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UNDERSTANDING OVERHEIGHT VEHICLE BRIDGE STRIKES: A MULTI-STATE STUDY OF CAUSES, DATA CHALLENGES, AND RISK MODELING
No full textWhen critical infrastructure becomes unusable, it creates additional costs for road users and businesses, and infrastructure owners (such as state agencies). Due to their ubiquity and versatility, bridges are a very common and vital piece of roadway infrastructure. When they are damaged, bridges need to be properly inspected, leading to their closure for significant periods of time in many cases. A common cause of this damage, and these closures, are bridge strikes by Overheight Vehicles (OHVs). While significant research has been conducted on the topic of bridge strikes, without special regard for OHV bridge strikes, this issue remains to be significantly prevalent, costing State Departments of Transportation (DOTs) substantial amounts annually for maintenance and upkeep. Furthermore, research into bridge strikes by OHVs has remained limited with many researchers placing more emphasis on run-off-road incidents on or below bridges rather than strikes to the bridge’s superstructure (the part of the bridge overhanging above the roadway). This dissertation aims to remedy this gap in literature by placing emphasis on OHV bridge strikes. To tackle this issue, the research first reviews existing research and documentation on the causes of bridge strikes, the state of practice in incident reporting, current risk modeling practices, bridge inventory data sources, data linking approaches, and prevention and mitigation strategies. The goal is to identify the accepted causes for bridge strikes and their impact on bridge strikes, as well as to evaluate the current state of practice of data management, incident reporting, and bridge strike prevention and mitigation. The research then examines surveys conducted over two decades targeting state agencies across the country. These surveys gauge current attitudes towards OHV bridge strikes, current state of practices in reporting, mitigation, and prevention, levels of communication with the motor carrier industry, comprehension of OHV bridge strike causes, and regulations applicable to OHV permitting and standards. The results show that while more state agencies recognize this issue as significant, there has been little progress in implementing and adopting mitigation and prevention techniques, improving reporting methodologies, updating relevant regulations, and improving communication efforts with the motor carrier industry. Additionally, analysis was conducted into available data repositories used for storing bridge and related crashes was conducted. This was to determine key attributes in these repositories that relate to OHV bridge strikes and consider them for further analysis. The analysis also presented issues and setbacks within the databases used that hinder comprehensive analysis and affect data quality. Crash models placing emphasis on OHV bridge strikes have been rarely investigated. Data on police-reported bridge strikes by OHVs spanning (from 2017 to 2021) and bridge structure inventory, were collected from eleven states (Connecticut, Florida, Idaho, Illinois, Maine, Michigan, Mississippi, North Carolina, Oregon, Washington, and Wisconsin) and grouped by US regions for analysis. Random Parameter Negative Binomial Lindley (RPNB-L) models were developed for each region, with Negative Binomial (NB) and Negative Binomial-Lindley models developed as benchmarks for comparison. RPNB-L was chosen to overcome the data issues of excess zeros and a long tail, as well as to overcome heterogeneity. A Grouped RPNB-L model was also developed to determine parameter impact variations on strike risk by state. The model results revealed important findings: 1) bridges with lower underclearance are more prone to strikes; 2) higher average annual daily traffic (AADT) increases the likelihood of bridges being struck; 3) the age of a bridge, a proxy variable of changing regulations and vehicle sizes, was determined to be significant; 4) key bridge dimension characteristics play a significant role in strike risk; 5) bridges crossing urban collector and local roads are more likely to be struck; and 6) bridges crossing a large number of lanes being more likely to be struck. The appropriate developed model was used as screening tools to determine bridge strike hotspots within Wisconsin. This model was compared to baseline machine learning methods to demonstrate its ability to pinpoint high strike-risk locations more effectively. The findings revealed that urban hubs and certain routes were more prone to strikes and efforts for countermeasure application should be targeted at these areas. A brief review of emerging cost-effective technologies is presented to provide potential options for countermeasure implementation at the identified regions. Safety implications and recommendations along with future research directions are provided at the end of the dissertation.2026-05-1
A Case Study in K-12 Education for Sustainable Development
No full textFull Text DissertationThe K-12 sector needs curriculum that will better ready students for the sustainability challenges
of the future. This research is a mixed methods case study that uses Kotter’s theory of change to
prioritize Education for Sustainable Development (ESD) in the curriculum and co-curriculum of
the Nightingale-Bamford School and explore the impact the changes have on both faculty and
students. The Nightingale-Bamford school is K-12, private all-girls school located on the Upper
East side of New York City. The Professional Action Competence (PAC) of faculty was
measured with a survey both before and after the ESD program was developed. Faculty were
interviewed after the change process to further investigate its impact on PAC. Students were
also interviewed after the change process to explore whether the changes influenced their
intentions to act on the Sustainable Development Goals (SDGs). The development and
implementation of the program increased the willingness of faculty to engage in ESD, had
mitigating effects on self-efficacy, and had a small impact on the faculty’s knowledge of
pedagogical approaches. The ESD program increased the intention of students to act on the
SDGs. The results imply that Kotter’s theory of change can be used to impact the PAC of
faculty to engage in ESD and to positively impact the intention of students to act on the SDGs.
