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Efficacy of Online Social Movements for Sparking Change: The Case of the Missing Murdered and Indigenous Women Movement (#MMIW)
No full textThe current study examined the context of the Missing and Murdered Indigenous Women Movement (#MMIW) in the context of activist engagement, media representations, and public awareness and beliefs related to the movement. The present study framed the movement within the context of social movement theory, intersectionality, and feminism, to determine the applicability of these frameworks in explaining an Indigenous social movement. While the use of social media to facilitate and mobilize social movements is not a new phenomenon, limited research has examined the functionality of online social movements, particularly in the context of movements concerned with intersectional identities. Research highlights, however, that online social movements have the potential to influence public opinion, particularly when they are sustained over time and have widespread exposure and mobilization (Weeks et al., 2015; Donks, 2004). Three separate methodologies were used to examine the movement, including a social network analysis of online Twitter activists, a content analysis of media representations of #MMIW, and a survey of public beliefs related to #MMIW and use of social media. The findings highlight the lack of activism engagement and exposure to the movement outside of Indigenous communities, particularly in the context of social media and mainstream media coverage of the movement. Further, exposure to #MMIW and having a more diverse online network impacts support for the movement and Indigenous concerns more generally. Implications of the studies are presented, particularly related to the need for future research to identify ways in which Indigenous activists and community members may be better supported within their work and the need for more culturally-specific models of social movement and feminist perspectives
Evaluating the Effects of Academic and Social Breaks on Off-Task Behavior in a College Classroom
No full textEducators and researchers aim to develop effective teaching practices to increase on-task behavior and decrease off-task behavior during class time to ensure positive outcomes for students. The types of off-task behavior observed in classrooms with high school and college populations have changed in recent years due to the prevalence of accessible technology. The purpose of this study was to evaluate the effects of social and academic breaks on off-task behavior in the college classroom. The social break allowed for a time for students to socialize and/or engage with a mobile device, and the academic break allowed for students to take a break from regular class while still remaining on-task. Participants’ off-task behavior occurred at high rates, with most off-task behavior being related to technology usage rather than socializing with a peer. Although the social break was rated as more favorable by the consenting students, neither the academic break nor the social break consistently decreased off-task behavior following the break. However, the least amount of off-task technology usage occurred during the academic break itself rather than during the data collection periods before and after the breaks. This may have implications for interactive pedagogical practices
Policy and Leadership Accountability on Black Special Education Teacher Persistence
No full textThere is a persistent shortage of qualified special education teachers in schools across the country. This issue is exacerbated by the need for special education teachers of color who can help serve the disproportionate number of minority students in schools. Over time, researchers and government entities, alike, have considered ways to increase the recruitment and retention efforts of Black teachers However, given the lack of investigation regarding the needs of Black teachers in special education and what encourages their persistence, efforts to increase representation have been unsuccessful. For this reason, using a qualitative methodology, the purpose of this study is to explore the experiences of successful Black teachers in special education who work with students with high incidence disabilities. Findings indicate, Black special education teachers confront enormous difficulties. Along with the usual pressures that special that special education teachers encounter, Black special education teachers also indicate that there is a lack of understanding among educators, leaders, and policy makers, which is made worse by racism’s overt and covert effects. To overcome these challenges, Black special education teachers leverage their strong relationships with peers to get through these obstacles and find solutions to difficult problems. By collecting stories from participants who meet this qualifying criterion and who serve in Florida’s K-12 public schools, this study provides insight regarding factors that show the persistence of Black teachers in special education
A Novel Role for eNOS in Regulating Lymphatic Valve Development During Embryogenesis
