This project explores the potential of the Sunny Buddy, a theoretical solar-powered portable kiosk, to address energy access disruptions in Costa Rica, particularly in the Monteverde region. Given Costa Rica’s advanced renewable energy infrastructure yet persistent grid disruptions due to natural disasters and maintenance, the Sunny Buddy offers a sustainable alternative to fossil-fuel-dependent generators. By researching aspects of sustainability, barriers to adoption, and potential partnerships, this study aims to enhance climate resilience and equitable access to renewable energy solutions. The insights gained will inform strategies to accelerate the adoption of sustainable technologies in Costa Rica and similar contexts globally. The goal for the study is to understand current sustainability initiatives that relate to the Sunny Buddy, build partnerships, and drive interest towards investment and development of sustainable technology. The future research hopes to implement Sunny Buddy in broader applications like the Keweenaw in Upper Michigan, US and measure environmental impact.

This research addresses the performance of Voice User Interfaces (VUIs) across multiple languages—specifically French, English, Spanish, and potentially Arabic—in accurately interpreting user commands. The primary focus is to investigate the variability in error rates among these languages, hypothesizing that English commands may be better understood due to potentially superior training data. The secondary focus explores the integration of Alexa with a Large Language Model (LLM) to assess if utilizing structured phrases and commands reduces errors. The study involves testing VUIs with commands in these languages and analyzing error rates. Data collection, including user input simulations and systematic error logging, will reveal insights into which languages exhibit higher accuracy rates in VUI command interpretation. Initial observations suggest potential benefits in error reduction when integrating Alexa with an LLM. Additional observations will hopefully further highlight the positive impact of structured command formats on VUI performance. The findings aim to inform future developments in VUI design and implementation strategies, emphasizing the importance of language-specific training and structured input formats for enhanced user interaction.

Bone grafting plays a pivotal role in restoring and reinstating the structural integrity of bone tissue. However, post-procedural complications, such as immune rejection and infection, present notable challenges in clinical practice. This project seeks to address these concerns by not only devising strategies to mitigate such insecurities but also by integrating biomaterials into clinical research protocols, thereby potentially reducing procedural costs, while maximizing overall potency. The significance of this research within the tissue engineering domain lies predominantly in the incorporation of biomaterials that mimic the physiological environment of the human body, thereby enabling more accurate modeling of clinical scenarios that influence treatment outcomes. The implementation of scaffolds in bone grafting procedures and subsequent clinical testing holds promise for mitigating risks associated with earlier techniques, thereby advancing the field's clinical efficacy.

According to the American Cancer Society, 1 in 87 women will develop ovarian cancer.1 Recognizing this statistic underscores the importance of readily available and advancing treatment options. However, due to the personalized nature of cancer, treatments tend to be both expensive and potentially harmful to the body, i.e. chemotherapy. A brand new approach is being proposed to address this challenge: employing extracellular matrix-infused hydrogels for testing cancer cells, which can be customized to meet individual needs and circumstances. These hydrogels are composed of a polysaccharide sugar known as Dextran Methacrylate, with UV radiation serving to regulate the stiffness of the gel. Additionally, four extracellular matrix proteins will be utilized to influence the growth of ovarian cancer cells across various stiffness conditions. Should it be determined through many physical and microscopy tests that cancer cells can be directed to grow in a specific manner, it may be deemed possible to align these cells more closely with those of the patient. This alignment could lead to a more biomimetic and realistic representation, in which the final step would be the testing of cancer drugs on the extracellular matrix-infused hydrogels. By harnessing this innovative testing platform, it may be possible to achieve more tailored and effective treatments for ovarian cancer, ultimately improving outcomes for patients. This approach could revolutionize how cancer treatments are developed and administered, offering hope for a future where personalized medicine is more accessible and impactful..