Institutional Repository
The UDSpace Institutional Repository collects and disseminates research material from the University of Delaware.
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- Departments can use UDSpace to publish or distribute their working papers, technical reports, or other research material.
- UDSpace also includes all doctoral dissertations from winter 2014 forward, and all master's theses from fall 2009 forward.
To learn more about UDSpace, and how you can make your research openly accessible to the public, visit our UDSpace Policies website.
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Recent Submissions
Modeling Study on Heat Capacity, Viscosity, and Density of Ionic Liquid–Organic Solvent–Organic Solvent Ternary Mixtures via Machine Learning
(Processes, 2024-07-07) Shu, You; Du, Lei; Lei, Yang; Hu, Shaobin; Kuang, Yongchao; Fang, Hongming; Liu, Xinyan; Chen, Yuqiu
Physicochemical properties of ionic liquids (ILs) are essential in solvent screening and process design. However, due to their vast diversity, acquiring IL properties through experimentation alone is both time-consuming and costly. For this reason, the creation of prediction models that can accurately forecast the characteristics of IL and its mixtures is crucial to their application. This study proposes a model for predicting the three important parameters of the IL-organic solvent–organic solvent ternary system: density, viscosity, and heat capacity. The model incorporates group contribution (GC) and machine learning (ML) methods. A link between variables such as temperature, pressure, and molecular structure is established by the model. We gathered 2775 viscosity, 6515 density, and 1057 heat capacity data points to compare the prediction accuracy of three machine learning methods, namely, artificial neural networks (ANNs), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). As can be observed from the findings, the ANN model produced the best results out of the three GC-based ML methods, even though all three produced dependable predictions. For heat capacity, the mean absolute error (MAE) of the ANN model is 1.7320 and the squared correlation coefficient (R2) is 0.9929. Regarding viscosity, the MAE of the ANN model is 0.0225 and the R2 is 0.9973. For density, the MAE of the ANN model is 7.3760 and the R2 is 0.9943. The Shapley additive explanatory (SHAP) approach was applied to the study to comprehend the significance of each feature in the prediction findings. The analysis results indicated that the R-CH3 group of the ILs, followed by the imidazolium (Im) group, had the highest impact on the heat capacity property of the ternary system. On the other hand, the Im group and the R-H group of ILs had the most effects on viscosity. In terms of density, the Im group of the ILs had the greatest effect on the ternary system, followed by the molar fraction of the organic solvent.
The Future of Mathematics Education Research: A Discussion Group
(Proceedings of the 14th International Congress on Mathematical Education, 2024-06) Bakker, Arthur; Cai, Jinfa
With help of a review study by Inglis and Foster published in Journal for Research in Mathematics Education, Jinfa Cai summarized trends in the past 50 years of mathematics education research. Next, Arthur Bakker presented a recent survey published in Educational Studies in Mathematics about the future of mathematics education research. Anna Sfard compared this survey with an earlier survey for ICMI. The presentations were discussed in the whole group, after which Jill Adler highlighted a few points she considered relevant.
An AI Solution: Using ChatGPT to Counter Plagiarism and Boost Enrollments in Hispanic Literature Courses
(Middle Atlantic Review of Latin American Studies, 2023-12-28) McInnis Dominguez, Meghan
This study presents an exploration into the application of the artificial intelligence chatbot ChatGPT 3.5 in the context of two Hispanic literature survey courses at the University of Delaware during the Spring 2023 semester. The introduction of ChatGPT into these learning environments aimed to address two key challenges in teaching Spanish and Latin American literature: falling enrollment rates and rising instances of plagiarism. ChatGPT’s role was two-pronged: it served as a component of in-class discussions and a resource for final papers. A total of twenty-one students participated in a follow-up survey designed to gauge their perceptions of ChatGPT as an innovative learning tool. The outcome revealed mixed, yet promising, responses to the use of AI technology in a literature classroom. The data suggest that the ongoing incorporation of cutting-edge tools like ChatGPT into literature courses holds the potential to captivate a diverse group of students and potentially increase enrollment. In addition, the data collected, along with the professor’s analysis of final papers, indicate that ChatGPT can be effective in curbing plagiarism. Responsible AI utilization is becoming increasingly vital in various job markets, and integrating such skills into curricula from STEM to Humanities is crucial for our students’ future career success.
