31825 research outputs found
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Applications of computational optimal transport in machine learning and signal processing
No full textBrockmeier, Austin J.Recently, there has been a surge of interest in using optimal transport between probability distributions to measure the Wasserstein distance and enable better machine learning systems. More specifically, optimal transport can be used to define clustering algorithms, semi-supervised learning algorithms, and techniques for data compression and for correcting for covariate shifts in classification tasks. Additionally, Wasserstein distances can be used as cost functions in generative modeling and as constraints for robust modeling. The tremendous success of these techniques in wide application domains is due to the fact that optimal transport combines the related but distinct concepts of geometric distances and statistical divergences. ☐ The first work in this dissertation thoroughly investigates variants of optimal transport to deal with the cases where a subset of the support of one distribution aligns with complete support of another distribution, such as in the case of a carefully curated dataset that can be augmented by a source of less reliable data. In our experiments we demonstrated the utility of our approach in partial point cloud alignment, color transfer, positive-unlabeled (PU) learning and semi-supervised learning. Additionally, we propose to investigate the effect of partial alignment in generative modeling and to examine partial alignment in the case of global covariate-shift correction in classification tasks. ☐ In the second work for this dissertation, we investigate partial optimal transport in the case of two or more stochastic processes with application to matching bio-signals represented as univariate stochastic processes from a population of subjects, where the representation space underlying the transport is not Euclidean. In particular, we consider the case where spectral patterns observed in short-time windows can occur at different time scales for different processes. We seek a monotonic transformation of the spectra of each process that minimizes the Wasserstein distance between the distribution of spectra across windows. We anticipate that the spectral alignment for multiple subjects with different frequency spreads can enhance the performance of downstream learning systems. That is, learning on the aligned data performs better than learning on the original data. This has wide applications in cases where the machine learning system is better off learning to be invariant to the time scale. ☐ In the third work for this dissertation, we focus on the development of algorithms for neural network parametrized support subset selection approaches, where we only have access to the sample from underlying data distributions. More specifically, we developed algorithms for training neural network parameterized Monge-like maps in static formulation of continuous subset alignment and velocity-fields in dynamic formulation of continuous subset alignment. We applied our frameworks to PU-Learning and latent-space image alignment problems.University of Delaware, Department of Electrical and Computer EngineeringPh.D
Do protective factors matter?: examining the impact of cumulative risk and psychological well-being
No full textBarnes, Tia NaveleneExposure to cumulative risks during childhood and adolescence can have profound and lasting effects on psychological well-being. Fortunately, not all individuals who experience adverse circumstances develop negative outcomes. Protective factors may explain why some individuals flourish and thrive despite adversity. While a vast majority of research has focused on understanding risk factors and cumulative risk, research on protective factors remains understudied. The purpose of the current study is to identify protective factors, specifically clusters that can buffer the effects of cumulative risk. Rutter’s Resilience Theory and Bronfenbrenner’s Bioecological Theory guide this investigation. Latent Class Analysis (LCA) is used to examine how multiple protective factors can cluster together to influence psychological outcomes. Results indicate that cumulative risk significantly predicts lower psychological well-being, with perceived discrimination providing additional explanatory power. Regression analyses confirmed that cumulative risk significantly predicted reduced psychological well-being (p < .001), yet moderation analyses revealed that certain protective clusters, particularly Class 3, mitigated this impact. These findings emphasize the importance of a strength-based approach. Exploring strengths alongside risks allows for a more comprehensive understanding of how one’s existing protective resources (i.e., including confidence, self-perceived intelligence, self-rated health, life expectancy, religiosity, wealth, social support) promotes resilience and psychological well-being in the future.University of Delaware, Department of Human Development and Family SciencesPh.D
