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Acoustic monitoring of Oak Toads (Anaxyrus quercicus), a Longleaf Pine (Pinus palustris) ecosystem endemic amphibian
No full textThe Longleaf pine ecosystem is one of the most endangered ecosystems in the world with only 3% remaining. Many endemic species to the longleaf pine ecosystem are also in decline and suffer from habitat loss resulting from fire exclusion, urbanization, agriculture, and industrial silviculture. Oak Toads (Anaxyrus quercicus) are a longleaf pine ecosystem obligate; the species is experiencing declines across its range and only has protections in Virginia and North Carolina. We used data from an array of Automated Recoding Units across four years (2013, 2014, 2015, 2019) at three state-owned wildlife management areas to capture audio files recorded 2000-0500 from April through July. We used autonomous call recognition software to create a detector for Oak Toad breeding calls and evaluated weather variables as they relate to Oak Toad call probability using a mixed effect model. Our detector suffered from high rates of false positives (68.1%) and a moderate rate of false negatives (28.1%). Oak Toads only occurred at 10 out of 37 wetlands and called between April 11th and July 20th. Daily mean temperature and daily precipitation were positively associated with Oak Toad calling probability. Oak Toad call probability was greater than 50% when daily precipitation was ≥ 46.63 mm, indicating heavy rainfall events are important drivers of chorusing. Improving detector design and sampling scheme to include dates when climatic conditions are ideal can lead to greater monitoring success and better information on population trends of this declining amphibian
A teacher preparation program\u27s stakeholders\u27 perceptions since campus closure due to COVID-19
No full textCOVID-19 closed colleges and forced faculty and students to learn a new way of teaching and learning. Like most institutions, Marshall University’s College of Education and Professional Development struggled to provide the practicum experience required for teacher preparation when most public schools shifted to remote learning. This qualitative study investigated the reactions of, and ongoing impact on, a university’s college of education’s administrators, faculty, undergraduates, the institution’s instructional designers, and the Counseling Center’s director when the campus closed spring of 2020 due to the pandemic. Initial and ongoing challenges faced, and strategies implemented were categorized by the four themes that emerged from the literature: academic, financial, psychological, and social. The researcher conducted 17 interviews using her created instrument to gain the participants’ perspectives and employed snowball sampling to identify participants. Member checks and data triangulation increased the study\u27s validity. Topics commonly mentioned by the participants included: working from home issues like lack of internet access, feelings of isolation and stress over lack of online readiness, and utilizing Microsoft Teams to continue teaching and learning. The pandemic demonstrated that colleges of education not only need to prepare their teacher candidates to teach in person, but also to teach virtually so that learning can continue when in person is not an option. Faculty and students alike need better preparation on how to teach online. Institutions of higher education should consider the wholistic needs of their students as they prepare contingency plans for in person interruptions of learning
Leveraging Vision-Language Models for advancing digital dentistry
No full textDeep learning methods have advanced rapidly. Digital dentistry has adopted them for tasks such as tooth segmentation from intraoral scans and tooth crown generation. However, there is still a significant gap in implementation due to factors such as limited data availability, the complex nature of tooth images, and inherent ambiguities. My research began with exploring a gap in the tooth segmentation methods for intraoral scans. Intraoral scans are large, containing over 200K mesh cells, and need to be downsampled to make them suitable for deep learning methods. We tested different resolutions to assess the extent of information loss during downsampling. We found that segmentation quality drops sharply when the resolution is below 6K mesh cells. I also experimented with large language models and prompt engineering in the process of cleaning and preparing a scientific text dataset. We compared the performance of two large language models on the task of scientific text categorization on a dataset that we prepared. While conducting the above experiments, we realized that there is currently a very limited number of specialized models for the overall analysis of dental images, and there is a lack of datasets for dental image captioning which can train such specialized models. This led to the research question: Can Vision-Language Models be used to generate structured dental image captions in the absence of paired datasets, and thereby support the creation of a dental captions dataset? Building on these experiences, we devised a framework to generate captions for dental images using vision-language models and evaluated the quality of the generated captions. The model was able to generate clinically relevant captions with structured tooth type and surface information, achieving high accuracy for certain tooth types and disease conditions. Manual evaluation confirmed that the framework produced consistent and interpretable captions across multiple datasets. Overall, this methodology was designed to advance the field of dental image analysis and dental caption generation by using Vision-Language Models and addressing a critical gap in the domain
