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Experimentally Testing Computational Predictions of Liquid-Liquid Phase Separating Proteins in Yeast
No full textLiquid-liquid phase separation (LLPS) is a phenomenon in which a single homogeneous solution de-mixes and forms two distinct solutions. In biological systems, LLPS is demonstrated by particular proteins and their substrates de-mixing from the cytoplasm and forming droplets enriched in these biomolecules. LLPS is implicated in a variety of processes, such as cellular stress responses and disease progression. Despite the importance of LLPS, it is difficult to predict whether a protein can undergo LLPS from its sequence alone. Multiple algorithms exist that are capable of predicting whether proteins are capable of undergoing LLPS. The goal of this project is to develop a screening assay to test the predictions made by one such algorithm, ParSe, as well as to test whether poorly studied proteins demonstrate LLPS. To test these proteins, they will be expressed with a green-fluorescent protein tag in order to be visible under a fluorescent microscope. Cytoplasmic, non-LLPS proteins are expected to appear as a uniform diffuse fluorescent signal throughout the cell, while LLPS proteins are expected to appear as bright, discrete fluorescent spots. Proteins to be used in the development of the assay were identified using a pre-defined set of criteria, and cloning of four of these genes into an appropriate plasmid vector was initiated using gap repair cloning. Two out of the four desired plasmid constructs were made and sequence verified. With these sequence-verified plasmids and higher-throughput cloning method established, the project is now ready for expression and microscopy screening experiments.Chemistry and Biochemistr
Creative Liberation: The Transformative Power of Black Art
No full textIt is no surprise that the civil rights movement will always be an important time in the history of America, but this book shines a light on the neglected voices of the black arts movement that served as the heartbeat of the culture. During this time there was a shift in the culture and the attitude of African - Americans. Oftentimes this shift is marked by the music, poetry, art, and films of that day. Verifying that Black Artists always could shape, mold, and define not only a moment but also a generation. Often created to inspire pride within their people. In addition to that, we know that artists were pivotal to the community due to comments made by political leaders, such as Malcolm X when questioning why black performers, artists, and poets are considered leaders of the African American community. Proving that it is undeniable the impact that these artists had during this time. Like many minority groups, African Americans have found solace within their art. The ability to reflect on their daily lives, escape from reality, and encourage people to rethink the systems of racism and sexism found within our society.Art and Desig
Environment Emotion Recognition for Children with ASD
No full textAutistic children frequently encounter distinct difficulties in identifying and interpreting emotions, particularly when affected by their environment. Conventional emotion recognition algorithms predominantly emphasize facial expressions, overlooking the significant influence of environment context on emotional perception. This research presents a novel approach for environment-aware emotion recognition specifically designed for ASD applications, integrating environmental and facial cues to develop a more contextually thorough model. We explored the potential of utilizing a synthetic dataset generated by the EEF-GAN to improve emotion recognition as part of this thesis. However, due to limitations in exploring different feature fusion techniques and generating high-quality synthetic images, the primary focus shifted toward developing the EER Classification Model, which incorporates transfer learning and feature fusion methodologies to categorize environmental and emotional aspects. This research establishes groundwork for future developments in environment-aware emotion recognition. Future research may investigate more advanced feature fusion methodologies, including adaptive or attention-based fusion, to enhance visual realism. Augmenting the dataset to incorporate diverse surroundings, emotional fluctuations, and more authentic data might improve the model's resilience. Moreover, incorporating supplementary modalities, such as auditory signals or bodily movements, could establish a multimodal framework for thorough emotional analysis. These advancements would improve the model's precision and relevance in practical environments, particularly in benefiting autistic children.Engineerin
Spaceflight-Induced Changes in Polymicrobial Biofilm Structure and Silver Susceptibility
