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Machine learning-based energy estimation for sterile neutrino searches in the NOνA experiment
No full textUniversity of Minnesota Ph.D. dissertation. August 2025. Major: Physics. Advisor: Gregory Pawloski. 1 computer file (PDF); x, 171 pages.This dissertation presents a search for sterile neutrinos using Monte Carlo datasets and experimental data from the NOνA experiment. This work introduces novel machine learning techniques for energy reconstruction in neutral current events. A deep learning-based energy estimator was developed and integrated into the analysis framework. Using this new energy estimator, the sensitivity to sterile neutrino-induced oscillations is evaluated and presented. Furthermore, the dissertation explores potential methods for further improvement of the analysis.Wu, Shaowei. (2025). Machine learning-based energy estimation for sterile neutrino searches in the NOνA experiment. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/278122
From urban trees to watersheds: an evaluation of green infrastructure integration for effective climate adaptation
No full textUniversity of Minnesota Ph.D. dissertation. July 2025. Major: Civil Engineering. Advisor: Xue Feng. 1 computer file (PDF); x, 145 pages.Green infrastructure (GI) has the potential to provide multiple ecosystem services to cities, via stormwater management and urban heat mitigation, but its biophysical response to its surrounding environment and hydrological outcome considering its within-watershed placement can create large margins when estimating its realized benefits. This is in part due to the inherent heterogeneity of urban landscapes (e.g., land cover types, gray infrastructure distribution), leading to wide-ranging scenarios of growing conditions and watershed-level impact. To better quantify green infrastructure's climate adaptation potential, we need to first understand green infrastructure's functions at a fine-resolution, and relate its outcome when distributed within an urban watershed. The series of work presented in this dissertation evaluates GI's integration to its physical environments at two scales: one at the tree level, offering a biophysical lens into how trees respond to and simultaneously change their environment, and the other at the watershed scale, examining how the hydrological processes of distributed GI interact with existing gray infrastructure. By first developing a novel method to de-centralize an individual tree's water use measurement (i.e., sap flux), I conducted a multi-year monitoring study on urban ash trees in St. Paul, Minnesota, USA relating their water uptake to their health and their physical environments. I found that healthier trees not only used more water but also tended to conserve their water usage particularly during drought, whereas sick trees used less water and lacked regulation. Then I modeled the hydrological outcome of a distributed system of GI (i.e., bioretention cells), and found that the gray infrastructure’s spatial configuration can introduce tradeoffs between increased peak flow and increased flooding, and further interacts with GI coverage and placement to reduce peak flow and flooding at low rainfall intensity. Findings from this work suggested that GI is not a cure-all solution for climate adaptation, as the environmental conditions (e.g., heat stress, water availability, precipitation extremes) strongly affect GI functions---both on its own and in combination within a watershed, and in turn benefits. To effectively plan for climate change, cities must invest in both forestry maintenance and gray infrastructure expansion, in conjunction with spatially strategizing GI expansion, to help GI reach its potential.Chen, Xiating. (2025). From urban trees to watersheds: an evaluation of green infrastructure integration for effective climate adaptation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/278146
Supporting data for Computational search for materials having a giant anomalous Hall effect in the pyrochlore and spinel crystal structures
No full textSupplemental_results.json file is provided as an electronic record of the results presented in this work. This .json is a python dictionary that includes the DFT-computed formation energy, energy above hull, band gap, space group, magnetic ordering, and optimized structure along with their origin (DMSP, Materials Project, or GNoME) for 508 compounds considered in this work.Ferromagnetic pyrochlore and spinel materials with topological flat bands are of interest for their potential to exhibit a giant anomalous Hall effect (AHE). In this work, we present computational predictions of stability and electronic structure for 448 compositions within the pyrochlore (22O7) and spinel (2O4) frameworks. Of these, 92 are predicted to be thermodynamically stable or close (<100 meV/atom) to the convex hull, with trends deviating from expectations based on ionic radius-ratio rules. Thirteen are predicted to adopt a ferromagnetic ground state among the collinear configurations considered. Two additional materials meeting these criteria were also identified from open materials databases. Calculations of anomalous Hall angles (AHA) and conductivities reveal that 11 of the screened materials are promising candidates for spintronic applications requiring high electronic conductivity and a giant AHE. Our results suggest that the AHA can be further enhanced by tuning the Fermi level, for example, through chemical doping. Using this approach, we identify five materials whose AHA exceed 0.2 under the approximation of collinear magnetism. Notably, Ag2Pt2O7 exhibits a high AHA of 0.405 when its Fermi level is optimized. These findings provide a roadmap for the targeted synthesis of new pyrochlore and spinel compounds with enhanced AHE properties. They also broaden the compositional design space for these structures and support the discovery of high-performance materials for next-generation spintronic applications.