No full textLymphedema is a disease that occurs when lymph flow is impaired, resulting in tissue swelling, fibrosis, chronic inflammation and recurrent secondary infections. Lymphatic valves play a critical role in maintaining unidirectional lymph flow and evidence for valve defects have been reported in lymphedema patients. The lack of drugs that can correct lymphatic valve defects warrants a better understanding of the molecular regulators of lymphatic valve development and maintenance. Lymphatic valves first develop during embryogenesis in response to mechanotransduction signaling pathways triggered by oscillatory lymph flow. Since eNOS (gene name: Nos3) is a well characterized mechanotransduction signaling molecule in blood vessels, we studied the role of eNOS in lymphatic valve development. We show that Nos3-/- mice experience a delay in lymphatic valve formation due to a defect in valve specification during embryonic development. We further show that eNOS regulates valve specification by forming a complex with the transcription factor β-catenin to regulate its activity. Genetic expression of a β-catenin gain-of-function allele was unable to rescue the loss of valves in Nos3-/- embryos, supporting that eNOS is required for nuclear translocation of β-catenin to promote its transcriptional activity. OSS-induced AKT signaling was previously shown to regulate lymphatic valve formation by attenuating FOXO1-mediated repression of valve gene expression and, consistent with this, we show that genetic deletion of FOXO1 rescued valve formation in Nos3-/- embryos. In conclusion, we demonstrate a novel, nitric oxide-independent role for eNOS in regulating lymphatic valve specification and propose a mechanism by which eNOS forms a complex with β-catenin to regulate its transcriptional activity
Do Firms Overreact to the Enactment of Corporate Laws: Evidence from Anti-Price Gouging Laws
No full textThe enactment of state corporate laws increases attention to issues related to price fairness.I present evidence that firms become less efficient in generating margins but not revenue upon enacting anti-price gouging laws. This finding is consistent with a prediction of salience theory that increased attention to unfair pricing induces firms to adopt more conservative pricing strategies. I provide evidence that companies that are more sensitive to unfair pricing risks have larger changes in efficiency. The results are consistent with the salience theory of choice and imply that attention that corporate laws generate may substantially impact firms
Evaluation of a Prototype Deep Learning-based Autosegmentation Algorithm on a High Quality Database of Head and Neck Cancer Radiotherapy Patients
No full textThis dissertation is devoted to the study of deep learning-based autosegmentation in head and neck radiotherapy. Much of the work presented here is motivated by the need to introduce a clinically useful autosegmentation model for head and neck organs at risk, with the aim of reducing inter-observer variation in structure segmentation and enhancing time efficiency of the treatment planning process. This dissertation describes autosegmentation approaches, introduces a prototype deep learning-based autosegmentation algorithm trained with carefully curated local gold data, and presents a series of comprehensive evaluations to verify the feasibility of implementing the prototype model in clinical settings.
One of the challenges of adopting a deep learning-based autosegmentation technique in radiotherapy is the need for a large size of carefully curated high-quality gold data that accurately represents the population being treated. Combined with a deep learning algorithm, the training data plays a critical role in determining the ultimate performance of the autosegmentation model. Although deep learning algorithms do not rely heavily on prior knowledge like more conventional autosegmentation techniques, the precise delineation of the various organs in the head and neck region within the training data is crucial in determining the performance of autosegmentation models. These relationships are explored in detail in this thesis chapters.
Starting in Chapter 1, we provide a brief overview of the limitations of manual segmentations in various aspects that necessitate the automation of the process. We also discuss the transition of autosegmentation techniques and the current status of the deep learning-based approach.
In Chapter 2, we first trained and evaluated a well-established commercial deep learning-based autosegmentation software to verify the feasibility of the approach and assess the need for a higher quality autosegmentation model that can generate more clinically useful structures in a fraction of the time. A commercial software was trained with local data and compared its performance to the same algorithm trained at different institutions, as well as to the gold data. We confirmed that deep learning-based autosegmentation has a potential to be a useful time-saving solution in HN radiotherapy treatment planning. However, due to the complexity of anatomical structures in the HN region, we also found that most of the autosegmented structures in this study required minor or major editing, which defeats the time-saving benefits, especially if repeated for the large number of OARs in HN area. This study revealed two main findings. Firstly, the quality of training data plays a critical role in the performance of deep learning models and should align with user preferences. Specifically, the model trained with local data showed superior performance compared to the model trained with data from different institutions. Secondly, even with carefully curated high-quality local data, the DL model\u27s performance was suboptimal due to inherent imperfections in the algorithm. These findings emphasize the need for ongoing research and development to enhance the accuracy and reliability of DL-based autosegmentation algorithms.
Moving forward, in Chapter 3, we evaluated a newly developed prototype deep learning-based autosegmentation algorithm based on a fully convolutional network that combines U-Net and V-Net architectures which was developed in a collaboration with a vendor and presents our experience in training and evaluation of the prototype DL model. The model was trained with more than 600 carefully curated previously treated HN cases. Our findings highlight that the prototype model outperformed a commercial algorithm and generates clinically useful HN OAR structures. Specifically, 93% of the autosegmented structures generated by the prototype model were deemed clinically useful, and 20% of these structures required no editing at all, which is a tenfold improvement compared to other models. Furthermore, the prototype model exhibited the highest geometric similarity to the gold standard data compared to the commercial models, across all evaluation metrics.
