Click on this link to download the full high-definition interactive pdf for AJUR Volume 23 Issue 1 (March 2026). The Crossref link for this issue is https://doi.org/10.33697/ajur.2026.162
Links to individual manuscripts, abstracts, and keywords are provided below.
p. 3 Special Purpose Acquisition Companies: An Examination of Litigation Risk and Mitigation Strategies
Yitong Jiang, Elizabeth Claire Krawze, & Hyoseok (David) Hwang
https://doi.org/10.33697/ajur.2026.163
ABSTRACT: Special purpose acquisition companies (SPACs) have emerged as a popular alternative to traditional initial public offerings (IPOs), offering speed, pricing certainty, and flexibility in taking private companies public through de-SPAC transactions. However, SPACs face significantly higher litigation risks than IPOs due to limited regulatory oversight, conflicts of interest, and poor post-merger performance. Using hand-collected data on 2,450 SPACs and 25,879 IPOs from 2013 to 2024, we find that 4.8% of SPACs are sued compared to 0.6% of IPOs. This study investigates the structural factors driving these lawsuits, including weaker disclosure requirements and the use of forward-looking projections permitted under the Private Securities Litigation Reform Act (PSLRA) safe harbor. We employ regression analysis to examine how macroeconomic conditions influence litigation risk. Our findings suggest that enhanced due diligence, stricter disclosure standards, and robust post-merger governance could mitigate these risks, fostering greater investor confidence and market stability. KEYWORDS: SPAC; IPO; litigation risk; securities litigation; macro economy; consumer sentiment. JEL CLASSIFICATION: G14, G18, K22
p. 11. Health Behaviors of Athlete College Students Compared with their Non-Athlete Peers, and their Associations with Depression, Anxiety, and Stress
Andreas M. Wingert & Jennifer P. Lilgendahl
https://doi.org/10.33697/ajur.2026.164
Abstract: This study compares health behaviors between athlete vs. non-athlete college students and investigates associations of those behaviors with depression, anxiety, and stress. An online questionnaire was administered to 160 students at Haverford College, including 83 athletes and 77 non-athletes. The results show that athletes are more likely to engage in positive health behaviors than non-athletes, including physical activity and muscle-strengthening activities, and eating three meals per day. Regarding negative health behaviors, athletes are more likely to consume alcohol and energy drinks, but less likely to skip breakfast compared to non-athletes. Positive health behaviors are associated with better mental health, including less severe depression and anxiety symptoms. Athletes have less severe symptoms of depression compared to non-athletes, and this difference is largely explained by athletes’ greater engagement in positive health behaviors. Overall, college athletes are more likely than non-athletes to engage in positive health behaviors and have less severe symptoms of depression.KEYWORDS: College Athlete Students; Non-Athlete Students; Positive Health Behaviors; Negative Health Behaviors; Mental Health; Depression; Anxiety; Stress
p. 21 Strategic Swinging Model: Building a Model That Optimizes Swinging Decisions in Baseball
Henry Zhan & Alex Lyfor
https://doi.org/10.33697/ajur.2026.165
ABSTRACT: The most important battle in baseball is the battle between the pitcher and the batter, as hitting the baseball hard and far will drastically change the outcome of a game. In this research, we are attempting to build the strategic swinging model that can help Major League Baseball (MLB) hitters decide whether they should swing at a pitch before it has been thrown. We used random forest classifiers to output a probabilistic prediction of pitch type and pitch location, and estimated how well the hitter would like the pitch based on his past batting data. We evaluated the model by calculating how much better it performed compared to the scenario in which the batter did the opposite. The model outperformed any random swinging strategy. However, the decisions of most above average hitters are better than the model’s decisions. KEYWORDS: Baseball Analytics; Strategic Swinging Model; Random Forest Classifiers; Machine Learning; Pitch Prediction; Batting Decision-Making; Statistical Modeling; Major League Baseball; Sports Data Science; Sabermetrics
p. 31 Resistance of Environmental Fungi to Azole Drugs that are Used to Treat Fungal Infections Including Coccidioidomycosis
Ahlam Alamamy, Benjamin Whipkey, Victoria Saez, & Antje Lauer
