Digital Commons Network^™

Murder Of The Magic Mushroom Man, Andrea Florian, Alexa Cabral, Olivia Fawkes, Emily Gomez

SPARK Symposium Presentations

Rowan Tucker is an heirloom vegetable farmer that lives in Newbury, VT on an 80-acre farm. Most of the money in Rowan’s name was from selling psilocybin mushrooms that he disguised as payments under “crop-selling”. He was found dead presenting symptoms early that morning of confusion, hallucinations, vomiting, sweating, and extreme salivation. How did he get murdered? Who did it?

A Day (Really Night) In The Life Of An Urban Raccoon, Grace K. Khalili, Sophia T. Concepcion, Darlene Panvini

SPARK Symposium Presentations

This project explores how urban environments shape the daily life, survival strategies, and ecological role of raccoons. Focusing on raccoons as non-human city residents, we examine their habitat use, feeding behaviors, and interactions with humans and other species. Using research articles, we highlight how raccoons adapt to urban spaces by using structures like trees, attics, and storm drains, and by relying on diverse food sources, including human waste. Our findings are presented as a children’s illustrated “day in the life” storybook, combining creative storytelling with urban ecology concepts. Overall, the project emphasizes raccoons’ adaptability and their important role in maintaining …

Dose-Dependent Developmental Toxicity Of Cisplatin In Zebrafish Embryos, Reagan D. Sellers, Katherine T. Doucet, Jinhee Park, Andrea Florian

SPARK Symposium Presentations

Cisplatin is a widely used chemotherapy drug for treating various types of cancer. Although cisplatin is effective in killing cancer, it can also cause toxic side effects in normal tissues. Because cisplatin can cross the placental barrier, its use during pregnancy is generally avoided, particularly during early embryonic stages of fetal development. Exposure to cytotoxic drugs during embryogenesis may lead to developmental abnormalities, birth defects, or pregnancy complications. Understanding how cisplatin affects early development is therefore important.          
       Zebrafish (Danio rerio) are an established model for studying developmental toxicity due to their rapid external development, transparent embryos, and genetic similarity to …

Effects Of Glucagon And Insulin On Sw480 Colorectal Cancer Cells In Combination With Cisplatin, Sarah M. Gabous, Andrea Florian

SPARK Symposium Presentations

Colorectal cancer is known to be one of the most common forms of cancer in the world. Over time, treatment responses are affected by various metabolic changes along with chemotherapies. Glucagon signaling and Insulin are linked to colorectal cancer and have also been shown to affect tumor growth, as well as the chemotherapy drug response.In this experimental study, the purpose was to determine whether glucagon and insulin decrease the viability of SW480 colorectal cancer cells during cisplatin (CDDP) treatment. CRC cells were treated with cisplatin alone and in combination with either glucagon or insulin, and cell viability was measured to …

Using Provided Guided Notes In Coordinated Introductory First-Year Mathematics Courses, Jennifer L. Huber

Mathematics Dissertations

The goal of this study is to investigate how standardized guided notes shape instructional practices and student engagement in coordinated introductory first-year college mathematics courses at a large public university. The researcher explored three multi-section introductory mathematics courses with overlapping learning objectives. Each course required students to purchase a student workbook as part of the instructional materials for the class. The instructors taught primarily from the workbook containing guided notes created by a former coordinator of the course. The researcher used a mixed-methods approach. Instructors and students participated in surveys, class observations and provided class meeting notes. Instructors shared additional …

Adaptive Synchronization In Digital Twin–Enabled Iot Systems: A Unified Framework For Energy, Fidelity, And Latency Trade-Offs, Uzma Zehra

Computer Science and Engineering Theses

Digital twin technology has emerged as a foundational paradigm for enabling real-time monitoring, analysis, and control in Internet of Things (IoT) systems by maintaining virtual representations of physical processes. Its effectiveness, however, critically depends on timely and accurate synchronization between distributed sensing devices and their corresponding digital counterparts. Frequent synchronization improves reconstruction fidelity and system responsiveness but incurs significant communication energy consumption and network latency. In contrast, infrequent synchronization conserves communication resources but can lead to stale or inaccurate digital twin states, particularly in environments with rapidly changing dynamics. These opposing effects give rise to a fundamental trade-off among energy …

Hostos Community College Academic Bulletin 2025-2026, Hostos Community College

College Bulletins

This is the official college catalog for 2025-2026. It contains course descriptions as well as information on degree programs, college resources and services, financial aid, admissions, and the academic calendar.