Data set includes crystal structures, formation energies, electronic structures, and transport properties of predicted pyrochlore and spinel materials.University of Minnesota MRSEC under Award No. DMR-2011401Sullivan, Sean; Lee, Seungjun; Szymanski, Nathan J; Merchant, Amil; Cubuk, Ekin Dogus; Low, Tony; Bartel, Christopher J. (2026). Supporting data for Computational search for materials having a giant anomalous Hall effect in the pyrochlore and spinel crystal structures. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://hdl.handle.net/11299/277782
Relationships between barriers to food pantry use, healthy food access and diet quality among food pantry users
No full textUniversity of Minnesota M.S. thesis. 2025. Major: Nutrition. Advisor: Marla Reicks. 1 computer file (PDF); iii, 85 pages.Relationships between Barriers to Food Pantry Use, Healthy Food Access and Diet Quality among Food Pantry Users.
Study 1: To determine whether reporting barriers to use was associated with (1) demographic characteristics of users, (2) frequency of pantry visits and amount of food accessed, and (3) perceived satisfaction with experiences visiting the food pantry using quantitative data collection and analysis methods. We hypothesized that reporting barriers to pantry use would be associated with demographic characteristics of users, limited frequency of pantry visits and a smaller amount of food accessed, and with a less satisfactory food pantry visit experience.
Study 2: To examine the relationships between perceptions of limited healthy food options in stores and pantries and potential diet quality of food pantry users. We hypothesized that perceptions of limited access to healthy food options in stores and pantries would be related to diet quality based on intake of fruits and vegetables, convenience and fast food meals and a lower frequency of scratch cooking.Zhao, Haisu. (2025). Relationships between barriers to food pantry use, healthy food access and diet quality among food pantry users. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/278021
Functional and chemical proteomics analysis to explore lysine posttranslational modifications
No full textUniversity of Minnesota Ph.D. dissertation. April 2025. Major: Biochemistry, Molecular Bio, and Biophysics. Advisors: Douglas Mashek, Yue Chen. 1 computer file (PDF); xiv, 228 pages.Metabolomic sensing through protein modification is an important mechanism to regulate protein function, activity, and gene expression. Due to an amine functional group, the lysine residue on proteins harbors a unique reactivity and is sensitive to cell metabolism, environmental changes, and enzyme regulation. However, due to the limitations of the tools and the understanding of the regulation mechanism, the knowledge of lysine modification is still limited. Therefore, with our developed tools, we characterize the three lysine modifications in this study, including lysine sorbylation, 5-hydroxylysine modification, and allysine modification. First, lysine sorbylation is a new type of acylation induced by sorbate, a widely used food preservative. We validated the induction of lysine sorbylation and developed a pan anti-sorbylation antibody to profile the regulation of HDAC. With this antibody, we identified a noncanonical function of HDAC1-3 to induce lysine sorbylation. In addition, we correlated the inflammation response with the HDAC, Nfkb, and sorbylation regulated pathways. This study reveals a novel mechanism for regulating a new lysine modification and inflammation response. Second, protein hydroxylysine has multiple hydroxylation constitutional isomers, including 5-R-hydroxylysine, 5-S-hydroxylysine, 4-hydroxylysine, and 3-hydroxylysine modification. Among the hydroxylysine modifications, 5-S-hydroxylysine is a vital protein modification regulated by JMJD6. However, due to the lack of a globally and constitutionally specific tool for protein modification profiling, the understanding of 5-hydroxylysine modification induced by JMJD6 is restricted. This study developed a periodate oxidation strategy to specifically oxidize the protein 5-hydroxylysine modification. Proteins were further pulled down by hydrazide beads and subjected to trypsin digestion and methoxyamine cleavage for LCMS analysis. With this method, we can discover the regulation of JMJD6 to 5-hydroxylysine modification in a complex system. Third, protein allysine modification is a lysine modification with an aldehyde functional group on the side chain. Due to the uniqueness of the functional group and the low natural abundance, identifying allysine modification is challenging. To overcome this issue, we developed a hydrazide beads capture and D3-methoxyamine release strategy to understand the regulation of allysine modification. This strategy can broaden the understanding of the modification's potential regulation pathway. Collectively, these studies provide insight into the lysine acylation, 5-hydroxylysine modification, and allysine modification regulation pathway.Sin, Yi-Cheng. (2025). Functional and chemical proteomics analysis to explore lysine posttranslational modifications. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/278805
Deep learning and state of the art infant brain MRI processing methods
No full textUniversity of Minnesota Ph.D. dissertation. 2025. Major: Biomedical Informatics and Computational Biology. Advisors: Damien Fair, Lynn Eberly. 1 computer file (PDF); xi, 107 pages.Over the past decade there has been heightened interest from federal funding partners, such as the National Institutes of Health, in the developing brain. This interest led to the funding of the Adolescent Brain Cognitive Development study in 2015, the largest long term study of brain development and child health in the United States. Following the developmental brain health momentum, the National Institute of Health and other federal partners more recently funded the HEALthy Brain and Child Development study, which aims to collect information beginning at birth through early childhood, including magnetic resonance imaging of the brain. Due to the dynamic brain development changes that occur during the first year of postnatal life, traditional magnetic resonance imaging brain processing and analysis implemented on adult, adolescent, and pediatric study samples do not work well with infants. With this backdrop in mind, alternative processing and analysis approaches are needed. With improvements in computing power, namely graphical processing units, machine and deep learning approaches have proliferated within the brain magnetic resonance imaging space. Here, within this work, deep learning approaches are explored to improve infant brain image processing, to bridge the gap between data collection and analysis.Hendrickson, Tim. (2025). Deep learning and state of the art infant brain MRI processing methods. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/278189