In Chapter 4, we evaluated the dosimetric impact of the autosegmented HN OARs generated by the prototype model. To verify the ability to use unedited autosegmented OARs in treatment planning, while maintaining the plan quality, we generated new treatment plans based on original targets and unedited DL-produced OARs. The new dose distributions were then applied back to the manually delineated structures to test if the treatment plan generated based on the autosegmented structures were still valid with the manually delineated structures. The nearly identical primary target coverage for the original and re-generated plans was achieved, and the areas under the corresponding pairs of the dose-volume histogram (DVH) curves were also nearly identical. 99% of the critical DVH points met the clinical objectives with both the re-planned dose and autosegmented structures, and with the manual ones. In short, the DL-generated HN OARs resulted in treatment plans of equivalent quality to the original ones.
In Chapter 5, we explored the potential correlation between the inter-observer variation in OAR contouring and radiation-induced toxicities in HN radiotherapy and assess if the prototype DL autosegmentation model could help with reducing the toxicities. We divided previously treated HN cases into two groups, based on physicians with different segmentation and treatment planning approaches. The first group (A) of physicians include the physician who contoured the gold data which was used to train the prototype model, and other physicians in this group were trained to contour the HN OARs in the same way. And the physicians in the other group (B) were trained elsewhere, and the inter-observer variation was possible between these two groups. A significant difference in radiation-induced toxicities between the two groups was observed. Patients in group B were more frequently hospitalized, experienced higher weight loss, and had more feeding tube placement. In the critical DVH points analysis, the percentage of DVH points that failed to meet the clinical objective were much higher in group B in all OARs. In group B, the autosegmented structures, which mimics the manual structures of group A physicians, received even higher dose than the manual structures. This indicates that the actual OARs might have received higher dose than indicated in some of the group B treatment plans. Therefore, the deep learning-based autosegmented structures could help reduce toxicities by generating consistent high quality HN OAR structures.
Finally, Chapter 6 provides an overview of the major findings. Additionally, future research plans are introduced, including the development of an automatic dose prediction algorithm and the exploration of correlations between dosimetric parameters and complication probabilities. These efforts aim to achieve the goal of substantial automation of the treatment planning process consistent with the proven clinical outcomes
Diatom Diversity and Functional Groups in 72 Florida Lakes: Assessing Ecological Changes for Improved Protection and Management
No full textFlorida lakes are diverse ecosystems and are an important part of the state\u27s biodiversity and ecosystem services. As human population and development increase across the state, many lakes have been documented as nutrient impaired and are unable to maintain essential ecological functions. In this study, diatom diversity and functional groups in 72 Florida lakes were assessed for their relationships with associated water-quality data. Common alpha diversity indices, including Shannon-Weiner Index, the Gini-Simpson Index, and Hill’s numbers were utilized to measure trends in diatom communities, while the relationships between diatom lifeform characteristics and environmental data were explored using multivariate methods and data visualization. This study showed that nutrients have little effect on measures of alpha diversity. Species composition and functional lifeform groups, however, showed important differences across nutrient gradients. Florida’s current lake-management approach is based on limnetic chlorophyll a and nutrient concentrations, but eutrophication involves disturbance to many aspects of the biological structure in shallow lakes, such as those in Florida. The results of this study provide a basis for the development of a diatom biomonitoring index that would introduce more biological assessments to lake-management approaches. Such an index would further promote the successful conservation and management of the state’s freshwater resources
Advocating for Diversity, Equity, and Inclusion: A Study of the NHL’s #HockeyIsForEveryone Campaign on Twitter
No full textWith more than 6.8 million followers on Twitter (as of Feb. 2023), the National Hockey League (NHL) has a large platform that has the potential to influence societal change not only in the United States and Canada, but also globally. This study aims to understand how corporate social responsibility initiatives pair with diversity, equity, and inclusion (DEI) programs. Furthermore, this research seeks to understand how organizations communicate these messages with their publics through social media. This study specifically examines news frames and charity support behaviors implemented by the NHL in messages about its DEI campaign, “Hockey Is For Everyone,” and analyze fans’ reactions to understand which posts either resonate well or spark backlash. The results of the study aim to provide insightful data for the NHL, as well as other professional sports leagues and organizations, in how to approach corporate social responsibility campaign messaging that is received with positive reactions online
Synthesis of Small Molecule Modulators of Non-Traditional Drug Targets
No full textThis work details the effort toward structure-activity-relationship (SAR) studies and synthesis of the small molecule modulators of two non-traditional drug targets. The first part of this manuscript (chapters 1–2) will discuss the collaborative work and synthesis of an inhibitor of Slingshot Homology 1 (SSH1) with the potential therapeutic application toward Alzheimer’s Disease (AD) treatment. The second part (chapters 3–6) will discuss the synthetic efforts toward modulation of a protein target known as STING, or stimulator of interferon genes, with the therapeutic application toward autoimmune disease or anti-tumor activity.