Ai Literacy Frameworks In Secondary Cte: Supporting The Next Generation Of The Workforce, Reagan Kaylee Montross

All Electronic Theses and Dissertations

The purpose of this literature review is to understand how generative AI (GenAI) is impacting the future employment of high school students at the forefront of the most significant technological, cultural, and educational shift of this generation. It examines five AI literacy frameworks relating to secondary education. These frameworks each emphasize the importance of educating students in AI literacy and provide educators with a structure for integrating AI skills. Among the frameworks reviewed, those published by the United States Department of Labor and the OECD place greater emphasis on applied practices, while the AI4K12 and KAT frameworks emphasize how AI …

Enhancing Team Science By Training Collaborative Biostatisticians To Have A Strong Statistical Voice, Gina-Maria Pomann, Steven C. Grambow, Marissa C. Ashner, Bibhas Chakraborty, Nan Liu, Megan L. Neely, Sarah Peskoe, Lacey Rende, Emily Slade, Tracy Truong, Lexie Zidanyue Yang, Greg P. Samsa, Jesse D. Troy

Biostatistics Faculty Publications

Strong statistical voice is defined as the ability to advocate and negotiate for good and ethical statistical practices, including integrating and resolving differing scientific approaches. This skill is crucial for biostatisticians who work on biomedical research teams, as it ensures the integrity and accuracy of statistical analyses and fosters productive collaborations with non-statisticians. Despite its importance, new graduates often lack targeted training opportunities. This manuscript presents a scalable training approach through the development of online videos. Preliminary didactic materials focused on two key applications: providing written comments on manuscripts and engaging in study design discussions. To evaluate this training approach, …

Should The Illiberal Arts Be Servile In A Classical Christian Education, Nadine B. Kong Mrs.

Master of Arts in Classical Studies

The purpose of this thesis is to research the role and position of the illiberal arts in a classical Christian education (CCE).  The current climate of growth for CCE makes it a fitting moment to consider what bearing the illiberal arts should have on paideia formation.  To answer this question, the historical context of CCE and the illiberal arts is presented.  This leads to a complex issue around the various imprecise terms and historical attitudes surrounding the illiberal arts.  Some synonymous terms have demeaning connotations: ‘servile arts’ or ‘illiberal arts,’ and others less negative, such as ‘common arts’ or ‘mechanical …

Preliminary Observations From The Relativistic Electron Atmospheric Loss (Real) Satellite Mission, Evzen Selvon, Robyn Millan

Wetterhahn Science Symposium Posters

The Relativistic Electron Atmospheric Loss (REAL) spacecraft (launched in July 2025) is a 3U cubesat designed to measure the precise energies (1 keV – 2MeV) and pitch angles of electrons entering the Earth’s ionosphere. The mission involves Dartmouth, BU, JHUAPL, MSU, and NASA. REAL carries three particle sensors measuring low, medium, and high energies. This work is focused on the ElectroStatic Analyzer (ESA) instrument, designed to measure lower energy electrons (1-40 keV) in the directions parallel and perpendicular to the Earth’s magnetic field. This research aims to identify notable events observed by the REAL spacecraft for future analysis.

Predicting Next-Day Eur/Usd Direction Using News Sentiment And Technical Indicators With Finbert And Xgboost, Darshan Sanjaybhai Khunt

Selected Full-Text Master Theses 2021-

Forecasting exchange-rate movements is a challenging task because currency prices are influenced not only by macroeconomic and financial variables but also by market sentiment reflected in financial news. This thesis examines whether financial news headlines can be used to predict the next-day directional movement of the EUR/USD exchange rate by applying finance-specific natural language processing and machine learning techniques.

The study uses a dataset of approximately 466,000 finance-related English-language news headlines collected between 2021 and 2025, aligned with daily EUR/USD closing prices. After preprocessing and temporal alignment, the data are used to construct a binary classification task in which the …

Exercise Science Pre-Pt, Kinesiology, Sport, And Recreation

Program Revisions/Additions

No abstract provided.

