Blockages in sewerage systems may lead to backups and can be costly to clear. To better understand the composition of non-degraded solid waste in Eau Claire’s sewage, we conducted three audits of the solid waste captured by the bar screens at the Eau Claire Municipal Wastewater Treatment Plant (WWTP). Wearing personal protective equipment, we collected solids that had been captured over a two-hour period and sorted the waste into six categories: 1-4) disposable wipes in various stages of decay (intact, mostly intact, mostly shredded, and shreds entangled with hair), 5) feminine hygiene products, and 6) miscellaneous items (e.g., plastic, latex, leaves, and food). Waste groupings were measured by volume. Our findings show consistent trends across the three sampling dates: disposable wipes accounted for 81.3% (±5.6%), feminine hygiene products 11.3% (±1.6%), and miscellaneous waste 7.3% (±4.2%). Our study demonstrates that disposable wipes account for most non-degraded waste that reaches the WWTP. Beyond the potential for causing blockages, non-degraded waste must be collected and transported to the municipal landfill, increasing the costs for taxpayers. Our next step is to conduct outreach efforts to raise public awareness of the need for proper disposal of non-woven wipes and feminine hygiene products.
Plastic pollutants are a significant environmental concern. Biodegradable plastics are a large area of research because if plastics are accidentally released into the environment, biodegradable plastics will break down into harmless byproducts. A blister pack is a type of packaging that consists of plastic pockets that hold individual pills. Current blister packs on the market are not biodegradable and contribute to environmental harm. The goal for this research project is to find an eco-friendly material to replace current blister packs that can also handle chemical reagents (such as medical reagents). Initial testing focused on developing a film from cassava starch that was adapted from the literature. The standard ASTM D543 was used to evaluate the resistance of the material to chemical reagents. The samples were placed under strain using a 3D printed strain jig, the chemical reagent was applied, and the samples were held at fixed temperature for varied amounts of time. After chemical exposure, the samples were tested to determine changes in mechanical properties. These results will be used to determine if cassava starch can replace traditional plastic blister packs to open the door to many environmentally friendly swaps in the medical field.
Caviar refers to processed salted roe obtained from large fish, and it often requires the sacrifice of a pregnant female. With the increasing global human population, the demand for caviar is rapidly growing, threatening wildlife fish populations everywhere. While many improved versions of caviar analogs have been created, they are unable to mimic natural caviar color, texture, structure, popping (while chewing), and taste. The goal of this project is to develop a scalable method for developing caviar analogs using engineering techniques. For this study, we investigated the use of sodium alginate and calcium chloride (CaCl₂) in the production of engineered caviar analogs that replicate the texture, appearance, and sensory characteristics of natural caviar. Alginate solutions of different concentrations (1-5%) and needles of different gauges were calibrated to achieve structural integrity and mimicry of caviar analog size. Furthermore, CaCl₂ was frozen in liquid nitrogen before soaking in a bath of alginate to form caviar analogs with an outer crusty shell and a softer center, to re-create the popping-effect. Future work will include incorporating our findings within a microfluidic device for a scalable way of producing engineered caviar analogs, furthering the broader pursuit of sustainable food design.
Grazing steers partner with their rumen microbiomes to efficiently convert plant-derived carbohydrates into meat. Considering the socioeconomic importance of the beef industry, it is critical to develop strategies that maintain quality while lessening negative environmental impacts. Diet supplementation and hormonal implants have been shown to variably impact methane emissions and animal performance. The response of the rumen microbiome to such treatments remains unknown. Here, we will analyze 16S rRNA gene amplicon sequencing of the rumen microbiome from grazing steers across four treatment groups: diet supplemented, hormonal implanted, combined diet and implant, and no intervention. The diet, implant, and combined treatment showed no significant impact on methane emission or N excretion over the 90-day grazing trial. Given this lack of difference, we hypothesize the rumen microbial communities will not be different across treatments. However, we hypothesize the 90 days of grazing will significantly alter the rumen microbiome. Results from this study will provide insight into rumen microbiome dynamics during the life cycle of a grazing steer, further informing management strategies.
Caviar refers to processed salted roe obtained from large fish, and it often requires the sacrifice of a pregnant female. With the increasing global human population, the demand for caviar is rapidly growing, threatening wildlife fish populations everywhere. While many improved versions of caviar analogs have been created, they are unable to mimic natural caviar color, texture, structure, popping (while chewing), and taste. The goal of this project is to develop a scalable method for developing caviar analogs using engineering techniques. For this study, we investigated the use of sodium alginate and calcium chloride (CaCl₂) in the production of engineered caviar analogs that replicate the texture, appearance, and sensory characteristics of natural caviar. Alginate solutions of different concentrations (1-5%) and needles of different gauges were calibrated to achieve structural integrity and mimicry of caviar analog size. Furthermore, CaCl₂ was frozen in liquid nitrogen before soaking in a bath of alginate to form caviar analogs with an outer crusty shell and a softer center, to re-create the popping-effect. Future work will include incorporating our findings within a microfluidic device for a scalable way of producing engineered caviar analogs, furthering the broader pursuit of sustainable food design.