No full textBiofilms, surface-adherent microbial populations, represent a common mode of bacterial growth in nature and in built environments, including the water recovery system (WRS) in spacecraft. Several factors have been associated with biofilm structure, including shear forces associated with turbulent flow, microbial community composition, and available nutrients and other culture conditions. Here we investigated biofilm formation of a mixed Escherichia coli F11-mCherry - Pseudomonas aeruginosa PAO1-gfp culture during microgravity in spaceflight, and full gravity (ground control), in BioCellTM flight hardware with an artificial urine medium. At the early 4-d time point in spaceflight samples, the gas-permeable Teflon membrane on the BioCell hardware surface was heavily colonized by green-fluorescing P. aeruginosa, whereas the underlying 316L stainless steel coupon had a notable red-fluorescing E. coli population. The 4-d spaceflight P. aeruginosa Teflon biofilm had a clumped appearance with regions of higher cell density (microcolonies) and low cell density (water channels). Interestingly, the overall structure resembles Van Gogh’s Starry Night. In contrast, the corresponding 4-d ground control P. aeruginosa-dominated Teflon biofilm was completely uniform with no obvious clumping. At later time points (14-d and 117-d), P. aeruginosa became much more prominent on both Teflon and stainless steel surfaces, the unique spaceflight biofilm structures were no longer observed and the overall populations decreased. Based on our results and similar findings of other investigators, we propose that microgravity conditions during spaceflight represent a factor that can influence biofilm structure in some culture conditions.Biolog
Understanding the Academic Literacy Engagement of Students with Intersectional Identities
Get PDFThe multiple case study featured in this dissertation study presented the experiences of students from intersectional backgrounds as they navigate through developmental literacy or integrated reading and writing (INRW) courses at a four-year public university in Texas. The theoretical framework that best supports and highlights the experiences of students who possess intersectional identities, particularly from marginalized communities, includes intersectionality as conceptualized by Crenshaw (1989), culturally sustaining pedagogy (Paris, 2012), raciolinguistic ideology (Flores & Rosa, 2015), and transactional theory (Rosenblatt, 1994). Participants were primarily selected through convenience sampling as a result of my affiliation with the developmental literacy program at a large public university in Texas. The goal of this study is to contribute meaningful research on the experiences of students with intersectional identities to administrators and instructors of developmental literacy programs to broaden the expression of students progressing through literacy course sequences where social justice and culture is inclusive of many identities.Curriculum and Instructio
The Role of Organizational (In)Action and Social Capital in Disaster Recovery Pathways
No full textNo abstract prepared.Anthropolog
Enhancing Energy-Efficiency in Cloud Computing and Green Software Design through Accurate Power Measurement for Heterogeneous Hardware
No full textThe growing energy demands of modern computing, from software development to expansive cloud platforms, necessitate accurate power measurement tools to optimize energy usage and address environmental concerns. Although a variety of frameworks and methodologies have been developed to measure power consumption of software, respective inherent limitations of each of these methods make those unsuitable and, in many cases, inapplicable for deployment environments. Technologies relying on methods like Thermal Design Power (TDP) fall short due to their large inaccuracies. Whereas Running Average Power Limit (RAPL) is restricted by its administrative access requirements despite its high precision [1]. It is leaving developers, users, and software-based service providers without practical means to measure or optimize energy usage. To bridge such technology gaps, we leverage ML-based methodologies to propose precise and convenient real-time power consumption estimation technology which is capable of performing irrespective of deployment environments or host specifications. We have taken a novel approach of combining the decision tree algorithm with a multi-variable regression model to adapt to the host environment and capture power trends with precision in the highly heterogeneous computer ecosystems to-date. Our proposed GreenCode-PowerMeter (GCPM) is integrated within the popular platform of VS Code to let its 14 million users estimate power consumption across diverse programming languages and hardware configurations directly within the IDE with a mean absolute percentage error of only 0.075%. This enables developers to adopt energy-efficient coding practices without the complexity of accessing administrative privileges.
Meanwhile, cloud computing's rapid expansion since the end of the past century has raised significant energy consumption and environmental concerns. Accurate power measurement is crucial in addressing such concerns, as precise data helps both cloud providers and consumers to optimize usage by enabling informed resource allocation to meet sustainability goals. Complementing the effectiveness of GreenCode-PowerMeter, we extend the ML-based approach for addressing the challenges of providing an accurate power consumption method in diverse cloud environments where administrative access is unattainable. We propose Cloud Power Meter (CPM) which is trained on 34 cloud instances from providers like AWS, Microsoft Azure, and Google Cloud Platform. CPM achieves a mean absolute percentage error of 0.31% while tested on the dataset that is constructed from the real-world cloud processors’ power measurements based on the CPU benchmarks from SPEC (Standard Performance Evaluation Corporation). The decision tree guarantees performance capacity across heterogeneous cloud environments by locating the ‘CPM Instance’. To demonstrate its efficacy, we perform and present an analysis on 2.7 million Virtual Machines (VMs) traces on Microsoft Azure, identifying a significant 25,000 kWh energy-saving scopes from 17% inefficient allocations in a month.
