Intercollegiate athletics is a very important part in American higher education both financially and symbolically. One of the most distinct features of college sports is athletic mascots and nicknames of colleges and universities represent not only the athletic programs but also the whole institutions and communities. As they were deeply ingrained in American culture, some colleges and universities maintained Native-American themed mascots. Scholars and activists criticized the use of these mascots due to offensiveness and racial stereotyping. After the criticisms and the sanctions by the National Collegiate Athletics Association in 2005, many abandoned or modified the mascots in a more politically correct way. In case of Florida State University (FSU), however, the university could avoid the possible nickname change mainly because of the endorsement by the Seminole tribe in Florida. The purpose of this dissertation is to explore the roles of the Native American nickname and the mascot (the Seminoles and Chief Osceola) at the Florida State University as organization builders for the university. The following research questions framed this study: (a) What organizational roles have the Seminoles nickname and Chief Osceola mascot played at Florida State University and what can these roles tell us about the organizational trajectories of the university? (b) Do the nickname and mascot and their use correspond to the conceptual framework of “invented tradition?” If so, what is the utility of this framework in understanding the role these traditions play at the university? Qualitative data sources for this case study were collected from informal observations, documents, and semi-structured in-depth interviews. I reviewed how FSU’s football and its Native-American mascot and nickname played a huge role in the process of institutional growth and development from a small regional women’s college to a research-oriented, flagship state university, utilizing Eric Hobsbawm and Tony Collins’s framework of “invented traditions".

Genetic sequences are being collected at an ever increasing rate due to rapid cost reductions; however, experimental approaches to determine the structure and function of the protein(s) each gene codes are not keeping pace. Therefore, computational methods to augment experimental structures with comparative (i.e. homology) models using physics-based methods for building residues, loops and domains are needed to thread new sequences onto homologous structures. In addition, even experimental structure determination relies on analogous first principles structure refinement and prediction algorithms to place structural elements that are not defined by the data alone. Computational methods developed to find the global free energy minimum of an amino acid sequence (i.e. the protein folding problem) are increasingly successful, but limitations in accuracy and efficiency remain. Optimization efforts have focused on subsets of systems and environments by utilizing potential energy functions ranging from fixed charged force fields (Fiser, Do, & Sali, 2000; Jacobson et al., 2004), statistical or knowledge based potentials (Das & Baker, 2008) and/or potentials incorporating experimental data (Brunger, 2007; Trabuco, Villa, Mitra, Frank, & Schulten, 2008). Although these methods are widely used, limitations include 1) a target function global minimum that does not correspond to the actual free energy minimum and/or 2) search protocols that are inefficient or not deterministic due to rough energy landscapes characterized by large energy barriers between multiple minima. Our Global Optimization Using Metadynamics and a Polarizable Force Field (GONDOLA) approach tackles the first limitation by incorporating experimental data (i.e. from X-ray crystallography, CryoEM or NMR experiments) into a hybrid target function that also includes information from a polarizable molecular mechanics force field (Lopes, Roux, & MacKerell, 2009; Ponder & Case, 2003). The second limitation is overcome by driving the sampling of conformational space by adding a time-dependent bias to the objective function, which pushes the search toward unexplored regions (Alessandro Barducci, Bonomi, & Parrinello, 2011; Zheng, Chen, & Yang, 2008). The GONDOLA approach incorporates additional efficiency constructs for search space exploration that include Monte Carlo moves and fine grained minimization. Furthermore, the dimensionality of the search is reduced by fixing atomic coordinates of known structural regions while atoms of interest explore new coordinate positions. The overall approach can be used for optimization of side-chains (i.e. set side-chain atoms active while constraining backbone atoms), residues (i.e. side-chain atoms and backbone atoms active), ligand binding pose (i.e. set atoms along binding interface active), protein loops (i.e. set atoms connecting two terminating residues active) or even entire protein domains or complexes. Here we focus on using the GONDOLA general free energy driven optimization strategy to elucidate the structural details of missing protein loops, which are often missing from experimental structures due to conformational heterogeneity and/or limitations in the resolution of the data. We first show that the correlation between experimental data and AMOEBA (i.e. a polarizable force field) structural minima is stronger than that for OPLS-AA (i.e. a fixed charge force field). This suggests that the higher order multipoles and polarization of the AMOEBA force field more accurately represented the true crystalline environment than the simpler OPLS-AA model. Thus, scoring and optimization of loops with AMOEBA is more accurate than with OPLS-AA, albeit at a slightly increased computational cost. Next, missing PDZ domain protein loops and protein loops from a loop decoy data set were optimized for 5 ns using the GONDOLA approach (i.e. under the AMOEBA polarizable force field) as well as a commonly used global optimization procedure (i.e. simulated annealing under the OPLS-AA fixed charge force field). The GONDOLA procedure was shown to provide more accurate structures in terms of both experimental metrics (i.e. lower Rfree values) and structural metrics (i.e. using the MolProbity structure validation tool). In terms of Rfree, only one out of seven simulated annealing results was better than the Gondola global optimization. Similarly, one simulated anneal loop had a better MolProbity score, but none of the simulated annealing loops were better in both categories. On average, GONDOLA achieved an Rfree value 19.48 and simulated annealing saw an average Rfree value of 19.63, and the average MolProbity scores were 1.56 for GONDOLA and 1.75 for simulated annealing. In addition to providing more accurate predictions, GONDOLA was shown to converge much faster than the simulated annealing protocol. Ten separate 5 ns optimizations of the 4 residue loop missing from one of the PDZ domains were conducted. Five were done using GONDOLA and five with the simulated annealing protocol. The fastest four converging results belonged to the GONDOLA approach. Thus, this work demonstrates that GONDOLA is well-suited to refine or predict the coordinates of missing residues and loops because it is both more accurate and converges more rapidly.