Many technologically important materials are used in amorphous form, and a fundamental understanding of their structure is crucial for optimization of their performance. Due to the disordered nature of amorphous materials, experimental structural characterization is challenging. Computational techniques such as ab initio molecular dynamics simulations have been widely used to reveal atomistic insights into the structural characteristics of amorphous materials. The simulated melt-quench process is typically used to generate the amorphous structure. Such generated structures contain varying amounts of defects due to differences in system sizes and simulation history. Consequently, reported structures for amorphous materials are subject to substantial variations and inconsistencies. Using silicon dioxide (SiO2) as a model system, the effects of simulation history on the structural characteristics of amorphous SiO2 have been studied. By manipulating simulation parameters such as time, temperature, and thermodynamic ensemble, this research examines which conditions eliminate the most defects in an amorphous structure through a statistical analysis. The optimal parameters for generating high-quality, defect-free amorphous SiO2 structures were proposed. The same protocol is expected to be applicable to other materials, thus advancing the study of amorphous materials by providing a reliable computational protocol for producing amorphous structures with minimal defects.
Residents on the shoreline of Lake Michigan in southwest Wisconsin are subject to air quality issues from high ozone concentrations near ground level. Meteorological data was collected for the August 2023 AGES+ campaign concerning ozone concentration, temperature, wind speed, and wind direction. Measurements were conducted using a DJI M300, with two IMETs and POM sensors attached, with flights occurring over Lake Michigan near the Chiwaukee Prairie area. Results were then correlated with the Wisconsin DNR’s ground station in Chiwaukee Prairie, which found moderate correlation of data between measurements conducted above water and on land.
The development of sustainable routes to organic building blocks is a critical endeavor for reducing the environmental impact of traditional organic chemical synthesis. Biocatalysts offer an alternative method to facilitate sustainable synthesis, as they perform highly selective reactions at an increased rate. Ring-cleaving dioxygenases (RCDs) are a class of enzymes responsible for selectively breaking open the ring of benzene derivatives to provide a carbon source for microorganisms in bioremediation. To access the biocatalysts, many microbiology methods were utilized. The E. coli cells were transformed to contain the desired gene, the cells were then grown until there optical density was at the ideal value for cell viability (0.6-0.8) and induced with IPTG to facilitate protein expression. After heterologous expression, the enzyme was purified to homogeneity by immobilized metal affinity chromatography. We continue to analyze RCD types (type I, II, and III) through endpoint screening and product isolation using various substituted catechols. We envision that this approach to muconic acid synthesis will contribute to ongoing efforts to streamline synthesis of these important organic building blocks and reduce the usage of fossil fuels for organic synthesis.
Variable Rate Agriculture (VRA) is a data-driven approach aimed at reducing the environmental impact of commercial farming. It leverages machine learning models (MLMs) to enhance crop yield predictions more rapidly than traditional soil analyses. However, MLMs require large datasets, and agricultural data is often limited. Cross-validation (CV) techniques help improve model generalization by testing model performance on reserved subsets of data, even with limited data. This study used a three-year dataset on hybrid wheat, covering pre-planting, crop growth, and yield mass from Minnesota. Four machine learning models—linear regression, random forest, XGBoost, and feed-forward neural networks (FFNN)—were developed to link pre-growing conditions with yield outcomes. Two CV methods, Random CV and Spatial Grid CV, were applied to compare model performance, assessing overfitting using the coefficient of determination (R²) and Root Mean Squared Error (RMSE). Feature selection was performed to pinpoint critical spectral indices impacting model output. Findings indicated that Random CV generally outperformed Spatial Grid CV across both full and reduced feature sets. While linear regression suffered from feature selection limitations, FFNN showed occasional improvement. Overall, Random CV proved more effective, especially with a diverse dataset, enhancing model reliability in VRA applications.
Transportation is a fundamental human activity, and cycling offers significant potential to improve community health, reduce carbon emissions, and lower transportation costs both for individuals and the community at large. To foster widespread adoption, sufficient cycling infrastructure is essential, as safety issues present a major barrier to ridership. Understanding cyclists' perceptions of safety, location, and the built environment is crucial for enhancing safety and increasing participation. This poster presents findings from a study on spatial perceptions of cycling safety in Marburg, Germany. Through a web-based survey, respondents identified two major clusters of unsafe areas. In general, unsafe locations were identified as such due to inadequate infrastructure and potential conflicts with motor vehicles. The study reveals that while women and men share similar levels of confidence in cycling, safety concerns have a greater influence on where women choose to ride. The insights from this study are valuable for identifying specific areas in Marburg that require improvement, but they also offer guidance for urban planners seeking to design safer and more equitable transportation systems.