Este estudio presenta una exploración de la aplicación del chatbot de inteligencia artificial ChatGPT 3.5 en el contexto de dos cursos panorámicos de literatura hispana en la Universidad de Delaware durante el semestre de primavera de 2023. La introducción de ChatGPT en estos entornos de aprendizaje tenía como objetivo abordar dos desafíos clave en la enseñanza de la literatura española y latinoamericana: la caída de las tasas de inscripción y el aumento de los casos de plagio. El papel de ChatGPT fue doble: sirvió como componente de las discusiones en clase y como recurso para los trabajos finales. Un total de veintiún estudiantes participaron en una encuesta posterior diseñada para medir sus percepciones de ChatGPT como una herramienta de aprendizaje innovadora. El resultado reveló reacciones mixtas, pero prometedoras, ante el uso de la tecnología de IA en clases de literatura. Los datos sugieren que la incorporación de herramientas de vanguardia como ChatGPT en los cursos de literatura tiene el potencial de cautivar a un grupo diverso de estudiantes y aumentar potencialmente la inscripción. Además, los datos recopilados, junto con el análisis de los trabajos finales por parte de la profesora, indican que ChatGPT puede ser eficaz para controlar el plagio. El uso responsable de la IA se está volviendo cada vez más vital en varios mercados laborales y la integración de estas habilidades en los planes de estudio, desde STEM hasta Humanidades, es crucial para el futuro éxito profesional de nuestros estudiantes.
Enhancing Hispanic Literature Courses with Large Language Models: The Power of AI Tools
(Middle Atlantic Review of Latin American Studies, 2024-06-29) McInnis Dominguez, Meghan
My current practice of incorporating AI tools into literature classes within the Latin American Studies branch provides versatile opportunities to develop engaging and meaningful exercises that inspire greater depth of creativity and critical thinking. AI tools allow students to take an active role in their learning and broaden their understanding of various literary traditions.
Mi práctica actual de incorporar herramientas de IA en las clases de literatura dentro de la rama de Estudios Latinoamericanos brinda oportunidades versátiles para elaborar ejercicios atractivos y significativos que inspiran mayor profundidad en creatividad y pensamiento crítico. Las herramientas de IA permiten a los estudiantes asumir un papel activo en su aprendizaje y ampliar su comprensión de las diversas tradiciones literarias.
Device-estimated sleep metrics do not mediate the relation between race and blood pressure dipping in young black and white women
(Journal of Clinical Hypertension, 2024-07-09) D'agata, Michele N.; Hoopes, Elissa K.; Keiser. Thomas; Patterson, Freda; Szymanski, Krista M.; Matias, Alexs A.; Brewer, Benjamin C.; Witman, Melissa A.
Short, disturbed, and irregular sleep may contribute to blunted nocturnal blood pressure (BP) dipping, a predictor of cardiovascular disease. Black women (BLW) demonstrate less BP dipping and poorer sleep health than White women (WHW). However, it remains unclear whether device-estimated sleep health metrics mediate the relation between race and BP dipping in young women. We hypothesized that the relation between race and BP dipping would be partly mediated by sleep health metrics of sleep duration, sleep efficiency, and sleep regularity. Participants (20 BLW, 17 WHW) were 18–29 years old, normotensive, nonobese, and without evidence of sleep disorders. Systolic and diastolic BP dipping were derived from 24-h ambulatory BP monitoring. Habitual sleep duration and sleep efficiency were estimated via 14 days of wrist actigraphy. Sleep duration regularity was calculated as the standard deviation (SD) of nightly sleep duration (SDSD). Sleep timing regularity metrics were calculated as the SD of sleep onset and sleep midpoint (SMSD). Mediation analysis tested the mediating effect of each sleep metric on the relation between race and BP dipping. BLW experienced less systolic (P = .02) and diastolic (P = .01) BP dipping. Sleep duration (P = .14) was not different between groups. BLW had lower sleep efficiency (P < .01) and higher SDSD (P = .02), sleep onset SD (P < .01) and SMSD (P = .01). No sleep metrics mediated the relation between race and BP dipping (all indirect effects P > .38). In conclusion, mediation pathways of sleep health metrics do not explain racial differences in nocturnal BP dipping between young BLW and WHW.