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Attachment Representations and Behaviors Toward God Amid Spiritual Struggles: An Experimental Study
No full textRepresentations of God involve the activation of internal working models of attachment. Spiritual struggles, defined as tension or strain centered around the sacred, could involve a rupture in the subject’s relationship with God. Thus, recent work to identify behavioral patterns in one’s relationship with God amid spiritual struggles (i.e., approach, disengagement, protest, suppression) may be extended by investigating how attachment representations are associated with these behavioral patterns. This experimental study used an attachment security priming paradigm to investigate whether baseline attachment avoidance or anxiety would moderate the effect of induced felt security on protest behavior. There was an interaction of the experimental effect of induced attachment security on protest behavior for attachment avoidance but not attachment anxiety. Therefore, protest motivations increased along with felt security, especially among subjects with higher baseline attachment avoidance (if they completed the security induction). For individuals whose spirituality includes a focusing on a personal relationship with God, protest may be a consequence of increasing felt security in this relationship amid spiritual struggles. These results have implications for clinical practice with religiously affiliated clients
[sic]: A Critical Memoir on Remembering the City of Forgetting
No full textIn a dialectic with the American frontier narrative, [sic] is a genre-bending work of prose that maps the story of western masculinity onto three shipwrecks buried beneath the tumultuous waters of Los Angeles’s Santa Barbara Channel in a poetic interweaving of ethnography, film criticism, and personal memoir. Spanning from the asphaltum tomols that first carried prehistoric peoples down the Pacific onto North American soil to John Wayne’s Wild Goose converted WWII minesweeper yacht, these shipwrecks become poetic containers through which to process the historiographic violence of manifest destiny and our desperate need to restore public memory to a place of collective consciousness
Alice in 1D-Land: Fluctuations and particle entanglement in one-dimensional systems of identical particles
No full textOne-dimensional quantum matter, like the Wonderland that astonished Alice, breaks the paradigms of higher-dimensional physics: quasiparticles fragment, spin and charge decouple, and correlations exhibit universal power-law decay. The emergent low-energy theory of these systems is the Tomonaga–Luttinger liquid (TLL). In this thesis, we study the \emph{-particle entanglement entropy}—the entropy obtained by tracing out particles in a system of identical fermions. This entropy is sensitive to particle statistics, interactions, and proximity to phase transitions, yet independent of external length scales or basis choice. Because it can be computed from experimentally accessible -point correlation functions, it offers a powerful probe of many-body correlations and entanglement.
Combining bosonization with large-scale density matrix renormalization group (DMRG) simulations, we extend prior studies on particle entanglement. In \autoref{ch:scaling}, we propose and verify a scaling form for the Rényi -particle entropy in an interacting model, identifying universal contributions and subleading corrections. In \autoref{ch:2rdm}, we obtain a closed-form expression for the equal-time four-point function in a fermionic TLL, clarifying the microscopic origins of the entropy scaling. Diagonal elements recover known density correlations, while off-diagonal terms encode particle entanglement for .
We then examine nonequilibrium dynamics in \autoref{ch:quench}, deriving the time-dependent one-particle entropy following an interaction quench. We show that strong coupling alters the entanglement spectrum and modifies late-time decay exponents. In \autoref{ch:fluctuations}, we turn to bosonic systems and analyze particle number fluctuations in the Bose–Hubbard model. By fitting DMRG and Quantum Monte Carlo data to bosonization predictions, we extract the Luttinger parameter and resolve the long-standing location of the Berezinskii–Kosterlitz–Thouless transition. Our finite-size RG scaling reveals the critical point with high precision.
Together, these results deepen our understanding of entanglement scaling and dynamics in one dimension, and bridge the gap between low-energy field theory and microscopic models. Extensions include finite-temperature effects, spinful systems, and particle entanglement in bosons — promising further adventures down the one-dimensional rabbit hole
Dynamics of Drop Impact and Infiltration into Fur-Like Structures
No full textThis experimental work unifies insights from a series of investigations into the dynamics of drop impact and liquid infiltration in fur-like fiber structures, inspired by the multiscale architecture of mammalian pelage. Using both natural fur samples and 3D-printed fiber arrays with tunable geometries, densities, wettabilities, and orientations, we characterize the mechanisms governing drop penetration depth, lateral spreading, and splash suppression across a broad range of Weber numbers. Through sequential drop impacts, we observe that liquid infiltration into fiber networks saturates over time, establishing a dry insulating zone near the base—analogous to that in mammalian coats. This saturation behavior is quantitatively linked to macroscopic pelage parameters such as fiber density, length, contact angle, and cross-sectional geometry, as well as microscopic traits including scale roughness and aspect ratio.