Within college organizations, very few encompass certifications that promote environmental health, students’ physical well-being, and the community. With the Eau Claire community being 75k+ members, a center that has good quality access to health care is vital to seniors, children and young adults. The UWEC Sonnentag Center has Gold LEED certification, which states the building has outstanding sustainability energy efficiency and environmental design. However, this is not enough to tackle the environmental issues in Eau Claire. Within our research to achieve the WELL certification, we collected data on the clarity of the water (turbidity), total and free chlorine, the pH levels of the water; levels of volatile inorganic compounds (carbon dioxide, carbon monoxide, sulfur dioxide, nitrogen dioxide), ozone levels, and humidity in the air. Interestingly, what our team found was that the turbidity, as well as, free and total chlorine levels were low, and the pH was slightly higher but within range. In addition, the air quality was above and beyond good standards for the WELL Certification, due to the ventilation systems in and around the building. However, nightly cleaning procedures caused a rise in VOC’s and low humidity. Overall, the measures of WELL Certification build upon the LEED certification principles, allowing for the best achievable environmental impact.
This project aims to map buried river channels beneath the desert sands to identify potential agricultural sites, particularly focusing on areas within irrigatable distance of the Nile River in Sudan. With fertile land along the Nile becoming increasingly limited, there is a growing need to explore new areas that can support farming. Sudan, a country in northeastern Africa, was once lush with river systems and vegetation but is now mostly covered by the Sahara Desert. Beneath the sands lie palaeochannels (ancient riverbeds and drainage systems) that contain fertile sediments and are highly suitable for agriculture. Agriculture has expanded into the desert over the past decade, revealing the potential of buried channels, but more fertile land is needed to continue this growth. In this study, we utilized a radar remote sensing sensor called PALSAR (Phased Array L-band Synthetic Aperture Radar) to image subsurface hydrologic and geomorphic features. This sensor is capable of penetrating deeper into the ground from space, detecting buried palaeochannels and revealing areas that may harbour soil. Our reconnaissance mapping has uncovered a vast network of palaeochannels within a 40-mile radius of the Nile River, offering potential locations for agricultural expansion.
Libya lacks a permanent natural body of water, causing it to rely on fossil water from underground aquifers that originate more than tens of thousands of years ago. The ancient aquifers are a relic from a time when the Sahara was green and home to rivers and lakes. Since this water is not naturally replenished, there is an increasing need to explore more sources of fossil water under the Sahara's sands. Remote sensing data from the Phased Array L-band Synthetic Aperture Radar (PALSAR) sensor, onboard the Advanced Land Observing Satellite (ALOS), has been shown to penetrate and reveal subsurface features up to several meters deep. This is especially useful in regions such as Libya, where dry, shallow sand cover allows effective PALSAR’s L-Band Penetration. PALSAR, along with optical remote sensing and topographic data within the Google Earth Engine platform, provides new capabilities to conduct multi-level spatial analysis. Preliminary results reveal a previously unidentified and/ under-appreciated network of ancient drainages, streams, and small-scale deltas or alluvial fans, many of which are connected to previously identified megalakes. These findings will provide valuable insight into the region's ancient hydrological system and its potential for future water resources.
Microbial species that fix atmospheric nitrogen can benefit plants by colonizing the area around the roots or internal plant tissues and increasing nutrient availability. This process can reduce the need for synthetic fertilizers, therefore maintaining healthy soil and promoting environmental sustainability. Three endophytic bacterial species (Herbaspirillum, Gluconacetobacter, Methylobacterium) are gaining attention as potentially effective plant growth promoters when applied to the leaves directly, whereas an associative species Azospirillum is conventionally applied to soil. This field study investigated the impact of the foliar application of these four bacterial species independently and in combination, on the growth, physiological performance, and yield of corn and soybean. Overall, corn plants treated with the endophytic bacteria had increased leaf nitrogen content, chlorophyll, and greater reproductive yield compared to the untreated plants. However, the associative Azospirillum showed no growth benefits. In soybean, chlorophyll content was enhanced when all microbe species were combined in mixture, while seed mass was increased under only some of the endophytic microbes compared to the control. These results suggest that foliar treatments could be effective when using bacterial species classified as endophytic for boosting crop productivity, offering a more environmentally friendly way to supply nitrogen to plants than conventional synthetic fertilizers.