https://doi.org/10.33697/ajur.2026.166
ABSTRACT: The increasing use of fungicides in the agricultural hub of the Central Valley of California to fight plant pathogens has led to concerns about fungal pathogens developing resistance against these agents. The soil environment harbors many opportunistic fungal species that can cause disease in plants, animals, and humans. Among them are Coccidioides spp. known to cause Valley fever, an orphan disease, endemic to the arid regions of the Southwestern U.S. The disease is often misdiagnosed, delaying treatment with antifungal agents in the early stages of the disease, which has led to the dissemination of the disease in many patients. In this study we found and tested a large cache of fungal isolates, identified as members of ten fungal families and obtained from the air of Bakersfield, Kern County, CA. A large percentage showed strong resistance against three different azole drugs, namely fluconazole, itraconazole, and voriconazole, that are used to treat fungal infections including aspergillosis and Valley fever in humans and animals. Especially fluconazole, one of the most commonly used azole drugs prescribed for treatment, showed no or only minimal effect against most fungal isolates, in contrast to posaconazole which strongly reduced fungal mycelium growth of most isolates in azole challenge assays on Sabouraud Dextrose medium. These results were statistically significant. Two-way ANOVA were used to compare the effects of four azole drugs on fungal mycelium growth among members of ten fungal families. The ANOVA revealed a significant difference in efficacy when comparing the impact of individual drugs on fungal mycelium growth, p < 0.05. Post-hoc comparisons showed that posaconazole significantly inhibited fungal growth more than all other azoles (p < 0.05). Members of most fungal families tested showed a high measure of resistance to azole drugs and 20-39% showed even an increased growth in the presence of fluconazole. The results of this study are concerning in times where Valley fever incidence is increasing due to increased soil disturbance and climate change in the Central Valley of California. KEYWORDS: Coccidioidomycosis; Valley fever; agriculture; fungal pathogen; azole drug; drug resistance; antifungal susceptibility; airborne fungal spores; fungal resistance mechanisms; fungicide
p. 51 The Different Paths to the Same Journey: Identifying Consumer Segments with Distinctive Environmental Behaviors
Ethan Chiu, Cecilia Yang, & Richard Alden
https://doi.org/10.33697/ajur.2026.167
ABSTRACT: Prior sustainability research indicates that consumers, according to their social values and personal characteristics, might vary in terms of the specific environmental behaviors they tend to engage in. However, limited research to date has explored how consumers can be segmented into distinct clusters based on the extent of their sustainable behavior. To address this gap, the current research utilized a cluster analysis performed on data from the 2020 U.S. Sustainability Consumer Trends Database by the Natural Marketing Institute (NMI) to identify four consumer segments based on their environmental behavior patterns: Sustainability Champions, Sustainability Apprentices, Sustainability Lonewolves, and Sustainability Laggards. Of note, the Lonewolves displayed high levels of individual sustainability, despite their aversion to socially-oriented sustainability. Overall, these clusters reveal discernible attitudinal, behavioral, and demographic differences, and thus have significant practical policy implications for future sustainability campaigns and intervention. KEYWORDS: Sustainability; Cluster Analysis; Consumer Behavior; Environmental Policy; Sustainability Segmentation; Sustainable Living; Sustainable Consumption; Environmental Behavior
p. 65 Numerical Computations of Advanced Water-Cooled Cold Plates for Thermal Management of Microchips with Hotspots
Matthew Selvaggio, Mahdi Farahikia, Ping-Chuan Wang, Eric Rosenfield, & Alexander Gorzula
https://doi.org/10.33697/ajur.2026.168
