing factors to crashes and establishing suitable countermeasures through shared responsibility among policymakers, stakeholders, and road users is essential to maintaining safer roadways. Maintaining and evaluating transportation data using appropriate statistical approaches is vital for such comprehensive analysis.Traditional statistical methods based on historical crash records provide insight into crash causality. Novel transportation data analysis techniques integrated with intelligent transportation systems can significantly enhance safety and performance analysis. This research encourages stakeholder cooperation by leveraging novel transportation data analysis techniques to examine various traffic operation and safety performance measures, including crashes and crash surrogates. This dissertation has three primary objectives. Initially, it creates a framework for classifying suburban-type roadways (STR), a context-specific roadway classification system emphasizing VRU safety. Second, by addressing problems associated with unobserved heterogeneity in crash data, it investigates an advanced approach towards crash data collection and analysis. Third, it investigates the application of surrogate safety measures (SSM) alongside video analytics techniques to evaluate risky behavior, such as red-light violations (RLV) and near-miss events. These objectives are achieved by conducting research projects utilizing multiple data sources on highway safety, including crash data, crash surrogates, and intelligent transportation systems. The findings from this dissertation contribute to three critical areas of transportation safety and operations: - Novel context-specific transportation evaluation - Novel analytics in transportation evaluation - Novel performance measures for transportation evaluation Overall, this study contributes to a larger initiative to upgrade transportation data analysis while employing recent technological developments to improve safety by reducing fatalities and mobility by reducing congestion
Black Girls’ White Schools: Black Girls\u27 Perceptions Of Attending Predominantly White Schools In The Metro Detroit Area
No full textThis dissertation explores the experiences of Black girls attending predominantly white schools in suburban Detroit, focusing on how these educational environments shape their racial identity development. Using Black Girl Cartography as a theoretical framework and employing a narrative inquiry methodology, the study captures the voices of Black girls, addressing critical gaps in the literature by offering a nuanced understanding of their experiences in racially isolated environments. The findings reveal the pervasive impact of racial isolation, systemic racism, and identity struggles, which significantly affect both the personal and academic development of Black girls. Participants frequently encountered microaggressions, discriminatory school policies, and biased academic expectations, which exacerbated their feelings of exclusion and invisibility. Despite these challenges, the study also highlights the resilience displayed by Black girls, particularly through the creation of safe spaces—both physical and conceptual—that allow them to reclaim their identities and resist marginalization.The research underscores the importance of addressing systemic inequities within predominantly white schools by advocating for educational policy reforms that foster inclusivity and equity. Key recommendations include the development of culturally responsive support networks, the creation of safe spaces, and the re-examination of disciplinary practices that disproportionately target Black girls. Additionally, the study contributes to the literature by introducing Black Girl Cartography as a novel framework for understanding the spatial and social dynamics of identity development among Black girls. The research has practical implications for educators and policymakers, offering actionable strategies for creating more equitable and supportive school environments. Future research directions include expanding the study to explore the intersectionality of race, gender, and other identities, as well as evaluating the effectiveness of proposed policy reforms in reducing racial isolation and promoting positive identity development. By amplifying the voices of Black girls, this dissertation lays the groundwork for continued efforts to advance educational equity and social justice within school systems.
KEYWORDS: Black girls, racial identity, systemic racism, educational policy, Black Girl Cartography, narrative inquiry, resilience, predominantly white schools, equity, social justic
I Am Who I Am; Am I Celebrated/supported Here? Minoritized Student Experiences In College Composition
No full textAs debates around the privatization of education and the removal of critical race theory intensify, this qualitative study investigates how these students navigate the challenges of academic Discourse communities. Eight first-year students and one composition professor participated in semi-structured interviews, which were thematically coded around two core themes: students\u27 co-creation of identity through writing, family, and university membership, and their struggles with feelings of inadequacy and loss of identity within academic gatekeeping structures, such as white English norms. The findings reveal that while inclusive practices exist, they are insufficient for minoritized students to feel fully integrated into academic discourse. The study calls for greater attention to linguistic diversity and justice to foster a more inclusive academic environment that acknowledges and values diverse student voices
Data-Driven Approaches To Improving Urban Cycling And Enhancing Bikeshare Systems For Equitable And Sustainable Transportation
No full textAs cities continue to grow, they face mounting challenges in providing efficient, sustainable, and equitable transportation options. Bikeshare systems have emerged as a flexible, environmentally friendly alternative that can complement existing transit networks. This dissertation presents a comprehensive, data-driven analysis of urban cycling and bikeshare systems, using advanced analytics to provide actionable insights for urban planning and transportation policy.Focusing on the Detroit Metropolitan Area, the research examines three key dimensions of bikeshare systems: usage patterns, integration with public transit, and travel time reliability. By employing statistical and econometric modeling such as hazard-based duration models and Tobit regression analysis, the study explores the factors influencing bikeshare usage and user behavior in urban settings.
The findings highlight the complex interplay of environmental, infrastructural, and demographic factors that shape bikeshare utilization. A significant discovery is the identification of a 20-minute threshold in ride durations, offering strategic insights for system optimization. The research also reveals how variables such as traffic stress, weather conditions, and pandemic-related changes impact bikeshare usage, underscoring the need for strategic station placement and seamless integration with public transit to enhance accessibility and user satisfaction.Through an in-depth analysis of travel time reliability along major urban cycling routes, the dissertation provides critical guidance for targeted infrastructure enhancements and policy interventions. It demonstrates how factors such as road segment characteristics, time of day, and day of the week affect travel time consistency, offering a framework for improving the reliability and appeal of urban cycling networks. This research bridges academic study and practical urban planning, offering evidence-based recommendations to optimize bikeshare systems, enhance public transit integration, and improve urban mobility. While focused on Detroit, the findings provide a framework applicable to cities worldwide, promoting efficiency, equity, and sustainability. By combining data analytics with urban planning, this dissertation supports informed decision-making and offers valuable tools for policymakers, planners, and transportation professionals to create more resilient and inclusive cities
