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Firm Disclosures and Retail Investor Behavior: The Role of Information Type, Disagreement, and Social Networks
No full textThis paper examines whether disclosure characteristics–specifically hard versus soft information–influence disagreement among retail investors, whether due to differences in information sets or interpretation, and how such disagreement subsequently affects trading volume. Using a sample of 85,050 earnings conference calls and StockTwits disagreement data from 2010 to 2021, I find that hard information (i.e., earnings figures) is negatively associated with investor disagreement, while soft information (i.e., forward-looking statements) is positively associated with it. Further analysis reveals that the disclosure characteristics impact trading activity only indirectly, through their influence on investor disagreement. Additionally, I examine the moderating role of social network centrality, which is proxied by the centrality of the firm’s headquarters county. Results offer limited evidence that network centrality reduces interpretative disagreement associated with soft information. Cross-sectional analyses show that penny stock investors respond differently to disclosures, likely reflecting variation in investment preferences and information processing. Lastly, the results remain robust when excluding the post-COVID period, which saw an influx of a new group of retail investors. This study contributes to the literature on disclosure processing, retail investor behavior, and the informational sources of market disagreement, as well as its trading implications
Photochemical Fabrication and Tribological Evaluation of Hexagonal Grooves with Corner Dimples on Cast Iron Surfaces
No full textThe traditional honing process used to texture cylinder liners in internal combustion engines has long been recognized as suboptimal, as evidenced by the need for a break-in period before achieving peak performance. Although laser-based methods can produce micro-scale features with high precision, they are often cost-prohibitive and difficult to scale for large or complex components. This study explores photochemical machining (PCM) as a low-cost, scalable alternative for fabricating high-resolution surface textures—specifically, hexagonal grooves with corner dimples—on gray cast iron. The resulting textures exhibit uniform groove widths (~13 μm) and varied depths, demonstrating PCM’s capability to create high-resolution patterns with sub-micron precision on industrially relevant substrates. To assess the effects of surface texturing, pull-off adhesion and reciprocating friction tests were conducted under three lubrication regimes: 1 μL (starved), 10 μL (semi-starved), and flooded oil. Adhesion forces increased with oil quantity but consistently decreased with texture depth, indicating that the patterns disrupted capillary-bridge formation and reduced oil-mediated adhesion. Friction behavior was strongly dependent on sliding frequency (1–30 Hz), oil quantity, and texture geometry. At low frequencies, deeper textures often increased the coefficient of friction (COF), likely due to delayed film formation or lubricant trapping. At higher frequencies – especially under starved and semi-starved lubrication – deeper textures reduced COF, attributed to improved oil retention, greater hydrodynamic lift, and smoother transitions into hydrodynamic regimes. Under flooded conditions, textures showed limited or negative effect on friction, potentially due to flow disturbances or groove-induced drag. Statistical analysis using least squares regression and two-way ANOVA confirmed texture was the predominant factor affecting friction at low frequencies, whereas oil quantity played a more important role at higher frequencies. These findings underscore the importance of context-specific texture design and highlight PCM as a cost-effective, scalable alternative to laser-based methods for fabricating \u3c 50 μm features on curved or engine-relevant surfaces such as piston rings and cylinder liners
Prone to Prejudice: Trans Experiences and Structural Harm in the U.S. Prison System
No full textThis qualitative study examines transgender individuals\u27 experiences within the justice system. This study seeks to illuminate the complex realities of incarceration using social constructionism and reflexive thematic analysis. The social constructionist perspective offers a framework for understanding how gendered identities are shaped, constrained, and policed within institutional contexts. The analysis of narratives from Large Reddit communities allows this study to examine how transgender individuals make sense of and survive correctional environments. A comprehensive analysis of the data generated the following six major themes: (1) Solitary Confinement Universally Induces Horror, (2) Discriminatory Treatment Leads to Disillusionment with the Criminal Justice System, (3) Purposeful Endangerment by Authority, (4) Paranoia and Hypervigilance, (5) Crash Course in Navigating Prison, and (6) Resilience as a Coping Mechanism. Ultimately, this study contributes to a growing body of scholarship advocating for the rights and dignity of transgender individuals in the justice system. This research provides critical insight into the intersection of gender, power, and institutional violence in the lives of incarcerated trans people. It additionally discusses the implications for correctional reform and mental health interventions
Comparative Study on the Long-Term Performance of BMD Mixtures Prepared Using Different Sample Preparation Techniques and Superpave Mixtures Under Varying Pavement Structures