ABSTRACT: Thermal and hydraulic performances of several cold plate designs suitable for 3-D printing are analyzed using finite element analysis (FEA). Computers lie at the center of today’s modern world of technology. As technology keeps progressing, greater processing power of these chips is increasingly demanded, and this has led to significant challenges, including overheating, uneven microchip temperature distribution, and localized areas of high temperatures known as hotspots, reducing their reliability and lifespan. Conventional cooling techniques, such as air cooling, often fall short of addressing these problems. Liquid-cooling, micro-channel structures known as cold plates, are developed to address such thermal challenges. In this study, five cold plate designs suitable for 3-D printing are analyzed using FEA. The objective of this study is to assess the effects of varying internal geometries and coolant flow rate on thermal and hydraulic performance. The thermal performance was quantified by the thermal resistance and chip temperature uniformity, while the hydraulic performance was quantified by pressure drop and pump power. Results show cold plates with the highest flow rate and more pin-fins near the hotspot than the rest of the cold plate, specifically Model E, outperforms traditional designs in terms of thermal resistance by 3.67%, but at a cost of 120% increase in pump power requirement. KEYWORDS: Cold Plate; Hotspots; Thermal Management of Microelectronics; Water-Cooled Cold Plates; Computer Chips; Liquid Cooling; Additive Manufacturing Cold Plates; Numerical Analysis of Cold Plates
p. 83 Stock Return Prediction Using Television Advertising Data
Haruto Hirata
https://doi.org/10.33697/ajur.2026.169
ABSTRACT: This study proposes the TV Index, a novel alternative data source constructed from 6.6 million television commercial records spanning 965 Tokyo Stock Exchange-listed firms, and demonstrates its utility for systematic equity investment in the Japanese market. By applying Golden Cross strategies ( traditionally applied to price series) to this attention-based signal, this study shows that television advertising intensity contains predictive information about future stock returns that is not captured by conventional risk factors. The best-performing strategy achieves a Sharpe ratio of 1.030 and a cumulative return exceeding the TOPIX benchmark by approximately 65 percentage points over the 2019–2024 sample period. Multiple performance evaluations, including risk-adjusted analysis and sub-period decomposition, consistently confirm the robustness of these findings. These results demonstrate that television advertising data constitute a viable and practically implementable alternative data source, bridging behavioral finance theory with quantitative and econometric implementation. KEYWORDS: Stock Return Prediction; Television Advertising; TV Index; Alternative Data; Investor Attention; Golden Cross Strategy; Japanese Equity Market; Fama–French Model
p. 105 Comparative Analyses of Neurorehabilitation Regulations and Health Equity in the U.S., Switzerland, and China
Linyue Lu
https://doi.org/10.33697/ajur.2026.170
ABSTRACT: As populations age and the burden of neurological conditions rises, equitable access to neurorehabilitation has emerged as a critical yet under-addressed public health priority for aging populations. This comparative study examines how healthcare structures in the United States, Switzerland, and China shape neurorehabilitation equity. This analysis combines semi-structured interviews with seven healthcare experts (neurorehabilitation clinicians, health economists, and scholars) and a systematic review of peer-reviewed literature, policy documents, and demographic data. In the U.S., fragmented insurance models and high out-of-pocket costs disproportionately limit access for low-income and rural populations. Switzerland’s universal coverage masks the inequities driven by uneven financial incentives between acute and long-term care, urban-centric resource allocation, and referral mandates. Despite recent reforms, China’s hybrid healthcare system struggles with hospital-centric resource concentration, varying policy implementation, and rehabilitation workforce gaps, particularly exacerbating urban-rural divides. Across all three, technology innovations like telerehabilitation offer promising potential for alleviating disparities, but are hindered by infrastructure gaps, digital literacy barriers, and cultural traditions. The findings underscore that financial systems, care-delivery hierarchies, and technology adoptions need to be aligned with health equity principles to alleviate neurorehabilitation gaps. The study proposes targeted policy reforms, including adjusting reimbursement schemes, easing referral mandates, and investing in digital infrastructure implementation, to inform international strategies for inclusive, sustainable rehabilitation care systems. KEYWORDS: Neurorehabilitation; Universal Health Coverage; Comparative Health Systems; China; United States; Switzerland; Health Equity; Regulatory Analysis