Water quality plays a crucial role in achieving WELL certification, ensuring a safe and healthy indoor environment. This study assessed the water quality at the newly constructed Sonnentag Center at the University of Wisconsin–Eau Claire, focusing on key parameters such as turbidity, chlorine levels, and microbial contamination. Using the Hanna Instruments HI93414 Turbidity and Chlorine Meter, we observed an unexpected absence of chlorine (0 µg/mL) in all tested samples. A control test with bleached water confirmed the instrument’s accuracy, suggesting a genuine lack of chlorine in the water supply. Additionally, coliform and E. coli tests verified the absence of bacterial contamination, indicating that the water met microbial safety standards. The findings highlight both the strengths and challenges of water quality monitoring in WELL certification. While microbial safety was confirmed, the absence of chlorine raises concerns about potential regulatory non-compliance and long-term water safety. This study underscores the importance of continuous monitoring and evaluating disinfection protocols to maintain WELL standards. Future work will focus on investigating water treatment processes and identifying solutions to ensure consistent compliance with health and safety regulations.
Food insecurity is a global phenomenon that affects a wide range of people and is a significant concern for Americans. Students in higher education also grapple with food insecurity and can struggle to access nutritious and regular meals due to tuition, housing, and other competing costs. The purpose of the programs described in this project is to build food equity and increase students’ well-being. In the first “food rescue” program, leftover food is packaged from on-campus cafeterias and donated to the university food pantry where students have access to the food for free. The second program, “Free Food Alert” utilizes a mobile application that sends out email and push notifications to students who opt into receiving these updates. Notifications are sent when leftover catered food on campus is available for students to have. The implementation of these programs has already helped numerous students who are facing food insecurity by giving them access to free food in addition to reducing food waste from campus functions. It is important that college campuses continue to recognize the impact of food insecurity to their students and prioritize food access through programs like these.
This research explores how various factors, particularly parenthood and employment, influence the cognitive dimensions of gendered well-being in Brazil, the Netherlands, and the United States. Using data from the World Values Survey Wave 7, we find that the impact of parenthood on women’s well-being varies across countries. For husbands, occupational status has a greater effect on happiness than fatherhood, while wives’ employment appears to have little to no significant relationship with their well-being. We discuss the implications of these findings and offer policy recommendations to address the motherhood dilemma, advance gender equality, and support female workforce participation.
This project aims to assess groundwater quality in rural Eau Claire County by collecting and testing water samples from 244 private wells between June 2023 and December 2024. Samples were analyzed for contaminants such as nitrate, coliform, E. coli, hardness, and metals like arsenic, lead, copper, and manganese at the Eau Claire Public Health Laboratory. This data complements existing information in the Eau Claire City-County Health Department database. Well construction logs were also reviewed to understand well depth and geology, helping identify spatial patterns related to contamination. The project responds to the 2018 Eau Claire County Groundwater Advisory Committee’s recommendations in the “State of the Groundwater Report,” which called for systematic well testing, identifying high-risk areas, and reviewing groundwater protection regulations. With around 9,000 private wells serving 25% of the population, most are infrequently tested due to financial barriers and lack of accessible educational materials. This initiative, funded through an American Rescue Plan Act grant, aims to address these challenges and support environmental public health in rural communities.
Blockages in sewerage systems may lead to backups and can be costly to clear. To better understand the composition of non-degraded solid waste in Eau Claire’s sewage, we conducted three audits of the solid waste captured by the bar screens at the Eau Claire Municipal Wastewater Treatment Plant (WWTP). Wearing personal protective equipment, we collected solids that had been captured over a two-hour period and sorted the waste into six categories: 1-4) disposable wipes in various stages of decay (intact, mostly intact, mostly shredded, and shreds entangled with hair), 5) feminine hygiene products, and 6) miscellaneous items (e.g., plastic, latex, leaves, and food). Waste groupings were measured by volume. Our findings show consistent trends across the three sampling dates: disposable wipes accounted for 81.3% (±5.6%), feminine hygiene products 11.3% (±1.6%), and miscellaneous waste 7.3% (±4.2%). Our study demonstrates that disposable wipes account for most non-degraded waste that reaches the WWTP. Beyond the potential for causing blockages, non-degraded waste must be collected and transported to the municipal landfill, increasing the costs for taxpayers. Our next step is to conduct outreach efforts to raise public awareness of the need for proper disposal of non-woven wipes and feminine hygiene products.
Given the rapid expansion of human presence across the globe, coping with humans is an important aspect of life in the modern world for most animals. The California ground squirrel (Otospermophilus beecheyi) is a facultatively social rodent that has a long evolutionary history of residing near humans. While it is well understood that humans disrupt their foraging and social behavior, the role of humans and dogs on the stress physiology of these animals is unclear. As part of a long-term study, we live-trapped and released California ground squirrels and measured “stress” levels from fecal glucocorticoid metabolites (FGMs) using a fully validated enzyme-linked immunoassay (ELISA). Drawing from 12 years of data, we show that FGM levels vary across years but are elevated in areas with high exposure to humans and dogs. These patterns tracked variation in human activity across a gradient from high to low disturbance across our study site (from the south to the north). FGMs were repeatable for individual squirrels within and between years. Our findings offer insights into the relationships between anthropogenic disturbance and stress physiology over small temporal and spatial scales.
