cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25549/usctheses-c40-360414
title: Trinucleotide repeat instability regulated by mismatch repair proteins during DNA replication

description: Trinucleotide repeats, which are defined as three nucleotides repeated consecutively within a DNA section such as CAG and CGG, play a direct role in the etiology of ≥ 30 human diseases, including fragile X syndrome (FRAXA), and Huntington’s disease (HD). Most of these diseases alter neurological functions and are classified as progressive neurodegenerative disease. During DNA synthesis, the DNA mismatch repair (MMR) system is identified to be the major driving force leading to expansion of trinucleotide repeats. Although DNA mismatch repair is considered as a conserved rectified pathway to recognize and correct mismatched base pairs, the proteins involved in mismatch repair also play the important roles in many triplet repeats. For example, MutSβ promotes trinucleotide repeat expansion and stabilizes unusual DNA structures such as hairpins and loop-outs, which can lead to somatic mutations and ultimately to onset and progression of neurological diseases. Histone acetyltransferase p300, encoded by EP300 gene, acetylates numerous DNA repair proteins and increases the efficiency of DNA repair. It has been noted that the activity of p300 promotes trinucleotide repeat instability. In this project, the EP300 gene was knocked down in HeLa (CAG)·(CTG)₁₂ cell lines by using the CRISPR/Cas9 system. These cell lines presented a substantially decreased level of p300 expression, and trinucleotide repeat expansions were accelerated by knocking out EP300.
DOI: 10.25549/usctheses-c40-370099
title: Paraspace: collaborative programming by demonstration in mixed reality

description: The best digital interfaces make effective use of the affordances provided by the physical hardware for which they are made and the capabilities of the people that interact with them. The growing emergence of affordable mixed reality devices may herald the next big shift in interface design. Considering the new spatial affordances offered by mixed reality environments, I believe it is time to re-examine the interfaces we use to program computers. I present Paraspace, a research project that investigates how Programming by Demonstration might work in mixed reality. Paraspace is inspired by Stagecast Software's Stagecast Creator and Bret Victor's Stop Drawing Dead Fish. ❧ Please visit http://jceipek.com/paraspace/ for more information.
DOI: 10.25549/usctheses-c40-381858
title: Building leadership capacity in a higher education institution

description: This study applied the theoretical framework of transformational leadership to understand the promising leadership development practices in place at The Clemente University (CU). While there is no “right way” to build institutional leadership capacity, the purpose of this study was to determine a set of strategies empowering the next generation of leaders to pursue internal leadership opportunities. This study also sought to determine the facilitating and inhibiting factors involved in the implementation of a leadership pipeline as well as the perceptions of seven senior student affairs leaders and aspiring leaders. ❧ Using data collected from interviews, observations, and documents, Creswell’s model for qualitative data analysis was utilized to identify several themes. Findings from this study indicated that CU is successfully fostering internal leadership talent as a way to fill leadership positions. It was further revealed that the senior student affairs leaders and aspiring leaders perceived CU leadership practices as critical to building leadership capacity. This study’s results may be of interest to both senior leaders and aspiring leaders around the country determining their own approach to developing the next generation of leaders within their campus.
DOI: 10.25549/usctheses-c40-383508
title: Adaptation of FingR intrabodies for visualizing endogenous synaptic proteins in vivo

description: The ability to visualize synapses in vivo is critical for understanding the complex and dynamic properties of neuronal connections. However, currently there is no effective approach to fully achieve this. ❧ Our lab has generated molecular probes called FingRs (Fibronectin intrabodies generated with mRNA display) that specifically recognize the synaptic markers PSD-95 and Gephyrin. When fused to fluorescent proteins, these two FingRs allow excitatory and inhibitory synapses to be visualized in living neurons. ❧ The work presented herein describes the production of transgenic mouse lines and rAAV vectors that can express fluorescently tagged PSD95.FingR and GPHN.FingR conditionally. These transgenic mice and rAAV vectors are powerful tools for visualizing synapses in specific subsets of neurons in vivo. Using FingR expressing rAAV vectors, this work characterizes the synaptic properties of SST-positive neurons in adult mouse cortex, providing insight into this important subtype of interneurons. ❧ This work also describes the experiments aimed at developing a FingR that labels the axon initial segment. Although ultimately these experiments did not produce a usable FingR, much was learned during the process that may be helpful for future production of FingRs.
DOI: 10.25549/usctheses-c40-44252
title: Towards a new equation for Israel-Diaspora relations
DOI: 10.25549/usctheses-c127-629047
title: Challenging the white supremacist system: antiracist organizing and multiracial alliance in the United States