This study explores the development of second language (L2) fluency during a semester abroad and its relationship to the development of grammar, vocabulary, and language processing speed. It also considers the influence of individual participants' first language (L1) and pre-study abroad (SA) L2 fluency on the development of fluency during study abroad. Additionally, the study examines issues in the measurement of fluency, focusing on questions related to measuring pauses in L2 speech. Thirty-nine undergraduate students (L1 English) studying in Buenos Aires, Argentina, completed a pretest consisting of speaking tasks in English and Spanish, Spanish grammar and vocabulary tests, a picture-naming task, and a measure of sentence processing speed. Approximately three months later, near the end of their time abroad, they completed a posttest consisting of the same tasks, with the exception of the speaking tasks in English. Participants also filled out a questionnaire every other week during the semester in which they estimated the amount of time that they had spent interacting with native speakers of Spanish. Results show that participants experienced significant gains on most measures of fluency during study abroad. This finding was especially true for participants who began their time abroad with low L2 fluency. Nevertheless, students who began the semester abroad with high L2 fluency still had significantly higher fluency at the end of the semester than students who began with low L2 fluency. Looking at the relationship between L2 fluency and L2 linguistic knowledge (vocabulary and grammar scores) and language processing speed (picture-naming and sentence-matching scores), the study found a moderate relationship between pretest measures of L2 fluency and pretest measures of linguistic knowledge and processing speed. However, the results show no relationship between pre-SA linguistic knowledge and processing speed and gains in L2 fluency, and little relationship between gains in linguistic knowledge and processing speed and gains in L2 fluency. The best predictor of gains in L2 fluency was pre-SA L2 fluency. These results suggest that although there is a relationship between L2 linguistic knowledge and L2 fluency, having more advanced L2 linguistic knowledge prior to study abroad does not necessarily give students an advantage in the area of fluency development during study abroad. Regarding the measurement of fluency, the data show that learners with low and high levels of lexical-grammatical competence significantly differed from one another on all measures of rates of pauses (short and long pauses, filled and unfilled pauses, and mid-clause and end-of-clause pauses) as well as in the percent of pauses occurring in the middle of a clause. However, they did not significantly differ from one another in the percent of filled pauses. The findings suggest that measuring all of these pauses may be useful in examining L2 fluency. However, there is perhaps little or nothing to be gained from counting filled and unfilled pauses separately, as speakers' tendency to use more of one or the other appears to be more closely related to personal speaking style than to L2 ability.

Variation in the shape and position of the internal nasal floor relative to the lower border of the piriform aperture in the genus Homo has been described as having three primary shape configurations: level, sloped, or depressed. The high frequency of depressed nasal floors among Neandertals relative to other fossil and extant groups (>80%) had originally led to the idea that nasal floor depression was related to an overall enlarged nasal capsule - an adaptive feature that would have been under selection among Neandertals living in cold, glacial climates. For a variety of reasons, subsequent research has found little empirical or theoretical support for this adaptive idea. Recent research on extant humans has also demonstrated that nasal floor shape variation, unlike many other midfacial traits, does not arise until well after birth, with nasal floor depression (when it occurs) appearing at the earliest around 3.0 years of age. Furthermore, nasal floor depression was also shown to correspond with a vertically expanded premaxillary region. Thus, it was hypothesized that nasal floor depression might be related to variation in key developmental and morphological aspects of the anterior maxillary dentition. This study metrically quantifies nasal floor topography for the first time in order to more objectively examine patterns of shape variation and to test explicit hypotheses regarding potential causative factors for nasal floor variation. The variables examined include anterior tooth dimensions, dental developmental rate, aspects of midfacial shape, overall facial size, and patterns of premaxillary/post-maxillary integration. It was found that among these, only dental developmental rate was clearly correlated with internal nasal floor shape. This result indicates that aspects of anterior dental development may indeed be a causative factor in the development of nasal floor shape variation. The existing visual discrete coding system for nasal floor topography was also evaluated in light of the new, quantitative data produced by this study as well as a critical comparison of the consistency of nasal floor topography definitions used previously in the literature. While it is suggested that quantitative data are preferable to qualitative data for this trait when possible, limitations in research methods for collecting quantitative data on osteological and fossil collections remain difficult to overcome. Thus a new, two-category presence/absence based system for describing nasal floor shape is proposed.