Anticipating Tomorrow: How the University of Delaware is Preparing for an AI-Driven World
No full textIn February 2025, the University of Delaware (UD) Library, Museums, and Press launched a focused exploration of how artificial intelligence (AI) could shape the future of their work across libraries, museums, and publishing. With AI technologies evolving rapidly and reshaping how knowledge is produced, accessed, and preserved, UD convened its senior leadership team for a half-day strategic planning retreat grounded in foresight, collaboration, and scenario-based thinking. Guided by the Association of Research Libraries (ARL) and the Coalition for Networked Information (CNI) AI-Influenced Futures Scenarios, participants explored the challenges and opportunities that AI could present over the next decade and worked together to surface robust strategies to help the Libraries, Museums, and Press navigate this complex and shifting landscape. This article shares the goals, structure, strategic insights, and outcomes from that retreat and outlines how scenario planning can be a useful tool for an organization grappling with uncertainty in the age of AI
Strengthening staff knowledge to support adults with disabilities in community fitness facilities
No full textEisenman, Laura T.Persistent health disparities among adults with disabilities are linked, in part, to limited disability-specific knowledge among community fitness staff, which creates a barrier to the consistent delivery of inclusive, evidence-informed wellness programming (Obrusnikova, Jadach, Cavalier, & Firkin, 2023; Rimmer & Vanderbom, 2016). In my role as co-founder of Endless Possibilities in the Community (EPIC), a 501(c)(3) nonprofit that partners with individuals with disabilities and community stakeholders to promote inclusive community fitness, I undertook this Educational Leadership Portfolio (ELP) with the specific goal of identifying, implementing, and evaluating an example of “good practice” in professional development training for EPIC’s fitness staff. The long term goal is to reduce health disparities among adults with disabilities by strengthening staff knowledge, self-efficacy, and instructional competence while increasing participant engagement in physical activity. ☐ This ELP study first identified the Empowerment Model (Moran, Block, & Taliaferro, 2014) as an example of a professional development framework for inclusive fitness. Building on that foundation, the study then implemented and evaluated the Strategies of Success (SOS) online instructional modules, designed to increase EPIC staff members’ knowledge in disability awareness and inclusive fitness practices within community fitness facilities (CFFs). Using a mixed-methods design, the study quantitatively assessed pre/post knowledge and self-efficacy of staff participants across four SOS modules (Addressing Challenging Behaviors, Planning Inclusive Programs, Modifying Instruction for Inclusiveness, Accessibility Considerations) and gathered qualitative feedback on application to practice through focus groups. Study participants demonstrated a mean knowledge gain of 22 points (scale of 0–100) on the four modules. Self-efficacy was examined as a complementary outcome and improved on average (0.5 on a 0–10 scale). Focus group data indicated that the modules were valuable for onboarding new staff, equipping them with foundational disability awareness and fitness-specific knowledge and strategies, while also providing experienced staff with a review and opportunities to expand their repertoire of inclusive instructional knowledge and practices. Focus group findings informed creation of a draft EPIC professional development policy, procedural guidelines, and a staff resource manual. The intent is to use these mechanisms to embed ongoing knowledge building into organizational routines and support sustainability. ☐ Taken together, the findings demonstrate that CFF staff training needs, such as those at EPIC, can be addressed through a research-informed professional development approach centered on knowledge acquisition, which may serve as a foundation to increase staff confidence and capacity in an effort to reduce persistent physical health disparities among adults with disabilities.University of Delaware, School of EducationD.Ed
Catalytic activation of bioorthogonal chemistry without photochemistry
