Establishing the Effectiveness of the OpenBCI EEG System in Identifying Physiological Markers of Healthy Brains

Parkinson disease (PD) is the second most common neurodegenerative disorder in the United States, affecting 1.1 million people. However, ~20% of PD patients are misdiagnosed because diagnosis often relies on subjective motor assessments by doctors. Electroencephalography (EEG) is a non-invasive, accessible tool that records neural activity using electrodes placed on the scalp, and can be used to improve diagnostics with objective neural biomarkers of PD. The cognitive neuromodulation lab bought the OpenBCI EEG system last spring, and this project sought to identify the reliability of the system. Three experiments were conducted with healthy volunteers. The data for each experiment was preprocessed using EEGLAB to isolate neural data from electrical noise. Then, MATLAB’s signal processing toolbox was used to extract the neural features. The first two experiments looked for robust neurological biomarkers of health data identified with more advanced EEG systems. With subjects alternating between eyes open and eyes closed states in the first experiment and performing thirty trials of finger tapping in the second experiment, two nonmotor biomarkers and one motor biomarker were successfully identified. The third experiment had patients perform finger tapping and spiral drawing, bilaterally, replicating motor tasks in PD assessments. With this data, three biomarkers known to differ between PD and healthy subjects were identified in this healthy cohort, consistent with the data in the literature. Having identified these biomarkers, the reliability of the OpenBCI system is verified and a comparative study between healthy subjects and PD patients will be conducted to identify novel PD biomarkers.

Continue reading Quinn Smith »

Historical Gradient of Host-Pathogen Dual Transcriptomics in White Nose Syndrome
White Nose Syndrome (WNS) is a cutaneous fungal disease caused by the fungus Pseudogymnoascus destructans (Pd) . Since its arrival in 2006, WNS has spread rapidly across North America (NA), resulting in mass mortality in hibernating bats and threatening extinction in some species. These findings aim to provide insight into how Pd pathogenesis changes over time to identify potential targets for the prevention and treatment of WNS.

Continue reading Sophia Perkins »

Unlocking Potential: The Case for Crypto Assets in the U.S. College Endowment Funds

Since 2017, crypto assets have emerged as a prominent and transformative financial
instrument globally. While major financial institutions such as BlackRock, Fidelity, and Franklin
Templeton have widely adopted these digital assets and legislation surrounding crypto holdings
has become increasingly clear, college endowment funds have remained hesitant to embrace
them. Known for their traditionally conservative investment strategies, most endowment funds
have yet to integrate crypto assets into their portfolios. To date, only a few prominent
institutions, such as Ivy League schools and Emory University, have included crypto assets in
their treasuries or invested in crypto projects as private equity.
However, this cautious approach began to shift in 2025, as endowment funds started to
seriously explore the potential of crypto assets. With their capacity to deliver high returns,
mitigate risks inherent in traditional markets, and diversify investment portfolios, crypto assets
align closely with the strategic goals of endowment funds. These goals include fostering
intergenerational equity and engaging with younger generations.
This paper will analyze the current state of college endowment fund assets, including key
investment considerations such as Environmental, Social, and Governance (ESG) factors,
propose diverse strategies for integrating crypto assets, and highlight the potential benefits of
incorporating digital assets into college endowment fund portfolios.

Continue reading William Le »

Comparing Functional and Anatomical Division of the Subthalamic Nucleus as a Predictor of Clinical Outcomes in Deep Brain Stimulation

The subthalamic nucleus (STN) is one of the most common targets for deep brain stimulation (DBS), a treatment for alleviating the motor symptoms of Parkinson disease (PD). DBS involves implanting electrodes into the STN to deliver electrical stimulation, with the goal of reducing motor symptoms and improving quality of life for patients with PD. However, its success strongly depends on where within the STN the stimulation occurs. This study aims to determine which segmentation method more closely correlates with motor symptom improvement in DBS.

40 PD patients who previously underwent bilateral STN DBS were included for analysis. Outcomes were measured as percentage improvement across rigidity, tremor, bradykinesia, and overall motor symptom. Anatomical segmentation was performed by dividing each STN into six regions using its center of mass as a reference point. Functional segmentation was derived using the Accolla atlas, which labels the STN into motor, associative, and limbic zones. The atlas was registered to each STN and then the volume of tissue activation relative to the total volume of the STN was calculated to quantify stimulation.

