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Review of James K. Galbraith and Jing Chen, Entropy Economics: The Living Basis of Value and Production (The University of Chicago Press, 2025)
No full textEquity vignettes: A practice-based resource
No full textMathematics teachers have the power and responsibility to center equity in their teaching practices. Yet their framings and mindsets about equity can impact whether and how they use equitable teaching practices. In this manuscript, we describe how secondary mathematics teacher candidates responded to two equity vignettes focused on (1) gender identity and (2) race and tracking. We wrote these vignettes to expose candidates to situations they may encounter and decisions they may need to make as mathematics teachers. The purpose of this study was to explore the teacher candidates’ beliefs. We use the FAIR Framework and the Educator Mindsets for Equity to interpret teacher candidates’ responses. We discuss how mathematics teacher educators can adopt or adapt the equity vignettes to provoke awareness and reflection among the teachers they work with
The Present Interregnum: The Ultra-Right Revolution
No full textThis paper deals with recent political consequences of presentism as conceptualized by the historian Francois Hartog. It clarifies how our experiences of time and history have enlarged the present and the past and have almost disappeared the future (except for catastrophic views). The consequences of these changes in the experiences reflect profound changes in expectations about the future, and how this regime of historicity allows people to become disoriented. They were moved into the margins of precarity. As a result, many of their views on politics find resonance redesigned by the distorted narratives of ultra-right leaders who blame those who are the weakest, the immigrants. These ultra-right narratives have learned how to create counter-hegemonic views to bring about their revolutions by furbishing the past myth of greatness to head towards a future\u27s-past
Automated Yield Monitor Data Post-processing Pipeline via Explainable Model Benchmarking and Stacked Ensemble
No full textAccurate yield data post-processing is a key component of agricultural field management and precision farming analyses. Traditional approaches to post-processing yield monitor data rely on rule-based filtering, manual inspection, and thresholding, which is time-consuming, inconsistent, and relies on expert knowledge. This study demonstrates the viability of machine learning for automated, non-expert detection of erroneous data points, thereby increasing the scalability of yield map generation from raw yield monitor data. Historical yield data (4.6 million data points) were collected from 326 soybean and corn fields in the Delta region of Mississippi. Extensive feature engineering was conducted to derive spatial, operational, and geometric features to enrich model learning. Eight machine learning algorithms (Decision Tree, Random Forest, XGBoost, CatBoost, K-Nearest Neighbors, Artificial Neural Network, Naïve Bayes, and SGDClassifier) were trained with Bayesian-optimized hyperparameters and evaluated across multiple resampling strategies. CatBoost emerged as the best performing model on the raw feature set, achieving an F1-score of 0.77. Random Forest (F1 = 0.76), XGBoost (F1 = 0.74), and Decision Tree (F1 = 0.72) also performed competitively on the raw dataset, though they fell slightly short of CatBoost\u27s score. Evaluation on unseen fields demonstrated the model\u27s ability to locate error-prone regions, though isolated false negatives were observed. A stacked ensemble model using XGBoost as the meta-learner slightly improved F1-score (0.78), but gains were limited by high prediction correlation among top base learners and the suboptimal performance of weaker classifiers. SHAP-based interpretation of CatBoost and XGBoost revealed that their predictions aligned well with the domain knowledge
Quantifying benefits of biochar with variable absorption capacity as a partial cement replacement in concrete
No full textExtensive research has been conducted on biochar-incorporated concrete. However, no concrete mixture design guideline is currently available for implementing biochar incorporation in practice. The objective of this study was to correlate biochar absorption capacity with the compressive strength of biochar-incorporated concrete, to quantify the benefits of biochar and develop mix design guidelines. Biochar with varying absorption capacities was incorporated into concrete at 10%, 20%, and 40%. Strength and moisture loss were recorded over the 90-day curing period of the biochar-incorporated concrete. Results revealed three main findings: (1) in 10%, 20%, and 40% biochar mixes, the normalized strengths ranged from 0.65–0.85, 0.30–0.45, and 0.15–0.25, respectively; (2) moisture loss in all specimens was approximately 10%; and (3) adding biochar reduced the slump of the concrete. With results in this study and previous studies, a preliminary design chart was developed to guide the design of biochar-incorporated concrete
Nuclear transparency of photoproduced Rho-0 Mesons.
