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Indigenous Peoples\u27 Heritage Month - A Digital Exhibit
No full textNovember is Indigenous Peoples\u27 Heritage Month, a time to honor the rich and diverse cultures, traditions, and histories of Indigenous nations and communities across North America. This display highlights contemporary Indigenous leaders and healthcare providers making significant contributions to providing care and reducing healthcare disparities. It also features links to eBooks available through the Leatherby Libraries and online resources to aid in supporting the health of Indigenous peoples. This display is part of the Leatherby Libraries’ Diversity, Equity, and Inclusion efforts in alignment with the Chapman University Strategic Plan for Diversity & Inclusion, fostering a diverse and inclusive campus climate
Bibliography for Code Talkers Display
Get PDFA bibliography created to support a display about Code Talkers at the Leatherby Libraries during November 2024 at the Leatherby Libraries at Chapman University
2024 2nd Place Winners: Daniel Umoru, Olajide Adekunle, and Adeola Bakare, “Physician Visits for Patients with Diabetes by Gender, Age and Race in the United States”
No full textPictured are 2024 second-place winners Daniel Umoru (second from right, holding the certificate), Adeola Bakare (second from right, holding the certificate), and Olajide Adekunle (third from right, holding the certificate), with (left to right) Taylor Greene (Chair of Research and Instructional Services), Dr. Lawrence Brown (Associate Dean of the School of Pharmacy), and Mr. Eric Scandrett (contest sponsor).https://digitalcommons.chapman.edu/graduate_research_prize_photos/1001/thumbnail.jp
A Protocol for Immunostaining of Macrophages in Whole-Mount Mouse Cornea, Conjunctiva, and Lacrimal Gland
Get PDFThe healthy lacrimal functional unit contains a resident macrophage population. Here, we present a protocol for immunofluorescent staining of macrophage markers, CD11b, F4/80, and CD206, in whole-mount mouse cornea, conjunctiva, and 50-μM-thick lacrimal gland section. We describe steps for dissection, fixation, permeabilization, and blocking. We then detail procedures for the detection and spatial localization of macrophages through immunostaining and confocal imaging. This approach circumvents the need to obtain thin tissue sections and acquire macrophage images from each tissue section
Ideational Diffusion and the Great Witch Hunt in Central Europe
Get PDFThe great upsurge of witch trials in early modern Europe remains a historical puzzle. Popularly known as the “witch craze”, this eruption of persecution is puzzling because belief in witchcraft had existed for centuries, but large-scale witch-hunting appeared rather abruptly, spread widely, and was remarkably brutal in comparison with the past. We define a theory of ideational diffusion to describe the general process of the emergence and spread of a new idea along with its prescribed behavioral change, in this case the adoption of witch-hunting. Ideational diffusion distinguishes between the adoption of new ideas, which lead social actors to reinterpret the world and thus to change their behavior, and the adoption of behavior alone. We relate how a new theory of witchcraft appeared in the fifteenth century and show that its widespread propagation, owing to the new technology of printing, matches our description of ideational diffusion. We then analyze the diffusion of witch trials in Central Europe by combining data on the publication of demonological treatises alongside climate, state capacity, religious economy, and city network variables. We find that cities adopted persecution after demonological treatises were printed, and that nearby trials induced neighbors to adopt persecution. Tracing the print vectors and social interdependence spurring witch-hunting helps us understand the general mechanisms behind the spread of persecution
“The Kindness of Color: Researching Mendez v. Westminster” event
No full textDigital video recording of The Kindness of Color: Researching Mendez v. Westminster event held at the Leatherby Libraries on November 14, 2024. The event featured a panel examining how researchers have used Chapman University\u27s Mendez, et al. v. Westminster School District of Orange County, et al., Archives to amplify understanding of the case\u27s role in desegregating Mexican-only public schools in Orange County, California (later influencing statewide desegregation), while considering the context of World War II and the Japanese American incarceration. The panel included Brendan Bubion, Jeff Hittenberger, Jessica Lander, and Janice Munemitsu, and was moderated by Annie Tang.https://digitalcommons.chapman.edu/library_event_videos/1010/thumbnail.jp
Correlation Enhanced Distribution Adaptation for Prediction of Fall Risk
Get PDFWith technological advancements in diagnostic imaging, smart sensing, and wearables, a multitude of heterogeneous sources or modalities are available to proactively monitor the health of the elderly. Due to the increasing risks of falls among older adults, an early diagnosis tool is crucial to prevent future falls. However, during the early stage of diagnosis, there is often limited or no labeled data (expert-confirmed diagnostic information) available in the target domain (new cohort) to determine the proper treatment for older adults. Instead, there are multiple related but non-identical domain data with labels from the existing cohort or different institutions. Integrating different data sources with labeled and unlabeled samples to predict a patient\u27s condition poses a significant challenge. Traditional machine learning models assume that data for new patients follow a similar distribution. If the data does not satisfy this assumption, the trained models do not achieve the expected accuracy, leading to potential misdiagnosing risks. To address this issue, we utilize domain adaptation (DA) techniques, which employ labeled data from one or more related source domains. These DA techniques promise to tackle discrepancies in multiple data sources and achieve a robust diagnosis for new patients. In our research, we have developed an unsupervised DA model to align two domains by creating a domain-invariant feature representation. Subsequently, we have built a robust fall-risk prediction model based on these new feature representations. The results from simulation studies and real-world applications demonstrate that our proposed approach outperforms existing models
Representation and Bracketing in Repeated Games
Get PDFIn this experimental paper, the author investigates the framing effect of different representations of multiple strategic settings or games on a player’s strategic behavior. Two representations of the same environment are employed, wherein a player engages in two infinitely repeated prisoner’s dilemma games. In the first representation (termed Split), the stage games are shown separately. In contrast, the second representation (termed Linked) displays a combined stage game. The choice bracketing, distinguishing between Narrow and Broad bracketing, is considered a potential cause behind any disparity in behavior between the two representations. The Split representation does not necessitate broad bracketing, whereas the Linked representation compels it. Each type of bracketing has its own equilibrium implications. The author employs both a between-subject design (Study 1), where each subject observes only one representation, and a within-subject design (Study 2), where each subject is shown both the Linked and Split representations. In Study 1, significant differences in average behavior between the two representations are observed for both symmetric and asymmetric payoffs, albeit only after conditioning for session fixed effects. Study 2 reveals a more prominent effect of representation, and a sequence effect is observed, wherein the tendency to defect in both games is higher in the Linked representation if administered after the Split representation. In Study 2, for individuals who cannot be categorized as broad bracketers, the effect of seeing the Linked representation instead of the Split representation is economically significant. It increases the probability of choosing to cooperate in both games by more than 20% and decreases the probability to defect in both games by more than 25%
