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Dormant No More: How the Supreme Court's Sharpened Pike in NPPC v. Ross Signals a Path to Overturning State Dealer Franchise Laws
Get PDFDormant No More: How the Supreme Court’s Sharpened Pike in NPPC v. Ross Signals a Path to Overturning State Dealer Franchise Laws examines how the Supreme Court’s decision in National Pork Producers Council v. Ross reshaped dormant Commerce Clause doctrine by clarifying and tightening the application of Pike balancing. It explains how the Court’s treatment of state regulations with significant interstate effects revives judicial scrutiny of protectionist or economically distortive laws without relying on broad extraterritoriality principles. Using this framework, Dormant No More analyzes state dealer franchise laws as a case study of entrenched regulatory regimes that impose substantial burdens on interstate commerce while delivering primarily local benefits. The analysis traces how these statutes, particularly in the automotive sector, fit uneasily within the refined Pike framework articulated in NPPC v. Ross. The piece concludes that the decision signals a viable doctrinal pathway for future challenges to state dealer franchise laws under the dormant Commerce Clause
Shape-directed CuNi@Pt-Cu nano-octahedra for enhanced formic acid electrooxidation
Get PDFShape-controlled core@shell nanoparticles have attracted considerable interest for their potential to minimize the use of precious metals in the shell while enhancing catalytic performance through lattice strain and shape effects. However, challenges such as core dissolution and morphological degradation during shell growth remain major obstacles to their broader applications. In this study, we successfully demonstrated core@shell CuNi@Pt-Cu nano-octahedra by leveraging a previously developed protocol based on CuNi nano-octahedra templates. Precise control of key reaction parameters, including a high reaction temperature (240 °C), a rapid heating ramp (~ 12 °C/min), and slow injection of the Pt precursor, enabled the retention of sharp-edged morphology during shell formation. The resulting nanocrystals feature (111)-facet-dominated surfaces and exhibit lattice strain at the CuNi/Pt-Cu interface, both of which contribute to their enhanced electrocatalytic performance. In the formic acid oxidation reaction, the CuNi@Pt-Cu nano-octahedra demonstrated a high specific activity of ~ 25.2 [equation viewable at version of record], significantly outperforming CuNi@Pt-Cu nanopolyhedra/C (15.7 [equation viewable at version of record]) and commercial Pt/C catalysts (4.36
[equation viewable at version of record]). They also exhibited enhanced stability, with only a 17% loss in activity after a 1-h chronoamperometry test, compared to a ~ 44% loss observed for both the polyhedral counterpart and Pt/C. These results underscore the effectiveness of integrating shape control, interfacial strain, and multimetallic synergy within Pt-based nanostructures to improve both electrocatalytic activity and durability
Structure and function studies of EGFR mutations in colorectal cancer
No full textColorectal cancer (CRC) is the 2nd leading cause of death from cancer in the United States, the 3rd most fatal cancer, and 4th most diagnosed cancer worldwide. While early diagnosis typically leads to better prognosis with treatment, there are tumor specific characteristics that may make certain cases more difficult. The Epidermal Growth Factor Receptor (EGFR) is found to be overexpressed in 25-82% of colorectal cancer cases and typically correlated to more aggressive and symptomatic disease expressions. Given the well-documented association between EGFR overexpression and cancer, understanding the role of dimerization in this process is crucial. The goal of this project was to investigate whether colorectal cancer-associated mutations in EGFR—such as L858R and S422I—affect its activation, dimerization, and whether these mutations potentially drive receptor overactivation, thereby amplifying downstream signaling pathways. To assess these aspects, I used methodologies that integrate genetic manipulation, cell biology techniques, and advanced imaging methods to study the cellular and molecular consequences of introducing cancer-related mutations in EGFR. The techniques selected include transfection, bacterial transformation, fluorescence microscopy, and cell culturing, alongside careful use of experimental controls and replicates. The expected outcomes when cancer-like mutations in EGFR are present are increased ligand-mediated dimerization, increased receptor activation, and significant functional differences in oncogenic and wild type receptors. Observing an increase in dimerization could help clarify the mechanism underlying EGFR overexpression in cancer. Currently, treatments for those impacted by these EGFR-linked diseases include tyrosine kinase inhibitors (TKIs). However, there remains a substantial gap in knowledge about how the receptors function under normal conditions versus in an oncogenic environment
