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Jiujitsu as a Form of Behavioral Activation to Reduce Negative Affect
No full textRoutine aerobic exercise typically improves mood, anxiety and depressive symptoms. Some research has expanded this concept to include martial arts. Jiujitsu has become a recent area of focus for studying improvements on mental health. However, there is sparse literature on the subject and there is little research measuring potential benefits for the general population. It seems plausible that Jiujitsu could function as a mechanism of Behavioral Activation to improve mental health because of similarities in the training environment and skill acquisition associated with Jiujitsu, and because research suggests that BA and martial arts have an association with self-efficacy, which has been associated with improvements in mood, anxiety, and depressive symptoms. This study used longitudinal self-report surveys to measure changes in score on the PHQ-9, PANAS, and GAD-7, across three groups of participants, those participating in an aerobic exercise group, those participating in Jiujitsu, and a control group not participating in group exercise. Mixed design ANOVA was conducted with participants who responded at all three time points (n = 16) and for participants who responded to at least two time points (n = 23). Results indicated no significant difference between the Jiujitsu group and the control group. Participants in the aerobic group did not complete follow-up surveys, therefore comparisons between Jiujitsu and aerobic exercise groups could not be made. The results of this study may be due in part to the lack of participation, and high attrition (54% attrition by the 4th-week, and 68% by the 8th-week). This study did not find sufficient evidence to suggest significant change in mood, anxiety, or depressive symptoms from participation in Jiujitsu.Psycholog
Devil Town, Texas: A Southern Gothic Twist on the History of San Marcos through Television Writing
No full textDevil Town, Texas, is a serialized TV drama of supernatural thriller and southern gothic suspense that takes place in the fictionalized version of San Marcos, Texas, still keeping its rich culture and history, adding in religious and mythological influences to bring out the elements of southern gothic suspense and supernatural thriller. The pilot episode focuses on Dante McCallum, a college student at Texas State University with near-prophetic visions after a near-death experience from his childhood triggered some otherworldly presence to hunt him. After the disappearance of one of his friends, Marcus Sanders, Dante and his other roommates, Zion Church and Erik Lawson, start to uncover the twisted and supernatural forces at work within this town. The purpose of this project was to develop my craft in dramatic writing through new mediums and utilize the environment and culture around me to strengthen my storytelling. I have always drawn my inspiration from epic legends and folktales from other cultures that end up shaping the world around them after attempting to explain the impossible and inconceivable. However, recently, I have also been able to gather my writing style through the southern part of the world that I live in, and believe that it has been an integral part of my growth as a writer. Stories can change the course of civilization as we live in them, and I strive to reinvent the world around me by asking how it can be seen through other lenses, what stories can be told as we move through life, and what can be discovered with imagination.Theatre, Dance, and Fil
The Rohingya Genocide Case and Genocide Accusations
No full textStates make different decisions on when they consider something a genocide based on their own ties to other states. These ties can affect how they respond to atrocities in the international system. The way they respond can be altered to fit their needs, and the perceived needs of their ally, foe, or their own state. When violations are committed, more states are likely to condemn the situation if they themselves do not have the same types of violation. Diplomatic, economic, and political ties can all change how a state responds to an atrocity.Political Scienc
How Mate Value Discrepancies Influence Conflict, Competition, Jealousy, and Mate Retention: A Comparative Analysis of Consensually Non-Monogamous and Monogamous Relationships
No full textMate value discrepancy (MVD)—the perceived difference in desirability between partners based on traits such as appearance, personality, and status—has been linked to greater conflict and jealousy in monogamous relationships. However, little research has examined whether similar patterns occur in consensually non-monogamous (CNM) relationships, where partners agree to engage in romantic and/or sexual relationships with others. In this study, participants in CNM (n = 200) and monogamous (n = 312) relationships reported their own and up to two partners’ mate value (MV), conflict, jealousy, intrasexual competitiveness, and relationship maintenance strategies (assessed using the Multi-Partner Maintenance Scale). Across relationship types, participants who rated themselves as higher in MV than their partner reported more conflict and intrasexual competitiveness with their primary partner. CNM experience was associated with more positive reactions to a partner’s extra-pair interactions, while those in monogamous relationships reported greater mate retention and intrasexual competitiveness. Across both relationship types, greater disclosure of extra-pair attractions, comfort discussing jealousy, compersion, and shared extra-pair sexual experiences predicted lower conflict and jealousy. In contrast, endorsement of partner hierarchy was associated with higher conflict, jealousy, and mate retention. Intrasexual competitiveness was negatively associated with attraction disclosure, jealousy, communication, childcare investment, compersion, and sexual health practices, and positively associated with hierarchy. These findings suggest that although MVDs are linked to conflict in both monogamous and CNM relationships, relational outcomes in CNM dynamics may be buffered or intensified by individual differences in CNM experience, competitiveness, and engagement in relationship maintenance practices.Psycholog
Math Apps and Their Relationship to Student Motivation and Mathematical Identity
No full textDespite the increasing prevalence of mathematics learning application use in K–12 schools, there is limited research on non-achievement related outcomes of mathematics learning applications, or math apps. Because elementary students are a common population that utilizes math apps, and mathematical identity and motivation are acknowledged as important factors of students’ success and well-being, this qualitative multiple case study examined the relationship among third graders’ use of math apps and their mathematical identity and motivation. Five third-grade students were purposefully selected as contrasting case studies from a technology-rich classroom on the basis of their varied mathematical identities and motivation. Over the course of a semester, the participants were interviewed twice (start and end of the semester), given weekly surveys, and field notes were collected during weekly observations documenting the activities, engagement, and interactions of the five case study participants.
