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Non-Profit Foundation Boards: An Investigation into Best Practices using Fayetteville Public Library Foundation as a Test Case
Full text linkEffective governance is critical for the success of non-profit organizations, with foundation boards playing a central role in ensuring accountability, strategic direction, and resource allocation for the organization. This thesis investigates best practices for non-profit foundation boards, using the Fayetteville Public Library Foundation as a case study to evaluate the efficiency of its governance practices. The research aims to identify whether the Foundation board operates efficiently and adheres to established best practices for non-profit boards.
To address this, a two-phase methodology was employed. The first phase involved an extensive review of scholarly journals, industry guidelines, and other resources to define criteria for best practices in non-profit board governance. These findings informed the development of interview questions designed to assess the efficiency of a non-profit board, specifically the Fayetteville Public Library Foundation board in this case. In the second phase, interviews were conducted with board members and library executives, providing qualitative insights into their operational strategies, decision-making processes, and adherence to the identified best practices.
The research is expected to support the hypothesis that the Fayetteville Public Library Foundation board operates efficiently and incorporates several recognized best practices, including transparent decision-making, strategic alignment with the organization’s mission, and active engagement of board members. These results will contribute to the broader understanding of non-profit governance by highlighting how established best practices can be implemented and tailored within a specific organizational context to improve overall board effectiveness.
By combining theoretical research with practical application, this study will offer valuable insights for non-profit boards seeking to improve their governance practices and better fulfill their organizational missions.https://scholarworks.uark.edu/hnrcsturpc25/1001/thumbnail.jp
Can Spatiotemporal Gait Parameters Predict State Anxiety?
Full text linkBackground: Anxiety is one of the most experienced mental health disorders. Recent research has suggested a relationship between gait parameters and anxiety, however the disparity in measurement methodologies of both anxiety and gait makes it difficult to draw broad conclusions. Better understanding the relationship between anxiety and gait mechanics creates opportunity for a more holistic understanding of the interaction between mental health, functional capacity, and quality of life. Purpose: The purpose of this study is to evaluate if spatiotemporal gait parameters measured on a pressure-sensing walkway are related to anxiety.https://scholarworks.uark.edu/coesym25/1011/thumbnail.jp
The Relationship of Peer Recovery Support Specialists and Recovery of Perinatal Women with a Substance Use Disorder
Full text linkBackground: Substance use in pregnant and postpartum women is a growing issue in the United States. Drug use while pregnant can lead to birth defects, stillbirths, and problems providing positive parenting to their children. Many women with substance use disorders (SUD) feel extreme shame and stigma related to their substance use and have trouble accessing recovery-related treatment and other services. Peer recovery support treatment uses the lived experiences of individuals in current recovery from SUD to facilitate and support recovery in others. Purpose: The purpose of this review was to evaluate the impact of peer recovery support specialists on the recovery outcomes of perinatal women with SUD.https://scholarworks.uark.edu/coesym25/1001/thumbnail.jp
Understanding and Evaluating Multi-class Product Classification Methods for E-commerce
No full textIn e-commerce, enhancing Natural Language Processing (NLP) models\u27 understanding of search queries can significantly improve product relevance and overall user experience. Even with advancements in the search space, being able to accurately classify items for shopping queries remains challenging due to noisy data, ambiguous user intent, and the wide range of products available. This research aims to explore different strategies implementing and improving queryproduct classification. The methodology involves a comparative assessment of various model performances for multi-class product classification, data augmentation techniques for handling class-imbalances, and the design of the User Interface (UI) of a Human-In-The-Loop (HITL) Machine Learning (ML) system. The hope is that this approach will lead to enhancements in query-product matching, with direct implications for better search results and product recommendation
Creating a Multi-Sensory Room at the University of Arkansas
Full text linkAutism Spectrum Disorder, or autism, is a genetic neurological condition that can affect all aspects of an individual’s life, depending on their symptoms. Autistic people tend to struggle most significantly with social and emotional issues, which often results in declining academic success. With such a multifaceted disability, autistic students can struggle to perform at the same standards as their non-autistic peers, mostly due to the complications from their disability paired with limited accommodations. The consequences of these issues can manifest as lower admission rates, higher dropout rates, and higher stress levels for autistic students. This creative and service-learning honors thesis aimed to design and create a multi-sensory room on-campus for autistic and non-autistic students to use to escape academic and interpersonal stressors, receive positive sensory stimulation, practice self-soothing activities, and have access to educational materials about autism and wellness in an academic setting. After receiving a grant from Bumpers College, we were able to locate and outfit a space with the sensory additions necessary to create a “multi-sensory room.” Educational materials were also created to provide users with information regarding autism, stimming, and other relevant information to contextualize the items placed within the room. This space can offer University of Arkansas students multifaceted support by providing a service that is open to all students, regardless of diagnostic status, with the tools and space needed to assist in emotional regulation. Future researchers should (1) assess the quality and usage of this space, providing future adjustments as deemed necessary; and (2) assess the relationship between autism, burnout, sensory experiences, and the college environment to better understand and further develop accommodations for autistic students