More studies are needed to investigate long term impacts of the change process and how the
change process impacts faculty and students in other K-12 settings
Supplementary material for “Justifying Biodiversity Data Access Restrictions: A Global Comparison of Data Policies.”
No full textSupplementary material for Kaehrle, Martin and Kristin Eschenfelder. “Justifying Biodiversity Data Access Restrictions: A Global Comparison of Data Policies.” Forthcoming in Proceedings of the Association for Information Science and Technology 62 (2025). Contents include a current copy of our codebook (250607-Codebook.pdf), a list of sampled biodiversity databases (250607b-ASIST-Sample.xlsx), and more detailed information about our sampling procedures (250607-Sampling-Information.pdf)
ALTERING LEAF PH TO SUPPRESS DOLLAR SPOT IN AMENITY TURFGRASS
No full textDue to its high adaptability to novel stressors and variable environmental conditions, managing Clarireedia jacksonii, the causal agent of dollar spot disease, continues to pose a major challenge in turfgrass systems. Conventional control methods are increasingly constrained by limited chemical options, rising concerns over pesticide resistance, and inconsistent efficacy of biological products. As a result, there is a growing demand for non-conventional approaches to disease management. This field-based study evaluated the potential of foliar-applied alkaline substances to suppress dollar spot on a mixed stand of creeping bentgrass (Agrostis stolonifera L.) and annual bluegrass (Poa annua L.) over two consecutive growing seasons (2023–2024). Treatments varied by chemical identity, rate, application frequency, spray volume, and their
resulting foliar alkalinity, quantified as kilograms of CaCO₃-equivalent per hectare. Results demonstrated that disease suppression was strongly associated with surpassing a threshold level of foliar alkalinity, rather than the specific compound or nominal application rate. Across both years, treatments delivering >30 kg per ha CaCO₃-equivalent consistently reduced disease severity by over 85%, with weekly applications of potassium bicarbonate achieving suppression levels of up to 98%. Elevated foliar pH (>8.9) was a strong predictor of reduced disease development. While spray volume had minimal impact on outcomes, frequent reapplication proved critical to maintaining alkaline conditions on the phylloplane. However, high-alkalinity treatments also introduced phytotoxic effects, particularly under short reapplication intervals, resulting in reduced turf quality. This highlights a key trade-off between effective disease suppression and aesthetic turf performance. Although additional multi-year research and microbiological diagnostics are necessary to evaluate long-term sustainability, the present study offers strong field-based evidence supporting foliar alkalinity modulation as a viable non-conventional approach to dollar spot management. Current findings emphasize the importance of aligning product selection with site- specific goals, particularly in high-stakes turf systems. Future research into microbial interactions and physiological responses may further optimize these treatment strategies
Promoting students’ continuation writing performance through integrating task-based language teaching in Chinese high school EFL classes
No full textA seminar paper presented to the graduate faculty at the University of Wisconsin-Platteville.