Forecasting Precipitation In Cuba Using Graph Based Deep Learning, Taufiqul Islam

Earth & Environmental Sciences Theses

Daily precipitation forecasting remained a challenging problem in regions characterized by strong spatial heterogeneity, nonlinear atmospheric dynamics, and intermittent rainfall behavior. Cuba represented a particularly complex case due to the combined influence of tropical cyclones, easterly waves, mesoscale convective systems, and orographic effects, which produced highly variable rainfall patterns in both space and time. Conventional statistical and machine-learning models typically treated stations independently and therefore overlooked spatial dependencies that strongly influenced rainfall variability across the island.

This study developed a spatiotemporal deep-learning framework for daily precipitation forecasting across 40 spatial nodes in Cuba using data from 1979 to 2023. The …

Benjamin Panciera-Linda Mccormick Forrestal Rice '61, Benjamin Panciera, Linda Rice

Alumni Oral History Project

No abstract provided.

Investigation Of Reey Concentrations In Argillaceous Rocks Associated With Coal Beds In Southwestern West Virginia, Alyssa Cameron Long

Theses, Dissertations and Capstones

Rare earth elements (REEs) and Yttrium are classified as “critical minerals” that are used in many industries and are typically extracted from carbonatites and related alkaline plutonic rocks. The limited availability of REE+Y requires finding alternate sources such as coal fly ash, tonstein, fireclays, and shales. This study investigates the potential enrichment of shales, fireclays, and siltstones interbedded with coal from southwestern WV in REEY, and the mechanisms of such enrichment. Using ICP-AES analysis of various rock types shows that shales, silty shales, and siderite nodules interbedded with Fire Clay and Chilton Coal beds in the Kanawha Formation record the …

Game-Based Learning For Asynchronous Ai Literacy Course: Approach To Improve Students' Cognitive, Behavioural, Affective, And Ethical Learning Of Ai, Jinhee Kim, Guang Yang, Wing Sha Chan, Xi Lin, Yukyeong Song

STEMPS Faculty Publications

Educators in higher education face persistent challenges in scaling AI literacy across disciplines and helping novice learners understand abstract AI concepts. Although research on game-based learning (GBL) reports mixed outcomes, few studies have examined its large-scale use in mandatory, asynchronous AI literacy courses for diverse undergraduate populations. Addressing this gap, this study investigates a scalable GBL-based AI literacy course delivered to 4898 first-year undergraduates across disciplines. Using a mixed-methods design with 311 valid pre- and post-survey responses and 20 interviews, the study evaluates students' cognitive, behavioural, affective, and ethical learning of AI. Quantitative results show significant improvements in overall AI …

The Impact Of School Climate On Student Achievement, Tonia L. Schiro

All Electronic Theses and Dissertations

This literature review explores the relationship between school climate and student achievement by examining research from education, psychology, and school improvement literature. School climate encompasses many aspects of the educational environment, including perceptions of safety, the quality of relationships among students and staff, levels of engagement, and students’ sense of belonging within the school community. The review investigates how these factors contribute to academic success and influence students’ overall educational experiences. Findings across the literature consistently demonstrate that positive school climates are associated with higher levels of student achievement, stronger engagement, improved attendance, and greater social-emotional well-being. The review also …

The Impact Of Somali Parental Involvement On Elementary Education In Minnesota: Opportunities And Challenges, Abdiqani Abdullahi Elmi

All Electronic Theses and Dissertations

Abstract This qualitative study examines the challenges faced by Somali-American parents in Minnesota regarding involvement in their children's education, particularly during elementary school. The elementary level is a critical stage for students' learning and a foundational pillar for both academic development and social integration, making parental involvement during this stage especially important. However, immigrant families, specifically Somali-Americans, face significant challenges that impede their ability to participate actively in their children's educational journey. This qualitative phenomenological research investigated barriers that might stem from limited formal education, low English proficiency, cultural, linguistic, and socioeconomic challenges. The methodology used in this research is …

Floodwater Salinity And Flood Duration Regulate Greenhouse Gas Production In High- Latitude Coastal Wetland And Tundra Soils, Mia J. Dicianna