Both GCPM and CPM outperform the widely deployed TDP-based methods and closely align with the RAPL. Together, GCPM and CPM provide scalable, accurate, and accessible solutions for power measurement in modern computing environments. By addressing inefficiencies and enabling informed decision-making, these tools empower developers and cloud providers to optimize resource allocation, reduce carbon footprints, and contribute to sustainable computing practices.Computer Scienc
Social Media Campaign Strategies: A Case Study of Political Issue Framing by 2024 Presidential Candidates in Ghana
No full textDespite extensive scholarship on social media political party strategies or intra-party-political campaigns across digital platforms, it remains relatively unexplored how individual presidential candidates adopt social media to frame their messages on key political issues for voter engagement, especially in the West Africa region. To fill this gap, this study examines how the two major presidential candidates in Ghana, John Mahama of the National Democratic Congress (NDC) and Mahamudu Bawumia of the New Patriotic Party (NPP), use social media platforms to frame key political issues during the 2024 election campaign. Using framing theory (Entman, 1993) and digital multimodal discourse analysis (Stewart et al., 2023; Keshavarzian & Stewart, 2025) as the conceptual and methodological frameworks, the study examines content on X (formerly Twitter), Facebook, and Instagram, with a focus on issues related to the economy and education, while also assessing how platform-specific affordances shape the presentation and visibility of these frames. The findings of the study reveal three core dynamics in the framing strategies of both candidates: (1) contrasting economic narratives (‘Resetting Ghana’ vs. ‘It Is Possible’), (2) competing visions of education (reform vs. continuity), and (3) platform specific engagement patterns. These findings offer insight into how political actors leverage digital affordances beyond simple messaging tools into structured framing mechanisms and strategically construct narratives to shape public discourse and influence voter engagement.Journalism and Mass Communicatio
Failure in the Writer's Journey: How New College Composition Instructors Experience Failure as Writers
No full textThe value of failure is often reduced to a mere learning opportunity, especially in writing, but as composition scholar Allison Carr has argued, this narrative masks the complex emotional landscape that renders failure a profoundly affective and transformative experience for writers. This qualitative case study uses phenomenography and mindset theory to analyze the complex experiences of failure among three new college composition instructors at Texas State University. The first writer, Candace, endured intimidation thanks to what she perceived as exclusively negative feedback from her committee chair on her master’s thesis, an experience emerging from tensions within the rhetorical situation of the thesis genre. The second writer, Alex, experienced self-doubt while navigating writing processes impacted by dyslexia but, through consistent practice and time management, learned a lesson in patience while navigating these writing processes. The third writer, Malcolm, experienced exhilaration while facing failure, realizing his true identity and future as a writer. This thesis ends by urging more college composition instructors to reflect on their own writer’s journeys as impacted by failure so they can empathize with their students’ struggles and thereby foster process-centered perceptions of writing wherein failure becomes a subject of critical reflection.Englis
Utilizing finite element analysis to analyze ice hockey skating blade design for enhanced performance and safety
No full textSkate blades hold the key to unlocking peak performance in ice hockey, influencing every stride, turn, and sprint on the ice. This research studies how adjusting different zones of the skate blade could help athletes perform better and lower their risk of ankle injuries. The main objectives of this research are to optimize the skate blade’s geometry based on the dynamic coefficient of friction, evaluate the effects of hollow depth and multi radius profiles on skating performance and develop surface-specific blade profiles for different ice conditions. Furthermore, this study analyzes biomechanical stress on the ankle joint to prevent injuries and validates these improvements through a combination of experimental and computational methods. Preliminary findings showed consistent DCOF values during experimental trials, providing reliable data for further simulations.Engineerin