Drawing on Cribbs et al. (2015) framework of math identity as consisting of students’ views of mathematics, views of self, and views of others’ recognition, data was analyzed for these three components of math identity. Drawing from self-determination theory, I analyzed motivation using the constructs of autonomy, competence, and relatedness, and the interest task value from expectancy-value theory’s subjective task values. In addition to using a priori codes drawing from theories of identity formation and motivation, I used thematic analysis to create descriptive subcodes and capture nuances in students’ experiences and views. Math app data was also analyzed to understand participants’ engagement and proficiency with various math apps throughout the duration of the study.
On the basis of the analyses and findings presented in Chapter 4, I have reached the following conclusions: (a) Math apps are related to students’ mathematics identities and appear to have a particular influence on students’ views of what mathematics is as evidenced by students’ reported experience and my observations; (b) Students’ values and experiences of the motivation components of autonomy, competence, relatedness, and interest varied; (c) Students were, in general, motivated by non-mathematical features of math apps and the classroom context in which math apps were used, but the relationship between math apps and motivation played out in different ways for different students; (d) Student engagement with math apps varied by student, by app, and across the semester; and (e) The construct of congruence emerged as a potential explanatory construct in the cross-case analysis that proved helpful explaining why participants responded positively, negatively, or minimally to a semester of math app use.Mathematic
Perceived Burdensomeness and Acute Stress: An ERP Examination of Dual Process Conceptualizations of Suicidal Ideations
Get PDFOver the past few decades, tremendous strides have been made towards understanding the consequences of mental health disorders. With this, more nuanced antecedents of detrimental outcomes (i.e., suicide) have come to light. Specifically, perceived burdensomeness has been integrated into prominent theories seeking to understand factors contributing to suicide. Despite this, a significant amount of variance between suicidal ideation and attempt remains. Therefore, the present study sought to examine the role of stress on dual processes (i.e., automatic and controlled behavior) within an antecedent of suicide – perceived burdensomeness. Fourteen students who scored a clinically significant score 12 on the perceived burdensomeness subscale of the Interpersonal Needs Questionnaire participated in an in-person study. The study was broken up into two three-hour visits, which required the participant to complete questionnaires, either a math/computer game (depending on the session), and “word” tasks, while their brain activity was recorded. The word tasks consisted of three sets of stimuli: “negative” (i.e., burdensomeness related words), “neutral”, and “non-words”. Participants were instructed to press a button on a keyboard when they saw a word from one of these groups. Furthermore, one session was designed to induce stress, the other was not. Both behavioral and physiological data offered evidence towards biases for negative stimuli (i.e., stimuli appealing to both self-relevance and negativity biases). However, when cognitive resources were depleted following a stressor, these biases remained unaffected. These findings hold relevance as the first test of dual processes within conceptualizations of suicide. Future work would be fruitful in expanding sample size, recruiting a control group, and testing the effects of different types of stress on dual processes.Psycholog
Exercisers' perceptions of music, movement, and performance: Insights for biomechanical interventions
Get PDFNo abstract prepared.Health and Human Performanc
NeuroNest - The safety sssessment tool for sging environments
No full textNo abstract prepared.Art and Desig
Efficient Large-Scale Graph Neural Network Training
No full textThis dissertation focuses on efficient training of graph neural networks (GNNs) on largescale graphs. Graphs and networks are ubiquitous in various domains, such as web graphs, social networks, and transportation networks. Mining graph-structured data and learning on graphs have been central to understanding the structures and dynamics of such networks and facilitating the use of graph-structured data for many different applications. Particularly, GNNs have emerged as a powerful tool for machine learning on graphs and have attracted great attention in recent years. GNNs have been shown effective not only for several graph-related learning tasks, such as node classification, link prediction, and graph generation, but also in other domains, such as natural language processing, computer vision, and cybersecurity. However, despite the rapid growth in the field, scalability remains a critical issue in building GNN models for large graphs, as real-world graphs are continuously growing, often reaching sizes of billions of nodes and edges. Therefore, it is desirable to examine existing GNN training frameworks to understand their limitations, especially when it comes to training GNN models for large graphs, and develop efficient solutions to scale GNN training to large graphs.
In this dissertation research, we first develop a benchmark suite named GNNpS, which allows us to systematically examine the existing GNN models and frameworks in order to identify their characteristics and limitations. Next, we develop SDT-GNN, a memory-efficient distributed GNN training framework for GNN training on large graphs under limited computational resources. SDT-GNN is empowered by our novel streaming-based graph partitioning algorithm named SPRING to partition large graphs effectively and efficiently. SDT-GNN with SPRING shows up to 24× smaller memory footprint than mainstream distributed GNN frameworks without sacrificing the per-epoch training speed and model accuracy. Finally, we delve into the performance of distributed GNN training for link prediction and propose SpLPG, a communication-efficient framework, which reduces the communication overhead by up to 80% while mostly preserving link prediction accuracy.Computer Scienc