This study investigates how financial security shapes the cognitive dimensions of well-being in China, India, and the United States. Utilizing data from the World Values Survey Wave 7, we find that different saving behaviors influence well-being—measured by happiness and life satisfaction—differently across countries. We examine the implications of these findings and propose policy measures to enhance financial literacy.
Anthropogenic changes are expected to influence behavior, stress physiology, and ultimately, lifetime fitness of animals. For social animals, external stressors imposed by human activities may interact with the social environment to either exacerbate or buffer stressors. In the context of human-induced rapid environmental change, long-term data on individually recognized social mammals has the potential to offer novel insights into the extent to which organisms can cope with social and ecological stressors. In this research, we established a new project focused on the behavioral ecology of North American beavers (Castor canadensis), a native ecosystem engineer, through monitoring using camera traps. We surveyed various public lands and identified several active family groups of beavers in West-Central Wisconsin. Our camera trap data indicate that the behavioral patterns and their interactions with other local fauna vary temporally within days and across seasons. Future research will focus on their social behaviors, including their monogamous lifestyles, dominance structures, communication systems, and movement ecology. The plethora of wildlife we monitored on our camera traps illustrates how beavers play a key role in shaping diverse and healthy wetland ecosystems. This research therefore has important implications for the management of wetlands and conservation of beaver populations in the region.
How well does the general public understand the current recycling process in the United States? Does Eau Claire County recycle a significant amount of waste? Where does it go? This study hopes to answer these questions and more by surveying Eau Claire County residents on their recycling habits, as well as interviewing employees at the top recycling companies operating in Eau Claire county to determine the level of public disconnect from the material reality of recycling and waste management.Many people assume the recycling system functions well and serves to reintroduce waste back into production of new consumer products and packaging, but in reality only a small amount of material is recovered. The rest takes up space in landfills or becomes incinerated to produce electrical energy. Recycling materials comes with several costs: Time, money, and energy. Often, the costs of recycling outweigh the benefits, and without the profit incentive there are no companies willing to recycle materials. Previously, the United States shipped most of its recyclable waste overseas to China, but following a 2017 Chinese decision to halt waste imports, American companies were forced to find alternate methods for waste disposal and material recovery. This research focuses specifically on waste management and material recovery in Eau Claire County, but it has broader implications for the rest of the United States.
The design of skateparks plays an important role in promoting positive mental health benefits within communities. Public Spaces like skateparks are created to be used for physical recreation and provides a place for social interaction and community. Skateparks have been shown to reduce stress and yield as an outlet for self-expression. Because of this, skateparks not only create a place for community and physical activity, but also can be a space for individuals to feel a sense of individuality and belonging. This paper explores the connection between skatepark designs and mental health and how that plays a significant role in city space planning with the intent of harboring community cohesion and individual wellbeing.
As the use of car dashboard cameras (dashcams) has increased, the availability of dashcam imagery has also increased. In recent years, dashcam imagery has been predominantly used in conjunction with computer vision techniques for autonomous vehicle systems. However, this research explores an alternative application of these technologies in the domain of public safety and security. Specifically, we apply object detection to dashcam imagery to address the challenge of identifying vehicles associated with active Amber Alerts. With the goal of aiding law enforcement in locating abducted children more efficiently, we employ the YOLO (You Only Look Once) object detection model, a state-of-the-art deep learning framework known for its real-time performance and accuracy. Our methodology involves training and fine-tuning the YOLO model on a custom dataset of dashcam footage, incorporating diverse environmental conditions such as varying lighting, weather, and traffic scenarios. Experimental results demonstrate that the model achieves high precision and recall rates in detecting target vehicles, validating its effectiveness for real-world deployment. This research highlights the potential of leveraging deep learning and computer vision techniques to address critical public safety challenges, offering a novel application of these technologies beyond their traditional use in autonomous driving. Our findings contribute to the growing body of work in computer science that seeks to harness AI for societal benefit.
Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer, accounting for over 90% of cases, and is characterized by aggressive growth, early metastasis, and resistance to therapy. A comprehensive understanding of the molecular mechanisms driving PDAC is essential for improving diagnosis, prognosis, and treatment. In this study, a multiomics approach was applied by analyzing both DNA methylation and RNA-sequencing datasets obtained from The Cancer Genome Atlas Pancreatic Adenocarcinoma project.The methylation dataset included significantly more tumor samples than normal samples, and a similar imbalance was observed in the RNA-seq dataset. This disparity posed a challenge for direct feature selection, as it could lead to a model biased toward tumor-associated features. To address this issue, six data imbalance correction techniques were evaluated and compared: Random Oversampling, Synthetic Minority Over-sampling Technique (SMOTE), and Adaptive Synthetic (ADASYN) for oversampling, along with Random Undersampling, Cluster Centroids, and AllKNN for undersampling. Identifying the most effective imbalance correction method is essential for improving feature selection accuracy and facilitating the discovery of novel genes associated with pancreatic ductal adenocarcinoma (PDAC). A deeper understanding of these oncogenes could contribute to the development of non-invasive diagnostic tests and personalized treatment strategies for PDAC.
As climate change continues to escalate, it is evident that some countries are making substantial efforts, while others fall behind. Through participation in a Faculty-Led Intercultural Immersion program, we observed that Costa Rica has emerged as is a pioneer in developing a green economy, prioritizing sustainability, and implementing environmental protections. This project investigates Costa Rica’s existing policies and future initiatives aimed at improving planetary health, with the goal of identifying strategies that may inspire global efforts. Additionally, we seek to raise awareness of the urgent effects of climate change and emphasize the importance of international collaboration, particularly the role of the United States, in promoting a healthier and more sustainable planet.
Cattle that eat the same feed and come from the same environment can emit methane (CH4), a potent greenhouse gas, at vastly different levels. An estimated 32% of anthropogenic CH4 can be traced to ‘enteric fermentation’ in livestock production. During enteric fermentation, specialized microorganisms will digest complex plant fiber to create compounds like acetate and hydrogen (H2). Some of these organisms, called methanogens, will consume and use these products to produce CH4. Emerging data suggests natural inter-animal variation in CH4 emissions could derive from host genetics or differences in rumen microbial digestion. Here, we will analyze 16S rRNA gene amplicon sequencing from rumen microbiomes to look for differences in the structure and composition of microbial communities from the rumen of twenty beef cattle of varying CH4 emission levels. There is no significant difference in microbial community diversity by CH4 emission level. We will analyze microbial community structure and composition to identify microbial taxa associated with high and low CH4 emissions. The findings of our work will begin to explain why some cattle emit higher methane levels compared to others, and may aid in finding solutions to reduce methane emissions in cattle while keeping their feeding efficiency and meat production high.
Grazing steers partner with their rumen microbiomes to efficiently convert plant-derived carbohydrates into meat. Considering the socioeconomic importance of the beef industry, it is critical to develop strategies that maintain quality while lessening negative environmental impacts. Diet supplementation and hormonal implants have been shown to variably impact methane emissions and animal performance. The response of the rumen microbiome to such treatments remains unknown. Here, we will analyze 16S rRNA gene amplicon sequencing of the rumen microbiome from grazing steers across four treatment groups: diet supplemented, hormonal implanted, combined diet and implant, and no intervention. The diet, implant, and combined treatment showed no significant impact on methane emission or N excretion over the 90-day grazing trial. Given this lack of difference, we hypothesize the rumen microbial communities will not be different across treatments. However, we hypothesize the 90 days of grazing will significantly alter the rumen microbiome. Results from this study will provide insight into rumen microbiome dynamics during the life cycle of a grazing steer, further informing management strategies.
Extradiol dioxygenases are known to oxidatively cleave aromatic pollutants, such as catechol. DfdB is an extradiol dioxygenase whose activity on substituted catechols has not been studied. Catechols and other aromatic hydrocarbons are a by-product of coal conversion, coal tar chemical production and other coal industries and are found in the air and wastewater surrounding these facilities. As catechol substrates are possible human carcinogens, their potential breakdown by DfdB is a significant area of interest. Ultimately, this research aims to define the conditions under which DfdB breaks down catechol substrates most efficiently and characterize the products of this bioremediation pathway. To accomplish this goal, the enzyme kinetics of DfdB were measured with varying concentrations of catechol substrates using Ultraviolet-Visible (UV-vis) Spectroscopy, and initial rates of reaction were calculated. Upon analysis, the data suggests that DfdB experiences concentration-dependent substrate inhibition, which has been noted for other extradiol dioxygenases. By measuring kinetic profiles for a variety of substituted catechols, we have better defined the characteristics of DfdB as a potential bioremediation catalyst. This information will be leveraged to improve the utility of this catalyst broadly for synthesis and bioremediation.