Molecular Insights: Advances in Single Molecule and Single Particle Detection for Analysis of Chemical, Physical, and Biological Phenomena
Full text linkThis thesis is focused on recent advancements made in the field of chemical imaging, optical microscopy, and recent developments that have improved spatial, temporal, or spectral resolution or have made certain techniques more accessible and cost effective for their wider adoption. This thesis is organized based on the systems of interest we studied with each new technique. Although, it is important to note that many of the methods here can be used with a multitude of systems even if not explicitly mentioned. The first chapter of this thesis will discuss the current state of chemical imaging, common terminology, and important first notes to assist the reader in more complex future chapters. Chapter7 two focuses on our recent advancements in spectroscopically enabled microscopy with singleparticle specificity with implications across many disciplines to study a variety of systems. Chapter three discusses advancements in five-dimensional single particle orientation and rotational tracking (SPORT) for two main purposes: monitoring of real-time biological processes and empirical single particle diffusion observed in accordance with the Stokes-Einstein relation. Chapter four will discuss bioinspired self-organizing lattices of various nanomaterials that have potential applications as highly sensitive detectors along with the analysis of these lattices by grazing incident small-angle x-ray scattering (GISAXS) and x-ray reflectivity (XRR). Chapter five will focus on our advances in single-molecule localization microscopy (SMLM) for superresolution imaging by direct stochastic optical reconstruction microscopy (dSTORM) with true color single molecule spectral in the analysis of biological nanostructures
What\u27s in it for me? The Benefits of Breastfeeding for the Mother
Full text linkThe purpose of this systematic review was to investigate both the short- and long-term benefits that breastfeeding has on maternal physical and mental health. The PICOT question was: In postpartum mothers, how does breastfeeding compared to formula and mixed feeding affect maternal physical and mental health, including outcomes in cardiovascular health, BMI, bleeding risk, and mental health both short term and long term? For this research, EBSCOhost and the National Library of Medicine databases were searched to find relevant studies and systematic reviews. Terms such as “breastfeeding and maternal health benefits,” “breastfeeding and postpartum health,” and “breastfeeding and weight loss” were used to find appropriate studies. The review included 15 peer-reviewed articles, all published within the previous 5 years, that focus on the benefits of breastfeeding for the mother. The benefits of breastfeeding for the mother are clear and numerous, both short- and long-term. Pronounced long-term benefits include increased prevention of cardiovascular disease, decreased allostatic load, decreased incidence of breast and ovarian cancers, and decreased incidence of type two diabetes mellitus. Important short-term benefits include improved mental health and reduced rates of postpartum depression, better quality sleep, decreased BMI, improved recovery with less bleeding, and many more. Promoting awareness of the benefits of breastfeeding for mothers and expectant mothers would serve the interest of public health as a whole. Tiny Tusks Breastfeeding and Infant Support program addresses this need by providing mothers a safe and clean place to breastfeed at almost all Arkansas athletic events. The program provides education to mothers and the community on the benefits of breastfeeding. Additionally, their resources make breastfeeding at public athletic events more accessible and comfortable. Although research supporting these outcomes is available, additional studies related to the effects of public health interventions, such as programs like Tiny Tusks, may be needed. Since most recent studies have focused on the breastfeeding couplet (mother-baby), additional studies focused primarily on maternal outcomes could improve our understanding of the effects breastfeeding has on specifically the mother. More community education about these effects and benefits could serve to both increase breastfeeding rates and improve maternal health
Closing Equity Gaps in Biomedical Engineering: Measuring the Influence of a Clinical Immersion Class on Marginalized Students
No full textCombating clinical challenges with innovative engineering solutions is the sole purpose of biomedical engineering. To equip students with the skills needed for their future careers in biomedical engineering, our department has implemented a junior-level clinical and industry immersion course into the curriculum, aiming to combine unique clinical experience and design building. This service-learning course emphasizes hands-on clinical observation and the identification of healthcare issues, with the goal of building students\u27 confidence and skills in applying the engineering principles that are taught in class. Recognizing the disparities in STEM demographics, this study specifically examines the course\u27s impact on historically marginalized groups (HMG), such as women, Hispanic, Black/African American, Native American, and first-generation students, compared to their non-historically marginalized group (NHMG) counterparts. The disproportionate spread of demographics in engineering poses significant barriers for HMG students. These students often battle with underrepresented or repressive environments, unequal opportunity to resources, and a lack of strong community with their peers—factors that can affect confidence and students’ overall chances at succeeding.