In partial fulfillment of the requirement for the degree of Master of science in education - English educationTask-Based Language Teaching (TBLT) is widely applied in English language teaching practices, especially when teaching speaking and writing skills. TBLT can significantly enhance students' language proficiency and learning results. This paper mainly explores the approaches to apply TBLT in Chinese high school English EFL classrooms, particularly focusing on its effect on promoting students' continuation writing performance. Continuation writing takes a rather high score proportion in the writing section of the Chinese National College Entrance Examination (Gaokao), which requires students to read a passage of several paragraphs and then write two following paragraphs that are logically connected to the former content. By synthesizing current research results and literature viewpoints, this study aims to explore the proper role of TBLT in enhancing students' writing fluency, creativity level, and critical thinking capability in continuation writing process. The findings of the study suggest that TBLT activities based on effective analysis of students can help promote students’ continuation writing skills, enabling students to write the continuation essays with better coherence and cohesion. Finally, the study offers practical TBLT applying strategies for Chinese high school English teachers to teach continuation writing in EFL classrooms
A Genome-Wide Association Study Assessing the Genetic Underpinnings for Response to Polyamine Cadaverine in Brachypodium distachyon
No full textPolyamines (PAs) are small organic molecules characterized as carbon chains with two or more amine groups, derived from the decarboxylation of amino acids. Plants possessing the requisite decarboxylase genes produce their own PAs and use them for a variety of purposes including the regulation of plant growth and development, tissue differentiation, and gene expression regulation. PAs are also stress metabolites in plants, accumulating in response to biotic and abiotic stimuli and contributing to stress mitigation. Microorganisms within the rhizo- phyllo- and endosphere take up amino acids, decarboxylate them into PAs, and often export them back out into the environment, where they can influence plant development. In plants, exogenous PAs have been demonstrated to modulate root system architecture, inhibiting primary root growth, promoting branching and altering growth behaviors, thereby favoring soil exploration to facilitate nutrients uptake.
This study investigates the genetic basis of primary root growth responses to exogenous cadaverine in Brachypodium distachyon, under two light intensities, utilizing light intensity as an independent variable. Using a genome wide association study (GWAS) approach, we analyzed root growth data from a diverse panel of B. distachyon accessions exposed to the PA cadaverine under high and low light intensities. SNPs will identify gene regions associated with high or low light adaptations related to polyamine utilization pathways, and in doing so will aid in the characterization of cadaverine’s method of action. Root length measurements were normalized and subjected to GWAS using a mixed linear model to identify loci associated with cadaverine response. Significantly associated single nucleotide polymorphisms (SNPs) were mapped near and/or within genes potentially involved in cadaverine signaling and homeostasis under high, low and/or both light conditions. Our findings reveal that light modulates cadaverine’s impact on root growth and highlights candidate genes for future functional characterization.
Persistent radiative states in the Arctic: Drivers, trends, and model representation
No full textThe Arctic climate is rapidly changing. The ability for the high latitudes to effectively emit longwave radiation to space is vital for shedding excess energy received in the tropics, thus regulating the global energy balance. Several Arctic field campaigns have found the presence of two preferred radiative states, each of which heavily modulate the surface energy balance, affecting whether processes such as the melting or freezing of ice and snow can occur. These states are characterized by persistent optically thick clouds (‘opaque’) rapidly transitioning to persistent optically thin clouds or cloud-free conditions (‘transmissive’), and vice versa. Using satellite observations, models, and in-situ measurements, we investigate the spatial and temporal occurrence of these states, their underlying mechanisms, models’ ability to represent them, and their long-term trends. Our findings demonstrate that CloudSat and CALIPSO can effectively detect bimodal longwave flux distributions across the polar regions. We show that these two radiative states are ubiquitous throughout the Arctic and Antarctic and are connected to both liquid-containing and ice-only clouds. The frequency of these states varies by region and season.