AD is a progressive and degenerative illness that holds the title of being one of the lead causes of death worldwide. It has long been theorized that this disease is caused by the formation of toxic plaques and tangles in the brain. SSH1 is a phosphatase that, through knockout studies, has shown to play a role in the manifestation of such plaques and tangles. Thus, it is hypothesized that the inhibition of this pathway can lead to a new treatment for AD. For a long time, AD treatment has not addressed the underlying biology of disease. Additionally, while there is much known about kinase inhibitors (the biological opposition to phosphatases), there is around a ten-fold decrease in information on phosphatases. Prior screening campaigns and work on this project focused on the SAR studies of one of two leading hit molecules. This work will outline the efforts toward analogs synthesis of the second of those two molecules, focused on the bioisosteric replacement of the various functional groups present on our initial hit compound. Disclosed in this manuscript are the successful synthetic pathway toward sixteen analogs, fourteen of which were tested via an in vitro colorimetric assay to analyze their potency as SSH1 inhibitors. Of the fourteen tested, two analogs have shown to have significant activity. Further SAR studies have begun with the goal of exploiting these favorable changes to our initial hit compound with the overall goal of future analog development.
The innate immune system is the first line of defense toward potential pathogens in mammals. A key protein in this process is the recognition of cytosolic DNA by STING leading to downstream production of type 1 interferon. The STING protein is a versatile target for drug discovery with a large variety of applications. Prior work in this area has shown that agonists of STING have led toward anti-cancer and anti-tumor activity, while antagonists of this protein have promising applications toward modulating autoimmune disease. Recent efforts through academic collaboration have shown that clonixeril, a known anti-inflammatory drug, acts in a concentration-dependent manner as either a partial agonist or potent antagonist of this pathway in substoichiometric concentrations. The latter half of this manuscript outlines our SAR efforts toward optimizing STING modulation with the synthesis of 40 analogs of clonixeril, many of which exhibit high-affinity binding concentrations in the attomolar range. Further work into the biological activity of these compounds is currently ongoing
The Politics of Waves: A Transnational and Cultural Surfing History of Popoyo, Nicaragua
No full textDuring the 1970s and 1980s, as surfers were carving out new international surf spaces around the globe, Nicaragua was on a much different trajectory—one that engendered the Sandinista guerrilla insurgency that deposed a four-decade-long, US-backed dictatorship in 1979. In response, the United States waged a decade-long, low-intensity counterinsurgency against the Sandinista government. While other surfing destinations were growing in popularity, notably neighboring Costa Rica, Nicaragua was, by most accounts, considered off-limits due to the conflict. In 1990, a watershed moment fostered an environment conducive to international tourism and foreign investment. The election of Violeta Barrios Torres de Chamorro ushered in a time of peace unseen for decades. Chamorro’s embrace of market-driven economics created a scenario welcoming for international visitors and their foreign capital. A perhaps unforeseen beneficiary of these policies were surfers, who started gravitating to the once rural peripheries of southwestern Nicaragua. This radically changed the economic and cultural character of these historically indigenous communities. Over the course of three decades, surfing and its subculture permeated virtually all parts of these coastal pueblos, resulting in a profound and largely irreversible sociocultural and economic transformation. This dissertation places surfers and surfing at the center of this phenomenon, tracing the evolution of the Popoyo area, and the Tola Municipality more broadly, from an undeveloped stretch of Pacific coastline to an international epicenter for surf tourism and expatriate communities