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EXAMINING THE PSYCHOLOGY OF WORKING THEORY AMONG NIGERIAN COLLEGE STUDENTS
No full textSTUDY 1: EXAMINING PREDICTORS AND OUTCOMES OF FUTURE DECENT WORK PERCEPTION AMONG NIGERIAN EMERGING ADULTSHigh levels of poverty and unemployment are pervasive barriers to Nigerian emerging adults entering the job market (Olorunfemi, 2021). The current study employed the Psychology of Working Theory ( Duffy et al., 2016) to explore career engagement, academic satisfaction, and life satisfaction predictors in a nation experiencing the intersections of high poverty and high unemployment rate. We tested a model predicting these outcomes from economic constraints and marginalization mediated by work volition, career adaptability, and perceptions of future decent work. We administered online surveys to 310 undergraduates in Nigeria. Career adaptability and work volition predicted the perception of future access to decent work. Also, those who reported higher chances of securing decent work after graduation reported greater academic and life satisfaction and career engagement. While economic constraints predicted career adaptability in this model, marginalization did not predict career adaptability. In contrast with previous studies, economic constraints, and marginalization were not predictive of work volition or future decent work perception. We also found a positive relationship between economic challenges and career adaptability against the propositions of the Psychology of Working Theory (PWT). The implications of our findings were discussed. STUDY 2: QUALITATIVE EXAMINATION OF PSYCHOLOGY OF WORKING THEORY AMONG NIGERIAN EMERGING ADULTS.This study utilized qualitative document analysis (QDA) to explore the perceptions of 443 Nigerian college students regarding future access to decent work in sub-Saharan Africa, amidst high unemployment rates. Guided by the Psychology of Working Theory (PWT) and Nigerian cultural dynamics, we delved into their definitions of decent work, barriers hindering access, available choices within these constraints, and the impact of these perceptions on academic outcomes and well-being. Notably, participants viewed decent work as more than just a source of income, indicating its reflection of personal values and societal norms, emphasizing the complex interplay of individual agency, systemic obstacles, and socio-economic environments in shaping career outlooks and academic outcomes. In addition, our research expands the PWT framework by introducing new dimensions of decent work perception such as social protection and market economy, underlining the necessity for cross-cultural investigations to refine existing theories and measures. These results inform future research inquiries and provide actionable insights for policymakers and professionals working with Nigerian college students. STUDY 3: PREDICTING WORK VOLITION AMONG NIGERIAN EMERGING ADULTS: A PSYCHOLOGY OF WORKING PERSPECTIVE This study employed hierarchical regression analysis to evaluate the predictors of work volition within Nigeria's collective cultural context, drawing from the Psychology of Working (PWT) perspective. In a sample of 375 participants, we found that familial guidance and a sense of belonging in the university community significantly influence the perception of control over one’s choice of career amidst barriers. Surprisingly, economic constraints and marginalization showed minimal impact on work volition, contrasting with PWT's central tenets. Our findings emphasize the importance of disseminating accurate career information and fostering inclusive campus environments to support career development among Nigerian youths. This research contributes to the ongoing discourse on cultural responsiveness in vocational psychology and offers practical insights for career counseling programs tailored to Nigerian contexts
THE MIDDLE OF NOWHERE: THE GAY RODEO’S ROLE IN FIGHTING THE SYMBOLIC ANNIHILATION OF QUEER RURALITY
No full textABSTRACT THE MIDDLE OF NOWHERE: THE GAY RODEO’S ROLE IN FIGHTING THE SYMBOLIC ANNIHILATION OF QUEER RURALITY by Eleanor Clement The University of Wisconsin-Milwaukee Under the Supervision of Professor Dr. Kristin Pitt This research explores how the community archives created by the International Gay Rodeo Association (IGRA) impact the symbolic annihilation of queer rurality in the archival record of gay liberation within the United States. Within academia the process of queer migration to urban areas and the process of assimilation to urban habitus has been more widely considered, largely ignoring the radical potential of queer rurality politically. This research was done by engaging directly with the material in the IGRA’s collection, considering not only the ways in which the records themselves may combat the imposed closet of metronormativity, but the impact of community centered archiving as a practice. The Reno Gay Rodeo and the surviving tradition of gay rodeo as a whole offers a distinctly rural queer lens by which metronormativity, within the collective memory of gay liberation, historically and contemporarily, may be challenged. Gay rodeo acts as an example of action that is not only locationally rural but is also symbolically rural and reflective of that lived experience. As the queer community faces continued challenges the need of a coalitionary politic that recognizes the rural as more than a place to escape is necessary for sustainable change. By deeply engaging with this material and utilizing it to construct countermemory to metronormativity these records can be used to inspire and guide current liberatory action
Changing Reproductive Phenology of the Eastern Gray Squirrel (Sciurus carolinensis) Due to Climate Change in New England
No full textPlan BGeneralist species of great abundance are often overlooked as data sources showing how climate
change affects local ecosystems. While there is a lack of studies in peer-reviewed literature,
decades of quantitative data about these species have been collected by conservation medicine
and wildlife rehabilitation organizations. Using 20 years of data from the Center for Wildlife of
Cape Neddick, Maine, I analyzed trends in reproductive phenology of the eastern gray squirrel
(Sciurus carolinensis) that correlate with climate change. Using the approximate birth dates of
neonate and juvenile eastern gray squirrels admitted as patients, I analyzed the timing of two
seasonal birth pulses from 2004 through 2024. Compared to 2004, the first and second birth
pulses had shifted 8.8 (95% CI: 3.2, 14.3) and 5.9 (2.5, 9.3) days earlier, respectively, by 2024.
