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This study aims to discover whether there is a difference in philanthropy between billionaires who made their own wealth and billionaires who inherited their wealth by testing the applicability of an earlier statistical model from previous research. Two samples of billionaires from the 2019 Forbes 400 list were used, one sample of the top 100 and another of a random 100. Forbes's self-made scores were used to measure the degree to which each billionaire made their own wealth. Two different variables in separate tests were used to measure philanthropy: Forbes's philanthropy score and impact investor designation. ANOVA and Pearson's r statistic tests were used. Only the top 100 \nsample when using philanthropy score to measure philanthropy showed a difference in charitable giving between billionaires with inherited wealth and those with self-made wealth. As a secondary finding, the results indicated that the billionaires in the top 100 sample were more philanthropic than the billionaires in the random sample. This study has implications for future research on factors that influence the charitability of billionaires, including source of wealth and political and social costs. Research on charitable motivations of ultra-wealthy individuals is important because it helps not-for-profit organizations understand how to appeal to these individuals for donations,Honors Thesis Advisor: Dr. Joshua Chicarelli.
One of the most important aspects of the analysis and identification of human skeletal remains is determination of the biological profile, which consists of the age, sex, ancestry, and stature of an individual. Typically, anthropologists analyze the pubic bone in adult human skeletal remains, which is highly sexually dimorphic due to a female's capacity for childbirth. However, when these fragile bones are broken, damaged, or altogether missing, it is necessary to look to other areas of the skeleton for sex information. DiMichele and Spradley (2012) developed a method of sex estimation using four measurements of the calcaneus. For this project, this method was tested using the left calcanei of modern American skeletal remains from the Texas State University Donated Skeletal Collection (TXSTDSC). This skeletal sample consists of 264 individuals (151 males, 113 females) with an average age-at-death of 65.2 years, 91.3% of whom are classified as white. The sectioning points for individual measurements were able to accurately estimate sex for 76.7–80.9% of this skeletal sample. Univariate and multivariate equations provided classification rates ranging from 77.4% to 89.6%. The results of this study further validate that the calcaneus is sexually dimorphic and can be used to estimate sex in a modern American skeletal sample.,Honors Thesis Advisor: Dr. Cassandra Kuba.
The current project explores the influence of mental health in musical theatre. The prevalence of mental health in musical theatre is crucial to the development of an imperfect character that is relatable and circumstantial situations in which the audience can see the character living and dealing with these different mental health issues. One of the greatest accomplishments of musical theatre has been creating a platform to raise awareness for mental health issues and disorders of any size or degree. Utilizing seven different Broadway songs sung by female characters that each deal with a different mental health issue or illness, each one is analyzed through lyrical content, performance, characterization, musical significance and mental health inquiry. Each song choice and character showcase a different mental health issue and how the character copes with the challenges. The results showed limited research but contribute to a field that is beginning to emerge as a staple in American society and culture. Musical theatre shows that mental health issues and disorders are prominent in society and normalizes the stigma, illustrating the concept that people struggle together. Different characters are portraying different issues and conveying the message that everything will be okay.,Honors Thesis Advisor: Dr. Yugo Ikach.
Some technical optimization problems that have been normally solved manually or with other traditional techniques, can be optimized by using different advanced techniques. Techniques have evolved to include artificial intelligence (AI) algorithms to get better results. Genetic algorithms are a great example of one of these optimization techniques that uses AI. While these techniques are designed to solve problems more efficiently than before, there are some problems that are better suited to these algorithms compared to others. By analyzing experimental data, it is possible to discern what types of problems are better solved using genetic algorithms are better at solving. Studies that have isolated genetic algorithmic applications have been chosen to better compare the solutions that were found, straying away from hybridizations of any kind that could influence results and blur the line of responsibility. Five optimization problems were analyzed to find the problems that had the best improved results and the style best suited for genetic algorithms. These optimization problems that were studied include: PID control tuning; traveling salesman shortest path; generation of machine turning code; design of a wind turbine tower; and A-Mazer, a maze-solving algorithm. By breaking down these problems and how genetic algorithms are used to enhance solutions, a comparison can be made. It was found that problems that would have multiple trials within traditional techniques are more suited for genetic algorithms over other optimization problems.,Honors Thesis Advisor: Dr. Jennifer Wilburn.

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