No full textAsphalt mix design has advanced significantly since the 1930s, with Balanced Mix Design (BMD) emerging to address durability concerns found in the Superpave method by optimizing binder content based on performance criteria. The performance of bituminous mixtures can be assessed through laboratory testing. These tests require proper sample preparation, and various techniques are employed for this purpose. Understanding the differences between these techniques is essential for the successful application of bituminous mixtures in the field. The objective of this study is to assess the differences in the predicted long-term performance of two sample preparation techniques, Lab Mix Lab Compacted (LMLC) and Reheated Plant mix Lab Compacted (RPMLC). The study also assessed the differences in predicted long-term performance between Superpave mixtures and BMD mixtures. Predicted long-term performance was assessed using AASHTOWare Pavement ME software (MEPDG). The study found that RPMLC samples generally have a higher dynamic modulus than LMLC, resulting in lower IRI, permanent deformation, and bottom-up cracking but higher top-down cracking. These reductions ranged from 0.075% to 0.92% for IRI, 1.06% to 10.40% for total permanent deformation, 3.10% to 31.98% for AC layer deformation, and 0.58% to 3.75% for bottom-up cracking. Permanent deformation was notably affected by sample preparation, with RPMLC showing up to 32% variation compared to LMLC. A slight increase in top-down cracking was observed, while thermal cracking remained virtually unchanged, reflecting its weak dependency on dynamic modulus and stronger ties to binder and volumetric properties, which were similar between the mixture. Superpave mixtures had significantly higher IRI and thermal cracking than BMD mixtures, indicating BMD mixtures have better performance, with performance differences ranging from 251% to 611% for thermal cracking, clearly showcasing the benefits of BMD. RMSE proved to be the most effective metric for analyzing changes in dynamic modulus supported by R-squared values of 72% for total structural deformation and 74% for AC layer deformation, while pointwise differences were valuable for identifying directional trends. Overall, variation in dynamic modulus accounted for over 60% of the differences in IRI, 78% of the deformation in the asphalt concrete layer between LMLC and RPMLC, and approximately 40% of the variation in thermal cracking between BMD and Superpave mixtures
Algorithmic Recourse in Sequential Decision-Making for Long-Term Fairness
No full textAlgorithmic decision-making systems are increasingly being deployed in high-stakes domains such as criminal justice, education, and financial services. While machine learning models have demonstrated significant utility in automating complex decisions, they have also raised substantial concerns regarding fairness and equity. Much of the existing work in algorithmic fairness has focused on static, one-shot settings, where interventions are aimed at miti- gating bias in a single decision. However, many real-world systems operate sequentially, where decisions made at one point in time can influence future outcomes through dynamic feedback loops. In such scenarios, addressing fairness at only one decision point can be insufficient or even counterproductive, as it may ignore the cumulative and compounding nature of disadvantage over time. This thesis addresses the challenge of achieving long-term fairness in sequential decision-making through a causal recourse framework. Our key contri- bution lies in offering a novel perspective that complements the literature by bridging causal inference, generative modeling, and fairness-aware optimization to develop a principled ap- proach for mitigating disparities over time. Specifically, we propose a two-part framework named SCARF (Sequential Causal Algorithmic Recourse for Fairness), which combines a Variational Causal Graph Autoencoder (VACA) and a Recurrent Conditional Generative Adversarial Network (RC-GAN) to model and simulate how interventions influence future outcomes through causal pathways. VACA captures path-specific effects within a struc- tural causal model, allowing us to identify actionable and temporally sensitive interventions. Meanwhile, RC-GAN models time-lagged dependencies in the data, enabling the genera- tion of counterfactual trajectories that evolve under specified interventions. Our problem is formulated as a constrained optimization task that balances predictive utility with fairness constraints over a finite decision horizon. Interventions are restricted by a predefined budget, reflecting the practical cost of altering an individual’s features or opportunities. The opti- mization objective incorporates both short-term fairness and long-term fairness goals over the trajectory of decisions. The framework supports counterfactual simulations that allow us to trace the downstream impact of fairness interventions, identify path-dependent inequali- ties, and evaluate intervention strategies in terms of both effectiveness and cost. Empirical evaluation is conducted on both synthetic and real-world datasets, including benchmark data in algorithmic fairness literature. Results show that the proposed method significantly reduces group disparities in long-term outcomes without sacrificing predictive performance. The contributions of this thesis are threefold. First, we introduce a novel integration of structural causal models and generative sequence models for fairness-aware decision-making. Second, we provide a fairness-aware optimization procedure that operates under realistic constraints and supports principled recourse planning. Third, we offer empirical insights into the trade-offs between fairness and intervention cost over time. By unifying these el- ements, this thesis advances the study of long-term algorithmic fairness and highlights the importance of causal reasoning in designing equitable decision-making systems that extend beyond single outcomes to entire life trajectories