Assessing Post-Traumatic Stress Symptoms with the Minnesota Multiphasic Personality Assessment Inventory – 3 amongst Sexual and Gender Minority Adults
No full textSexual and gender minorities (SGM) experience considerable mental health disparities, including high rates of trauma-related psychopathology and common co-morbidities. These disparities are largely attributed to the high rates of trauma exposure amongst SGM populations in conjunction with the insidious impacts of minority stress, identity-based discrimination, and subsequent internalization of discrimination. Accurately identifying SGM populations’ health needs is one method of addressing these health disparities, which can be achieved by advancing effective psychological assessment methods. Prior research supports the MMPI-3’s utility for assessing the heterogeneous facets of PTSD and trauma pathology, making it a uniquely valuable assessment tool. However, there are unique challenges to assessing trauma-related symptoms amongst sexual and gender minorities that are understudied, but critical to understand if we are to practice cultural responsivity when using the MMPI-3 for this purpose. Specifically, there is conceptual overlap between minority stress factors and PTSD symptom clusters that can impact the interpretation of psychological tests (e.g., heightened vigilance and hyperarousal, negative mood, and internalized heterosexism). For instance, research suggests that transgender and gender diverse adults produce significantly higher MMPI-3 test scores when compared to the normative sample across scales central to assessing trauma-related symptoms. Due to overlaps between minority stress factors and trauma-related symptomology, it is unclear to what extent higher test scores amongst transgender and gender-diverse adults represent non-pathological experiences of minority stress and/or PTSD symptoms. In this study, we focus on the use of the MMPI-3 within SGM individuals broadly. First, MMPI-3 scale means and elevation rate differences were examined across three subsamples: cisgender heterosexual (n = 240), cisgender sexual minority (n = 162), and transgender sexual minority (n = 132). Second, this study examined the influences of sexual minority identity and transgender and gender-diverse identity on MMPI-3 mean scores across various levels of PTSD symptom severity. Third, this study examined how the overlap between minority stress and PTSD symptoms influences the MMPI-3 scales' relationship with PTSD symptomology. Broadly, results from this study identified broad trends in how SGM individuals present on the MMPI-3 relative to non-SGM individuals and the MMPI-3 normative sample, identifying where there is a risk of misinterpretation of scale scores. Further, these findings provide initial insight into how sexual minority and gender minority identities, as well as minority stress factors, influence the interpretation of MMPI-3 scores when assessing PTSD symptomology. Results lend support for the integration of culturally sensitive assessment practices in which minority stress factors are considered when interpreting the MMPI-3, particularly heightened vigilance that is inherent to minority stress. Incorporating measures of minority stress in conjunction with the MMPI-3 is warranted to provide a culturally sensitive interpretation of scale scores. Finally, these findings provide initial insight into the degree to which PTSD and minority stress facets overlap
Scalable and Deep Bayesian Nonparametric Survival Analysis for Large-Scale Data
No full textAs a powerful and flexible method in classical survival analysis techniques for latent data heterogeneity, Bayesian nonparametric (BNP) modeling frameworks are increasingly overshadowed with the emergence of the advanced machine learning approaches in modern survival analysis. It may be attributed to two main reasons. First, classical BNP modeling, especially the DP mixtures, is typically limited to small datasets, whereas modern clinical and medical databases are often large and high-dimensional. Second, while integrating BNP modeling with deep learning is a promising direction, the inherent complexity of BNP models has hindered the practical implementation in deep learning architecture, especially in survival analysis, where additional model modifications in BNPs for survival tasks further exacerbate this complexity.
This dissertation proposes two preliminary solutions to address the aforementioned limitations. To tackle the first limitation with respect to data size, a scalable framework for BNP models is introduced. In this framework, the large dataset is partitioned into several subsets of manageable size, and BNP models are independently trained on each subset using classical algorithms in parallel. After obtaining the subset-specific posteriors, a unified clustering structure across all subsets, along with the corresponding cluster parameters, is inferred by aggregating the subset posteriors in a consistent manner. However, the influence of the partition strategy on the accuracy and stability of the unified clustering structure is still unclear.
