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Rhyme and Reason: Examining the Causes of Variance Within the Absolute DW Nominate Scores of U.S. House Members
No full textHow do different factors impact the voting behavior of members of the U.S. House of Representatives? Existing research asserts that factors related to the House itself or its institutions (district competitiveness and majority/minority party membership) tend to push members’ voting behaviors in a more polarized direction, with member seniority serving as an exception (Donnelly, 2019, Jones, 2010, Konisky and Ueda, 2011, Taylor, 2019). However, other recent scholarship demonstrates that descriptive factors (race, gender, age) also continue to influence members’ vote choices in more moderating ways (Wilson and Ellis, 2014, Broockman, 2013, Bauer and Cargile, 2023, Curry and Haydon, 2018). In order to test these relationships, I run an OLS regression of district competitiveness, majority/minority party membership, seniority, age, race, and gender on the absolute values of House members’ DW Nominate scores from the 100th through the 117th U.S. Congresses. From that point, I utilize the results of my OLS regression to assess which factors explain variance in absolute DW Nominate behavior
Digital Politics: Assessing the Influence of Election Officials’ Social Media Usage on Youth Voter Turnout
No full textYouth voter’s behaviors, along with their rates of turnout in elections, are unique and vary from their older counterparts. This is due to the variance in the participatory resources that are available to these two groups. The influence of social media on elections in recent decades has been a significant point of discussion within political science research. With these platforms changing how elected officials communicate with citizens, understanding its influence is growing in importance. Furthermore, the ways in which younger Americans use social media is different than their older counterparts, making these platforms an important place for younger Americans to obtain information. This study analyzes how the informational provisions presented on the social media accounts of state election officials influences the probability of youth voter turnout. Specifically, I ask to what extent does the frequency of social media posts made by state election officials impact the level of youth voter turnout? I hypothesize that if state election officials have a high frequency of social media posts, then that state will have higher rates of youth voter turnout compared to low frequency states. To conduct this study, I use both a bivariate and a multivariate hypothesis test. I collected data from the Cooperative Election Study (CES) and the #TrustedInfo2022 dataset to complete these quantitative tests. Both of these datasets include data from the 2022 United States midterm election. The results from this study imply that increased social media provisions by state election officials influence the frequency of youth voter turnout within a state
Zines Unearthed: Affirming Identity, Navigating Community and Communicating Emotions Within Queer Rural Zines.
No full textThis Independent Study focuses on the complex experiences of rural queer individuals as portrayed in the short form publications of zines, with a focus on themes of Rurality, Community, and Positive/Negative emotions. Through a qualitative and quantitative analysis of six zines, my research reveals the challenges and resilience of rural queer individuals. Findings exhibit the indispensable role of community support in navigating isolation and negative emotions, alongside moments of positivity, hope, and activism. When accessing the literature surrounding this topic I ask three questions: Who are queer farmers and what are their challenges? How do queer farmers find community and affirm themselves through media? And finally, how do people especially rural queer people use zines? Academic literature surrounding this topic is limited so I hope that my research fills some of these gaps in studies as more data and about rural queer individuals is brought to light
Cryptography: Protecting Data in the Digital Age
No full textIn an era dominated by digital interactions, the protection of data from unauthorized access and malicious threats has become a critically essential task. This paper explores the pivotal role of cryptography in ensuring the security and confidentiality of information, with a specific focus on the Rivest-Shamir-Adleman (RSA) encryption algorithm. This paper serves two objectives, first, to improve the understanding of diverse encryption types, their benefits, and the importance of encrypted data, second, to clarify the fundamental principles that form the basis of encryption. By demystifying the complexities of cryptographic algorithms, with a specific focus on RSA, this paper contributes to the broader conversation on data security. It also fosters a more profound comprehension of the mechanisms that protect our digital interactions
The Social and Economic Impact of the Great Migration on Akron, Ohio
No full textThe Great Migration was the mass movement of over six million African Americans who left the South and resettled in cities across the North, West, and Midwest. This thesis focuses on the Great Migration in the context of Akron, Ohio. These migrants were pushed out of the South and pulled to cities for a variety of reason. The push factors included Jim Crow laws, chronic racial segregation and violence, and bleak economic opportunities. Pull factors were more location-specific but included economic opportunities and less racial violence. In the case of Akron, African American migrants were attracted to the city to work in the rubber industry. This I.S. seeks to answer the question of how did the African American migrants during the Great Migration economically and socially impact Akron, Ohio? Profound changes and developments economically and socially occurred due to the influx of the Black population brought to Akron by the Great Migration. Among the economic developments are the creation of an independent and separate Black commercial economy and the constant supply of labor for the booming rubber industry. Socially the changes included a strong Black community with ties to social clubs and churches
Examining Late Cretaceous (Maastrichtian) North American Dinosaur Teeth and Their Paleoecological Implications in the Hell Creek of Carter County, Montana
