The Desire for Chaste Love in Book Three of The Faerie Queene

This paper examines the complex relationship between chastity and consummation presented in Book Three of The Faerie Queene. By recasting the Ovidian myth of Venus and Adonis, Spenser creates a definition of chastity that is based in the bond of natural emotion that includes sexual expression without the damaging effects of lust. Venus and Adonis are the first to enact love based on this definition and exemplify perfection in their expression and acceptance of love. From their example, all other lovers in Book Three act in favor of or against the notion of selfless and chaste love. Chapter two details Britomart’s quest to find Artegall. Like the love between Venus and Adonis, she similarly focuses her desires on creating a chaste relationship with Artegall. As she is the protector of chastity, she is able to exercise her training as a knight and defend the qualities of pure love from the damaging effects of lust. The damages of lust are most apparent in the House of Busirane. By kidnapping Amoret, Busirane becomes the embodiment of the damages of lust, and the marriage he attempts to create with Amoret is a defiled marriage based in lust rather than purity. Through his warped worship of Cupid, he becomes a corrupted version of Scudamour and intends to corrupt Amoret as well. Britomart’s rescue of Amoret proves that chaste love is a more powerful force than lust and has the power to heal the damages created by impure desires

Special Educators, Employers, and Special Students: A Comparison of Perceptions of the Working World

Education is designed to prepare all students for productive citizenship. Students with disabilities, however, are employed at lower rates, earning less money, and accruing fewer benefits than their nondisabled peers. In order to design a curriculum that targets employment as an outcome, special educators must determine the needs and expectations of employers. This study compared the perceptions of employers, special education teachers, to learning disabled students .Employers and special education teachers rated work related, communication, personal, and social skills similarly while students with learning disabilities formed in congruent perceptions of the working world

Dopamine Precursor’s Effect on Habitation in Hermit Crabs

A Research Methods Project supervised by Dr. David Stahlman (Fall 2021

Coach-Facilitated Nutritional Behavior Change in the Context of Organized Youth Sports

African American (AA) adolescents have the highest rates of obesity in the United States. AA males have the highest cardiovascular disease (CVD) burden of any ethnic subgroup; yet paradoxically, they have higher or equal rates of youth sports participation compared to their peers. As a prevention effort against obesity and CVD, pediatric lifestyle behavior counseling is delivered during outpatient clinic visits. However, whether clinic-based counseling creates sustainable positive behavior change is not clear. A partial-systematic review of the literature on coach-facilitated behavior change in the context of youth sports demonstrated promising results for creating sustainable lifestyle change in children. A primary study revealed that coach-lead nutritional behavior change in youth athletes has the potential to create sustainable health behavior change. Greater than eighty percent of children participate play sports. Therefore, a behavior intervention in this context may demonstrate sustainable and positive health effect for AA male youth and all children.Master of Public Healt

Convergence, Adaptivity, and Applications of Physics-Informed Machine Learning

Extensive work in applying deep learning to broader fields of science and engineering have been emerging in recent times, to include materials informatics, thermodynamics, and numerous other fields of computational sciences. Advances in these areas have been of particular excitement as future materials and new and informative laws of nature can be learned from data, even if that data is less than what would typically be required of a deep learning approach. In this work, we focus on the development and democratization of Physics-Informed Deep Learning, a field of science that was proposed before the turn of the century but has recently been gaining rapid popularity among academia and industry alike. This dissertation is centered around recent work in physics-informed deep learning, as well as other areas of deep learning applications in computational sciences, such as materials informatics. Specifically, we will address recent advances in training stability and convergence of PINN solvers to semi-linear and stiff problems where the baseline PINN fails to converge or train effectively. We will discuss specific applications of PINNs to computational science domains where it could provide a force multiplier to researchers, and work performed in deep learning estimation of phase field modeling. Additionally, we will discuss the open-source package TensorDiffEq, a Python package based on Tensorflow that allows for easy implementation of PINN-based forward, inverse, and data assimilation solvers

Optimal State Estimation for Partially Observed Boolean Dynamical Systems in the Presence of Correlated Observation Noise

Recently, state space signal models have been proposed to characterize the behavior of discrete-time boolean dynamical systems. The current system model is one in which the system is observed in the presence of noise. The existing algorithms, however, rely on an assumption of independent and identically distributed (i.i.d.) white noise processes. The existing recursive MMSE process of estimating a Boolean dynamical system (in the presence of i.i.d. noise) is called the Boolean Kalman Filter (BKF). Here we address a different sort of noise, one that is correlated in time to other observation noise, specifically through an AR(1) time series process. In this thesis, we propose modifications to the state-space model that will allow the existing Boolean Kalman Filtering recursive process to adapt to handle time-correlated noise. Additionally, we will propose a modification to the Boolean Particle Filtering approximation to compensate for the same correlated noise AR(1) process. In addition, this document will address a new software package created in the R programming language that will allow the scientific community easier (and free) access to the algorithms created by the Genomic Signal Processing Lab at Texas A&M University. These algorithms will be explained in this document, with results of the algorithms derived from the use of the package