To address the second limitation, a deep conditional Hierarchical Dirichlet Process (DcHDP) mixture model is proposed. In the DcHDP prior, the traditional Hierarchical Dirichlet Process (HDP) is modified using the Joint Dirichlet Process (JDP) prior. Specifically, the global layer in the HDP is replaced with a standard Dirichlet Process (DP) mixture over the feature space, while the JDP prior is decomposed into two layers: a marginal feature layer and a conditional response layer. In this decomposition, the marginal feature layer is replaced by the random measure learned from the global layer of the HDP. These modifications simplify the model structure and enforce a one-way dependency of clustering structures of responses on features. Therefore, a deep variant of the standard DP mixture model can be employed to learn the global random measure, followed by a truncated MCMC algorithm for inference in the conditional layer. The proposed DcHDP model demonstrates strong capability in capturing nonlinear relationships between features and responses in large-scale clinical datasets. However, its overall performance is highly dependent on the performance of the deep DP mixture model used in the marginal layer
Development of a High Current Solid-State Linear Transformer Driver (LTD)
No full textThis research presents the design, development, and experimental validation of a thyristor-based solid-state linear transformer driver (LTD) for high-current pulsed power applications. LTDs have emerged as a promising approach for fast, high-voltage pulse generation. While traditional solid-state implementations predominantly rely on MOSFETs as the main switching device due to their reliability and controllability, these devices often face limitations in high-current applications. This research explores thyristors as an alternative switching device in solid-state LTD technology due to their superior current handling capabilities and relatively high voltage holdoff characteristics. The thyristor-based LTD demonstrated successful voltage addition scaling from single-stage to three-stage configurations. The three-stage system delivered a peak current of 19.75 kA into a shorted load at a charging voltage of 1.2 kV per stage, achieving current rise times of 199 ns and voltage rise times on the order of 11 ns. Critical design factors were identified and optimized, further increasing LTD performance. Experimental validation confirmed the robustness of the approach and the ability to achieve the targeted current outputs while maintaining system reliability. LTspice simulations validated the experimental results and projected 10-stage performance, indicating a potential of a 30 kA current output into a shorted load. This research establishes thyristor-based LTDs as a viable high-current alternative to conventional solid-state switching technologies with demonstrated scalability and robust performance characteristics
Recruitment through social media ads and videocalls: Cost, effectiveness, and lessons from the Experiences of Pregnancy study
No full textWhile participant recruitment via social media is increasingly used, its cost-effectiveness remains unclear for pregnancy cohorts, especially across social media platforms and in the context of increasing threats from web robots (i.e., bots) and fraudulent participants. Accordingly, we report on the implementation and results of online recruitment for a longitudinal cohort study about mental health in pregnancy and postpartum (Experiences of Pregnancy (EoP)). We describe: (1) the cost-effectiveness of Facebook, Instagram, Reddit, and Twitter/X for recruiting individuals in their first trimester (2) methods, experiences, and solutions for preventing bots and fraudulent participants (3) the representativeness of EoP compared to the United States (US) population and pregnancy cohorts recruited in person. Over 2.5 months (beginning June 2023), 574 participants were recruited at an advertising cost of US$6.19 per participant. Social media recruitment was highly time-efficient compared to in-person recruitment, reaching comparable sample sizes in 1/10th of the time. However, a range of safeguards to counter bots and fraudulent participants had to be implemented, resulting in 995 staff hours during recruitment. EoP also allowed reaching individuals without access to prenatal care but was not representative of the US population, suggesting stratified sampling would be needed to reach representativeness with online recruitment
Staffing Elections
No full textObjective: We identify two different dimensions of retaining poll workers: the successful retention of experienced, more seasoned poll workers and the continued participation of newer, less experienced poll workers.
Methods: Using a unique national survey of poll workers, we test separate explanations for the successful retention of experienced and inexperienced (newer) poll workers. A web-based survey of poll workers (n = 4529) in 19 counties within 10 states was conducted before the 2022 midterm election.
Results: The retention of experienced poll workers is largely shaped by their positive affect and their tenure working the polls. The retention of less experienced poll workers is influenced by interactions with voters, poll watchers, and the compensation they receive for working the polls.