Births overall have expanded earlier in the spring, gradually lengthening the reproductive season
by 37.6 (-6.8, 82.0) days. Should current trends continue, the changing breeding phenology of
the eastern gray squirrel may affect the greater ecosystem. Additionally, these findings
demonstrate the potential value of existing data from wildlife rehabilitation and conservation
medicine organizations in understanding the effects of climate change, describing dynamics in
local ecosystems, and informing conservation
Investigating Silicone Degradation and its Implications for Menstrual Cup Safety
No full textColor poster with text, images, charts, photographs, and graphs.Menstrual cups have become increasingly popular in recent years for their environmental benefits, cost-effectiveness, and user comfort. Most menstrual cups are made using silicone, taking advantage of its flexible and leak-proof material properties. However, there has been limited research on the hydrolytic degradation of silicone biomaterials, particularly in the acidic vaginal environment, raising potential safety concerns. The objective of this research project is to study the hydrolytic degradation of silicone under acidic conditions to better understand the safety profile of biomedical devices like menstrual cups. Our initial study tested 40 silicone samples over a 29-day period at 37 °C and 67 °C in a 1 M hydrochloric acid (HCl) solution. Results of this accelerated study indicated a maximum mass loss of 11.4 %. Future studies will be performed using a vaginal fluid simulant (VFS) primarily composed of a lactic acid buffer system to assess physiologically relevant degradation behavior and to characterize potentially toxic degradation products. Ultimately, this research aims to develop a standardized workflow for studying the degradation of polymeric biomaterials in a VFS that could also be applied to other biomedical devices such as intravaginal ring (IVR) drug delivery systems.University of Wisconsin--Eau Claire Office of Research and Sponsored Program
ESTIMATING THE RELATIVE CONTRIBUTION OF WILD BEES IN THE POLLINATION OF APPLE, CRANBERRY, AND SQUASH IN WISCONSIN (USA)
No full textFarmers growing pollinator-dependent crops such as fruits, vegetables, nuts, and oilseeds traditionally rely on managed bees for pollination. However, managed bee populations have suffered significant colony losses due to agricultural intensification, pesticide exposure, diseases, parasites, habitat loss, and climate change. Wild bees, although often underestimated, play a vital role in pollination services and can enhance fruit quality, particularly in diverse landscapes.
Despite their potential, farmers are cautious about relying solely on wild bees due to their inconsistent abundance and uncertain contributions to crop pollination. This study evaluated the contributions of wild bee morphogroups to the pollination of apple (Malus × domestica), cranberry (Vaccinium macrocarpon), and squash (Cucurbita spp.) in Wisconsin (USA). Flower visitation rates on farms were measured using standardized 5-minute visual surveys during the flowering period of each crop in Wisconsin in 2024. Additionally, we obtained single-visit pollen deposition data through empirical observations in our cropping systems and combined these with additional information from published studies. Honey bees were the most frequent visitors in apple and cranberry, attributed to the abundance of managed hives, whereas large dark bees dominated visitation in squash. Large dark bees deposited the highest pollen grains per visit in apple (̄ = 253), while bumble bees deposited the highest pollen grains per visit in cranberry (̄ = 36) and in squash (̄ = 209). We estimated the expected full-day pollen deposition to flowers of each crop based on visitation rates and single-visit pollen deposition (pollen supply, Ps) and compared this to the minimum pollen requirements for full pollination from known studies (pollen demand, Pd), to estimate a pollination index Pi = (Ps/Pd). The Pi values varied across farms within each crop: apple (Pi =1.3 to 12.6), cranberry (Pi =2 to 49.2), and squash (Pi =
1.8 to 13), indicating the potential of wild bees to provide effective pollination services, even in the absence of honey bees. However, variability in visitation and deposition across farms suggests potential shortfalls in some farms, especially in apple and cranberry, without supplementation from honey bees. By utilizing tools like the pollination index (Pi), growers can make informed decisions and promote sustainable, resilient pollination systems. Future research should further validate these results and explore the broader scalability of wild bees’ contributions.