Electronic Theses and Dissertations

Coastal high-latitude ecosystems are increasingly flooded from storm surges associated with climate change, exposing soils that were historically infrequently inundated to higher-salinity waters for longer durations. Sub-Arctic wetlands and tundra store large amounts of carbon, yet how flooding characteristics, particularly flood duration, influence microbial mineralization and, consequently, greenhouse gas (GHG) production in these soils remains poorly understood. We conducted a full-factorial microcosm incubation experiment in which coastal wetland and tundra soils were subjected to simulated flooding with three durations (1, 3, and 10 days) and four salinity treatments (unflooded, freshwater, 3 ppt, and 12 ppt) and measured carbon dioxide (CO2) …

Winter-Feeding High Forage Vs. High Concentrate Diets To Beef Cows: Effects On Placental Transcriptomics, Lactation Capacity, And Enteric Methane Emissions, Megan Ann Wehrbein

Electronic Theses and Dissertations

Nutritional management and lactation performance are critical factors influencing productivity in cattle. This research includes two complementary studies. The first study was a meta-analysis to develop a lactation curve for Bos taurus cattle in North America using data from machine or hand milked cows. Data from 7 studies were used resulting in 1340 cow-day observations. Milk yield was analyzed by parity (primiparous or multiparous) and feeding management (non-nutrient restricted or nutrient restricted), revealing that primiparous cattle peaked earlier and at lower yields than multiparous cattle, and nutrient restriction reduced peak milk yield. Overall, Bos taurus cattle followed lactation trends similar …

Simulating Social Attitudes With Llms: Accuracy, Demographic Effects, And Refusal Behavior In The Sensitive Domain Of Suicide Prevention, Cristina J. Perez, Michael P. Vasquez Jr., Philippe J. Giabbanelli, Patrick Y. Wu

VMASC Publications

Large language models (LLMs) are increasingly used to simulate public opinion, yet their validity in sensitive policy domains remains underexplored. We evaluate whether LLMs can reproduce attitudes toward suicide prevention policies using 32 questions drawn from seven nationally representative U.S. surveys (2023-2025). We systematically vary demographic conditioning (race/ethnicity, gender, age, education, income, party), prompt framing (direct elicitation, respondent embodiment, specialist embodiment), and model architecture (GPT-5 Nano, DeepSeek V3.2, Meta Llama 3.1 8B, Mistral Small 24B). Across 811,560 prompts, the mean absolute error—the average gap between predicted and human response distributions—is 23 percentage points. We also find that LLM responses to …

An Exploration Of Geomagnetically Induced Currents And The Accessibility Of Geomagnetic Data Collection, Richard Le

Physics Theses

Geomagnetically Induced Currents (GICs) are electrical currents induced in long grounded conductors during geomagnetic disturbances. They represent one of the primary space weather hazards to critical infrastructure, particularly high-voltage power transmission systems and other grounded conductor networks such as pipelines. As modern society becomes more dependent on these systems, understanding and mitigating the impacts of space weather has become increasingly important. This thesis examines the physical mechanisms that generate GICs, from the interaction of the solar wind with Earth’s Magnetosphere to Magnetosphere-Ionosphere-Thermosphere (MIT) coupling and the current systems that drive geomagnetic disturbances (GMDs). Case studies from Zimbabwe and Finland illustrate …

Computational Study Of Rotating Detonation Combustors, Aditya Balasubramaniam

Mechanical and Aerospace Engineering Theses

Rotating detonation combustors (RDCs) are pressure-gain combustion devices that sustain one or more continuously rotating detonation waves, offering potential thermodynamic and performance advantages over conventional deflagration-based systems. Their behavior depends strongly on combustor geometry and operating conditions. Understanding these effects is therefore essential for the design and optimization of practical RDCs. Accordingly, this thesis numerically investigates annular RDCs with two primary objectives: (1) to evaluate the effects of propellant mass flux and (2) to assess the influence of annular width on detonation-wave dynamics and combustor performance.

A finite-volume framework is used to solve the compressible reactive Euler equations with hydrogen–air …

Reliable And Label-Efficient Learning For Open-World Visual Perception And Robot Learning Under Uncertainty, Zongyao Lyu

Computer Science and Engineering Dissertations

Modern learning systems deployed in open-world environments must make reliable decisions despite predictive uncertainty, previously unseen classes, limited annotations, and distribution shifts. This dissertation develops methods for reliable and label-efficient learning in visual perception and robot control.