Economic insecurity is a critical but often overlooked determinant of public health. This study investigates how financial instability contributes to poor health outcomes. Financial instability is characterized by unpredictability of income, employment insecurity, and limited access to basic needs like food, clothing, housing and access to healthcare, all which affect physical and mental health outcomes. By analyzing the intersectionality of economic insecurity, healthcare access, and the role of social systems including healthcare policies and safety nets, this research aims to identify key factors that negatively impact health and wellbeing and exacerbate these effects. This research primarily relies on quantitative data from closed ended survey questions, supplemented by qualitative data from the addition of three open ended survey questions. The survey explores an individual’s economic position, experience with healthcare accessibility and the perceptions of the effectiveness of social programs. The objective of the research is to discover in what ways economics affect health and to highlight systemic shortcomings in addressing these issues. The findings from this research can provide insight to those dedicated to developing more effective interventions that would mitigate negative health consequences and improve healthcare accessibility.
Curling is a strategic team sport that presents unique challenges for artificial intelligence (AI) research, particularly in decision-making and physical simulation. However, a significant barrier to AI development in curling is the lack of structured and accessible datasets. This project aims to address this gap by leveraging standardized video feeds from Curling Stadium to generate datasets suitable for AI research.Our approach involves developing software that uses image detection models YOLO (You Only Look Once) and SAM (Segment Anything Model) to analyze YouTube videos of curling matches, tracking objects such as rocks and players to gather data on their positions and movements.The expected outcome of the larger project is a structured and scalable dataset that can be used for AI-based curling research, including game strategy analysis and predictive modeling. This project lays the foundation for broader AI applications in curling by automating data collection, enabling machine learning models to analyze strategic decision-making, and fostering human-AI collaboration in sports analytics.
The Internet of Things (IoT) encompasses a variety of systems and devices that enable data exchange across networks. With this interleaved connectivity comes an inherent vulnerability to attacks. Traditional intrusion detection in IoT environments has been primarily human-reliant, but modern malicious methods surpass manual approaches. Machine Learning (ML)-based Intrusion Detection Systems (IDS) show promise but require refinement to match human-monitored IDS effectiveness.This study involved a literature review of research involving the NetFlow dataset NF-ToN-IoT-v2, created in 2022 to enable ML-based IDS development. With balancing, the dataset includes approximately 16 million net-flows, with 63.99% attack and 36.01% benign. The data’s imbalanced nature was addressed through methods like down sampling to reduce training bias. A hyper-parameter tuning pipeline was used to optimize algorithm testing and cross-validation, especially for different data balancing methods.The algorithms tested based on previous research found during literature review include Naïve Bayes, Random Forest, K-Nearest Neighbor (KNN), Support Vector Machines (SVM), and XGBoost. Comparative analysis using confusion matrices and bar plots enabled the evaluation of algorithm effectiveness. Overall, this research highlights the potential of ML approaches in IoT IDS development, through leveraging NF-ToN-IoT-v2 to enhance detection accuracy and bridge the gap between human-monitored and ML-driven solutions.
We aimed to increase awareness of the local flora and fauna that many people may not be awarelive in the Chippewa River. We decided to create glass mosaics to adorn the windows of the busstop in front of Haas Fine Arts Center as it is an accessible location for many people passingthrough Water Street.We used glass for its translucent properties, durability, and longevity to ensure that no harmwould be brought to the local environment through use of toxic materials and to make sure itwill last for years to come with little need for maintenance.The various colors of the glass pieces and the location result in the appearance changingthroughout the day and seasons as the available light differs, keeping it intriguing for andvisible for both visitors and the bus drivers they are waiting for.Our project resulted in a beautiful piece of art that succeeds in showcasing many local endangeredfish and demonstrating the talents of graduates from the art program. The location nearby theriver may also tempt curious minds to see if they can spot any of the creatures themselves.
Plastic pollutants are a significant environmental concern. Biodegradable plastics are a large area of research because if plastics are accidentally released into the environment, biodegradable plastics will break down into harmless byproducts. A blister pack is a type of packaging that consists of plastic pockets that hold individual pills. Current blister packs on the market are not biodegradable and contribute to environmental harm. The goal for this research project is to find an eco-friendly material to replace current blister packs that can also handle chemical reagents (such as medical reagents). Initial testing focused on developing a film from cassava starch that was adapted from the literature. The standard ASTM D543 was used to evaluate the resistance of the material to chemical reagents. The samples were placed under strain using a 3D printed strain jig, the chemical reagent was applied, and the samples were held at fixed temperature for varied amounts of time. After chemical exposure, the samples were tested to determine changes in mechanical properties. These results will be used to determine if cassava starch can replace traditional plastic blister packs to open the door to many environmentally friendly swaps in the medical field.