Keywords: Pollination, Pollination service index, Single-visit pollen deposition, Visitation, Wild beesThis work was supported by the Agriculture and Food Research Initiative, project award no. 2023-67013-39066, from the U.S. Department of Agriculture’s National Institute of Food and Agriculture
Oral History Interview, Andrew Ruis (2494)
No full textIn his two 2025 interviews, Academic Staff Award winner Andrew Ruis reflects on his 20+ years spent studying and working at UW-Madison. To learn more about this oral history, download & review the index first (or transcript if available). It will help determine which audio file(s) to download & listen to.In his two 2025 interviews, Academic Staff Award winner Andrew Ruis reflects on his 20+ years spent at UW-Madison. Ruis attended UW in the early 2000’s as a graduate student in the History of Science Department, and then found a job with the Wisconsin Center for Education Research where he has worked since, assuming grant writing, researching, and administrative/leadership positions. He describes the role of the WCER, which houses grant-funded research for the School of Education. He describes the diversity of scale and type of research conducted, providing examples of studies on curriculum, teacher training, and cognitive learning processes. Ruiz describes the role of and his work in the Center for Research on Complex Thinking, a sub-center of the WCER, and its role in analyzing quantitative ethnography. He mentions people and groups he collaborates with in CRCT. He describes his typical day, the satisfaction he finds in his work, COVID, the changes in technology he’s witnessed throughout his time at WCER, faculty-staff relationships, and the process of being nominated for the award. In his second interview session, Ruiz describes the History of Science department as close-knit, well run department. He recalls becoming a TA, the challenges of learning effective teaching methods, and inspiration he drew from the notable historian David Lindberg. He also describes his dissertation on the origins and history of school lunch programs, which he found to be a fascinating intersection of public health, nutrition, politics, and education. He recalls his involvement in the ACT 10 protests and shares his thoughts on current federal research funding cuts and their implications for his work. This interview was conducted for inclusion into the Academic Staff Award Winners Projects to be housed in the UW-Madison Archives and Records Management Oral History Program
MACHINE LEARNING FOR RESOURCE ALLOCATION IN EMERGENCY DEPARTMENT
No full textEmergency Departments (EDs) face constant pressure from unpredictable patient arrivals, limited beds, and staffing challenges. These issues often lead to longer ED stays, higher costs, and clinician burnout. While machine learning (ML) is widely used in healthcare, it has rarely been applied to real-time staffing and resource allocation in the ED.The objective of this research is to (1) identify key factors that predict prolonged ED length of stay (EDLOS >6 hours), (2) simulate nurse staffing needs under different patient demand scenarios, and (3) forecast daily admissions with time-series models to support short-term planning. In this study almost 40,000 ED patient visits were analyzed, including demographics, vitals, acuity, primary diagnosis, and staffing levels. Most patients were between 50 to 80 years of age, 40% were African American and retired, and more than half were on Medicare. Common risks included obesity and smoking with higher acuity (2 & 3). Top admitting diagnoses were related to trauma, gastrointestinal and neurological, and top admitting units were internal medicine and surgery. Three supervised Machine Learning models, Logistic Regression, Support Vector Machine and CHAID Decision Tree were tested on 4 sets of data cohort to predict which patients would stay longer than 6 hours. Logistic regression gave balanced but moderate accuracy, SVM achieved very high accuracy (over 95%) on training set but moderate on largest data set, while CHAID decision trees provided easier-to-interpret rules with reasonable performance. Together, these models show the trade-off between predictive power and interpretability. Acuity and time series variables showed important predictors for longer EDLOS. We also performed what-if simulations on different staffing scenarios and analyzed EDLOS in different scenarios such as reducing staff, high patient volume, high acuity, and above baseline RN staffing. A time series ARIMA forecasting model was also built to project daily admissions to 30-day prediction. When compared with actual data, it showed reliable predictions with 5% margin of error. The findings of this study offer a practical decision-support framework by combining prediction, simulation, and forecasting. The implications are broadly valuable such as hospitals can cut costs by reducing overtime & inefficient staffing, HR can improve nurse retention by balancing workloads, and patients benefit from shorter wait times and smoother care transitions. Beyond the ED, this approach is adaptable to other hospital units, making it a scalable solution that supports efficiency, staff well-being, and better clinical outcomes.2026-12-2