Comparative experiments on horizontal and vertical arrays reveal directional asymmetries: horizontal fibers primarily exhibit inertial and transitional penetration regimes, while vertical arrays include a capillary-dominated phase marked by sustained wicking. Fiber orientation and cross-sectional shape significantly affect penetration dynamics: wedge-shaped fibers suppress fragmentation and promote lateral spreading more effectively than circular fibers, despite their greater hydrophilicity. Hydrophobicity delays initial infiltration, while higher fiber density and staggered arrangement reduce total penetration volume. The interplay between impact velocity, wettability, and geometry determines whether secondary drops increase infiltration depth or are arrested at the surface.
We introduce several dimensionless parameters—including a modified porosity-to-drop-size ratio and a fiber aspect ratio—to describe the onset of splash, critical Weber number for deformation, and the Bond number as a predictor of capillary infiltration. Energy-based models are developed to predict penetration depth from above-array imaging, applicable to fibers of arbitrary convex cross section. Collectively, our findings unravel how the multi-functional design of natural and synthetic fibrous surfaces can resist wetting through a synergy of geometry, material properties, and impact dynamics, providing design guidelines for engineered hydrophobic coatings, bioinspired textiles, and raindrop-resilient systems
Computational Design of Oligopeptides as Carbon Capture Agents
No full textThis work presents a computational framework for understanding and designing bioinspired materials for CO2 capture. We started by calculating highly accurate reference interaction energies with electronic structure theory for amino acid-CO2 complexes and benchmarking different density functionals for performing large-scale DFT calculations on oligopeptide-CO2 molecular systems. Building on this, we explored all possible dipeptides, revealing that cooperative effects significantly enhance CO2 binding, particularly in sequences containing polar residues. We then developed TriScore, a descriptor-based ranking metric, to screen 8000 tripeptides for CO2 interaction. DFT and SAPT0 analyses confirmed that the top-ranking tripeptides exhibit stronger, electrostatically driven non-covalent interactions. Finally, we extended our investigation to amino acids in solution to evaluate their potential in solvent-based direct air capture systems. This progression from single amino acids to solution-phase systems offers a scalable strategy for designing oligopeptide-based CO2 sorbents
Evaluating United States Consumers’ Willingness to Pay for Fresh Culinary Herbs
Get PDFThe demand for fresh culinary herbs in the United States has grown significantly in recent years, driven in part by increasing consumer interest in healthy, flavorful food options. This study investigates U.S. consumer preferences and willingness to pay (WTP) for fresh herbs based on production method, geographic origin, packaging format, and herb species, using a Discrete Choice Experiment (DCE) and mixed logit modeling across three event treatments (i.e., Holiday, Non-Holiday, and Meal-at-home). Results suggest that consumers are willing to pay significant premiums for organic, sustainably grown, local, domestically produced herbs relative to their respective baselines. Pre-cut herbs were preferred over potted and pick-your-own options, highlighting the importance of convenience for consumers. While parsley and basil were more valued than cilantro, the event treatments had a minimal effect on most attribute valuations, suggesting stable preferences regardless of social context. These results underscore the importance of credence attributes and convenience-driven packaging in consumer decision-making for fresh herbs and suggest that marketing strategies can remain consistent with consumer preferences across social contexts
Scaling and Dynamics of Cylinder–Induced Transitional and Turbulent Shockwave / Boundary-Layer Interactions in a Mach 4 Freestream
No full textShockwave / boundary-layer interactions (SBLI) are a prevalent, high-risk fluid phenomena on supersonic and hypersonic aircraft that have significant implications for a vehicle\u27s overall flight performance and safety. Their unsteady nature can generate large gradients in shear layer properties and localized thermal loads, and due to their complexity. With the use of newly developed diagnostic capabilities and analysis methods, it is possible to begin a systematic and efficient study of the driving behavior in transitional and turbulent shockwave / boundary-layer interactions. This investigation aimed to quantitatively measure characteristic SBLI features, capture general SBLI dynamics as a product of the incoming boundary layer state, understand how frequency content associated with characteristic SBLI unsteadiness changes during the transition process, and assess what driving mechanisms promote the growth and collapse of the separation bubble.
To complete this assessment a cylindrical shock generator was installed on a 6-degree axisymmetric cone to study both transitional and turbulent shockwave / boundary-layer interactions in the UTSI Mach 4 Ludwieg tube. High-speed schlieren imaging and pressure-sensitive paint were utilized. Data analysis included power spectral densities, spectral heat maps, POD, DMD, a custom feature-tracking algorithm, and analysis between the separation shock, upstream influence, and a distinct boundary-layer thickening feature.
