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Where Do I Belong? – Exploring How Students of Color Perceive Sense of Belongingness and Ego-Resiliency at Predominantly White Institutions
Get PDFThe landscape of higher education has witnessed a notable surge in the enrollment of racially underrepresented students, particularly individuals representing various nonwhite racial or ethnic identities. While universities acknowledge the importance of contextual diversity in their mission statements, given the evolving diversity of the student body, the real-life experiences of these students remain complex. The purpose of the study was to explore how students of color perceive ego-resiliency and sense of belonging within the context of academic life at Predominantly White Institutions (PWIs) using a phenomenological approach, drawing on in-depth interviews with eight graduate students of color. The findings through five identified themes suggest that students of color at PWIs often navigate complex experiences of belongingness shaped by systemic structures and personal resilience. Despite feelings of marginalization due to limited faculty diversity and culturally less responsive climates, participants fostered community support, accessed affirming spaces, and relied on internal coping strategies, highlighting the role of ego-resiliency. Even minimal cultural validation through peer support, identity-based groups, or inclusive pedagogy reinforced their sense of belonging. These results emphasize the need for institutional transformation that centers student voices and promotes inclusive, affirming academic environments.
Keywords: students of color, PWIs, ego-resiliency, belongingness, wellbeing
New-Generation Electron Propagators for Molecules, Ions, and Clusters
No full textNew ab initio electron propagator self-energies (one-particle Green’s function methods) for calculating electron binding energies and Dyson orbitals have been derived from an intermediately normalized, Hermitized superoperator metric. No adjustable or empirical parameters are tolerated in the derivation of the new self-energies or their reference Hartree-Fock orbital bases. The cubically scaling diagonal second order method (D2) has been demonstrated to systematically underestimate (overestimate) ionization energies (electron affinities). To ameliorate this deficiency, same-spin correlation is neglected in the opposite-spin second order method (os-D2) that significantly improves accuracy and efficiency. Renormalizations of the ring and ladder terms in the diagonal 2ph-TDA self-energy lead to the diagonal ring (DR) and diagonal ladder (DL) methodologies that have achieved improved efficiency and accuracy. Modification of the Outer Valence Green’s Function (OVGF) method because of the new choice of intermediately normalized, Hermitized superoperator metric leads to the derivation of the approximately renormalized linear third order (L3+). Simplification of the L3+ method leads to the approximately renormalized quasiparticle third order (Q3+) and the approximately renormalized partial third order method (P3+). When the approximate estimation of post-third-order terms is replaced by the explicit evaluation of all contributions from the expansion of inverted matrices, the resulting explicitly renormalized variants of L3+, Q3+, and P3+ are obtained, referred to as RL3, RQ3, and RP3, respectively. Restoration of off-diagonal matric elements leads to the NRL3, NRQ3 and NRP3 self-energies. In addition, non-Dyson (nD) versions of D2, os-D2, OVGF, L3+ and RL3 self-energies are obtained by deactivating energy dependence in 2ph denominators for electron detachment energies calculations and in 2hp denominators for electron attachment energies calculations. This deactivation is achieved by setting the E = εp in the Σpq(E) self-energy terms with these denominators. The non-Dyson version has improved efficiency in electron detachment energies calculations as the arithmetic bottlenecks are no longer iterative. This advantage does not necessarily occur for electron attachment energies calculations. Performance of the new methods has been evaluated using extensive experimental and computational benchmark databases for vertical ionization energies (VIEs), vertical electron affinities (VEAs), and vertical electron detachment energies (VEDEs) of anions. For VIEs and VEDEs, the best compromises of accuracy and cost, expressed in terms of mean absolute errors (MAEs) in eV, and arithmetic efficiency, expressed in terms of powers of occupied (O) and virtual (V) orbital dimensions in bottleneck operations, are os-nD-D2, Q3+, nD-L3+, and nD-RL3 diagonal self-energies. The corresponding MAEs and arithmetic scaling factors respectively are: (~0.18, OV2), (~0.15, O2V3), (~0.08, OV4), and ~0.07, OV4). NRL3 is