No full textFox, Joseph M.My research centers on developing novel strategies to activate the rapid tetrazine ligation reaction through “photochemistry-free” oxidation, enabling applications in biological systems. I demonstrated that the stable precursor dihydrotetrazine (DHTz) can be oxidized by enzymes and small molecules, via catalytic and stoichiometric pathways, to trigger subsequent tetrazine-trans-cyclooctene (TCO) ligation in the absence of light. I achieved the first intracellular enzymatic labeling reaction of DHTz in live cells using “dark” catalysis- defined as catalytic chemical reactions that occur without light. Building on this, I made progress toward development of new proximity labeling systems that leverage dark catalysis, and I have evaluated a range of dark catalysts and oxidants, comparing their efficiencies and biocompatibilities with the DHTz system. ☐ In chapter 1, I discuss my work with ascorbate peroxidase (APEX2) to turn on the bioorthogonal tetrazine ligation reaction. Kinetic studies revealed that APEX2-catalyzed oxidation of DHTz is enhanced by superoxide dismutase (SOD), a ubiquitous mammalian enzyme that regulates oxidative stress by converting superoxide into molecular oxygen (O2) and hydrogen peroxide (H2O2). The APEX2 oxidation with SOD achieved a catalytic efficiency of kcat/KM 4.90 × 103 M–1s–1 in vitro. While H2O2 is not strictly required, the addition of 10 µM H2O2 accelerated the oxidation reaction both in vitro and in live cells. Using a dual-transfection protocol expressing cytosolic APEX2 and HaloTag-DHTz conjugate, I demonstrated that APEX2 promotes DHTz oxidation and subsequent Diels- Alder chemistry in live HeLa cells. Labeling with a fluorophore-tagged TCO probe was confirmed via in-gel fluorescence, Western blot analysis, and confocal microscopy. In live PC3 cells, APEX2 also catalyzed the oxidation of a DHTz conjugated to an endogenous monoacylglycerol lipase (MAGL) through a selective covalent warhead. ☐ In chapter 2, I describe my screenings for proximity labeling using APEX2 fused to various proteins of interest (POI). Previous studies showed APEX2-biotin-phenol systems label proteins within a 20 nm radius. I wanted to compare this method for proximity labeling to a complementary approach based on enzymatically activatable bioorthogonal chemistry. I labeled lysine residues proteome-wide with a TCO-N-hydroxysuccinimide (NHS) ester, then activated a DHTz by APEX2 bearing a biological alkyne handle to assess proximity-based differences. The alkyne- labeled proteins were conjugated to biotin-azide or TAMRA-azide via a Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC). Among the constructs tested, cytosolic APEX2-GFP detected new proteins. While other constructs targeting cereblon (CRBN), the outer mitochondrial matrix (OMM), and a nuclear export signal (NES) did not show detectable labeling under these conditions, these results offered insight to the complexities of expression levels and accessibility for effective proximity labeling methods. To further analyze labeling targets, I optimized a small-scale streptavidin enrichment protocol. ☐ In chapter 3, I evaluate DHTz activation by small molecules for dark catalysis. Building on the heme enzyme of APEX2, I demonstrated that the iron porphyrin complex, Fe (III) tetrakis (N-methyl-4′-pyridyl) porphyrinato (FeTMPyP) activates DHTz in vitro and in extracellular environments. In addition, ferrocenium tetrafluoroborate promoted the rapid and stoichiometric oxidation of DHTz with a second-order rate constant of k2 = 1.82 x 105 M-1s-1. The low molecular weight of ferrocenium ion and the extremely rapid kinetics of DHTz oxidation make it a uniquely promising oxidant among the small molecules tested for tetrazine activation in biological applications. The compact structure of ferrocenium also offers an excellent scaffold for further functionalization. Beyond ferrocenium, I evaluated a range of other oxidants. Copper (II) sulfate (CuSO4) catalytically oxidized DHTz, while quinones acted as stoichiometric oxidants. Each class of oxidant presents unique advantages and limitations, which I critically analyzed in the context of their potential for biological compatibility, efficiency, and tunability.University of Delaware, Department of Chemistry and BiochemistryPh.D
Effects of landscape context on avian specialist response to increased surface temperature in protected areas
No full textThis article was originally published in Conservation Biology. The version of record is available at: https://doi.org/10.1111/cobi.70230
This is an open access article under the terms of the Creative Commons Attribution-Non Commercial-No Derivs License, https://creativecommons.org/licenses/by-nc-nd/4.0/ which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made