Models, including reanalyses, struggle to represent the correct frequency of the two states. However, cloud-resolving, polar-specific products, such as the Arctic System Reanalysis,generally perform better than coarser global models. Due to the non-Gaussian nature of polar longwave flux distributions, some traditional model evaluation methods, especially those relying on monthly means, likely miss errors in the representation of these states entirely. Thus, we urge model evaluators to consider the existence of distinct states in their assessments and, more generally, to adopt evaluation methods that can assess non-Gaussian distributions.
Long-term observations from the North Slope of Alaska reveal that pronounced changes in downwelling longwave radiation are linked to changing frequencies of these states,specifically, a disappearance of transmissive conditions. These changes are linked to both local and non-local moisture processes, which contribute to the formation of optically thick clouds. This shift highlights a strong positive feedback mechanism, where decreasing the transmissive state amplifies the warming and moistening of the Arctic atmosphere, further promoting the opaque state. Any region prone to future sea ice loss may experience a similar feedback, and thus, a disappearance of the transmissive state
Machine Learning for the Isolation of Geochemical Cycles in the Midwestern Cambrian-Ordovician Aquifer System
No full textGroundwater is a critical resource supporting millions of domestic and municipal users across the country. As pressures on this resource intensify, concerns about groundwater quality are only increasing. Large-scale monitoring efforts generate extensive datasets that capture spatial and temporal trends in groundwater chemistry, offering an opportunity to better understand and manage water quality challenges. Machine learning techniques, particularly decision tree models like random forests (RF), are well-suited to detect patterns in complex, high-dimensional environmental data. When paired with interpretability tools such as SHapley Additive exPlanations (SHAP), these models can insights into underlying geochemical processes. This approach enables the identification of potential risk zones and supports informed decision-making without the need for extensive, costly sampling. Our analysis demonstrates that machine learning models can accurately predict the presence of certain naturally occurring contaminants and highlight geochemical conditions—such as redox dynamics and groundwater mixing—that may influence their mobility. The integration of machine learning and geochemical interpretation holds promise for improving groundwater protection efforts, particularly for communities reliant on private wells and for regions where monitoring is limited. More broadly, this framework can be applied to aquifer systems worldwide, advancing both scientific understanding and management of groundwater quality
CONFIRMATION: HOW THE JUDICIAL NOMINATIONS PROCESS PERPETUATES GENDER BIAS
No full textExisting research tells us that women nominees are more likely to be questioned about their capabilities, impartiality, and to be subjected to interruptions, negative tone, and differentiation language. To what extent do gendered dynamics emerge in the context of judicial confirmation hearings? I employ a content analysis of the Senate Judiciary Committee’s confirmation hearings for Justices Sandra Day O’Connor and Ruth Bader Ginsburg—the first two women nominees to the Supreme Court—and Antonin Scalia and Steven Breyer—their contemporary counterparts. Throughout the hearings, gender shaped the ways in which nominees were questioned. This came through in two major ways. First, the gender (and implicitly concerns about the resulting biases) of Justices O’Connor and Ginsburg were brought up frequently, both indirectly and directly. Second, Justices O’Connor and Ginsburg were more likely to be asked about identity-based issues, like gender and race, and in different contexts than Justices Scalia and Breyer. Supreme Court judicial nominations have become of national significance, with confirmation hearings often watched closely in mainstream media. Unequal or biased treatment of women during confirmation hearings can perpetuate stereotypes and discrimination, and may convey a message to the public about the capabilities of the justices and the legitimacy of the Court
Dairy Farms and Disasters: Preparedness and Emergency Management
No full textAlthough the number of dairy farms in the United States is shrinking, the risk of tragic disasters is increasing due, in part, to changing climate conditions. The possibility of needing a plan for emergency management on dairy farms is a matter of when these plans will be needed – not if. Because the researcher’s roots run deep in agriculture - having grown up in the heart of America’s Dairyland and working on farms with different sizes and varying management practices - she has learned that being proactive is crucial to effective and efficient herd management. In the days of increasing technology use, more cows per farm, larger amounts of laborers lacking a farm background, and higher disaster risk, this study provides a look into disaster preparedness. The research covers the importance of preparedness and outlines a suggested emergency management plan with supporting case study interviews