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Breaking Down Data Science: A Low-Code Machine Learning Platform
No full textWith the rising popularity of data science and digital data storage, companies of many scales are looking to harness their data for decision making. Bentley Ave Data Labs, a data consultancy group, has sought to capitalize on this rising popularity by commissioning a low code machine learning platform. This thesis will explore the creation of a low code machine learning platform, intended to allow non-technical audiences to experience the power of data science.
The application will use Streamlit to allow for a user-friendly user interface and Python for the backend coding. The application will allow the user to clean, visualize, model, and interpret data from any CSV or Excel file. The models will be classification and regression based to accommodate a number of data types and include classification models such as Random Forest and Logistic Regression and regression models such as Polynomial Regression, Random Forest Regression, and Lasso Regression. The application detailed in this thesis will allow non-technical audiences to harness the power of data science and help push them towards data driven decisions
Breakthrough: How Committed, Long-Term Supports for Middle and High School Students Help Unlock the Power of Education and Create a Lifetime of Opportunity
Get PDFThis project explores the impact of Breakthrough, a program dedicated to supporting first-generation college-bound students, through the lens of a teaching fellow\u27s summer experience. With a mission to grow educational opportunity, Breakthrough provides academic enrichment, mentorship, and support starting in middle school to ensure college becomes an option for all of its students.
This research highlights experiential data from a teaching fellow’s week-by-week responsibilities. This project seeks to share the stories of different roles within the program and their influence on student outcomes, academic pathways, and personal growth. The research highlights the unique structure of Breakthrough’s support system and its emphasis on collaboration, leadership development, and mentorship.
The project emphasizes the great impact of relational teaching and mentorship on both students and program leaders. For students, the program fosters confidence, academic success, and a sense of belonging, while for teaching fellows, it builds leadership and classroom management skills that extend far beyond the internship
A Nano-Scale Approach to Controlled Apoptosis in Brain Cancer through Magneto-Mechanical Actuation
Get PDFIn this study, we investigate the effects of cell therapy and magneto-mechanical actuation (MMA) to treat glioblastoma (U87). MMA approach employs super low-frequency alternating magnetic fields (AMF) to actuate intracellular PEGylated superparamagnetic iron oxide nanoparticles (PEG-SPIONs). Magnetic forces are translated into mechanical agitation on PEG-SPIONs, which can disrupt key cellular components. We explored two ways in which the MMA approach can be used to combat cancer growth. First, we investigated MMA directly in U87 cells. Preliminary observations indicate that PEG-SPIONs are intracellularly taken up by the U87 cells via micropinocytosis. Cell-counting kit-8 toxicity assays revealed a cytotoxic effect of MMA treatment with increasing PEG-SPION concentration, likely due to cytoskeletal disruption. Microscopy images showed characteristic apoptotic blebbing and cellular protrusions in MMA-treated U87 cells, suggesting induction of apoptosis. Second, we investigated the regulation of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) expression using MMA in transduced neural stem cells. These cells were engineered via lentiviral transduction to express TRAIL, which selectively binds death receptors on cancer cells to induce apoptosis. TRAIL-secreting neural stem cells (tC17.2) were treated with PEG-SPIONs at various concentrations (0-200 ug/mL) and exposed low-frequency pulsed AMFs (100 mT, 50 Hz, 30 min). Confocal microscopy confirmed PEG-SPION uptake in tC17.2 cells, while cytotoxicity studies indicated that MMA treatment was sufficient to induce mild ER stress and modulate TRAIL expression without causing damage to the tC17.2 cells. Conditioned media from tC17.2 cells were transferred to U87 cells to assess cytotoxicity in comparison to commercial TRAIL with known concentrations, which revealed that the TRAIL secreted from tC17.2 cells exhibited a similar effect to commercial TRAIL at a concentration of 1000 ng/mL. This MMA approach has the potential to minimize side effects in patients without the need for interfering drugs. By leveraging MMA for targeted cancer therapy, this study represents a significant step forward in the field of cancer nanotherapeutics
How Perceived Political Uncertainty Affects Markets: An Investment Analyst’s Reflection
Get PDFThis paper explores the relationship between political uncertainty and financial market behavior, offering reflections based on personal experience as an Investment Analyst at an RIA. It discusses key events and highlights how market perceptions can dramatically influence financial markets. It highlights how an organization can overcome challenges and serve clients in uncertain times
Mathematics-AI Based Phylogenetic Analysis of Influenza Virus Mutation Data
Get PDFThe influenza virus is one of the most common viral infections each year and can mutate rapidly. Viral mutations pose significant threats to public health by increasing infectivity and strengthening vaccine resistance. To track these evolving patterns, agencies like the CDC annually evaluate thousands of virus strains to understand viral mutagenesis and evolution in depth. Therefore, a computational method for analyzing high-dimensional, noisy virus data could aid in the rapid identification of antigens essential for an effective influenza vaccine for the upcoming season. Through the integration of genomic analysis, clustering, and dimensionality reduction methods, this study specifically aims to develop such a computational method for tracking influenza virus mutation patterns. Additionally, this method can be applied to further investigate the differences in the mutagenesis of the influenza virus before and after the COVID-19 pandemic, potentially due to preventative measures such as quarantining and wearing masks. More specifically, K-means clustering is applied to pre- and post-COVID-19 influenza datasets that are reduced by principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP) then labeled by time collected. Post-COVID-19 influenza data is transformed onto the embedding from pre-COVID-19 influenza data to identify unique clustering of most recent influenza sequences. Furthermore, the latent space of a variational graph autoencoder is explored as a dimensionality reduction method. This method can include embeddings of similarities between sequences in both time collected and specific mutation changes for future mutation predictions. Findings indicate that clustering and dimensionality reduction provide insight into the complex dynamics of viral mutation, informing both future research directions and strategies for public health intervention