The high-speed schlieren imaging time series images display a shock collapse from an upstream disturbance in the incoming boundary layer. The upstream influence is seen to bow in response to the turbulent packet as it is pushed downstream. Following this collapse, the upstream influence appears to have a linear restoring behavior upstream towards its originating position. Local frequency probes generally see the most prominent frequencies at the mean location of these ranges of influence. As the SBLI shock generator is moved downstream, this frequency peak shifts to a higher frequency and is suspected to scale with the incoming boundary layer height. The dominant modes in the POD analysis revealed a shift in the SBLI structure between the first two and the final two-cylinder shock generator locations. In the DMD analysis, modes associated with rapid growth mechanisms were identified. A relationship between the UI presence and boundary layer thickening behavior was observed
Soil Nitrous Oxide Hot Moments: Identification, Characterization, and Prediction Across Agroecosystems
No full textNitrous oxide (N2O) emissions from agricultural soils contribute ~4% of total anthropogenic greenhouse gases (GHG) emissions globally. Events known as ‘hot moments’ can occur following environmental changes that favor N2O production, which contribute disproportionately to annual cumulative emissions. Despite their significance, hot moments have not been statistically well defined, particularly on a global scale. I collected 13,787 soil N2O flux measurements from 42 publications and evaluated 14 methods of statistical anomaly detection for their ability to identify hot moments within datasets. Two methods achieved highest overall performance by Matthews correlation coefficient (MCC): median absolute deviation (MCC: 0.80) and minimum covariance determinant (MCC: 0.80), the latter which also performed evenly across highly dissimilar datasets and identified more difficult-to-detect contextual hot moments than other top overall performers (39%). I next evaluated a variety of machine learning classification models for their performance in predicting daily hot moments from a limited set of management, environmental, and climate data. The XGBoost model trained using data labels of N2O flux measurements generated through a context-informed hand labeling process produced the best overall performance (Matthews Correlation Coefficient, MCC: 0.69; Accuracy: 90%), with fewer errors made when flux was \u3c 10 g N ha-1 d-1 or \u3e50 g N ha-1 d-1. Finally, I investigated the impact of extreme weather events on N2O emissions across soils ranging widely in climatological histories and textures collected from the Levant region. Soil cores were subjected to varying periods of very high moisture (90% water filled pore space) ranging from a transient flooding to seven days in an incubation experiment. I found that while cumulative emissions were primarily driven by carbon availability, longer periods of flooding significantly increased cumulative N2O emissions (p\u3c 0.0001) both in soils which experienced impeded gas diffusion by high moisture and those that did not. These findings suggest the possibility of a positive feedback loop as climate change increases the frequency of extreme weather events and flooding, which in turn contribute to greater N2O emissions
Faculty Handbook, September 2025
No full textThe Faculty Handbook is intended to be a general summary of university policies, guidelines, services, and resources. When official university policies and procedures are changed by the Board of Trustees or other duly constituted authority, such changes become effective on the date designated at the time of their adoption and supersede any conflicting or inconsistent provision in the Faculty Handbook. Notification of such changes is given to department and college offices. The most recent versions of the University of Tennessee System and UTK Fiscal Policies and the UTK HR Policies are available on the University of Tennessee website. Questions about a particular policy or issue should be addressed to the department administrator, human resources representative, vice provost for faculty affairs, or chief business officer.
This revision of the Faculty Handbook was done in accordance with Chapter 8 of the Faculty Handbook(“Revision of the Faculty Handbook”)
Rooted in the Collective: A Culturally Situated Artificial Intelligence (AI) Education Workshop For Urban Farmers
Get PDFThis paper describes our experiences related to a culturally situated Artificial Intelligence (AI) education workshop for urban farmers. The farmers explored the concept of AI and its implications in the context of their own farm. They engaged in hands-on activities, including using traditional sensemaking practices in conjunction with sensor technology to collect contextual data. They then used a tangible educational tool: a corkboard with push pins and images to build tactile AI models based on their farm data. Throughout this process, they discussed their hopes and desires regarding AI in farming, and their concerns about AI technologies. The perspectives of the urban farmers reveal their preference for AI systems that are contextual, integrate community values, Indigenous knowledge, and environmental concerns, and are rooted in community ownership of data. Our report provides a starting point for conducting future workshops that involve ‘critical participatory design’ of AI technologies to promote AI literacies rooted in the community