description: This dissertation is an interdisciplinary, ethnic studies project that traces a genealogy of white people and people of color using race to organize and mobilize allied grassroots resistance against the white supremacist system. Unique among projects on social movements, this study examines cases of white people and people of color organizing in allied, but racially separate, community formations -- or what the author terms ""autonomous-affiliate organizing"" -- as part of a larger, multiracial strategy to end white supremacist capitalism and imperialism. The study analyzes, in particular, the political uses of race by community organizers to build power to challenge the white supremacist system. ❧ Employing historical, textual, and ethnographic research methods, the project places community organizing at the center of antiracist theory and practice, and considers the implications of organizing for identity, agency, and power within and beyond both white and people of color communities. In order to make its case, the study mines organizational records, news articles, government documents, memoirs, manifestos, letters, films, photographs, and interviews representing the social, political, and historical context of five multiracial alliances against the white supremacist system from the dawn of the civil rights movement to the current ""post-racial"" era. ❧ The project analyzes these multiracial alliances through individual case studies, which include: 1) Southern Conference Education Fund and the Southern Student Organizing Committee in alliance with the Student Non-Violent Coordinating Committee in the South from 1960-1969, 2) Young Patriots in alliance with the Black Panther Party, the Young Lords Organization, the American Indian Movement and the Red Guard in Chicago from 1969-1970, 3) Motor City Labor League in alliance with the League of Black Revolutionary Workers in Detroit from 1969-1970, 4) Weather Underground and Prairie Fire Organizing Committee in a national alliance with the American Indian Movement, the Puerto Rican Socialist Party, and the Palestine Liberation Organization, among other organizations, from 1971-1976, and 5) the Alliance of White Anti-Racists Everywhere -- Los Angeles in alliance with the Labor/Strategy Community Center, South Asian Network, and Community Coalition in Los Angeles from 2006-2008. At a time when organizing across race succeeded in electing the first black president of the United States, but fails to resolve continuing racial and economic inequalities, this project offers an analysis of the possibilities and limitations of antiracist organizing and multiracial alliance for building mass-based social justice movements.
DOI: 10.25549/usctheses-c127-649396
title: Telecommuting, travel behavior and residential location choice: can telecommuting be an effective policy to reduce travel demand?

description: Whether telecommuting and personal travel are complements or substitutes is a key question in urban policy analysis. Urban planners and policy makers have proposed telecommuting as part of travel demand management (TDM) programs to reduce street and highway congestion. Based on small samples, several empirical studies have found that telecommuting has a substitution effect (although small) on conventional commuting, and have thus argued that policies promoting telecommuting might be promising in reducing travel. ❧ Using data from the 2001 and 2009 National Household Travel Surveys (NHTS), this study involves two large national samples to try to more accurately identify the impact of telecommuting on personal and household travel patterns. Through a series of empirical tests, this research investigates how telecommuting influences workers’ one-way commute trips, daily total work trips and daily non-work trips, how these influences differ across different MSA sizes, and how telecommuting affects household commute trips. The results of these tests suggest that telecommuting has been an important factor in shaping personal and household travel patterns over the 2001-2009 period, and that telecommuting consistently has a complementary effect on not just workers’ one-way commute trips, daily total work trips and total non-work trips, but also household total commute trips.
DOI: 10.25549/usctheses-c127-667127
title: Tree-adjoining machine translation

