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Discriminatory Censorship Laws
No full textThe summer of 2020 ignited global protests for racial justice. Across the United States, millions marched with a modest plea: that America reckon with its racism. For K-12 schools, this moment pushed local communities and district leaders to create more inclusive classrooms and curricula. Yet before the summer had ended, America\u27s antiracist turn provoked a backlash campaign that has proven far more impactful and enduring.
This campaign has featured the rise and spread of discriminatory censorship laws -a term we apply to government action designed to demean inclusionary values and to deny students access to critical knowledge, inquiry, and thinking. As of January 2024, over 20 states and 145 school districts had enacted at least one discriminatory censorship law regulating K-12 schools. These laws cover over 1.3 million educators and nearly half the nation\u27s 50 million public school students. Many have analyzed the legality of discriminatory censorship laws. Few have systematically assessed their impact. This Article fills that gap by synthesizing otherwise siloed research. Drawing on this scholarship, we identify two overarching threats discriminatory censorship laws pose to students, educators, and public education writ large: (1) hostile learning environments and (2) miseducation. We also surface how discriminatory censorship laws have spread notwithstanding their lack of popular support. Albeit unpopular, this ongoing campaign of discriminatory censorship is unlikely to relent absent an equally committed and coordinated response
The Public Utility Regulation of Dollar General
Full text linkAs food insecurity persists across the country, few solutions have been proposed to address the lack of access to healthy food in rural regions. This Note explores whether public utilities regulation is a theoretical avenue for addressing rural food deserts. The contribution of this Note is to encourage the recognition of healthy food as a critical public good through a modern public utility lens and build solutions to inadequate food access in rural regions by considering the qualities unique to rural populations. One solution proposed herein is to apply a modern public utility framework to dollar stores, ensuring reliable and affordable access to quality goods. The Note begins by defining rural food deserts through three key characteristics: (1) low-income households; (2) inadequate access to transportation; and (3) limited healthy food retailers. It then illustrates rural food deserts in a West Virginia case study, which further discusses the consequences of unaddressed food insecurity. Next, it examines existing legislation and initiatives addressing rural and urban food deserts. It then goes on to expose urbanormative thinking trends that contribute to the lack of conversations surrounding food deserts in rural communities and their persistence. Finally, it introduces a public utility framework as a new solution to treating rural food deserts, specifically proposing a modern public utility application to dollar stores in West Virginia. It further explores potential challenges to this framework
Eat My Brain
No full texthttps://researchrepository.wvu.edu/fixation-db-music-videos/8565/thumbnail.jp
Designing Into the Woods: An In-Depth Analysis
No full textThis thesis is intended to provide insight into the costume design process for West Virginia University’s production of Into the Woods. This thesis will document the entire process, starting with a close reading of the musical exploring its symbols, themes, and characters with some theory crafting thrown in for good measure. This will be followed by the early stages of the show’s production, as well as a full explanation of the development of each character’s design throughout the show’s conceptual evolution. The show’s production process will also be explored, highlighting notable instances and how this impacted the costume design
A Learning History of Online Portfolio Development in Kinesiology: Academic Innovation from Pilot to Powerhouse
No full textThis study examines the phased development of an online kinesiology education program, tracing its evolution from inception to institutionalization through Rogers’ Diffusion of Innovations (DOI) theory. Using a learning history methodology, this research synthesizes document analysis, stakeholder interviews, and focus groups, and historical program data to explore how strategic leadership, faculty engagement, student support, and technological advancements influenced the program’s growth and sustainability. The research is structured around three critical phases: inception, maturation, and institutionalization, highlighting key adaptations in curriculum design, administrative structures, and quality assurance. Findings reveal a transition from a decentralized, experimental model to a structured, integrated online program. Key themes include the role of leadership in online program advocacy, faculty development as a driver of instructional quality, student support mechanisms that enhance retention, and accreditation and regulatory compliance that shape long-term viability. The study aligns these findings with the Online and Professional Education Association’s UPCEA (University Professional and Continuing Education Association) Hallmarks of Excellence in Online Leadership, illustrating best practices in online program administration. This research contributes to the understanding of scalable, student-centered online education models, offering practical insights for institutions seeking to develop or expand their online programs. Implications highlight the importance of proactive leadership, structured faculty and student support systems, and ongoing quality assurance. Future research should explore cross-institutional comparisons, early-stage leadership strategies, and evolving frameworks for student engagement to refine best practices in online learning.