League of Women Voters of the Huntington Area E-mail Bulletin, April, 2025
Get PDFThe periodical is published by the League, which is a nonpartisan political organization that encourages the informed and active participation of citizens in government and influences public policy through education and advocacy.https://mds.marshall.edu/lowv_newsletter_2020-2029/1048/thumbnail.jp
Navigating artificial intelligence: how traditional midwestern four-year higher education institution distance learning programs are addressing artificial intelligence
Get PDFAI\u27s rapid evolution and integration into society has had and will continue to influence how distance education programs teach their students profoundly. This study aimed to explore the opinions of higher education distance education Provost administrators, program managers, directors, department chairs, and other subject matter experts on the perceived impact of AI in the classroom. This study used a qualitative, phenomenological approach to examine how AI impacts students, faculty, program delivery, institutional policies, and university budgets. Semistructured interviews were conducted with 13 faculty members meeting the criteria to answer research questions based on their experience or observations. The study used five research questions that were routinely observed in the literature review but without a consensus of finding or opinion. The study findings have provided insight into how universities approach policy development that accounts for AI’s disruptive nature in higher education. These findings describe perceived student and faculty use of AI in their education environment and personal lives. Finally, recommendations for future studies and the parameters and populations of focus are included
Assessing the impact of financial, educational, and managerial resources on the success of minority-owned businesses: an analysis of resources from the perspective of the minority business owner
Get PDFMinority-owned businesses (MOBs) in the United States have a failure rate that is 50% higher than that of their non-minority counterparts. Rectifying this imbalance and achieving parity could yield significant economic benefits, potentially adding $1.5 trillion to the nation\u27s economy if resources—financial, educational, and managerial—are equitably distributed and effectively made available to support the goals of minority businesses. However, historical injustices, from Jim Crow laws to systemic discrimination, have granted certain groups multi-generational advantages, exacerbating the divide. Addressing these disparities is both an economic imperative and a moral obligation to ensure equal opportunity. Lending Tree (2023)
With 1.2 million MOBs contributing 10.8% of total revenue generated by the 5.6 million small businesses in the U.S., the need for understanding the root causes of this disparity becomes apparent. Is it a lack of resources, management deficiencies, or a combination of both? This research aims to answer these questions, drawing on the Resource-Based View theory, the Dependence Theory, and the Racialized Organization Theory to examine how financial and educational resources influence MOB success. Intersectional analyses by scholars like Wingfield and Taylor (2016) and insights from Barnes (2019) and Bruton et al. (2022) provide a foundation for exploring the complex dynamics at play.
Literature underscores the pivotal role of financial and educational resources in shaping minority owned business outcomes. Studies by Fairlie et al. (2020) and Skrzek-Lubasińska and Malik (2023) highlight the influence of capital structure and educational attainment on MOB success. Integrating these perspectives, the proposed research aims to develop a robust theoretical framework and the Lussier Small Business Success Vs Failure Model to elucidate the relationships between resources, and MOB success from the perspective of the minority business owners. By incorporating the voices and aspirations of minority business owners, this study seeks to offer inclusive insights and practical solutions to foster a more equitable business landscape
Marshall Libraries Newsletter, Spring 2025, Community Edition
Get PDFMarshall University Libraries Newsletter is created to keep the campus community informed of the activities of university libraries.https://mds.marshall.edu/universitylibrariesnewsletter/1004/thumbnail.jp
Participant 010: Reiki Master with three years of experience (White; Female; Germany)
Get PDFThis is an interview about Reiki and its connection with overall well-being with a Reiki Master holding three years of experience (White; Female; Germany). She was interviewed on May 14, 2025. The participant agreed to the terms outlined in the verbal informed consent form before this interview. Some of the broad conversations during this interview were about Reiki\u27s use to help with physical health for her personally and with another family member; Reiki\u27s ability to help (re)build relationships with others; and Reiki\u27s ability to help the participant feel more grounded. Lindsey Harper was the interviewer and the primary investigator for this project. Please download this document to read the full de-identified interview.https://mds.marshall.edu/reikiconversations/1011/thumbnail.jp