Phytophagous (plant-feeding) insects are extremely species-rich and typically display tight host associations (meeting and mating on or near their host plant) with one or a small number of hosts. This specialized lifestyle can promote diversification through assortative mating, ultimately leading to genetically differentiated host races (host associated differentiation; HAD). It has been shown that HAD can cascade up to the parasitic wasps (parasitoids) that utilize the phytophagous insects as hosts. Cascading HAD occurs when there is genetic differentiation among parasitoids as a result of differential host plant use by their host insects. Thus, host switching can promote parasitoid diversification as well. Here, I present three studies designed to help understand aspects of parasitoid shifts to novel hosts and environments. All of the studies in this dissertation utilize the Rhagoletis complex of flies and their associated parasitoids. Specifically, I address i) the role of subtle trait variation and environmental context in predicting successful parasitoid host shifts; ii) whether parasitoid host discrimination (a trait that can influence host shifts) is an innate or learned behavior; and iii) whether contemporary patterns of host shifts among parasitoids are echoed by historical host shifts in cophylogenetic analyses of host and parasitoid genera? Towards my first aim, I present a phenomenological model developed to predict successful host shifts by parasitoids. The simulations of the model explore how environmentally mediated traits can affect successful parasitoid colonization of a new host. For my second aim, I hypothesize that behaviors impacting parasitoid host plant preferences host shifts will be genetically based rather than a learned behavior. Shifting to a new host plant has been shown to cause reproductive isolation in phytophagous insects because of strong fidelity with their host plant. Parasitoids, however, have no direct contact with the host plant as they develop entirely within the host insect. The differences in life history traits could result parasitoid host shifts being driven by random changes in host preferences. I present preliminary results suggesting that parasitoids preferentially respond to their ancestral host plant’s olfactory cues, suggesting that host preferences have a genetic basis. Finally, I present a cophylogenetic analysis of Rhagoletis hosts and their parasitoids. I find that cospeciation is the most common coevolutionary event, although there is evidence of recent host shifting that contributes to current parasitoid species diversity. The results of these studies can help us understand how host shifts can act as a potential mechanism driving diversification in parasitoids.

Effective practice determines the quality of a performance and it is essential to improving a musician's overall level of playing. Studies show that experts in the field of music display superior metacognitive skills, or the ability to think about one's thinking. Metacognition is an important skill that needs to be developed in order for a student to become a self-regulated, or independent learner. Effective practice can be improved by learning and developing metacognitive and self-regulated learning skills. An important component of self-regulated learning is reflective thinking. Reflective thinking is a mental process that contributes to deeper learning experiences, improves problem solving skills, and enhances creativity. Reflective thinking can be stimulated with writing activities. Research and theories of reflective practices informed the creation of the Reflective Writing Prompts. The Reflective Writing Prompts stimulate reflective thinking as they teach and develop metacognitive and self-regulated learning skills to make practice more effective. Each exercise prompts the student to think and write a response to questions focused on a specific skill. These prompts are based on research in music psychology and reflective thinking, with special focus on metacognition, self-regulated learning, practice habits, and reflective journaling. The pertinent studies and theories in these areas will be examined and explained in relation to each other. With this foundational knowledge in place, the Reflective Writing Prompts will be presented. The prompts are designed to support first or second year music students in their development as independent learners who practice effectively.