© 2026 The Author(s). Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation BiologyHuman development is a driver of global change and a major threat to biodiversity. Protected areas maintain and support biodiversity, but outside stressors, such as climate change and land use change, can negatively influence natural resources within protected areas. We examined the effects of land surface temperature and the surrounding landscape context on the structure and composition of the breeding bird community in national parks in the Mid-Atlantic (USA). We used avian point count surveys, conducted annually from 2007 to 2024, to estimate the composition of 16 avian guilds and estimated land surface temperature at each survey point. We defined 3 landscape context types (forested, urban, and agricultural) based on the dominant land cover surrounding each survey point. We used multivariate generalized linear models to test community-level (all guilds combined) and guild-level (individual guilds) responses to local land surface temperature and landscape context. We hypothesized a negative relationship between within-guild abundance and land surface temperature, and stronger negative relationships in specialist guilds and variation in response based on the landscape context. Landscape context influenced local land surface temperature and, therefore, avian guild responses. Points in forest-dominated landscapes averaged 2°C cooler than points in urban or agricultural landscapes. The majority of specialist guilds had an interaction with land surface temperature and landscape context. There were negative effects of high land surface temperature on the bird community. These effects differed across landscape context, with less extreme negative relationships detected at points surrounded by forest relative to points in urban or agricultural landscapes. Because increased forest cover is important to retain natural cooling and mitigate the effects of urban heat, preserving or increasing forest cover could help preserve and maintain bird community resilience in a warming climate.We thank the park managers and staff in the National Capital Region parks, the Center for Urban Ecology, and the Inventory & Monitoring Program for logistical aid and site access, especially J.P. Schmit for thoughtful editorial comments and support. This work was supported by the National Park Service Inventory and Monitoring Program grant number P20AC00441. We thank the many field technicians involved in 18 years of data collection (S. Goodwin, D. Narango, J. Quant, J. Dunlap, F. Owens, M. Edens, B. Furfey, Z. Poulton, Z. Ladin, S. Mkheidze, E. Tymkiw, T. McCuen, J. Petersen, K. Horton, A. Livingston, A.J. MacLaren, M. Albecker, C. Kovach, C. Hensley, C. Higgins, N. Jennings, A. Hanna, S. Robinson, J. Schlict, M. Sileo, M. Griffin, J. Hill, R. Trenkamp, E. Oswald, K. Serno, B. Swimelar, M. Chabra, K. Kennedy, E. Moser, H. Redmond, K. Freesland, C. Gable, M. Massa, L. Mills, J. Miranda, R. Thomas, M. Alt, B. Chambers, J. Heiser, B. Dooley, and L. Eselgroth). The NASA Applied Remote Sensing Training (ARSET) program and U. Gandhi from Spatial Thoughts provided valuable Google Earth Engine tutorials. We also thank the anonymous reviewers for improving earlier versions of this manuscript
Computational and experimental approaches to quantify the influence of pathlogical hemodynamics on hippocampal astrocyte dysfunction
No full textSlater, John H.Alzheimer’s disease (AD) and vascular dementia (VD) are major causes of disability and death in people over 65. While the cellular and molecular mechanisms that govern the initiation and progression of AD/VD are not fully understood, evidence suggests that changes in mechanical cues including high blood pressure, age-related arterial stiffening, and age-related brain softening are likely contributors. Arterial stiffening of elastic blood-vessels is thought to change normal blood flow patterns, thus resulting in neuronal inflammation and injury via mechanical strain-mediated mechanisms. Therefore, I hypothesize that exposure to pathological changes in elasticity, in both the µvessel wall and brain tissue, and high magnitude blood pressure exacerbates and astrocyte injury due to increased mechanical strain transmission to the surrounding tissue. Here, I propose investigating my hypothesis through the following means: (1) Develop methodology for characterizing micromechanical properties of hydrogels via microindentation. (2) Develop a predictive computational model of brain-tissue strain as a function of pressure and tissue elasticity. (3) Develop an in vitro microfluidic model to control pulse pressure to determine its influence on hippocampal astrocyte behavior.University of Delaware, Department of Biomedical EngineeringPh.D