First, this work studies uncertainty in object detection by representing semantic and spatial predictions probabilistically. A deep-ensemble framework aggregates detections into class-probability distributions and probabilistic bounding boxes, while a subsequent extension combines deep ensembles with Monte Carlo dropout to further investigate predictive uncertainty. Second, this dissertation addresses open-set recognition, where classes absent during training may appear at inference time. An empirical study shows …

Advancing Hate Speech Detection: Binary And Multiclass Approaches From Traditional Methods To Parameter-Efficient And Ontology-Guided Language Models, Mahmoud Abusaqer

Graduate Theses/Dissertations

The widespread proliferation of hate speech on social media platforms poses significant challenges for content moderation and user safety, requiring automated systems that are simultaneously accurate, efficient, and capable of fine-grained distinctions. This thesis investigates hate speech detection through five published manuscripts organized into two complementary threads: binary detection (hateful vs. non-hateful) and multiclass detection across demographic targeting categories. The binary thread progresses from a broad 38-model baseline spanning traditional machine learning, deep learning, and transformer architectures (where RoBERTa reaches 91.48% accuracy and CatBoost remains competitive at 88.60%) to parameter-efficient adaptation, in which Low-Rank Adaptation (LoRA) of large language models …

Constraining The Tectono-Climatic Evolution Of The Northern Rocky Mountains: Insights From Volcanic Glass, Leaf Water, And Leaf Wax Hydrogen Isotopes, Rijumon Nandy

Earth & Environmental Sciences Dissertations

The Eocene-Oligocene period in the North American Cordillera represents a period of great intrigue with complex interactions among tectonics, climate, and surface processes. Although this period is generally associated with synorogenic extension associated with gravitational collapse of the Cordillera, the paleotopographic history remains debated. Existing studies offer conflicting interpretations, suggesting either sustained elevations or modest uplift during this time. Notably, recent reconstructions based on volcanic glass δD values have proposed renewed uplift during the early Oligocene, which needs to be tested with a more extensive and robust dataset. Concurrently, global cooling and aridification during this interval may have been amplified …

The Critical Role Of Near-Surface Dynamics In Identifying Spawning Areas Of Atlantic Bluefin Tuna In The Gulf Of Mexico, Donald R. Johnson, William J. Teague, Harriet Perry, James S. Franks

Gulf and Caribbean Research

Atlantic Bluefin Tuna, Thunnus thynnus (ABFT), migrate long distances to broadcast spawn in the Gulf of Mexico (GOM) basin, the Mediterranean Sea and the Slope Sea (NW Atlantic). These areas have commonalities including a highly dynamic upper ocean eddy environment that draws nutrients from shallow thermoclines and adjacent continental shelves and can provide temporal sanctuaries from some larval predators. In the GOM basin, the Loop Current (LC) and its energetic spin—off eddies sweep weak swimming predators such as jellyfish (Pelagia noctiluca) into lines and aggregations, leaving relatively open areas as temporal sanctuaries for ABFT larvae during the vulnerable …

Students-Generative Ai Interaction Patterns And Its Impact On Academic Writing, Jinhee Kim, Sang-Soog Lee, Rita Detrick, Jialin Wang, Na Li

STEMPS Faculty Publications

Considering both the transformative opportunities and challenges presented by generative AI (GenAI) in academic writing, effectively integrating GenAI into the academic setting becomes a significant need requiring prioritization. Yet, there is limited understanding regarding the nature of interactions between different types of students, what behavioral patterns students exhibit during a student-GenAI interaction (SAI) on a given task, and how these different SAI patterns relate to the actual writing task performance. This study, therefore, aimed to identify SAI patterns of academic writing tasks depending on students’ level of AI literacy and examine the differences in academic writing performance between the identified …

Foreword, Pedagogical Innovations In Computer Science Education, Helen Crompton

STEMPS Faculty Publications

[Introduction] Computer science education sits at a defining moment. Across schools and universities worldwide, computing is no longer a niche discipline reserved for a select few. It is a foundational literacy that shapes how learners understand the world, participate in society, and imagine their futures. At the same time, the rapid pace of technological change, particularly in artificial intelligence, data systems, and intelligent tools, has placed unprecedented pressure on educators to rethink not only what we teach, but why and how we teach it. This book arrives precisely when such reflection is most needed.