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From Silence to Strength: Elevating the Critical Role of the Voices of Students Experiencing Homelessness to Impact School-Based Supports
No full textThe plight of students experiencing homelessness in the United States is reflected in both student outcome data and in personal narratives shared of their experiences. Those student experiences and the reasons for homelessness are often quite complex and layered. Educational outcome data reveal students experiencing homelessness consistently underperform their housed peers in many academic indicators and are twice as likely to experience a mental health challenge. Further, inequitable school outcomes result in a greater chance of experiencing attendance concerns as well as a lower high school graduation rate, impacting the ability to access a college experience. This study explores the impact of school programs and services on high school students experiencing homelessness in public education through data collected on how the students experience school, perceive school-based supports, how school staff behaviors impact the student's connectedness to school, and how homelessness impacts how the student perceives themself. Review of literature examines the impact of federal policy on students experiencing homelessness, the impact of positive school climate, how homelessness impacts socio-emotional development, and the role school-based programs and school staff can have on the educational experience of students experiencing homelessness. Student voice informs the findings of barriers, the impact of school staff, perception of homeless program support, the impact of school staff interactions, and how interactions impact the student's connectedness. Finally, the study delves into how the state of homelessness impacts a student's identity, finding that students perceive themselves negatively ten times more than they perceive themselves positively. The discussion includes recommendations for educational leaders at all levels, including district and site, on how to impactfully serve and support students experiencing homelessness. Keywords: cultural proficiency, education equity, educational leadership, homeless students, McKinney-Vento, poverty, students experiencing homelessnes
Sustainability through Incentives: An Exploration of Local Government Sustainable Energy Sourcing through Public Policy
Get PDFSenate Bill (SB) 100 is the State of California law regulating local governments and energy companies to have a portfolio of 100% renewable energy sources by the year 2045 (California Legislative Information, 2024). The aim of this study is to discover if there is a possible combination of both behavioral economic policies and sustainable energy sector policies California could use toward local governments to better manage the implementation SB 100. Research through a systematic literature review shows that various types of policies have been used to shape the behavior of individuals and corporations, but little work has been done in understanding how central governments can shape local governments selection of energy sources. The study shows that working with local governments as partners has powerful effects when it comes to sustainable outcomes (Ejderyan et all, 2019), and there is an opportunity for local governments to gain assistance from the state to get closer to the preferred regulation of SB 100. Combining a command-based policy with choice architecture provides an opportunity for positive impacts on local energy portfolios and eventual emissions
DACA: A Path To Citizenship
No full textThis literature review examines the Deferred Action for Childhood Arrivals (DACA) policy, which provides temporary relief from deportation for eligible undocumented immigrants who entered the United States as children. The review synthesizes existing research on the short-term benefits of DACA, focusing on its educational and employment advantages and highlighting the systemic barriers that hinder recipients from attaining permanent legal status. Additionally, the review discusses how the legal protections afforded by DACA enhance employment prospects, providing recipients with the opportunity for stable employment and economic stability. This literature review identifies gaps in the current literature regarding the long-term implications of these barriers and their impact on the overall well-being of DACA recipients. It advocates for further research to explore potential policy reforms that could provide a pathway to permanent residency for this vulnerable group. Keywords: DACA, undocumented youth, immigration policy, citizenship pathways, barriers, educational and economic impact, and integration
Investigating the Impact of Telework Practices on Public Sector Employees
Get PDFTelework has been around since the 1970s. When the COVID-19 pandemic arose in the United States, many organizations were required to implement telework practices to continue providing services. This graduate project intends to investigate the impact flexible work arrangements such as telework practices have had on public sector employees in areas such as job satisfaction, work engagement, productivity, work-life balance, and organizational commitment. This project utilized a systematic review of literature to better understand the impact flexible work arrangements has on public sector employees in areas such as job satisfaction, work engagement, productivity, work-life balance, and organizational commitment and the effects it has for public sector organizations. The analysis of the literature demonstrated that there are advantages and disadvantages to flexible work arrangements such as telework practices. As there are mixed results of the impact flexible work arrangements have on public sector employees, this study will help public sector organizations determine whether it is beneficial or not to implement a flexible work arrangement