description: Machine Translation (MT) is the task of translating a document from a source language (e.g., Chinese) into a target language (e.g., English) via computer.  State-of-the-art statistical approaches to MT use large collections of human-translated documents as training material, gathering statistics on the patterns of correspondence between languages according to the features specified by the translation model.  Using this bilingual translation model in conjunction with a target language model, created by gathering statistics from a large monolingual corpus, a new document in the source language can be automatically translated into its target-language equivalent with surprising accuracy. ❧ Much MT research focuses on types of the patterns and features to include in a translation model.  Recent statistical MT models have used syntax trees to enforce grammaticality, but the currently popular tree substitution models only memorize sequences of words or constituents, specifying exactly what phrases to use and exactly what trees are grammatical, which does not generalize well.  Adding the operation of tree-adjoining provides the freedom to splice additional information into an existing grammatical tree.  An adjoining translation model allows general, linguistically-motivated translation patterns to be learned without the clutter of endless variations of optional material.  The appropriate modifiers, such as adjectives, adverbs, and prepositional phrases, can be grafted into these core patterns as needed to translate details.  We show that the increased generalization power provided by adjoining, when used carefully, improves MT quality without becoming computationally intractable. ❧ In this thesis, we describe challenges encountered by both word-sequence-based and syntax-tree-based MT systems today, and present an in-depth, quantitative comparison of both models.  Then we describe a novel model for statistical MT which addresses these challenges using a synchronous tree-adjoining grammar.  We introduce a method of converting these grammars to a weakly equivalent tree transducer for decoding.  Then we present a method for learning the rules and associated probabilities of this grammar from aligned tree/string training data, and empirically analyze important characteristics of the resulting model, considering and evaluating many variations.  Finally, our results show that adjoining delivers a consistent improvement over a baseline statistical syntax-based MT model on both medium and large-scale MT tasks using several language pairs.
DOI: 10.25549/usctheses-c127-669499
title: Common genetic variation and obesity: a multi-ethnic and pediatric perspective

description: This dissertation work assesses the influence of genetic variation on measures of obesity in ancestrally diverse populations and in both adults and pediatrics. Quantifying how genetic variation influences such measures elucidates the genetic architecture of body mass index (BMI). The research presented in this work has been instrumental in generalizing established genetic findings as well as implicating a new set of potential variants important in influencing longitudinal BMI change in pediatrics. ❧ Chapter two entitled ""Fine-mapping of the Association with Obesity at the FTO Locus in African-derived Populations"" examines whether variants in the FTO locus associated with BMI identified in European populations also show similar association in African derived populations. This analysis was conducted in conjunction across five large studies that in total had nearly 10,000 subjects with African ancestry. The SNPs selected for analysis were correlated with the index signal of association in individuals of European ancestry but that have varying degrees of correlation in African-derived individuals. The work was published in 2010 in the journal Human Molecular Genetics (Human Molecular Genetics. vol. 19, no. 14, pp. 2907-2916, 2010.). ❧ Chapter three entitled ""Genetic Determinants of Longitudinal BMI Change in Both Hispanics and Non-Hispanic White Pediatrics From the Children's Health Study"" is focused on testing whether BMI genetic variants identified in adult cross-sectional studies associate with cross-sectional as well as longitudinal BMI measures among pediatrics. The most recent genome-wide association (GWA) study on BMI identified thirty-two variants in nearly a quarter million subjects of European ancestry. Generalizing these established variants in pediatrics is important in order to assess whether the same genetic determinants that influence BMI in adults have an impact children. This work utilized data from the Children's Health Study, which is a longitudinal study of health outcomes in children throughout southern California. Given the longitudinal structure of the data, in addition to assessing cross-sectional genetic effects, we were able to capture the longitudinal genetic effects which had yet to be analyzed in such a manner in the literature. This work is currently under further review at the journal Human Molecular Genetics. ❧ Chapter four entitled ""Genome-Wide Association Study of Longitudinal BMI and BMI-Z Change in the Children's Health Study"" examined whether additional variants across the genome influence BMI and BMI-Z change during childhood in pediatrics.  Utilizing subjects for the Children's Health Study, we conducted a GWA study on longitudinal BMI and BMI-Z change over a fourteen year period.  We identified many novel SNPs and further assessed their effects in published studies in adult populations of European ancestry. Given the nature of GWA studies, future replication in independent samples will be required to verify our initial findings.
DOI: 10.25549/usctheses-c40-148668
title: Are juvenile delinquents valid data sources in evaluative research on juvenile justice programs?
DOI: 10.25549/usctheses-c40-154384
title: Procedures and implications of the referral process at a child guidance center
DOI: 10.25549/usctheses-c40-316896
title: High-performance network traffic measurement and analysis