Key Terms: adoption, diffusion, innovation, institutionalization, learning histor
Exploratory Analysis and Improvement of Mine Accident Data
No full textThe Mine Safety and Health Administration (MSHA) plays a pivotal role in enforcing safety regulations, conducting mine inspections, and providing safety training. In collaboration with industry, labor, and other agencies, MSHA aims to understand accident causes and reduce their frequency. MSHA maintains a publicly accessible accident dataset, encompassing 263,455 accidents since 2000, with detailed information on mine and operator identification, accident characteristics, victim profiles, injury types, and more. This dataset is crucial for analyzing the relationships between various factors and accident occurrences. Furthermore, MSHA compiles extensive reports on accidents, injuries, illnesses, and coal production, serving as a foundation for safety analysis and regulatory actions. This study’s primary objective is to examine the relationships between accident parameters, identify trends in incident severity and frequency, and propose data-driven improvements to MSHA’s reporting framework. By utilizing advanced data processing techniques and exploratory data analysis, the research identifies key variables—such as mine type, worker experience, job function, and age group—that are strongly linked to increased accident risks. The findings highlight that high-risk activities, such as roof bolting and equipment handling, lead to significant injury rates, with younger workers (16-19 years) incurring higher medical costs, while older workers (45-64 years) experience more severe lost-time costs. Additionally, the study reveals that fatalities, especially in high-risk states like West Virginia, remain a significant concern, with fatality rates normalized by employment numbers to provide a more accurate risk assessment. The research also shows that coal mines experience more lost days due to hearing loss and strains, while metal/non-metal mines report more days lost from multiple injuries. This research underscores the value of data-driven approaches in identifying high-risk activities and developing targeted safety interventions. The findings emphasize the necessity for tailored safety protocols, enhanced worker training, ergonomic solutions, and technological innovations to mitigate accident risks. The insights provided aim to refine safety frameworks in the mining industry, reduce accident rates, and bolster operational resilience by advocating for continuous improvements in accident data collection and analysis, ultimately fostering safer working environments
Free energy approaches to understanding the mechanism of membrane-active peptides
No full textCancer is a leading cause of death in the world today. Current methods of treatment fail to distinguish the difference between cancer cells and cells of healthy tissue, leading to off-target effects, often with terminal outcomes. A potential solution to this challenge is to target the cancer cells’ microenvironment. One universal characteristic across all cancer cells is the acidic extracellular environment. The pH-Low Insertion Peptide (pHLIP) is a membrane-active peptide with acid-sensitive function, undergoing folding and insertion into a transmembrane alpha-helix. pHLIP is a promising candidate to be used to deliver anti-cancer agents exclusively to cancer cells. Although the mechanism for pHLIP is well-characterized, the detailed pathway of pHLIP function remains poorly understood. Using umbrella sampling (US) simulations, we mapped out the transition of pHLIP between all three states (I unfolded and solvated; II: unfolded and bound to the membrane surface; III: folded and inserted into the membrane). We found that it is necessary to quantify the behavior of pHLIP as an independent function of both the N-terminal and C-terminal halves of the peptide, consistent with biophysical studies that have identified unique a complex relationship between residue titration, bilayer hydration, and insertion of pHLIP.
It is possible to design membrane-active peptides with acid-sensitive properties similar to pHLIP with the use of hydrophobicity scales. One scale in particular, the Wimley-White scale, was developed using a level of detail that accounts for energy contributions from the backbone and side chains of each amino acid. This scale has limited applicability in model membrane systems as it fails to account for electrostatic contributions between residues and charged lipids. In this work, we use molecular dynamics to model the membrane partitioning of several hydrophobic residues. Our preliminary results show validation of the Wimley-White scale with atomistic detail. This provides us with the groundwork to explore the effects of electrostatic interaction in model lipid bilayers
Reliability of Diagnosis using the Andrews Six Elements Treatment Philosophy
No full textABSTRACT
Inter/Intra Reliability of Diagnosis using the Andrews Six Elements Treatment Philosophy
Jenna M. Schneider, D.D.S., Khaled Alsharif, B.D.S, M.S., Peter Ngan, D.M.D., Guoqiang Guan, D.D.S., Ph.D., Will A. Andrews, D.D.S.
Background and Objectives: In order to diagnose and treatment plan orthodontic cases, orthodontists employ many different treatment philosophies and disciplines, and practice with their own understanding and adaptation of such philosophies. Andrews-trained orthodontics incorporate the defined six elements: the dental arch and its supporting tissues/structures, anteroposterior jaw relations and positions, buccal-lingual jaw relations and positions, jaw heights, chin prominence, and the occlusion [ideal characteristics described in the Six Keys to Normal Occlusion].1 While treatment philosophies, like the Andrews Six Elements, help to guide those taught its methodologies, the reliability of implementing the Andrews Six Elements diagnosis and treatment planning has not yet been studied. This project is intended to be a pilot study in the evaluation of space analysis via the Andrews Six Elements methodology.