An Investigation of Mus81-Mms4 and Rad1-Rad10 Recruitment to Subcellular Structures in the Absence of Slx4
No full textMaintaining genomic integrity in the face of DNA damage is of the upmost importance for the health of a cell. Damage to DNA can take the form of double-strand breaks (DSBs) that are capable of causing mutations if not repaired. There are various pathways that cells may utilize for repairing DSBs; one used by eukaryotes, including Saccharomyces cerevisiae is the classical Double-Strand Break Repair (DSBR) pathway. DSBR utilizes an intact chromosome as a template for repairing the break, during which an intertwined intermediate structure called a Holliday Junction (HJ) forms, which may progress to form anaphase bridges if unresolved. The resolution of HJs is performed by multiple endonucleases, including Mus81-Mms4, Yen1, Slx1-Slx4, and potentially Rad1-Rad10. Mus81-Mms4 and Rad1-Rad10 have been shown to interact with DNA via the protein Slx4, independent of its role as an endonuclease when bound to Slx1. This project aimed to determine whether Mus81-Mms4 and Rad1-Rad10 required the Slx4 protein for cell cycle-dependent recruitment to DNA damage sites, or other subcellular structures. To achieve this, an SLX4 knockout mutant yeast strain containing fluorescently-labeled proteins was created. A transformant yeast strain was crossed with a strain containing fluorescently-labeled Mus81, Rad10, and Hta1, with Hta1 meant to label chromatin. Cultures were synchronized by α-factor at the G1/S phase boundary and returned to cell cycle following incubation with a damaging agent, either Zeocin or methyl methanesulfonate (MMS). Cultures were sampled at eleven timepoints, and investigated using flow cytometry and fluorescence microscopy. Treatment by either Zeocin or MMS caused the yeast cultures a delayed return to cell cycle following α-factor arrest and release back into cell cycle. Fluorescence microscopy revealed a lack of Rad10-YFP and Hta1-CFP nuclear foci in the absence of the Slx4 protein, in both damage-induced samples and uninduced controls. Contrasting this was the observation that Mus81-RFP foci were increased following the DNA damage, suggesting that Mus81-Mms4 may not require the Slx4 protein for localization to foci representative of repair sites, or that Mus81-Mms4 is sequestered away from repair sites in foci in the absence of Slx4. An increase in chromatin bridges containing all fluorescent labels was observed following damage induction, for both Zeocin and MMS samples
Investigating the Effects of Bent Fault Geometry and Surface Topography on Earthquake Propagation and Ground Motion along Double Compressional Bends
Get PDFDouble bends are nonplanar strike-slip faults that consist of a linking fault segment connecting to two parallel fault segments at some bend angle. Dynamic compression, in which both sides of the fault move towards each other and locally increase normal stress, occurs at the bends and defines the double bend as a double compressional bend (DCB). Transpression can occur along the linking segment statically due to fault orientation within a regional stress field. The combination of dynamic compression and transpression form high ground surface topographies along the linking segment. Fault geometry affects the endpoints of rupture lengths and influences ground motion. Recent studies suggest that surface topography also affects rupture behaviors and ground motion, but with minimal physical explanations. This project is a dynamic rupture modeling geometrical parameter study that investigates the combined effects of bent fault geometry and high surface topography on rupture propagation and ground motion on DCBs. Our primary variables are fault bend angle, and surface topography height and width. We ran our models in the 3D finite element dynamic rupture simulation software, FaultMod. Our results show that bend angles have a larger role in controlling rupture length than surface topography, whereas surface topography have a larger effect on ground motion than bend angles. Decreasing bend angles and increasing surface topography dimensions allow the fault to slip further. Bends affect rupture behavior because of dynamic compression, disrupted rupture directivity, and bend angles influence the strength of transpression. Increasing bend angles limits how far ground motion is distributed along the fault whereas including surface topography disperses ground motion further along the linking segment. High surface topographies experience stronger shaking compared to the adjacent flat areas. High surface topographies trap seismic waves, producing additional areas of slip ahead of the rupture front endpoint and amplifying ground motion. This additional slip could lead to overestimating paleoseismic and potential future earthquake magnitudes. Our results suggest that probabilistic rupture hazards should consider the effects of bends and surface topography on potential earthquake rupture lengths. This study affirms that surface topography is an important site condition factor for ground motion hazard assessments
Breaking Boundaries: The Evolution of Violin Techniques and the Demands of Modern and Contemporary Music