the best non-diagonal method with an MAE of ~0.06 eV and a non-iterative O2V4 scaling. For VEAs, the best compromises of accuracy and cost are D2, nD-L3+, and nD-RL3 diagonal self-energies. Their corresponding MAEs and arithmetic scaling factors respectively are: (~0.18, OV2), (~0.08, OV4), and (~0.07, OV4). NRL3 is the best non-diagonal method with an MAE of ~0.06. Tests on open-shell atoms, molecules, and ions show similar trends except that MAEs generally increase by ~0.05 eV due to spin contamination. For molecules with nuclei of the fourth or higher periods, RL3 and nD-RL3 are the best methods with MAEs of ~0.14 eV. For core 1s ionizations, the Brueckner doubles with triple field operators (BD-T1) method exhibits the highest accuracy with a MAE of ~0.39 eV. It shows excellent agreement with experimental data and minimal systematic bias. Composite schemes that incorporate the new methods for estimating basis-set effects have enabled highly accurate calculations of VIEs and VEDEs for organic photovoltaic molecules, which are important for optimizing solar energy devices, achieving MAEs that approach chemical accuracy (average errors of 0.04 eV). The new methods and their composite schemes also produce excellent predictions and clear interpretations based on Dyson orbitals for the photoelectron spectra of DNA nucleotide anions and green fluorescent protein (GFP) chromophore anions. Because the new methods developed in this dissertation require no adjustable or empirical parameters and the accuracy of several of them approaches chemical accuracy, they are reliable for predictions on novel molecules, ions, and clusters. Therefore, the existence, stability and VEDEs of OnH2n+1– and NH4-(H20)n double Rydberg anions have been predicted. These clusters are predicted to have well separated VEDEs and experimentally accessible total energies and therefore are expected to appear in mass-selected, anion photoelectron spectra that typically detect low-lying isomers
Spatial and Behavioral Dynamics of Socially Isolated Wild Pigs Following Sounder Removal
Get PDFEffective management of invasive wild pigs (Sus scrofa) requires understanding how individuals respond to social disruption. We GPS-collared 18 female wild pigs to evaluate spatial behavioral changes following partial sounder removal via trapping. Over a 30-day post-trapping period, pigs remained close to trap sites (mean: 1.2 km; max: 6.4 km), showed stable range sizes, and limited dispersal. Using net squared displacement modeling, we classified daily movement into six behavioral strategies and evaluated time allocation as well as the influence of social structure and composition. Wild pigs showed a clear temporal progression from structured, cautious behaviors (encamped, semi-roundtrips) to unstructured, more flexible behaviors (wandering, exploring), with a transition occurring around days 18-20. Lone pigs were influenced by social composition: individuals from adult- and female-rich sounders initially exhibited strong site fidelity following trapping but gradually shifted towards more exploratory behaviors over time. These results suggest that lone survivors often remain in or return to trap site areas, creating a critical window for follow-up efforts. Understanding spatial behavior after disturbance can improve control strategies and reduce the risk of disease spread
Signals Crossed: Testing Different Forms of Interoceptive Dysfunction as Facilitators of Muscle Dysmorphia Symptoms
Get PDFIntroduction. Interoceptive dysfunction (i.e., difficulties attending to internal sensations) may reflect a
risk factor for muscle dysmorphia (MD) symptoms. Specifically, gastric interoceptive dysfunction,
elevated pain tolerance, and poor interoceptive sensibility may facilitate MD symptoms. Thus, this study
tested various forms of interoceptive dysfunction as risk factors for MD symptoms. Additionally, both
self-report and psychophysiological indices of interoception were tested and comparatively evaluated as
MD risk factors. Methods. 151 (48.3% men; 90.7% White, Mage = 19.36) university students completed
two self-report surveys separated by one month. Participants completed psychophysiological indices of
interoception at baseline. Longitudinal regression analyses tested interoceptive variables as predictors of
MD symptoms stratified by interoceptive domain (e.g., gastric, pain, general) and sex. Significant
predictors were included in a larger model with the full sample to determine the predictive utility of these
constructs. Results. Among the subsample of men, self-reported interoceptive sensibility (e.g., viewing
body sensations as worrying and increased ability to attend to bodily sensations) predicted MD-functional
impairment longitudinally. There were no significant predictors of MD symptoms among the subsample