Influence of Human Attitudes and Activities on Sea Otter and Harbor Seal Behavior
No full textThis study investigated the influence of human attitudes and activities on
the behavior of northern sea otters (Enhydra lutris kenyoni) and Pacific harbor
seals (Phoca vitulina richardii) in the City of Homer Port and Harbor in Homer,
AK, USA. This location experiences high rates of human use and is likely
undergoing expansion to accommodate this. Thus, it is imperative to understand
how human presence and activities impact the species coexisting there. To
achieve this, I used an interdisciplinary approach where I both administered a
public survey and conducted behavioral sampling on the responses of sea otters and harbor seals to human activity between May and September 2024. Harbor seals co-occurred less often with humans and exhibited
increased vigilance behavior when humans were present. Sea otters exhibited
shorter behavior durations when disturbed by humans and exclusively
exhibited alert behavior in the presence of dogs. The majority of survey
respondents reported positive attitudes towards both species and reported
their interactions with them to be at closer distances than those that are recommended by the USFWS and NOAA. Non-visitor respondents reported
the closest interaction distances with, and more neutral attitudes towards, both
species. Knowledge of the MMPA did not correlate with interaction distance.
These findings underscore the importance of considering how human
attitudes and activities influence the behavior of sea otters and harbor seals
and serve as baseline information for understanding the current humanwildlife
interactions in an important area of shared use. These findings can
serve to inform future management strategies that have a greater probability of
supporting a positive coexistence between humans and wildlife
Oral History Interview, Steph Fones (2522)
No full textIn her August 2025 interview with Dadit Gunarwanto Hidayat, WiscAMP alum and mentor Stephanie Fones describes her experience as a member of the Indigenous community in STEM. To learn more about this oral history, download & review the index first (or transcript if available). It will help determine which audio file(s) to download & listen to.In her August 2025 interview with Dadit Gunarwanto Hidayat, WiscAMP alum and mentor Stephanie Fones describes her experiences as a member of the Indigenous community in STEM. She initially worked in construction before going back to college for her degree in geoscience. She was in WiscAMP as an undergraduate and is now working for the McNair program at UW-Milwaukee while earning her graduate degree. In WiscAMP, she found a supportive community of other students and faculty that helped her accomplish her goals and realize her aspirations for the future. She wants to get her PhD to become an educator and role model for women and Indigenous people in STEM. She also discusses the intersection of Indigenous and Western approaches to science. This interview was conducted for inclusion into the WiscAMP Legacy Oral History Project and the UW-Madison Archives and Records Management oral history collection
Exploring Machine Learning Models : For IoT Network Intrusion Detection : A Literature Review and Comparative Analysis
No full textColor poster with text, charts, and graphs.The Internet of Things (IoT) encompasses a variety of systems and devices that enable data exchange across networks. With this interleaved connectivity comes an inherent vulnerability to attacks. Traditional intrusion detection in IoT environments has been primarily human-reliant, but modern malicious methods surpass manual approaches. Machine Learning (ML)-based Intrusion Detection Systems (IDS) show promise but require refinement to match human-monitored IDS effectiveness. This study involved a literature review of research involving the NetFlow dataset NF-ToN-IoT-v2, created in 2022 to enable ML-based IDS development. With balancing, the dataset includes approximately 16 million net-flows, with 63.99% attack and 36.01% benign. The data’s imbalanced nature was addressed through methods like down sampling to reduce training bias. A hyper-parameter tuning pipeline was used to optimize algorithm testing and cross-validation, especially for different data balancing methods. The algorithms tested based on previous research found during literature review include Naïve Bayes, Random Forest, K-Nearest Neighbor (KNN), Support Vector Machines (SVM), and XGBoost. Comparative analysis using confusion matrices and bar plots enabled the evaluation of algorithm effectiveness. Overall, this research highlights the potential of ML approaches in IoT IDS development, through leveraging NF-ToN-IoT-v2 to enhance detection accuracy and bridge the gap between human-monitored and ML-driven solutions.University of Wisconsin--Eau Claire Office of Research and Sponsored Program