Get PDFAbstract Breaking Boundaries: The Evolution of Violin Technique and the Demands of Modern and Contemporary Music By Sahand Zare Master of Music in Music, Performance This thesis delves into the evolving demands of violin technique in modern and contemporary music and examines how composers have continuously expanded the expressive potential of the instrument. While I briefly touch upon various topics, each represents a facet worthy of more extensive research. My journey as a master's student in classical violin performance, enriched by coursework and comprehensive research on the topic of evolution of music, avant-garde practices, and contemporary styles, underscores the importance of this topic to my academic and artistic development. By analyzing extended techniques and the esthetic ideas behind them, I aim to highlight the dynamic interplay between technical evolution and artistic intention. This study draws on key sources, including the works of Max Paddison, Irène Deliège, Patricia and Allen Strange, and Peter Rosser, to contextualize these transformations within a broader aesthetic framework. Such analysis illustrates how composers leverage innovative timbres and sound effects to enrich musical narratives and challenge traditional soundscapes. My personal experiences as a performer and composer, coupled with collaborations with non-classical musicians outside of academia, have fostered a keen interest in the diverse aspects of contemporary music-ranging from technical execution to aesthetic considerations and philosophical inquiries. For instance, the transformation of vibrato from a controlled classical technique to a versatile, expressive tool in contemporary compositions exemplifies this shift and reflects the broader evolution within the field. Through a dual lens of scholarly analysis and personal insights, this thesis endeavors to provide a nuanced understanding of how violin techniques have adapted to meet the unique demands of modern compositions. Ultimately, I assert that the intersection of technique, artistry, and innovation is vital to the ongoing dialogue surrounding contemporary music, making this exploration both personally meaningful and academically significant
Energy Extraction via Magnetic Reconnection in a Rotating Black Hole
No full textRelativistic reconnection is a very efficient mechanism of magnetic energy conversion and particle acceleration, thus a primary candidate to explain nonthermal emissions from pulsar wind nebulae, gamma-ray bursts, and active galactic nuclei. Recent studies have shown magnetic reconnection as aviable mechanism for energy extraction in Kerr and Kerr-de Sitter black holes. Here, we extend the relativistic magnetohydrodynamics of general relativity to matter in negatively curved spacetime. In particular, we highlight the effects of the cosmological constant (Λ) and its role in energy extraction via magnetic reconnection. We examine the analytical results of the efficiency of the energy extractedvia magnetic reconnection and show how it changes with respect to the cosmological constant (Λ)
Multilingual Sentiment Analysis
Get PDFThe following paper provides a performance comparison of four distinct machine learning models, namely Transformer, LSTM, CNN, and MLP, on a multilingual emotion classification utilizing a Cross-lingual Emotion Dataset, XED, containing texts in both the English and Finnish languages. This would test the generalization across many languages and give a closer look at performance for high-frequency and low-frequency emotions. The best results were achieved on the Transformer model, reaching an accuracy of 0.81 and an F1 score of 0.87, probably because it brings in both multilingual BERT embeddings with the Transformer's self-attention mechanism. Hence, it shall be able to learn local and global contexts across languages. While the multilingual generalization, like those of the subtlety of fear and surprise, was problematic in the traditional models, such as LSTM and CNN, the worst performance for handling the complexities of multilingual emotion classification has been given by the MLP model. This indeed underlines how superior transformer-based architectures are for multilingual sentiment analysis when tasks require fine-grained emotion classification across many languages. Further studies are needed to investigate the expansion of the dataset to include low-resource languages, consider using hybrid models with transformers in addition to other architectures, and use few-shot or zero-shot learning to get better model generalization. These results are helpful in practical applications, including social media monitoring, customer feedback analysis, and diagnoses of mental health, which all depend on the robustness of a multilingual sentiment analysis system
Skin disease prediction by images using machine learning algorithms
Get PDFThe machine learning-based skin disease prediction system presented in this paper offers a dependable, automated way to accurately diagnose skin conditions. Medical professionals frequently face challenges while dealing with skin problems due to their diverse variety of causes and symptoms. This thesis examines the effectiveness of Convolutional Neural Networks (CNNs) in diagnosing skin disorders. Clinical data and images of skin conditions are part of a large dataset used for model training and evaluation. While feature extraction methods collect valuable information from images, preprocessing methods enhance the data's quality. Integration of clinical data gives prediction algorithms additional context. In order to identify the most effective approach, which will ultimately improve the precision of diagnosing skin related illnesses and reduce the burden for medical professionals, our study examines several machine learning algorithms. Clinical data and innovative machine learning methods provide potential for ground-breaking advancements in dermatological diagnostics