A Dylos DC1100 was evaluated to: 1. Establish relationship between low-cost DC1100 and higher-cost pDR 1200; 2. Develop a method to convert DC1100 particle number into mass concentration to compare with respirable and inhalable mass references. A Dylos DC1100 was deployed in a swine CAFO, along with a pDR-1200 and filter set to collect respirable and inhalable particles. Deployment was conducted from December 2013 through February 2014 in 24 hour intervals. The pDR-1200 and respirable mass concentration was used to convert the DC1100 particle count to mass concentration. Two methods of conversion were used, physical property method (Method 1) and regression method (Method 2). Direct measurements from the DC1100 and pDR-1200 had a coefficient of determination (R2) of 0.85. DC1100 particle number were converted to mass concentration using Method 1 and Method 2, the coefficient of determination (R2) was 0.72 and 0.73, respectively compared to pDR-1200. The slope of the best-fit line was 1.01 for Method 1 and 0.70 for Method 2. When the DC1100 daily averages were compared to respirable mass, the physical property method had an R2 of 0.64 and a slope of 1.10. Regression method had an R2 of 0.62 and a slope of 0.80. Both methods underestimated inhalable mass concentrations with slopes < 0.13. The Dylos DC1100 can be used to estimate respirable mass concentrations within a CAFO. Using expensive dust monitors to correct the number of particles into a mass concentration is needed to establish a correction factor for the DC1100. Using these methods, correction factors can be determine for many occupational environment, with the physical property method being preferred over the regression method.

Consider either (i) f = f1 ⊠ f2 for two Maass cusp forms for SLm(ℤ) and SLm′(ℤ), respectively, with 2 ≤ m ≤ m′, or (ii) f= f1 ⊠ f2 ⊠ f3 for three weight 2k holomorphic cusp forms for SL2(ℤ). Let λf(n) be the normalized coefficients of the associated L-function L(s, f), which is either (i) the Rankin-Selberg L-function L(s, f1 ×f2), or (ii) the Rankin triple product L-function L(s, f1 ×f2 ×f3). First, we derive a Voronoi-type summation formula for λf (n) involving the Meijer G-function. As an application we obtain the asymptotics for the smoothly weighted average of λf (n) against e(αnβ), i.e. the asymptotics for the associated resonance sums. Let ℓ be the degree of L(s, f). When β = 1/ℓ and α is close or equal to ±ℓq 1/ℓ for a positive integer q, the average has a main term of size |λf (q)|X 1/2ℓ+1/2 . Otherwise, when α is fixed and 0 < β < 1/ℓ it is shown that this average decays rapidly. Similar results have been established for individual SLm(ℤ) automorphic cusp forms and are due to the oscillatory nature of the coefficients λf (n).

The primary arithmetic information attached to a Maass cusp form is its Laplace eigenvalue. However, in the case of cuspidal Maass forms, the range that these eigenvalues can take is not well-understood. In particular it is unknown if, given a real number r, one can prove that there exists a primitive Maass cusp form with Laplace eigenvalue 1/4 + r2. Conversely, given the Fourier coefficients of a primitive Maass cusp form f on Γ0(D), it is not clear whether or not one can determine its Laplace eigenvalue. In this paper we show that given only a finite number of Fourier coefficients one can first determine the level D, and then compute the Laplace eigenvalue to arbitrarily high precision. The key to our results will be understanding the resonance and rapid decay properties of Maass cusp forms. Let f be a primitive Maass cusp form with Fourier coefficients λf (n). The resonance sum for f is given by SX(f;α;β) = Εn≥1λf(n)‑Φ(n/X) e(αnβ) where φ ∈ Cc∞((1, 2)) is a Schwartz function and α ∈ R and β, X > 0 are real numbers. Sums of this form have been studied for many different classes of functions f, including holomorphic modular forms for SL(2, Z), and Maass cusp forms for SL(n,Z). In this paper we take f to be a primitive Maass cusp form for a congruence subgroup Γ0(D) ⊂ SL(2, Z). Thus our result extends the family of automorphic forms for which their resonance properties are understood. Similar analysis and algorithms can be easily implemented for holomorphic cusp forms for Γ0(D). Our techniques include Voronoi summation, weighted exponential sums, and asymptotics expansions of Bessel functions. We then use these estimates in a new application of resonance sums. In particular we show that given only limited information about a Maass cusp form f (in particular a finite list of high Fourier coefficients), one can determine its level and estimate its spectral parameter, and thus its Laplace eigenvalue. This is done using a large parallel computing cluster running MATLAB and Mathematica

Freshwater mussels are a viable option to detect real-time changes in water quality within aquatic ecosystems. Known as ecosystem engineers, freshwater mussels are constantly filtering particles and recycling nutrients in the benthic community. Therefore, identifying their physiological responses to alterations in water quality will enable mussels to not only serve as biomonitors but help model their impact on nitrogen cycle. This research focuses on identifying how mussel gape and heart rate respond to the addition of phytoplankton following a period of limited food availability. Immediately following phytoplankton addition, mussels show a decreased gape position linked with changes heart rate. As the gape returns to an open position, overlying ammonia concentrations increase showing an end of the metabolism process. As a result, pairing physiological changes with increased concentrations of phytoplankton, freshwater mussels' impact on ammonium concentrations can be accurately predicted. By inputting experimental excretion rates combined with variations in gape position, dynamic models will be simulate ammonium concentrations in the overlying water.