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Intelligent PDF Extraction: Building a Regex-Driven and LLM-Assisted Pipeline for Document Analysis
No full textThis project presents a prototype for automated ingestion, extraction, and language model–based summarization of technical documents. The system integrates with Dropbox storage to identify, enumerate, and download files, then extracts and structures textual content from diverse document formats. Extracted text is stored locally and processed through OpenAI’s language models for summarization, question answering, and insight generation. The primary objective is to produce concise, human-readable summaries, and targeted responses that significantly reduce manual review time. By automating information retrieval and contextual interpretation, the pipeline enhances both accuracy and efficiency in document management workflows. Future development could incorporate retrieval-augmented generation (RAG) techniques to provide context-aware reasoning and improved traceability to original sources. Overall, this project demonstrates a scalable and practical application of large language models for domain-specific document analysis, supporting faster decision-making, improved collaboration, and operational excellence
An Update & Exploration of the Herbarium at Belmont University
No full textThe Belmont University Herbarium is a collection of plant samples used to catalogue species for research and teaching. These specimens have been collected by Belmont students since 1973, helping to document the flora of Middle Tennessee. This semester the specimens have been organized, and identifications have been confirmed. An Excel spreadsheet was developed to record the specimens. This allowed for analyses of the 1,790 specimens by phylum and family. The updated organization of the herbarium and spreadsheet allows for faster specimen retrieval and identification of target species for future collection
Metadata Analysis on the relationship between sleep, depression, and cognition in older adults
No full textMetadata Analysis on the relationship between sleep, depression, and cognition in older adults
Abstract
Previous research has revealed that both sleep and depression play significant roles in influencing memory. Adequate sleep facilitates memory consolidation during rest, ultimately enhancing cognitive performance. In contrast, elevated levels of depression are associated not only with physical symptoms, but also with declines in cognitive functioning. The present study aims to determine whether the cognitive benefits of sufficient sleep duration outweigh the detrimental effects of depression on memory. We hypothesize that sleep duration will have a stronger influence on memory consolidation in older adults than depression. Additionally, while depression is expected to negatively affect memory, we predict that its impact will not outweigh the protective benefits of adequate sleep. Using data from the National Social Life, Health, and Aging Project (Round 2, 2010–2011), we calculated a composite MoCA score by averaging results across five cognitive domains. From the same dataset, participants also reported their levels of depression and perceived restfulness. The linear regression analysis revealed statistically significant positive relationships between memory and both sleep (p \u3c .001) and depression (p\u3c .001). However, there was no significant difference in the strength of these relationships (p \u3c .001). These findings suggest that both sleep and depressive symptoms significantly influence memory performance. Consequently, maintaining adequate sleep and monitoring depressive symptoms are essential for preserving cognitive health in older adults
It\u27s Time for Resting Pitch Face: How Musical Key and Tempo Influence Neutral Face Appraisals
No full textCholesterol Accumulation in Hurler Syndrome
No full textLysosomal storage disorders (LSDs) are a group autosomal recessive disorders characterized by impaired lysosomal function, which typically leads to neurodegeneration and decreased life span. Because each condition is rare, it is difficult to develop therapeutics. Therefore, our lab is seeking to identify a common mechanism between different LSDs. Previous work in Niemann Pick Type C Disease (NPC) identified the cytoskeleton as a therapeutic target. In this study, we investigated the connection between Hurler disease, another LSD, and NPC to see if we could utilize this target in the future. First, we observed changes in cholesterol accumulation in both disorders using immunofluorescent microscopy. Second, we observed changes in lysosomal positioning and morphology. We found that although there are some similarities, there are some variations between NPC disease and Hurler Syndrome
Exploring the Synergistic Effects of Cisplatin and Curcumin in Osteosarcoma Cells
No full textOsteosarcoma (OS) is a highly aggressive bone cancer characterized by rapid metastasis, which drastically reduces patient survival rates from 70% in localized cases to 30% upon metastasis. Current treatments combining chemotherapy with cisplatin and surgical intervention are often ineffective against metastatic OS and are associated with significant side effects. Cisplatin targets cancer cells by binding to DNA, disrupting transcription and replication, and inducing apoptosis. To address the challenges associated with current treatments, this study investigates the potential of combining cisplatin with curcumin, the bioactive compound derived from turmeric, as a novel therapeutic approach. Curcumin has shown anticancer properties through the induction of oxidative stress, mitochondrial damage, and increased reactive oxygen species, leading to cell death. We treated OS cells with cisplatin and curcumin, both individually and in combination, to assess their effects on cell proliferation, migration, and apoptosis. Our results demonstrate that the combination therapy significantly decreases cell viability compared to either agent alone while potentially mitigating the adverse effects associated with traditional chemotherapy. These findings suggest that the synergistic effects of cisplatin and curcumin offer a promising new therapeutic strategy for improving outcomes in patients with OS