of women. In the larger model using the full sample, increased ability to attend to bodily sensations
predicted MD-functional impairment. Discussion. Self-reported interoceptive sensibility predicted MDfunctional impairment; however, no psychophysiological indices of interoceptive dysfunction
longitudinally predicted MD symptoms. Although unexpected, increased ability to attend to bodily
sensations predicted greater MD-functional impairment (e.g., prioritization of weight training above
social/personal responsibilities, anxiety/depression when missing weight training), perhaps by increasing
the ‘mind-muscle’ connection and making workouts more reinforcing. As such, clinicians may consider
applying clients’ skills in attending to physical sensations to non-exercise related activities to regulate
mood (e.g., progressive muscle relaxation) to reduce reliance on weight training sessions
Antimicrobial Activities of Canine Platelet Lysate
No full textPlatelet lysate (PL), an acellular product derived from lysed platelets, holds promise as a dual-function therapeutic with regenerative and antimicrobial properties. Rich in growth factors and antimicrobial peptides (AMPs), PL supports wound healing and disrupts bacterial membranes, offering a biologically based alternative or adjunct to antibiotics. While human and equine studies have demonstrated PL’s efficacy against pathogens such as Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa, its effects on bacteria common in canine wounds remain uncharacterized. Moreover, the impact of PL on bacterial growth kinetics in canine pathogens has not been previously investigated.
This study first looked at the effects of various preparation methods on the antimicrobial activity of canine PL, considering variations in leukocyte concentration, plasma content, and complement activity. Blood from eight dogs was processed into leukocyte-rich or -reduced PRP, followed by plasma depletion or heat inactivation before generating PL. Antimicrobial activity was tested against E. coli, E. faecalis, S. pseudintermedius, and S. aureus. PL significantly reduced S. aureus and E. coli counts, while plasma depletion and complement inactivation reduced efficacy against S. pseudintermedius and E. faecalis, respectively.
Next, we investigated how PL, alone or combined with amikacin, affects bacterial growth dynamics. PL (20% and 80%) with or without amikacin was tested against S. aureus, S. pseudintermedius, and MRSA. PL reduced bacterial yield and prolonged lag time in all strains, with stronger effects at 80%. The combination with amikacin further enhanced these effects, although μₘₐₓ remained unchanged.
These findings suggest that plasma components, including complement proteins, are important contributors to the antimicrobial effects of PL against certain bacteria, whereas leukocyte concentration does not appear to play a major role. In addition, PL primarily limits bacterial proliferation and delays the onset of growth, while its combination with amikacin amplifies these effects without influencing bacterial replication speed
Uncertainty Quantification and Inference under Differential Privacy
Get PDFAdvances in technology have led to the proliferation of adversarial techniques capable of undermining traditional data security protocols designed to ensure data privacy. Such breaches have resulted in significant financial and reputational costs for companies, particularly in addressing privacy violations and complying with regulatory penalties. Strict privacy regulations, including the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA), further necessitate the integration of privacy-preserving mechanisms throughout the data modeling pipeline to avoid legal repercussions. Differential privacy (DP) and its variants have emerged as the gold standard for mathematically quantifying and mitigating privacy loss in sensitive data analysis. However, the noise introduced to achieve DP often distorts data structure and statistical properties, rendering traditional inferential methods inapplicable.
This dissertation develops efficient and robust methods for privacy-preserving data analysis under DP guarantees. Chapter~1 introduces a flexible simulation-based framework that constructs the distribution of a DP estimator by matching observed DP statistics with simulated counterparts. The method is applied to one- and two-sample confidence interval estimation, hypothesis testing, chi-square tests of independence, and logistic regression with categorical predictors. Extensive simulations demonstrate that the proposed approach performs comparably to state-of-the-art methods. Applications to real-world datasets further confirm that inferences drawn from the DP statistical tests align with those obtained via conventional non-private methods.