Experimental Design and Methods: One bilateral Class I moderate crowding orthodontic patient case was selected and distributed for completion of space analysis using the Andrews Six Elements Diagnostic Sheet at two different time points to 12 participants of various levels of experience. Participants include Dr. Will Andrews, WVU Orthodontics faculty, recent WVU Orthodontics alumni, and current residents trained using the Andrews Six Elements philosophy.
Results: Intra-class reliability at the two separate time points (T1 and T2) was measured with moderate to excellent values (ICC of 0.651-0.951) for all measured variables. Statistically significant differences between the average measurement of all participants and Dr. Andrews’ measurements of CD Max, SI Max, BL (jaw), ICD Max, CD Md, AP Md, SI Md, BL L Md, and BL R Md measurements were noted. There was no significant difference noted between the average measurement of all participants and Dr. Andrews’ measurements for AP Max, BL L Max, BL R Max, Internal Max, Internal Md, and ICD Md measurements.
Conclusions: The Andrews Six Elements Diagnostic Worksheet is a helpful tool for orthodontic space analysis. Drawn maxillary core lines have more variation than drawn mandibular core lines. Intra-class reliability ranged from moderate to excellent reliability, with most measurements having good or excellent reliability. Despite all statistically significant findings, the average ICD for all participants and for Dr. Andrews, the gold standard, resulted in values that correspond with extraction treatment plans for both maxillary and mandibular arches
Flower Cluster Matching Utilizing The Unscented Transform For Robotic Pollination
No full textThe use of automated systems for agriculture is integral to keeping the food supply secure. Both industry and academia are exploring and applying methods to increase the yield of plants in environments ranging from outdoor fields to greenhouses. Specifically, many automated systems use continuous monitoring of plants to track plant health and yield. The use of computer vision is necessary when it comes to precision operations that use robotics. Today, robots are trained to weed, harvest, and pollinate. To accomplish these tasks autonomously, a lot of data is needed, which is where spatial-temporal observations of the plants are being recorded using cameras. Flowering plants like those of the bramble family produce terminal clusters of flowers that yield fruits. In robotics, accurately matching these flower clusters for precision flower pollination is particularly challenging. Through the use of vision sensors, visual data can be obtained. However, plant growth and external effects like manipulation, wind, and even light conditions can increase the challenge of matching. Additionally, with limited computation on board a mobile robot, the algorithm needs to be feasible for real-time operation in the use case of robotics pollination. This thesis explores the use of the Unscented Transform and descriptors in MATLAB to perform cluster matching based on visual data. Using a robot equipped with an RGB-D camera, the positions of the flowers in the cluster can be obtained using a vision model and transformed through a descriptor function. The simulated results are evaluated and validated using a Monte Carlo simulation. The experimental results are evaluated for matching based on the collected datasets. The simulation and experimental data results show that the proposed algorithm is a robust method for cluster matching and feasible for real-time application in precision robotic pollination
Didn’t He Hide Out In Egypt Though? A Mixed Methodological Study of Black American and Gendered Socialization and Perceptions of the White Jesus Phenomenon
No full textImages of a White/European Jesus are prominent in US society and particularly, prominent in Black Church culture. Yet, there is an extensive and complicated history which demonstrates that this white religious iconography was intended to disenfranchise racially minoritized communities. As such, the presence of the white religious iconography in Black Church culture is the subject of this dissertation. The dissertation explores how Black American religio-racial socialization contributes to their perceptions and interpretation of the racialized iconography and by association, the Black Church’s embrace or resistance to the imagery. This study explores the racial identity development in 330 participants, 19 interviewees and 311 survey respondents. Utilizing Nigrescence Theory, this study also implements logistic regression to determine association between the participant’s odds of identifying Jesus as white and their level of racial identity development. This mixed methodological study found marginal statistical significance (p-value\u3c .10), indicating that for each point increase in a participant’s racial identity development, the odds were 5% lower that the participant would identify Jesus as white. The study also found the odds of women perceiving Jesus as white were 4% higher than their male counterparts but the finding was not statistically significant. Lastly, the study demonstrates that regardless of their racial identity development, there are innumerable elements or layers of oppression that Black people cope with daily. The coping mechanisms may sometimes be counter-productive, such as embracing a white God who symbolizes the effects of your oppression. The significance of this study is broad as it is one of the first of its kind to consider Blackness and Black socialization as a real and consequential element of sociology of religion research. It is also one of the first mixed methodological studies which addresses the relationship between racial identity development, racialized religious iconography, and ideological whiteness as key to cultural trauma for Black people. This study has broad sociological implications and implications across other disciplines, including African American studies, history, theology, religious studies, and gender studies