Employee Engagement in the Manufacturing Industry
Get PDFThe primary objective of this paper is to analyze employee engagement in the manufacturing industry while explaining the implementation processes for putting engagement initiatives in place. Employee engagement has shown to have an impact on overall business performance and this paper examines the original introduction of engagement in a workplace setting, theories relating to employee engagement, the need for engagement in the manufacturing industry, the key drivers of employee engagement, and human resource practices. This paper also walks through my 10-week internship with Klein Tools, and the processes I took to implementing employee engagement methods at Klein Tools’ manufacturing plant and distribution center
Decoding Oncology-Focused Biotechnology Firms: Lifecycle Analysis and Predictive Insights for Valuation from a Junior Associate\u27s Perspective
Get PDFOncology-focused biotechnology firms present unique valuation challenges due to high R&D costs, long development timelines, and uncertain clinical outcomes. This thesis addresses such challenges by integrating the clinical development lifecycle with financial valuation models to provide predictive insights into company value. A structured framework is developed that primarily focuses on stage-specific probabilities of success (PoS) for drug candidates and their impact on firm valuation, embedded in techniques such sum-of-the-parts (SOTP) analysis. By quantitatively linking clinical trial phases and likelihoods of approval to cash flow projections, the model enables a more realistic, risk-adjusted estimation of a biotech firm\u27s worth. Through lifecycle analysis of oncology drug pipelines, the research demonstrates how incorporating clinical milestones and attrition rates can refine valuation accuracy. The approach, viewed from a junior associate’s perspective, emphasizes practical application—bridging scientific progress and financial modeling. Ultimately, this integrated methodology yields more nuanced valuations and aids stakeholders in assessing investment attractiveness, aligning a firm’s developmental progress with its economic valuation
Survey of the Labor Market for New Ph.D. Hires in Economics 2025-2026
Get PDFThis year, the survey questionnaire was sent to 478 organizations. Questionnaires were returned by 145 organizations (30.3 percent). Of this year’s responses, 78 (53.8 percent) were from those who responded to the last survey conducted for the 2024-25 academic year. Among the academic institutions responding, the distribution of highest degrees offered was as follows: Ph.D.—43.4 percent; Master’s—11 percent and Bachelor’s—44.8 percent.
The responses are reported for all respondents, and separately for Ph.D. Degree granting institutions and for schools whose highest degree offered is the Bachelor’s or Master’s Degree. Data for the top 30 institutions in the revised National Research Council’s Research Doctorate Report, 2011, are reported as a subset of Ph.D. Degree granting schools. They are referred to as the Top 30
Zyn: The Social Buzz
Get PDFUse of nicotine pouches among adolescents are increasing as marketing of Zyn through social media platforms such as, TikTok, is spreading quickly. Micro-influencers on TikTok are presenting the nicotine pouch, Zyn, and its abundance of flavors. The attractiveness of Zyn is primarily due to its subtleness, assortment of flavors, and convenience. The objective of this research is to examine how social media marketing of Zyn pouches is influencing the increased use of this product among adolescents and young adults. This research will aim to answer how Zyn is being communicated on TikTok, what demographic is primarily depicted using or talking about Zyn on TikTok, and what kind of sentiment is being portrayed on TikTok about Zyn.
Current research studies examine nicotine pouch marketing primarily though radio televisions and print advertising. What they often lack is a source that all adolescents and young adults are consumed by: social media. Ranking third worldwide for the largest social media platforms with the greatest advertise reach, this research investigates TikTok’s Zyn marketing towards adolescents. The methodology for this research included coding for 112 TikToks to identify popular demographics, gender expression, flavors, sentiments, and dependence of Zyn. Our research shows that many of the individuals making the videos are white males, with a wide variety of branding, focusing mainly on wintergreen and spearmint flavors. Additionally, the videos contain a primarily positive sentiment, satire, and little talk about cessation, addiction, or dependence.
My research team and I developed a codebook to accurately define the coded terms when examining TikTok videos. Our preliminary review included conducting an initial review of a sample of TikTok videos related to Zyn, and identifying preliminary codes based on recurring themes, phrases, behaviors, and symbols. We defined the codes by assigning clear, operational definitions to each code to standardize interpretation. Lastly, we finalized the codebook and maintained a log of codebook revisions to document changes and ensure transparency. Following codebook development, all 112 videos were annotated by two trained coders. The full metadata was examined for all videos based off number of followers, likes, comments, shares, and common Zyn hashtags.
Zyn is a tobacco-free nicotine pouch that is put inside an individual’s upper lip, risking gum damage and oral cancer. Nicotine pouches can be highly addictive and pose cardiovascular problems, increasing blood pressure and heart rate. With its appealing qualities of discreteness and uniqueness being marketed through TikTok, young adults are getting attracted to Zyn products. Using this research, we can effectively show how the marketing of Zyn affects the young adult population. Our findings allow us to make informed public health recommendations to mitigate the risks associated with nicotine use among young people.https://scholarworks.uark.edu/hnrcsturpc25/1024/thumbnail.jp
The Games Kids Play: Determining Concussion Risk of Playground Sports A Review of NEISS Data (2013-2022)
Get PDFThis study aims to identify which playground games or recreational sports pose the highest risk for injury, specifically concussions, and highlights the importance of concussion prevention training for all school personnel to minimize potential health risks for children.https://scholarworks.uark.edu/coesym25/1000/thumbnail.jp