Results showed that functional motor zone activation weakly correlated with rigidity improvement, while other functional zones showed no significant associations. In contrast, anatomical dorsal STN stimulation significantly correlated with rigidity and distinguished responder groups. The dorsal anatomical region demonstrated stronger clinical relevance.

Continue reading Deana Marchuk »

Development of a Laboratory Methodology to Manufacture Tailings
Recent failures of tailings storage facilities have demanded a greater understanding of the behavior of tailings. However, characterization of tailings properties can be challenging due to limited access to representative samples. Hence, this study aimed to develop a methodology to recreate tailings in the laboratory that reproduce field characteristics. To accomplish this goal, we performed self-learning on the topic, laboratory investigation, and analysis of the samples created. Various geotechnical and mechanical properties of soils were studied to gain an understanding of the properties that would be tested and examined. Material characterization, sample preparation, and sample testing standards were reviewed and then applied to Ottawa sand and bentonite clay. These standard materials are accessible and readily available for laboratory use, which would allow for easy replication of the methodology created. Additionally, these materials have characteristics, for example, plasticity and shear strength, that, when mixed, would resemble field tailings. As a result of the work, a preliminary observation is that Ottawa sand has a large grain size and may not be the appropriate material for the final tailings sample, as tailings usually have a very fine grain size. Further research showed that it is possible to obtain silt-sized soils by crushing Ottawa sand, which would allow us to make a sample that is similar to field tailings and still maintains other tailings properties. Future research includes investigation of the silt-sized soil and bentonite clay mixtures to find the proper ratio of these materials to recreate tailings and then their strength properties.

Continue reading Olivia Janas »

Nutrient Loading Reduction Capability in Aged Green Roofs

As climate change accelerates, intense rain events have been persistent, damaging communities in unprecedented ways. Green roofs are a type of sustainable infrastructure that has been implemented on top of modern buildings to mitigate the effects of climate change. However, the presence of nutrients important to plant life, such as nitrogen and phosphorus, in stormwater runoff can deeply damage nearby waterways through eutrophication. This research focuses on the capabilities of the four green roof test plots atop Academic East to reduce stormwater volume, how the green roof may affect nutrient loading in stormwater runoff, and how changing plant cover may affect these parameters. To do this, the green roof testing lab found in Academic East was restored and redesigned for side-by-side analysis of the test plots. Although the project could not be fully completed in one summer, it was found that the restored green roof, with no additional changes, considerably reduced stormwater volume, peak flow rate, and ammonium mass loading for one large storm event. For this same storm event, nitrate and phosphate mass loading in the runoff appeared to increase. In the future, more research focusing on the effects of changing plant cover plans needs to be done.

Continue reading Gabriella Santos Meltzer »

Environmental Degradation and Food Systems in Ghana: Gold Mining & Synthetic Pesticides

This research examines the relationship between environmental degradation and food systems in Ghana. While existing studies explore the effects of gold mining on farmers (Gilbert and Albert 2016; Agariga 2021; Kwang and Blagogie 2025), little attention has been given to how these impacts extend to market vendors and transporters. Even fewer studies analyze food and land through a sociocultural lens. My research addresses these gaps by asking: How do environmental degradation practices—specifically gold mining and chemical use—affect food production, distribution, and security in Ghana? And how does the decline of arable land reshape cultural food identity (Parasecoli 2014)? To explore these questions, I used qualitative interviews, policy analysis, and a review of existing scholarship. Over three months, I conducted 35 semi-structured interviews (20–60 minutes each) with small-scale farmers, cash crop farmers, and market vendors in Cape Coast, Agona, Kumasi, Obuasi, Busia, Tarkwa, Ho, and Mankessim. This approach centered local perspectives while capturing the broader structural context (Gyan and Mfoafo-M’Carthy 2021; Thow et al. 2021; Ahmed et al. 2021). Findings indicate that while mining has long been part of Ghanaian society, its mechanization under British colonial rule intensified environmental harm, disrupting food production and distribution and deepening food insecurity. Those in lower economic tiers—farmers, Indigenous miners, and non-mining community members—bear the greatest burdens. Chemical use reflects unequal access to quality inputs and pressures to maximize cash crop yields, degrading land and risking health. Participants also expressed concern over cultural loss as farmland diminishes, though some resist by revitalizing traditional agricultural practices.

