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The Scarlet - Volume CIII, No. 7 (January 24, 2025)
No full textThe January 24, 2025 edition of The Scarlet (est. 1939), Clark University\u27s student-run newspaper. The Scarlet is intellectually and editorially independent of the University.https://commons.clarku.edu/scarlet/1174/thumbnail.jp
Clark Student Voices Literary Magazine, Issue 5: Play (Spring 2025)
No full textIssue 5 of the Clark Student Voices Literary Magazine, published in the Spring 2025 semester. The theme of the issue is \u27Play\u27. A semesterly publication curated by Clark University students, CSVLM creates space for students to share their creative writing including poetry, prose, and artwork. Organizing and distributing Clark Student Literary Voices builds community by uniting the many creative students on the Clark campus.https://commons.clarku.edu/clarkstudentliterary/1000/thumbnail.jp
Language, Literature, and Culture Newsletter, Eighth Edition (May 2025)
No full textThe eighth issue of the Language, Literature, and Culture department newsletter, which went out in May 2025. The Language, Literature, and Culture department newsletter aims to share stories, news, ideas, achievements, and important information about and within our academic department that can be helpful to the campus community at large .https://commons.clarku.edu/llcnewsletters/1007/thumbnail.jp
[369] A portion of the National Air Museum exhibit in Washington D.C., undated
No full textPhotograph showing a portion of an exhibit about Robert Goddard at the National Air and Space Museum (then National Air Museum) in Washington D.C. This photograph is part of the final section of Esther Goddard\u27s photo album titled A Few Informal Photographs, Through the Years . Not all of these photographs were taken by Esther.
\u27The Goddard Rocket Researches: A Photographic Record\u27 is an annotated photo album covering Robert H. Goddard\u27s work and experimentation with rocketry. It was assembled and curated by Esther Goddard sometime after her husband\u27s passing in 1945. Additionally, almost all of the photographs were taken by Esther herself.
Photographs were scanned at 400dpi.https://commons.clarku.edu/goddardphotographs/1368/thumbnail.jp
French Club group photo [4], 1948
No full textGroup photograph of Clark University\u27s French Club, 1948.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/frenchclub/1003/thumbnail.jp
French Club group photo [3], 1951
No full textGroup photograph of Clark University\u27s French Club, 1951.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/frenchclub/1002/thumbnail.jp
Early-pandemic repricing of housing attributes: evidence from Middlesex County, Boston suburbs
No full textThis paper examines how the abrupt shift to remote work during the early COVID-19 period changed the implicit prices of housing attributes in Middlesex County, Massachusetts, a suburban region adjacent to Boston. Using nearly 40,000 single-family home sales from 2017 to 2021, I estimate a hedonic price model in a difference-in-differences framework, comparing inner suburbs, outer suburbs, and exurbs before and after the pandemic\u27s onset. I find that outer suburban and exurban home prices appreciated significantly more than those in the inner suburbs. In the outer suburbs, price premiums for proximity to railway stations and garages declined, suggesting that homebuyers anticipated less frequent commuting. Conversely, price premiums for features supporting remote work, such as additional bathrooms, increased across all regions, with home offices, outdoor spaces, and extra bedrooms particularly valued in the inner suburbs. These findings provide novel evidence of an early-pandemic revaluation of home values by shifts in work arrangements and locational preferences. The study contributes to asset pricing literature by showing how macroeconomic shocks and behavioral shifts drive real estate revaluation, offering insights for investors and policymakers. © 2025 Elsevier Inc
Improving STEM Teaching, Learning and Sense of Belonging Utilizing Design Thinking and Students-As-Partners Models in Higher Education
No full textThis article describes the Learning Partners model at Clark University, a program that combines and enhances research-backed instructional models and pedagogical practices in STEM education. By integrating strategies across frameworks more holistically, the program has supported both students and faculty, leading to demonstrable gains in teaching, learning, and student sense of belonging - especially in STEM courses where students often face disproportionate challenges. This article will highlight the foundational models, explain how to integrate these strategies into an effective program, and to share lived experiences from three STEM disciplines: Calculus, Biology, and 3D Modeling. The integrated model presented here also offers a framework for improving faculty development through a push-in, just-in-time approach, where students have significant input into the problems faculty address. © 2025 IEEE
Optimizing future cropland allocation in a biodiverse savanna by integrating agricultural benefits and ecological costs
No full textContext: Producing sufficient food to meet a growing population while minimizing the ecological impacts of agricultural expansion is a major global challenge, particularly in biodiverse regions where cropland development threatens ecological integrity. Tanzania exemplifies this tension, as efforts to meet food security goals often conflict with the conservation of its rich ecosystems. Objectives: We aimed to optimize the spatial allocation of future cropland to balance agricultural productivity with key ecological objectives. Additionally, we evaluated alternative strategies for meeting future food demands, such as increasing cropland usage intensity and expanding high-yield crops, to reduce pressure for further cropland expansion. Methods: We developed a spatially explicit trade-off model that linearly aggregates multiple land use objectives using flexibly assigned weights. The model integrates crop yield potential (for maize, paddy rice, sorghum, cassava, and common beans), travel time to markets, and ecological costs related to biodiversity, carbon sequestration, and landscape connectivity. We applied the model to Tanzania to identify optimal areas for cropland expansion under a range of decision-making solutions and agricultural development scenarios. Results: Our analysis revealed that incorporating more decision-making factors, even with modest weights, yields greater overall benefits than emphasizing fewer objectives. Compared to a yield-only strategy, a hybrid strategy that equally weighs agricultural and ecological priorities reduced travel time to markets by 25.4%, biodiversity loss by 1.4%, carbon loss by 0.8%, and connectivity loss by 27.5%, while requiring only 2.6% more land. Additionally, increasing cropland area usage intensity and expanding the cultivation of high-yield crops can effectively boost food production, with the potential to double the current production using existing cropland alone. Conclusions: Our findings highlight the potential of spatially optimized, multi-objective planning to reconcile food production with ecological conservation at the landscape scale. By explicitly quantifying trade-offs and synergies among competing objectives, this approach offers a flexible and transferable framework for sustainable landscape planning in other ecologically sensitive agricultural frontiers. © The Author(s) 2025
Enhanced Breast Cancer Classification Using Attention-Augmented CNN and Multi-View Learning on the Inbreast Dataset
No full textBreast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical need for accurate and early diagnosis. Convolutional Neural Networks (CNNs) have demonstrated remarkable performance in medical image analysis, particularly in mammographic classification tasks. Building upon prior work that employed a fine-tuned VGG-16 model combined with a Support Vector Machine (SVM) classifier on the INbreast dataset, this study proposes a novel extension to enhance both accuracy and interpretability. The proposed framework integrates Convolutional Block Attention Modules (CBAM) into the CNN architecture to enable adaptive feature refinement by focusing on salient spatial and channelwise information. Additionally, a dual-stream multi-view learning approach is introduced to leverage bilateral mammographic images, capturing cross-view contextual dependencies often overlooked in single-view analysis. To further improve classification performance, a lightweight Vision Transformer (ViT-lite) replaces the traditional SVM, facilitating effective global feature modeling through self-attention. Experimental results on the INbreast dataset demonstrate a significant improvement in classification accuracy, achieving 98.4%, along with enhanced precision, recall, and AUC scores. The proposed model not only advances the state-of-the-art in breast cancer classification but also provides a more interpretable and scalable solution, thereby contributing to the development of reliable computer-aided diagnostic tools in clinical settings. © 2025 IEEE