Dr. Vikki Krane: Shaping Research and Discourse on Gender in Sports
No full textRuntime 37:19In this episode of Tucker Center Talks, Dr. Nicole M. LaVoi speaks with Dr. Vikki Krane, noted for her groundbreaking application of feminist theories in sport psychology. The discussion focuses on Dr. Krane’s vital research regarding gender, sexuality, and the portrayal of queer, trans, and non-binary athletes in the sports arena. They examine how Dr. Krane’s academic contributions have not only highlighted these frequently marginalized identities but have also questioned the ingrained norms of sports culture, promoting a more inclusive and equitable sporting landscape
El conflicto colombiano como el Gran Horror (terror y brechas en un lejero)
No full textBastidas Pérez, Rodrigo. (2025). El conflicto colombiano como el Gran Horror (terror y brechas en un lejero). Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/269920
Data ownership & sharing decision tree
No full textThe authors of this research tool are members of the Data Curation Network's (DCN) Sensitive Data Interest Group. The Data Curation Network is comprised of professional data curators, data management experts, data repository administrators, disciplinary scientists, and scholars who strive to build a trusted community-led network of curators advancing open research by making data more ethical, reusable, and understandable. The Sensitive Data Interest Group is a DCN sub-group that creates guides and tools related to sensitive data (e.g., human participant, protected species, politically charged, etc.). The authors of this research tool represent three academic institutions: University of Minnesota (AHM and SLH), Princeton University (MC), and Washington University (JM).The "Data ownership & sharing decision tree" is a research tool the helps researchers decide 1) if they own the data they wish to share and 2) whether there are other factors beyond ownership that impact data sharing. This tool is especially helpful for those considering whether they can share human participant data. The PDF also links out to important background information and guidelines in certain decision pathways.Hofelich Mohr, Alicia; Hunt, Shanda L; Chandler, Matt; Moore, Jennifer. (2025). Data ownership & sharing decision tree. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/269486
Investigating the interplay of personality, job demands-resources, and burnout among Minnesota pharmacists
No full textUniversity of Minnesota Ph.D. dissertation. May 2025. Major: Social and Administrative Pharmacy. Advisor: Caroline Gaither. 1 computer file (PDF); xxiii, 736 pages.Hospital pharmacist burnout is a critical issue that affects mental and physical well-being, impairs job performance, and compromises patient safety. Research indicates that over 50% of pharmacists experience burnout, which arises from chronic occupational stress. Burnout includes three dimensions: emotional exhaustion, depersonalization, and reduced professional accomplishment. Unbalanced work conditions such as high physical demands and limited organizational support exacerbate burnout. Additionally, personality temperaments are thought to influence how pharmacists perceive job demands, access to resources, and vulnerability to burnout. Understanding one's personality may help mitigate burnout risk, as certain temperaments may be more sensitive to occupational stress. Alarmingly, fewer than 4% of pharmacists report awareness of available burnout resources. Two promising tools for addressing burnout are the Preferred Communication Style Questionnaire (PCSQ), a personality assessment, and the Job Demands-Resources (JD-R) model, a framework that links workplace conditions to burnout risk. The Maslach Burnout Inventory (MBI), the gold standard for measuring burnout, complements these tools. However, little research exists on how personality affects the experience of burnout in hospital pharmacists. This dissertation aimed to explore the role of personality temperaments in the relationships between job demands, job resources, and burnout. This research was guided by three objectives: (1) examine characteristics of hospital pharmacists, (2) analyze how personality temperaments relate to the three dimensions of burnout, and (3) assess the influence of temperament on JD-R model and burnout components. A cross-sectional, self-administered electronic survey was used to gather quantitative data on burnout dimensions, personality, job demands, job resources, and demographics. Four personality types, Traditionalists, Experiencers, Conceptualizers, and Idealists were examined within the JD-R framework.
This research provides a comprehensive understanding of the individual and organizational factors influencing burnout in hospital pharmacists. Findings offer insights into how personality moderates the JD-R model and highlight opportunities to personalize interventions. The study’s practical implications include targeted recommendations for reducing burnout, improving pharmacist well-being, and increasing awareness and use of burnout resources. Ultimately, the results support a refined JD-R model that incorporates personality as a key factor in addressing pharmacist burnout.Wilson, Gavin. (2025). Investigating the interplay of personality, job demands-resources, and burnout among Minnesota pharmacists. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/275932