This ongoing study evaluates the effectiveness of the clinical immersion course closing disparities between students by analyzing pre- and post-course survey data. The surveys, which included both quantitative and qualitative questions, assessed students\u27 skill development, sense of self-competence, and awareness of healthcare disparities. Overall, results showed the course was effective at increasing growth in skills, such as engineering design capability and understanding customer perspectives, for all students. Quantitative findings revealed significant gains in confidence and skill development across students, with HMG students demonstrating the most visible growth despite starting with lower confidence levels in comparison to NHMG students. Qualitative analysis using NVivo sentiment software highlighted the value students placed on clinical exposure and getting to speak to professionals, highlighting its role in deepening their understanding of engineering practices and healthcare inequities.
Despite the positive impact the course had on all students, the trend of lower confidence levels for HMG students before the course was taken alludes to the disparities these students may face in the classroom. By addressing these inequities in biomedical engineering education, we can begin to strategize how we can improve curricula and programs that are inclusive and tailored for underrepresented students, aiming to close the gap and promote equity in the classroom in order to build great future engineers.https://scholarworks.uark.edu/hnrcsturpc25/1051/thumbnail.jp
Rome Wasn’t Marketed in a Day
Full text linkThis thesis explores the topics of cultural branding, consumer behavior, and tourism marketing in Rome, Italy, based firsthand experiences during a summer study abroad program. By looking at how companies, brands, and places market themselves in Rome, brands in the United States can apply the same concepts and strategies that work in a global setting. This study highlights key differences between U.S. and Italian approaches to marketing tactics and insight into why these strategies work so well in Rome. Marketing is a way for brands to build emotional connections with consumers, and companies in Rome have mastered these connections with their storytelling, something not seen often from U.S. brands. Drawing comparisons to the United States, this research provides takeaways for American marketers on how to adopt culturally grounded and sustainable practices to build stronger connections to consumers
Machine learning-assisted analyses for identification and prediction of genetic abnormalities in human pluripotent stem cell populations
No full textStem cells are the cells in our body with the unique ability to both self-renew and differentiate into specialized cell types, making them fundamental to growth, development, and tissue regeneration across our various systems. However, the behavior and essential functions of stem cells are influenced by a complex interplay of genetic and environmental factors. Aberrations in their gene expression profiles can lead to dysfunctional or diseased cells, potentially compromising tissue repair and regeneration. Given their promise in regenerative medicine for restoring damaged tissues and treating various conditions, accurately classifying stem cells to detect abnormalities is critical. Such classification ensures that only healthy, viable cells are utilized in therapeutic applications, preventing issues that could limit effectiveness or introduce complications in clinical practice of stem cell therapies.
One such method of classification is via machine learning, which is a transformative tool that allows researchers to process and interpret vast, complex datasets, including these stem cell gene expression profiles. By leveraging machine learning, researchers can uncover subtle patterns within these profiles that might otherwise go undetected, which offers deeper understandings of cell quality and differentiation potential. The machine learning models are able to analyze thousands of genes simultaneously, allowing them to identify key biomarkers and expression patterns that distinguish normal from abnormal stem cells. This capability is valuable for this classification task and the potential for future predictive modeling. Furthermore, machine learning allows for high-throughput analysis, making it possible to evaluate large numbers of stem cells quickly and with lesser bias and greater precision than manual analysis. This not only accelerates the research process but also supports scalable, reproducible insights into stem cell health, ultimately enhancing regenerative medicine approaches and the safe application of stem cell therapies.
After comparing Logistic Regression, Decision Tree, Random Forest, and Gradient Boosting models, we found that Random Forest delivered the most consistent and contextually appropriate results for this study. While Logistic Regression achieved the highest overall accuracy, both the Random Forest and Logistic Regression aligned identically with our key performance priorities: a low false negative rate and high recall for Class I. Although Random Forest tended to produce more false positives, this skew reflects a conservative approach – favoring the identification of abnormal stem cells, even at the risk of overcalling. In the context of stem cell therapy, this trade-off is desirable: a false negative could allow a harmful cell to slip through, while a false positive simply errs on the side of caution. Ultimately, Random Forest’s ability to capture complex, nonlinear relationships – something Logistic Regression inherently lacks – combined with its emphasis on minimizing false negatives, makes it the most suitable choice for our application