Chapter 2 presents a binary search-based DP algorithm for conformal prediction in classification tasks. Extensive empirical evaluations reveal that this method outperforms the only existing alternative in both efficiency and predictive performance. Evaluations on benchmark datasets (CIFAR-10, ImageNet, and CoronaHack) demonstrate its superiority over the current state-of-the-art method across realistic and practical scenarios
Graph-Based Visual-Semantic Representations for Visual-Data Understanding
Get PDFVisual event perception tasks, such as activity recognition, require reasoning over visual-semantic concepts present in scenes. These scenes often exhibit hierarchical structure, both physically (e.g., objects contained within other objects or part of larger structures) and semantically (e.g., causal or contextual relationships among objects). Capturing and reasoning over these complex relationships directly from pixel data or textual descriptions (e.g., labels or captions) can be inefficient and limited in expressiveness. Most existing approaches rely on data-driven models trained in supervised or semi-supervised settings, typically under a closed-world assumption, where only a fixed set of categories or concepts is considered during both training and inference. This restricts the model’s ability to generalize to open-world scenarios, where arbitrary and previously unseen combinations of concepts may occur. This dissertation aims to address this challenge through the lens of graph-based visual-semantic representations, with the goal of developing frameworks that go beyond fixed taxonomies and closed-world assumptions to move toward open-world visual understanding.
We begin our investigation with static scenes, focusing on generating scene graphs that capture the underlying semantic structure. Using a generative approach, we first construct label-agnostic graph structures that represent potential interactions between objects in a scene. This is followed by a relation prediction module to label the sampled edges to form spatial scene graphs which encodes the spatial relationship between the objects present in a scene. The generated graph structure not only achieves state-of-the-art performance but also significantly improves zero-shot scene graph generation which shows the better generalization capabilities of our proposed approach.
To move beyond static scenes, the latter part of dissertation focuses on extending visual-semantic graph representations to egocentric video data, aiming to move toward open-world activity understanding. We first introduce a knowledge-guided learning approach that grounds concepts in a predefined label space and employs an energy-based neuro-symbolic framework to translate them into the target activity space with minimal or no supervision. We further improve this framework by incorporating advances in vision-language models and neuro-symbolic prompting to achieve more robust grounding of object concepts. The enhanced approach leverages an energy-based neuro-symbolic model to infer plausible actions over grounded concepts and integrates temporal smoothing for action prediction, supported by video foundation models.
Finally, we introduce a probabilistic residual search strategy based on jump-diffusion dynamics. This method efficiently explores the semantic label space by balancing prior-guided exploration with likelihood-driven exploitation. It incorporates structured commonsense priors to define a semantically coherent search space, adaptively refines predictions using Vision-Language Models (VLMs), and employs stochastic search to locate high-likelihood activity labels. We evaluate our approaches on standard egocentric video datasets, including GTEA-Gaze, GTEA-Gaze Plus, EPIC-Kitchens, and Charades-Ego, achieving competitive performance against fully supervised baselines.
Together, these contributions offer a unified framework for visual-semantic representation and reasoning in both static and dynamic scenes. The proposed models not only improve open-world generalization but also enhance the interpretability and trustworthiness of activity understanding systems. This work lays the foundation for building adaptable, explainable, and knowledge-aware visual perception systems capable of operating effectively in complex, real-world environments
Comparing Two Methods of Hoof Immobilization for Stabilization of Type III Distal Phalanx Fractures in the Horse: A Cadaveric Study
Get PDFType III distal phalanx (third phalanx; coffin bone; P3) fractures in horses are sagittal fractures with an articular component involving the distal interphalangeal (coffin) joint. Type III fractures of P3 results in a guarded to good prognosis for return to athletic function that appears to be dependent on age demographic. Internal fixation of type III fractures of P3 have been debated when compared to conservative management. Younger horses (<3 years of age) with articular fractures of the P3 have been reported to have a better prognosis when managed conservatively compared to mature horses, which had a more favorable prognosis with surgical management. In general, the major objective of articular fracture repair and healing to obtain joint congruity. A smooth and stable joint surface is needed for more rapid and complete healing, which decreases convalescence time and minimizes future development of degenerative joint disease of the coffin joint. Whether the P3 fracture is repaired surgically or not, hoof immobilization with a foot cast or bar shoe is traditionally utilized during fracture healing.