Architectural coatings are categorized as either solvent-based or water-based, with the latter gaining popularity due to their lower volatile organic compound (VOC) content and simplified manufacturing process. However, their performance can be limited compared to oil-based alternatives. To address these challenges, dispersants are incorporated to enhance stability and prevent titanium dioxide (TiO₂) particle aggregation, the primary pigment in the majority of architectural coatings. Our research investigates the structure-property relations of stimuli responsive polyethylene glycol:poly(2-(dimethylamino)ethyl methacrylate) [PEG:PDMAEMA] block copolymers and specifically their application as an eco-friendly TiO₂ dispersant in water-based coatings. These block copolymers were synthesized via ARGET ATRP (Activators ReGenerated by Electron Transfer - Atom Transfer Radical Polymerization), a process which allows for precise control of block length with minimal catalyst use. Various block length ratios were synthesized and characterized, with stress-dependent flow properties analyzed using rheometry and interfacial activity assessed via pendant drop tensiometry. Paint formulation performance was compared to a market standard through Leneta chart and water droplet testing, evaluating opacity, gloss, and resistance to leeching. These findings highlight the potential of incorporating PEG:PDMAEMA polymer dispersants into architectural coatings as a viable alternative to solvent-based coatings while maintaining essential performance properties.
Once roughly five times the size of the Lake Superior in the United States, Megalake Chad was a vast inland lake that has drastically receded over the past 5,000 years, leaving behind geomorphic features and drainage patterns indicative of its former expanse. This study investigates the geomorphic features and hydrology of this ancient lake using topographic data. Specifically, we utilized the Shuttle Radar Topography Mission (SRTM) 30-meter Digital Elevation Model (DEM) for analyses, generating slope maps to enhance our understanding of surface drainage patterns. To identify drainage features potentially overlooked by slope analyses, radar remote sensing data was used. Because much of Megalake Chad's northern basin is in the Sahara Desert radar sensors like PALSAR and RADARSAT are valuable for their ability to reveal subsurface features under the sand. Integrated topographic surface analysis and subsurface mapping offers a promising approach to uncovering buried channels and alluvial fans/deltas. Our findings not only reinforce evidence of a large ancient lake, but also reveal previously underexplored drainage patterns with potential valuable water resources and arable land.
This study examines the impact of goal orientations (results-oriented vs. process-oriented) on team dynamics and performance evaluations within global virtual teams, challenging traditional assumptions about team efficiency. Drawing on Herzberg's Two-Factor Theory (1959), Locke's Goal-setting Theory (1967), and intrinsic motivation frameworks, we analyzed data from the X-Culture Project, encompassing 3,660 undergraduate business students in 925 global virtual teams during Fall 2020. Our research specifically investigates how different approaches to incentive mechanisms and goal orientations influence team member perceptions and evaluations. Through multivariate regression analysis, we found that while both results-oriented (focused on monetary rewards and certificates) and process-oriented (valuing collaborative experiences and relationships) team members reported similar levels of subjective satisfaction, their peer evaluations differed significantly. Results-oriented members received lower peer evaluations, being perceived as less creative, less effortful, and less task-compliant. Conversely, process-oriented members were evaluated more positively, demonstrating stronger leadership qualities, active thinking, and perceived work ethic. This favorable evaluation of process-oriented members may be attributed to their stronger focus on team relationships, communication, and collaborative learning, which are particularly crucial in virtual environments where building trust and maintaining engagement require extra effort. Their emphasis on the journey rather than just the destination likely leads to more consistent participation, better communication patterns, and stronger relationship building – all qualities highly valued by peers in virtual collaborative settings. These findings challenge conventional wisdom about incentive structures in global virtual teams and suggest that process orientation may offer a competitive advantage in virtual collaborative environments. The study contributes to our understanding of team dynamics and has important implications for designing effective incentive mechanisms and managing diverse goal orientations in virtual team settings.
This research proposal investigates the communication tool preferences of native English speakers (NES) and English as a second language (ESL) learners within global virtual teams, focusing on the interplay between communication frequency (CF), communication tools (CT), team conflict (TC), and identification (ID). The study posits three hypotheses: (H1) communication frequency is negatively correlated with team conflict, suggesting that increased CF reduces TC; (H2) higher communication frequency positively influences the use of information-dense communication tools, such as Zoom, over less dense tools like text messaging; and (H3) communication tool preferences differ based on identification—NES members shift from low-density tools (e.g., texts) in low-frequency settings to high-density tools (e.g., Zoom) in high-frequency settings to minimize conflict, while ESL members consistently prefer text-based tools across all frequencies to mitigate interaction tension and reduce conflict. Based on the data collected from 153 global virtual student teams which participated in the X-Culture project, we found that higher communication frequency will reduce team conflict across both groups, with NES members not showing any preferences on communication tools, while ESL members exhibit a persistent reliance on text-based tools to address linguistic and social challenges. These findings aim to deepen insights into effective communication strategies in linguistically diverse virtual teams, providing actionable guidance for enhancing collaboration in globalized educational and professional settings.