“The Role of Machine Learning in Social Media Content Moderation”
No full textThe majority of the world\u27s over one billion active users depend on large-scale machine learning based social media platforms to personalize content through various methods of curation. Recommendation systems use many types of machine learning model including collaborative filtering, content-based filtering and deep learning to find what a specific user is likely to be interested in, and therefore increase user engagement. As beneficial as this is to the user experience, it has also generated a significant amount of concern about both bias in recommendations and the dissemination of false information on the web, as well as issues related to the digital well-being of users. This project will examine the computer science aspects of the development of recommendation systems (the process by which they are developed), explore some of the potential social impacts that may occur from the deployment of recommendation systems, and discuss how socially responsible algorithms can help create a better, healthier Internet
Bridging the Rural Telehealth Divide
No full textThis article examines the historical development, regulatory landscape, and post-pandemic future of telehealth in the United States, with a particular focus on its original purpose: improving access to care for rural populations. Although Congress first authorized Medicare reimbursement for telehealth in 1997 to alleviate rural health disparities, federal and state regulatory frameworks—especially restrictions on originating sites, licensure rules, and HIPAA-driven technology requirements—significantly limited adoption for more than two decades. The COVID-19 public health emergency triggered sweeping temporary waivers that removed geographic limitations, permitted the use of common communication technologies, liberalized supervision and prescribing rules, and allowed audio-only encounters. These changes produced an unprecedented surge in telehealth utilization, though disproportionately in urban rather than rural communities. The article analyzes emerging data showing that telehealth growth in rural areas has lagged behind urban uptake, raising concerns that universal post-pandemic expansion could exacerbate access disparities rather than resolve them—especially in mental health care, where telehealth usage is highest and rural shortages are most acute. After reviewing recent federal and state legislative efforts and private-sector trends, the article argues that telehealth policy must include targeted rural incentives—rather than broad, universal reforms—to avoid widening the rural–urban care gap. It concludes with recommendations for regulatory and financial strategies to ensure that telehealth serves as a genuine access equalizer for rural patients rather than a new frontier of health inequity
Bridges and Borders in the Legacy of Al-Andalus
No full textFrom 711 to 1492, large parts of today’s Spain and Portugal were ruled by Muslims in a territory that was known as al-Andalus. Although al-Andalus ceased to exist as a place in 1492, its legacies and memories have survived in many forms and have animated a diverse range of cultural and political projects around the world. In the process, they have bridged some of the cultural divides that have defined today’s world, producing neighbors where we might expect to find strangers. But these processes of affiliation are not seamless and often run into limits. While al-Andalus has often served to create connections between national, cultural, religious, and ethnic groups, it has also served to draw boundaries between them. Such tensions are at the center of this talk, which will explore how the memory of al-Andalus has helped to create both bridges and borders, especially between Europe and North Africa
Relationships and Sleep in Emerging Adults
No full textSleep is important for physical and mental health, especially for adolescents and emerging adults. Sleep disturbances are defined as any disruptions or alterations of normal sleep patterns (Buysse et al., 1989). Research has shown that healthy relationships (including those involving secure attachment) relate to better sleep quality (Gunn, 2019). Attachment is defined as a deep and enduring emotional bond with another, and is categorized into three categories: Closeness (i.e., the level of comfort a person has with being close to others), dependability (i.e., the extent a person feels they can depend on others) and a lack of attachment anxiety (i.e., the extent someone worries about being unloved or rejected; Alexander, R., Feeney, J., Hohaus, L., & Noller, P. (2001). This study aimed to examine how attachment factors that affect one’s relationships relate to sleep disturbances in emerging adults. In this study, emerging adults recruited via Prolific (N = 46; Mage = 24.24) filled out a survey on Qualtrics that measured demographics, sleep disturbances, and the three components of attachment (closeness, dependability, and anxiety). Results indicated that neither closeness nor dependability were related to sleep disturbances. However, scoring higher on attachment anxiety was related to greater sleep disturbances. Understanding how attachment styles can affect sleep disturbances in adolescents can allow them to better understand themselves, as well as allow them to potentially fix any sleep disturbances through altering their views on attachment