Continue reading Da’Mirah Vinson »

The Brutality of Prostitutes: A Study on Society In America Between 1775-1783
Women during colonial America were widely misrepresented, even in scholarly research after the time. This treatment was even worse for “women of the night.” Many of these women would serve in the trade of sexual deeds as prostitutes as a form of survival, resorting to this when they have nothing else left. Unfortunately, records, contemporary and modern, are left with heavy bias. The question of morality of the trade of sexual actions comes long before the colonial era, but remains prominent during the time. This creates problems in modern studies as talk of prostitutes during the time spoke on bias related to immorality and male victimhood. These women held an important role in the structure of the war as they increased the fear of disease, particularly venereal disease, among soldiers. This fear they created extended the bias against them during the time, a sentiment that has prevailed through research, and is something I will unravel in this study.

Continue reading Eryn Drobins »

Exploring 2D and 3D facial recognition systems and its security

Two-dimensional (2D) face recognition is widely deployed for authentication and security, yet it remains vulnerable to spoofing attacks using printed photos, replay videos, and deepfakes. Its reliability also degrades when real-world conditions drift from the enrollment image, especially under changing lighting, facial
expressions, and occlusions such as masks or glasses, creating ongoing concerns about both security and robustness. Three-dimensional (3D) facial recognition is often presented as a stronger alternative because it can exploit depth and facial geometry, but its practical resilience and attack surface under adversarial conditions still need clearer, reproducible evidence.

This study evaluated and compared the accuracy, robustness, and security of 3D facial recognition systems against 2D baselines, benchmarking open-source pipelines across public datasets and controlled laboratory experiments. Testing systematically varies illumination (direction and intensity), expression changes, and occlusions, measuring performance in verification and identification tasks. To assess security, the systems were exposed to spoofing attempts using printed media and 3D-printed facial models, recording attack success rates and characteristic failure patterns.

We revealed where 3D methods provide meaningful gains (for example, reduced sensitivity to harsh lighting and certain occlusions) and where weaknesses persisted (for example, vulnerability to high-fidelity 3D replicas or sensor-specific artifacts). By linking failure modes to specific conditions, the work aims to propose targeted upgrades, such as depth-consistency checks, temporal liveness cues, and multi-modal fusion, to harden 3D recognition. Overall, the research clarified trade-offs between 2D and 3D facial recognition and supports the development of more robust and secure 3D authentication in realistic environments.

Continue reading Zakaria Frane »

Control System Optimization for a Smart Residential Microgrid

This thesis began with a simple objective: to restore and optimize the control system of a smart residential microgrid so that it can respond intelligently to electricity prices while remaining safe and reliable on low-cost embedded hardware. The central research question is whether artificial intelligence can improve economic dispatch decisions without compromising system stability.

The work required restoring a legacy microgrid commissioned in 2015. Data acquisition was rebuilt using a Raspberry Pi 4 and an AcuRev smart meter to log voltage, current, power, power factor, and frequency at five-minute intervals. A stable data pipeline was achieved, with over 99 percent local logging uptime and 93 percent cloud upload reliability. This phase transformed the project from a control study into a grounded cyber-physical systems investigation.

A two-layer artificial neural network framework was developed. Layer 1 predicts next-hour PJM Real-Time Locational Marginal Prices using historical and time-based features, explaining about 92 percent of price variation. Layer 2 integrates predicted prices with real-time electrical measurements to guide operational modes such as load management and islanded operation. Although the controller achieved measurable economic improvement over a rule-based baseline, its performance was limited by constrained historical and seasonal data. Nevertheless, the implementation validated the complete data-to-decision pipeline and established a practical foundation for refinement.

The key finding is that economic optimization alone is insufficient. Safety must be explicitly enforced through hybrid control, combining AI prediction with rule-based protections.

Continue reading Anthony Nyoyoko »