No full textThe Hell Creek Formation is an iconic Late Cretaceous formation that is found throughout the states of Montana, Wyoming, and the Dakotas. Even though it has been studied for over 100 years, questions about the paleoecosytem it represents still need further research. I here examine dinosaur teeth from the Hell Creek of Carter County, Montana, a section that is understudied compared to other exposures of the formation. While many studies focus on the dinosaur fauna of this ecosystem, most of these studies focus on skeletal material. Dinosaur teeth are abundant within microvertebrate sites in the Hell Creek, and these teeth can tell and confirm similar information to that of the skeletal remains, while also providing information that preservation bias might otherwise obscure. By conducting a tooth census comprised of 1,522 dinosaur teeth and comparing that to similar skeletal censuses, I hypothesize that while certain fauna like Triceratops will, as reflected in the skeletal record, be the most abundant tooth taxa, other species not as common from skeletal remains, such as dromaeosaurs, will be more common from teeth surveys, as their hollow bones are subject to preservation bias. I also predict that different lithologies of microsites will contain different teeth assemblages due to niche partitioning within the environment
Investigating Physiological Abnormalities Induced by Contaminated Aquatic Sites in Freshwater Fish Across Northeast Ohio
No full textBiomarkers have become an effective tool to monitor the viability of aquatic environments and influences on human health. Early detection of exposure to pollutants in fish and assessments of their biological responses are an efficient way to keep track of environmental changes. The present study aims to investigate potential relationships between physiological abnormalities observed in 11 fish species that were in contact with contaminated sediment from different sites across northeast Ohio. Fish were collected from the Cuyahoga River, Silver Creek Lake, Sippo Lake, Tappan Lake, and Killbuck Creek. The sampled fish species were collected through hoop netting, gill netting, and electrofishing techniques. Examinations and analyses for external and internal abnormalities were conducted as defined by the guidelines from Illustrated Guide for Assessing External and Internal Anomalies in Fish and Biomarkers of exposure of brown bullheads (Ameiurus nebulosus) to contaminants in the lower Great Lakes, North America. In total, 45 fish were collected with 121 abnormalities counted across the study. Fish from the Cuyahoga River test site had a total of six abnormalities present across the body (n=6), while fish from Silver Creek Lake had n=10, Sippo Lake n=16, and Tappan Lake n=32 abnormalities. Samples from Killbuck Creek had a range of n=8 to n=49 total anomalies depending on the site location. Results suggest that fish from heavily polluted sites containing contaminated sediment may have adapted for better survival in a carcinogenetic environment, having a smaller body size and larger internal organs, for example. Additionally, there was an observed pattern of discoloration, hemorrhaging, scarring, and fin erosion in fish collected from sites contaminated with bacterial infection, high PAH chemical concentrations, and solid waste pollution
Relationships, Attachment, and Stress: How Do College Students Manage Romantic Relationships Under the Influence of Attachment Style and the Stress of College Life
No full textIn an extension of research on attachment styles formed in early childhood, the present study examines how adult attachment style affects the relationships of college students and the stress students experience. Male and female students between the ages of 18 and 23 at the College of Wooster (n = 202) were recruited to respond to three questionnaires. An adult attachment scale (ECR) was used to measure the distribution of attachment styles in college students and correlated with questions measuring satisfaction within romantic relationships. The Perceived Stress Scale (PSS) was used to measure the degree to which situations in one\u27s life are appraised as stressful. Participants were also asked to self-report their attachment style in a relationship as being Secure, Anxious, Avoidant, or Insecure-Fearful. Based on the questionnaires, participant’s scores were analyzed to find relationships between their attachment style and stress levels within their current relationship. The results indicated that college student participants were more likely to report their attachment style as Secure if they were involved in a local relationship. It was also found that high Avoidant attachment was positively correlated with perceived stress scores. In addition, ANOVA procedures revealed that participants not in a relationship were significantly lower in Avoidance scores and significantly higher in Anxiety scores than those who were in a Local or Long-Distance relationship
Evaluating Synthetic Routes to Functionalized PYBOX for Potential Use in Stacked Porphyrin Complexes
No full textFrom Delays to Data-Driven: Exploring Flight Departure Delay Causes with Random Forest and Interactive Dashboards
No full textFlight delays have been a common problem within aviation industry and air travel. It can cause negative impact on both aviation businesses and passengers. Therefore, flight delays analysis and prediction are applied to data-driven decision making in aviation related businesses and passengers. In this study, a dataset consisting of 119,631 flights operated by major airlines in U.S. in 2023 is used to determine the main factors influence flight departure delay based on interactive visualizations on Tableau. A smaller subset of the data, including flights departed from Texas within summer, is applied by random forest machine learning algorithms to create the classification tree-based model in RStudio. The result shows that destination state, taxi-out time, airtime, day of week, departure schedule time, and distance between origin and destination airport are important factors to determine departure delay flight. The random forest model, where the predicted probabilities are weighted, is tested on the out-of-bag sample and separated test set. The findings demonstrate that this approach results in overall prediction accuracy of 65%. To Dr. Manz, I saw your academic alert notice and I want to discuss that with you in person. Are you available after 1pm today? From, Dd Dawra