Afro-Cuban Bata Drum Aesthetics: Developing Individual and Group Technique, Sound and Identity

The Lucumi religion (also Santeria and Regla de Ocha) developed in 19th-century colonial Cuba, by syncretizing elements of Catholicism with the Yoruba worship of orisha. When fully initiated, santeros (priests) actively participate in religious ceremonies by periodically being possessed or "mounted" by a patron saint or orisha, usually within the context of a drumming ritual, known as a toque de santo, bembe, or tambor. Within these rituals, there is a clearly defined goal of trance possession, though its manifestation is not the sole measure of success or failure. Rather than focusing on the fleeting, exciting moments that immediately precede the arrival of an orisha in the form of a possession trance, this thesis investigates the entire four- to six-hour musical performance that is central to the ceremony. It examines the brief pauses, the moments of reduced intensity, the slow but deliberate build-ups of energy and excitement, and even the periods when novices are invited to perform the sacred bata drums, and places these moments on an equal footing with the more dynamic periods where possession is imminent or in progress. This document approaches Lucumi ritual from the viewpoint of bata drummers, ritual specialists who, during the course of a toque de santo, exercise wide latitude in determining the shape of the event. Known as omo Ana (children of the orisha Ana who is manifest in drums and rhythms), bata drummers comprise a fraternity that is accessible only through ritual initiation. Though they are sensitive to the desires of the many participants during a toque de santo, and indeed make their living by satisfying the expectations of their hosts, many of the drummers' activities are inwardly focused on the cultivation and preservation of this fraternity. Occasionally interfering with spirit possession, and other expectations of the participants, these aberrant activities include teaching and learning, developing group identity or signature sound, and achieving a state of intimacy among the musicians known as "communitas."

STRUCTURE AND FUNCTION OF THE GROUP III CHAPERONINS, A UNIQUE CLADE OF PROTEIN FOLDING NANOMACHINES

The survival and descent of cells is universally dependent on maintaining their proteins in a properly folded condition. It is widely accepted that the information for the folding of the nascent polypeptide chain into a native protein is encrypted in the amino acid sequence, and the Nobel Laureate Christian Anfinsen was the first to demonstrate that a protein could spontaneously refold after complete unfolding. However, it became clear that the observed folding rates for many proteins were much slower than rates estimated in vivo. This led to the recognition of required protein-protein interactions that promote proper folding. A unique group of proteins, the molecular chaperones, are responsible for maintaining protein homeostasis during normal growth as well as stress conditions. Chaperonins (CPNs) are ubiquitous and essential chaperones. They form ATP-dependent, hollow complexes that encapsulate polypeptides in two back-to-back stacked multisubunit rings, facilitating protein folding through highly cooperative allosteric articulation. CPNs are usually classified into Group I and Group II. Here, I report the characterization of a novel CPN belonging to a third Group, recently discovered in bacteria. Group III CPNs have close phylogenetic association to the Group II CPNs found in Archaea and Eukarya, and may be a relic of the Last Common Ancestor of the CPN family. The gene encoding the Group III CPN from Carboxydothermus hydrogenoformans and Candidatus Desulforudis audaxviator was cloned in E. coli and overexpressed in order to both characterize the protein and to demonstrate its ability to function as an ATPase chaperone. The opening and closing cycle of the Chy chaperonin was examined via site-directed mutations affecting the ATP binding site at R155. To relate the mutational analysis to the structure of the CPN, the crystal structure of both the AMP-PNP (an ATP analogue) and ADP bound forms were obtained in collaboration with Sun-Shin Cha in Seoul, South Korea. The ADP and ATP binding site substitutions resulted in frozen forms of the structures in open and closed conformations. From this, mutants were designed to validate hypotheses regarding key ATP interacting sites as well as important stabilizing interactions, and to observe the physical properties of the resulting complexes by calorimetry.

Heritage Language Maintenance and Biliteracy Development for Immigrants' Children: A Study of Chinese Immigrants' Family Language Policy and Biliteracy Practices

This study reports on research that examines the family language policy (FLP) and biliteracy practices of middle-class Chinese immigrant families in a metropolitan area in the southwest of the U.S. by exploring language practices pattern among family members, language and literacy environment at home, parents’ language management, parents’ language attitudes and ideologies, and biliteracy practices. In this study, I employed mixed methods, including survey and interviews, to investigate Chinese immigrant parents’ FLP, biliteracy practices, their life stories, and their experience of raising and nurturing children in an English-dominant society. Survey questionnaires were distributed to 55 Chinese immigrant parents and interviews were conducted with five families, including mothers and children. One finding from this study is that the language practices pattern at home shows the trend of language shift among the Chinese immigrants’ children. Children prefer speaking English with parents, siblings, and peers, and home literacy environment for children manifests an English-dominant trend. Chinese immigrant parents’ language attitudes and ideologies are largely influenced by English-only ideology. The priority for learning English surpasses the importance of Chinese learning, which is demonstrated by the English-dominant home literacy practices and an English-dominant language policy. Parents invest more in English literacy activities and materials for children, and very few parents implement Chinese-only policy for their children. A second finding from this study is that a multitude of factors from different sources shape and influence Chinese immigrants’ FLP and biliteracy practices. The factors consist of family-related factors, social factors, linguistic factors, and individual factors. A third finding from this study is that a wide variety of strategies are adopted by Chinese immigrant families, which have raised quite balanced bilingual children, to help children maintain Chinese heritage language (HL) and develop both English and Chinese literacy. The close examination and comparison of different families with English monolingual children, with children who have limited knowledge of HL, and with quite balanced bilingual children, this study discovers that immigrant parents, especially mothers, play a fundamental and irreplaceable role in their children’s HL maintenance and biliteracy development and it recommends to immigrant parents in how to implement the findings of this study to nurture their children to become bilingual and biliterate. Due to the limited number and restricted area and group of participant sampling, the results of this study may not be generalized to other groups in different contexts.

Ready for Transition: Factors that facilitate transfer to undergraduate engineering programs among Black African and American students

This study examines the factors facilitating the transfer admission of students broadly classified as Black from a single community college into a selective engineering college. The work aims to further research on STEM preparation and performance for students of color, as well as scholarship on increasing access to four-year institutions from two-year schools. Factors illuminating Underrepresented Racial and Ethnic Minority (URM) student pathways through Science, Technology, Engineering, and Mathematics (STEM) degree programs have often been examined through large-scale quantitative studies. However, this qualitative study complements quantitative data through demographic questionnaires, as well as semi-structured individual and group. The backgrounds and voices of diverse Black transfer students in four-year engineering degree programs were captured through these methods. Major findings from this research include evidence that community college faculty, peer networks, and family members facilitated transfer. Other results distinguish Black African from Black American transfers; included in these distinctions are depictions of different K-12 schooling experiences and differences in how participants self-identified. The findings that result from this research build upon the few studies that account for expanded dimensions of student diversity within the Black population. Among other demographic data, participants’ countries of birth and years of migration to the U.S. (if applicable) are included. Interviews reveal participants’ perceptions of factors impacting their educational trajectories in STEM and subsequent ability to transfer into a competitive undergraduate engineering program. This study is inclusive of, and reveals an important shifting demographic within the United States of America, Black Africans, who represent one of the fastest-growing segments of the immigrant population.

SEQUENTIAL DECISIONS AND PREDICTIONS IN NATURAL LANGUAGE PROCESSING

Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.