No full textPhotonuclear reactions using a real photon beam offer a unique opportunity to explore fundamental aspects of QCD within the nuclear medium. The experiment E12-19-003, conducted at Jefferson Lab’s Hall D in 2021, aimed to look for the transition from hadronic to partonic degrees of freedom and to explore the predicted QCD phenomenon known as color transparency in photons, mesons, and baryons. A key objective was to examine the transition of the photons from a resolved (hadronic fluctuation) configuration to a point-like electromagnetic probe. The experiment utilized liquid deuterium, helium, and carbon foils as target nuclei, which were probed by photon beams with energies of 6.5 - 10.8 GeV. Differential cross sections and nuclear transparency were extracted and compared with theoretical predictions. While the data are generally consistent with the resolved photon regime at lower momentum transfers, they do not provide conclusive evidence in favour of any specific scenario - resolved or unresolved photon regime, with or without color transparency effects
Exploring user acceptance of virtual reality head mounted displays
No full textA variety of potential options exist for using virtual reality head mounted displays (VR HMD) in the workplace such as training, data analysis, or design analysis. However, a common side effect impacts some VR HMD users referred to as Visually Induced Motion Sickness (VIMS). Other research continues to investigate possible mitigation options to reduce the occurrence VIMS. Investigating and understanding factors that influence acceptance could provide insights to support increased use of VR HMD in the workplace. Different theoretical technology acceptance models exist that support understanding user acceptance of VR HMD. This dissertation consists of three studies exploring the user acceptance of VR HMD in the workplace through examining prediction of the Behavioral Intention (BI) construct and associated acceptance models. The first study compared the general predictive performance of different theoretical technology acceptance models for a VR HMD workplace scenario. In this live experimentation study, participants used a VR HMD in a workplace scenario resulting in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) providing the highest predictive performance. The second study investigated developing a new acceptance model evaluating both significant factors from theoretical model frameworks as well as VIMS and mitigation related factors. This second study also involved creating a short questionnaire to allow for quick assessment without requiring a full model analysis. The generated Unified VR HMD Acceptance Model performed slightly better than the UTAUT2 while the new six item questionnaire significantly predicted BI. The third study focused on validating the Unified VR HMD Acceptance Model and questionnaire. This study used data from two sets of participants (live experiments and online survey). Results validated the three primary constructs of the Unified VR HMD Acceptance Model which also resulted in the highest adjusted R2 when compared to the other theoretical models and validated the acceptance scale questionnaire. However, a significant difference between the sets of users led to model fit indices achieving threshold (TLI, CFI) while the RMSEA fell outside of the acceptable threshold for live data, but within acceptable levels for the online data
Spectral methods and wavelets in quantitative finance problems
No full textThis dissertation leverages advanced spectral methods and wavelet techniques to address complex quantitative finance models, enhancing the computation of financial derivatives and risk assessments. Building on foundational studies, this research extends these methods to broader, intricate financial contexts. The first section explores fractional-order generalized Chebyshev wavelets (FOCW) applied to fractional advection equations, relevant in both mathematics and physics. Using a regularized beta function to compute the Riemann-Liouville fractional integral operator, this study introduces a novel numerical scheme with robust accuracy, confirmed through error analysis and empirical tests. The second part examines the fractional Black-Scholes equations for option pricing under subdiffusive dynamics, using fractional-order generalized Taylor wavelets (FGTW). This approach accurately approximates the Greeks of financial derivatives, showcasing precision in financial computation through rigorous error analysis and extensive testing, demonstrating its value for industry applications. Finally, inspired by work on credit risk, this research generalizes the Lévy model to incorporate tempered stable processes, a recent financial innovation. Using radial basis function (RBF) collocation methods, we address the singular nature of partial integro-differential operators in structural credit risk models. This approach enhances both the desingularization and computational efficiency of default probability estimations for public companies. Overall, this dissertation synthesizes and extends current methodologies, introducing new computational techniques that advance quantitative finance. The integration of spectral methods and wavelet techniques provides a powerful framework for tackling challenging problems in financial mathematics
The Bioarchaeology of Care in an asylum population: studying health-related caretaking in the Mississippi State Asylum
No full textThis study employed modified versions of the Bioarchaeology of Care (BoC) and the Index of Care (IoC) to assess signs of impairment, disability, and health-related caretaking within a sample of 15 individuals buried in the Asylum Hill Cemetery who were likely former patients at the Mississippi State Asylum (MSA). This aim is to explore perceptions of disability and health-related caretaking needs through a combination of skeletal evidence and historical documents. Twelve individuals likely experienced physical impairment and potentially disability through participation restrictions. Six individuals likely required health-related caretaking, and healing lesions suggest they may have received care while at the MSA. The specific skeletal changes, and the possible impairments, disability, and health-related caretaking needs are discussed for each individual, alongside a discussion of the limits of the study and recommendations for future research
Design and validation of a custom oscillation seeding chamber for bioreactor culture of ceramic coated polymer scaffolds
No full textScaffolds are essential in tissue engineering, providing a 3D structure that supports cell attachment, proliferation, and differentiation while guiding tissue regeneration. Enhancing cell scaffold interactions and replicating the native mechanical and nutrient environment remain major challenges. This study integrates surface functionalization and dynamic seeding to enhance cell function on 3D printed polylactic acid (PLA) scaffolds. A custom oscillation seeding device, automated via Python, enabled bidirectional flow of cell suspension. PLA scaffolds were coated with a hybrid polydopamine/nano-hydroxyapatite coating to enhance attachment and bioactivity. Pre-osteoblasts were seeded onto coated or noncoated scaffolds either statically or using oscillation seeding, and attachment and distribution were measured after 24 hours. After seeding, scaffolds were cultured for 14 days in a bioreactor system which applied both compressive loading and perfusion flow. The study investigated the effects of bioactive coatings, oscillation seeding, and mechanical stimulation, demonstrating a versatile platform for bone tissue engineering applications