Strain Induced Quantum Emitters in Monolayer WSe₂: Fabrication and Characterization of Dimple Dot Devices
No full textStrain induced defects in monolayer tungsten diselenide (WSe₂) give rise to localized exciton funnels, offering a promising approach for the development of tunable quantum emitters. The quantum devices fabricated for this thesis used a modified dimple dot geometry, in which nano indentation creates a strain profile on the monolayer WSe₂. This allows for the funneling of excitons to a confined region. These strain induced funnels enable localized emission from single excitons in WSe₂. Device fabrication was carried out through mechanical exfoliation, dry transfer, and electron beam lithography of Cr/Au gates on a SiO₂ substrate. These devices were then characterized using atomic force microscopy (AFM), photoluminescence (PL) spectroscopy, and Stark shift measurements under applied gate voltages. Optical spectroscopy at room temperature revealed localized emission features and early indications of electric gate tunability. Dimple dot devices in WSe₂ represent a promising platform for the deterministic placement and control of quantum emitters for integrated quantum photonics applications
Design and Validation of a High-Frequency Multi-Output DC-DC Converter for Radar Power Applications
No full textModern radar systems and advanced electronics demand compact, efficient, and reliable power solutions capable of delivering multiple tightly regulated voltage rails under strict size, weight, power, and reliability (SWaP-R) constraints. This thesis presents the design, implementation, and validation of a high-frequency (460 kHz – 1 MHz), multi-output DC-DC converter for a mission?critical radar platform, addressing both integration and performance requirements. The first implementation, an isolated modular converter (IMC), utilizes isolated silicon?based DC-DC modules to deliver twelve isolated voltage outputs from a single input. This approach provided robust electrical isolation, simplified system integration, and minimized design risk, making it well-suited for early development and functional verification. The IMC system relies on each module’s internal regulation and does not employ external feedback or digital control. Building on lessons learned from the IMC, a custom multi-output converter was developed using high-frequency Gallium Nitride (GaN) devices and discrete buck and Ćuk topologies to generate both positive and negative rails. The advanced design incorporated a digital control framework using a Texas Instruments C2000 microcontroller to enable precise output regulation and compensation. The digital control architecture was established, and initial open-loop testing was completed within the project scope. Further refinement, including closed-loop tuning and comprehensive validation, is defined for future work. Both converter systems were tested for output regulation, EMI, and thermal performance, with system-level integration and evaluation conducted using the isolated modular converter. Results showed that the IMC system met all standards for regulation and reliability, enabling its integration with the radar, while the custom GaN-based converter was validated in hardware and positioned for future development and system integration. This work establishes a practical foundation for developing multi-output power supplies in demanding electronic systems and highlights the benefits and challenges of modular high frequency approaches. The results lay the groundwork for future integration of wide-bandgap devices and digital regulation in next-generation radar, aerospace, and sensing platforms
The Law of Hard Times: What Today’s Lawyers and Policymakers Can Learn from the Farm Crisis of the 1980s
No full textIt is undeniable, the United States is experiencing another farm depression similar to the Great Depression of the 1930s and the Farm Crisis of the 1980s. While every era is different, knowledge of the case law developed during the farm struggles of the 1930s and 1980s, and the statutory and regulatory reforms that arose from advocacy during those difficult times will be helpful to today’s agricultural lawyers and policymakers. As farmers and ranchers again find themselves, due to circumstances beyond their control, in financial distress, they will contact attorneys, state secretaries of agriculture, state attorneys general, agriculture organizations, and state and federal policymakers. The information presented in this article will help attorneys and policymakers rapidly respond to the needs of farmers and ranchers. The 1980’s Farm Crisis may serve as the foundation from which solutions may be created and implemented to solve today’s farm economy crisis.
We begin the discussion by contextualizing the farm economy of the 1980s and explaining the immense hardships farmers faced that led to such a high number of farm foreclosures across the country. Next, we turn our attention to four major reforms born out of the struggles of the 1980’s Farm Crisis, which include improved National Appeals Division (“NAD”) appeal procedures, the creation of Farm Credit Administration (“FCA”) Borrower Rights, the creation of state mediation programs, and increased utilization of Chapter 12 bankruptcy filings. Then, we provide practical solutions and approaches to handling the current farm crisis, divided into advice for attorneys, attorneys general, commissioners and secretaries of agriculture, policymakers, and agriculture organizations. Finally, we conclude by highlighting the eerie similarities between the 1980’s Farm Crisis and present day