The objective of this study was to determine the effect of different methods of hoof immobilization on minimizing fracture gap increase in type III fractures of P3 in cadaveric limbs under compressive load with and without internal fixation. We hypothesized that the treatment group with internal fixation and a foot cast (IFFC) would provide the most stability of the fracture as determined by the smallest change in fracture gap under compressive load.
The study utilized 48 cadaveric equine distal limbs (n=48) from a total of 19 horses. A type III fracture was created in P3 of each limb. Limbs were randomly allocated to six equally numbered treatment groups (n = 48): barefoot (BF, no internal fixation or hoof wall support), hoof wall support with foot cast (FC) or bar shoe with clips (BS), internal fixation and no external support (IFBF), internal fixation with external support with foot cast (IFFC) or bar shoe with five clips (one toe clip, two quarter clips and two side clips) (IFBS). Serial radiographs were taken of the hoof to assess changes in fracture gap were performed at successive 50kg increases in monotonic compressive load applied. Interactions between independent and dependent variables were assessed via statistical testing.
IFFC resulted in the smallest change in fracture gap displacement under increasing compressive loads compared to the other treatment groups. In conclusion, greatest stability of the fracture was acquired using internal fixation and a foot cast as external coaptation. These data suggest that surgical management provides more stability to Type III fractures of P3 and should be considered for treatment in vivo, however, prospective studies are needed to confirm
Leveraging Geospatial Knowledge to Inform Water and Wastewater Management
No full textWater and wastewater management are persistent, evolving challenges, and geospatial knowledge provides a unique perspective to understand them. Although there are numerous studies on these topics and great progress in developing effective management strategies, gaps in knowledge remain. These gaps, such as understanding variability in impaired waters or addressing failing wastewater treatment infrastructure, vary spatially. Thus, the overarching objective of this dissertation was to leverage geospatial knowledge to inform water and wastewater management. Three chapters are included in this dissertation. For each chapter a different geospatial technique was utilized to addresses a unique aspect of water quality and wastewater management. Chapter 1 presents a novel spatiotemporal analysis of water quality impairment data (i.e., the 303(d) List) in Alabama and showed that Alabama coastal areas have more impaired waters compared to rest of the state. This manuscript exemplifies how existing water quality can be translated into new accessible insights for water quality managers, the public, and policy makers. In Chapter 2, the first national inventory of onsite wastewater treatment system (OWTS) data was completed. Results revealed that over half of the United States does not have parcel-resolution publicly available OWTS data (59% by area). This highlights the need to bolster open, accessible OWTS data, which are beneficial to inform local communities in decision making and infrastructure planning, academic research investigating related challenges, nonprofits or advocacy groups involved in grant applications or public education, and permitting agencies that seek to build an OWTS dataset. In Chapter 3 spatial optimization was used to model the cost-optimal layout of wastewater infrastructure in Lowndes County, Alabama to inform ongoing wastewater infrastructure improvement efforts. Results suggest that building more centralized infrastructure (i.e., clustered and centralized wastewater treatment systems) would be most cost effective for the county. Other communities could benefit from using this model to inform decision making. Altogether, these projects outline the range geospatial techniques that can be applied to address various water and wastewater challenges. Geographic information systems provide a unique platform to bring together various data and promote systematic analysis to improve management of water and wastewater
From Construction Sites to Coastal Wetlands: National Erosion and Sediment Control Synthesis and Coastal Vegetation Response to Thin Layer Placement
No full textErosion and sediment control (E&SC) measures play an important role in protecting water quality and preserving ecological balance in a changing environment. Sediment from construction activities can degrade water bodies by blocking sunlight, disrupting aquatic habitats, and transporting pollutants. Stormwater that mobilizes sediments not only reduces water clarity but also impairs the natural functions of receiving waters. Federal initiatives such as the Clean Water Act provide a regulatory framework for controlling these impacts and ensuring that construction operations implement sound pollution prevention measures through techniques like site-specific Stormwater Pollution Prevention Plans (SWPPPs). These measures help manage the flow of sediment into water bodies while balancing development needs with environmental protection.