description: Network traffic measurement is the process to compute the statistical characteristics of the behaviors of the flows in the network traffic. Network traffic analysis is the process to generate high-level abstraction of the flows in the network based on the data carried by the flows or the results of the network traffic measurement. Here, a flow refers to a series of packets in the network traffic sharing the common identity. Network traffic measurement and analysis are among the fundamental services of network management and security. As the network backbone (in both the Internet and data center networks) becomes more flexible, scalable and programmable, the demand for network traffic measurement and analysis in the data plane is higher. However, while the functionality of the network evolves, the performance remains a major concern for real-life deployment. In this thesis, we propose novel algorithms and architectures for high-performance network traffic measurement and analysis. We propose counter based techniques for statistical network flow feature extraction and heavy hitter detection. The deeply pipelined architectures can achieve around 100 Gigabits per second (Gbps) throughput on a state-of-the-art Field Programmable Gate Array (FPGA). Our architecture can seamlessly use external storage instead of on-chip storage to support a large number of network flows. A data-forwarding-unit is designed to guarantee the correctness of processing without sacrificing the throughput. For Sketch based anomaly detection, we first propose a generic architecture for Sketch acceleration on FPGA. We apply this generic architecture to two most widely used Sketches and achieve over 150 Gbps throughput on a state-of-the-art FPGA. We optimize the widely used existing offline algorithms for heavy hitter detection and heavy change detection. We propose the accelerators for online heavy hitter detection and online heavy change detection based on our generic architecture. Our accelerator can achieve over 100 Gbps. For network traffic classification, we first build a classification model using C4.5 decision tree algorithm. The model achieves over 97% overall accuracy when classifying eight major applications including encrypted applications, Peer-to-peer applications, and streaming applications. Then, we present high-throughput algorithms and architectures on both FPGA and multicore platforms. We optimize the decision tree to reduce the number of comparisons and further flatten the decision tree to multiple search trees to eliminate the adverse effects caused by the imbalances of the decision trees. On multicore processors, our algorithms achieve over 100 Million classifications per second (MCPS) throughput. On FPGA the throughput is over 10000 MCPS.
DOI: 10.25549/usctheses-c40-331696
title: A geographical assessment of the Santa Monica Mountains North Area Community Standards District Vineyard Ordinance

description: In early 2015, a surge of vineyard applications alerted Los Angeles County to a potentially large-scale habitat change in the Santa Monica Mountains North Area. The County took action by placing a ban on all applications until an ordinance could be written to protect the natural environment of the mountains. Then in December 2015, the Los Angeles County Board of Supervisors adopted a vineyard ordinance regulating the presence of vineyards in the Santa Monica Mountains North Area. The ordinance limits the size of vineyards and creates a set of regulations for landowners to follow. Several of these regulations have spatial manifestations that can be analyzed through the use of GIS. This project sought to visualize these regulations spatially and to evaluate their effectiveness in protecting the habitats of the Santa Monica Mountains North Area. This project evaluated the ordinance’s effectiveness in three ways: (1) by determining the amount of land protected by the ordinance as a whole; (2) by quantifying the impact of each regulation spatially and understanding how they compare to each other; and (3) through a statistical evaluation of the amount of vegetation saved due to the ordinance. The ordinance was effective in achieving its goal of preserving the natural habitat of the North Area by protecting 16,223 acres, which is an 88% drop in potential habitat change. The ordinance also protects nearly all vegetation classes by 50% or more, with 13 of them being fully protected. The natural habitat of the Santa Monica Mountains North Area is a rare and fragile Mediterranean ecosystem that should be closely monitored by its residents and local government. This project gives the community a quantifiable representation of the ordinance and its effects.
DOI: 10.25549/usctheses-c40-354993
title: Stochastic dynamics of synaptic membrane protein domains

description: Neurotransmitter receptor molecules, concentrated in synaptic membrane protein domains along with scaffolds and other kinds of molecules, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo (KMC) simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Finally, inspired by our results on synaptic domains, we investigate the diffusion of particles through media with spatially inhomogeneous particle hopping rates, both in the presence and absence of steric constraints on the particle density. Based on the deterministic parts of the corresponding lattice Langevin equations we obtain general solutions for the fractions of all particles in regions with distinct particle hopping rates, for arbitrary spatial dimensions of the system and numbers of distinct particle species. We confirm our general solutions using KMC simulations. The work described in this thesis sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.