Conclusion: We find the correlates of retaining experienced and less experienced poll workers are sufficiently different to support a bifurcation in the ways local election officials go about staffing elections. While far from definitive, our findings suggest a nascent strategy for staffing elections, as well as a framework for the future study regarding the recruitment and retention of poll workers
The Impact of Grassland Fires on the Archaeological Record—A Case Study Along the Eastern Escarpment of the Southern High Plains of Texas
No full textFires are an essential aspect of the grassland ecosystem across the Great Plains of North America. Wildfires can also transform surrounding rocks to appear like hearths or hearthstones used by prehistoric people. A grassland fire that swept through part of a historic ranch located along the eastern escarpment of the Southern High Plains of Texas has created surface features that mimicked the appearance of hearths. Fourteen wildfire features resembling hearths have been documented, and thermally modified rocks from the surface of three of these features were analyzed to investigate the impact of natural fires on the landscape. The results demonstrate that wildfires can create features resembling hearths when an adjacent shrub is burned. An excavation and detailed analysis, however, suggest that (1) the tops of thermally modified rocks from a wildfire will often have a relatively darker Munsell color value in comparison to their bottom halves, and (2) wildfire features will likely have a thinner cross-section of ash and larger pieces of charcoal produced from the incomplete combustion of the nearby shrub and deadfall. The broader implications are useful for understanding site formation processes within temperate grassland settings in other places
Understanding Key Physical and Surface Representation Processes in the WRF Model for Exploring Boundary Layer Features
No full textIn the rapidly warming climate of the 21st century—marked by intensifying weather extremes, escalating billion-dollar disasters, and increasing societal vulnerability—the demand for accurate and reliable weather forecasts has become more critical than ever before. Central to weather prediction and climate projection is the planetary boundary layer (PBL), the turbulent lowest portion of the troposphere that directly interacts with the Earth's surface and responds to surface forcings on hourly timescales or less. Despite its importance, accurate representation of the PBL remains one of the most persistent sources of uncertainty in numerical weather prediction. This dissertation investigates the sensitivity of the Weather Research and Forecasting (WRF) model to variations in physical parameterizations, terrain resolution, and urban land cover within a multi-scale modeling framework. The primary objective is to advance our understanding of how surface representations and model configurations affect the simulation of lower-atmospheric processes, particularly those associated with PBL dynamics, across diverse spatial and temporal scales.
The first part of the analysis explores surface–atmosphere interactions over the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) site under clear-sky conditions, focusing on the effects of grid resolution, lateral boundary condition (LBC) update frequency, and thermal roughness length (z₀ₕ) parameterization. Results reveal nonlinear interactions among these factors: high-resolution grids improved slope-flow representation and PBL structure; infrequent LBC updates restricted mixed-layer development, while overly frequent updates introduced boundary discontinuities. Additionally, initial surface temperature biases from the North American Regional Reanalysis (NARR) were shown to influence flux partitioning and PBL growth. The second part evaluates the influence of terrain resolution by comparing simulations using the Global 30 Arc-Second Elevation Dataset (GTOPO30) and the Shuttle Radar Topography Mission (SRTM) dataset over the complex terrain of the Korean Peninsula. Spectral decomposition and structural diagnostics demonstrate that fine-resolution SRTM terrain amplifies terrain-driven circulations, enhances sub-kilometer-scale energy, and strengthens dynamic–thermodynamic coupling. These improvements led to more realistic simulations of upslope lifting, gravity wave activity, and spatial distributions of moisture and heat fluxes. Case studies focusing on the evaluation of the precipitation field further confirmed the presence of enhanced rainfall intensity and improved microphysical variability in simulations using SRTM-based terrain. These results suggest that higher-resolution terrain data allows for better representation of topography-induced convective processes, leading to more realistic simulation of precipitation characteristics. The final part of the work investigates the impact of progressive urbanization in the Phoenix metropolitan area from 2001 to 2021 by integrating temporally updated National Land Cover Database (NLCD) datasets with observation-validated WRF simulations. This section examines how changes in urban land cover influence key near-surface meteorological variables—specifically, air temperature, humidity, and wind speed—and evaluates model performance against ground-based station observations. The results indicate that urban expansion during this period significantly intensified the urban heat island (UHI) effect, increasing 2-meter air temperatures by up to 5.6°C in newly urbanized areas, reducing near-surface specific humidity by 0.8–1.2 g/kg, and lowering wind speeds by 1.2–1.8 m/s. The simulation incorporating 2021 NLCD data exhibited the highest agreement with observational data (R > 0.85 for temperature and wind speed), underscoring the importance of using temporally accurate urban surface information to realistically represent land–atmosphere interactions in rapidly urbanizing regions. Collectively, the findings of this research demonstrate that detailed terrain representation and evolving urban land cover act as critical drivers of mesoscale atmospheric structure and variability. The accuracy of WRF simulations is highly sensitive to surface boundary definitions and the treatment of initial and LBCs. These results offer practical guidance for enhancing high-resolution numerical modeling in complex urbanized environments and provide implications for severe weather forecasting, land–atmosphere interaction studies, and urban climate resilience planning