Authorized states have used the flexibility granted by federal legislation to develop their own E&SC practices that reflect local environmental conditions, economic factors, and regional hazards. As a result, there exists a wide range of guidelines and standards, from the design of SWPPPs to the incorporation of best management practices. This state-level variation leads to noticeable differences in how construction stormwater is managed across the nation. The diversity in design approaches and performance metrics highlights the need for a systematic review that can consolidate these practices into a more uniform framework, thereby simplifying evaluation and ensuring consistency in achieving water quality goals.
The first component of this dissertation focuses on consolidating and evaluating E&SC practices through the development of a comprehensive database and synthesizing a state-of-the-practice of E&SC practices. By reviewing 176 manuals, standards, and handbooks from 50 states and six territories, the study categorizes these practices using the framework of the Five Pillars of Construction Stormwater Management. The framework organizes practices according to the management of communication, work, water, erosion, and sediment. This systematic analysis revealed that while practices such as vegetated filter strips, temporary slope protections, hydromulches, check dams, silt fence sediment barriers, sediment basins, and dewatering devices/practices, have an abundance of performance data, nearly all other BMPs have minimal or no peer-reviewed performance evaluations to support their effectiveness. The study also highlighted inconsistencies in terminology of BMPs and offers a glossary with a guided structure to improve understanding. Appendices provide a glossary, catalog of BMP names, state-specific summaries, and a compilation of peer-reviewed research by BMP to guide future studies and improve regulatory clarity. The findings reveal the need for targeted research to evaluate under-studied practices and normalize terminology and standards across U.S. states and territories.
This systematic analysis identifies methods that are supported by recent performance data as well as those that remain under-studied or outdated. The resulting compilation standardizes terminology and establishes an evidence-based foundation that practitioners and regulators can use to reassess and improve stormwater pollution prevention plans. The insights generated from this effort will assist in streamlining regulatory practices and optimizing the performance of E&SC installations.
The second component of the dissertation examines the application of Thin Layer Placement (TLP) for coastal erosion control in the context of living shorelines. Coastal wetlands play an important role in moderating the effects of storms and coastal erosion through natural processes that protect shorelines and support diverse species. In areas such as the Gulf of America, these natural systems are increasingly challenged by sea level rise and human activity. TLP is a sediment management technique that involves applying a thin layer of dredged sediment to areas where natural sedimentation is insufficient. This research focuses on black needlerush (Juncus roemerianus), a native coastal plant known for its robust root system and contribution to shoreline stabilization. Experiments were carried out in a controlled, small-scale marsh environment that simulates coastal conditions found in Alabama. The study used both non-destructive and destructive sampling methods to monitor plant survival, growth, and biomass accumulation across different TLP application depths. The objective was to establish TLP application parameters that preserve plant health and maintain the structure of living shorelines while minimizing the need for replanting. Experiments revealed that J. roemerianus maintained consistent survival and growth under control and 6" TLP treatments, with shoot survival reaching over 80% and shoot length and basal diameter increasing by over 500% in the 6" treatment. The 8" TLP treatment showed early signs of stress but ultimately recovered, achieving over 165% shoot growth. In contrast, the 10", 12", and 14" TLP treatments experienced high mortality with no recovery, with complete burial observed at the highest depths. Biomass trends and root-shoot ratios further displayed the strong growth for lower TLP treatments and stress-induced limitations for higher burial depths. The study found that J. roemerianus can tolerate sediment burial up to approximately 62% of shoot height (8" TLP), but burial beyond 78% (10" or more) compromises survival. These results define a critical TLP application depth threshold for effective living shoreline restoration dominated by black needlerush vegetation.
In summary, this dissertation brings together research on inland construction stormwater management and coastal living shorelines to address a broad spectrum of environmental protection. The study offers a comprehensive evaluation of current E&SC practices by identifying state-specific variations and performance gaps that can guide improved policy and implementation strategies. At the same time, the investigation of TLP on living shorelines provides empirical evidence for its effectiveness in sustaining coastal vegetation amid changing environmental conditions. The combined findings strive to enhance our understanding of sediment control from both inland and coastal perspectives and contributes practical, evidence-based guidelines to support more consistent and sustainable environmental management practices