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Specific Differential Phase Signatures Associated With Quasi-Linear Convective System Mesovortices
No full textIssuing convective warnings on mesovortices within quasi-linear convective systems (QLCSs) is a challenge for National Weather Service operations, as these rotation signatures develop quickly and are small-scale phenomena. To guide forecasters, the three ingredients method and QLCS mesovortex warning system were developed. However, this system doesn’t yet incorporate dual-polarization radar data other than tornadic debris signatures. Therefore, this study compares mesovortex evolution and strength to the evolution of specific differential phase (KDP) to determine if KDP offers any predictive ability (lead time) to mesovortex development and damage potential. To accomplish this study, we compared low-level KDP core, midlevel KDP core, and KDP drop evolution relative to mesovortex formation. We chose three QLCS events, 19 May 2022 in the Saint Louis county warning area (CWA), 20 February 2017 in the San Antonio CWA, and 10 January 2020 in the Memphis CWA, and examined the KDP signatures mentioned above for damaging vs non-damaging mesovortices and tornadic vs non-tornadic mesovortices. In general, KDP drops frequently precede mesovortex development and are slightly more frequent for mesovortices that produce damage. Furthermore, 65% of all KDP drops led to either a mesovortex or damage. Midlevel KDP cores have a higher magnitude for tornadic and damaging mesovortices prior to mesovortex genesis, therefore potentially offering prognostic ability. Furthermore, low-level KDP cores have a higher magnitude for tornadic and damaging mesovortices during mesovortex life, therefore potentially offering diagnostic ability. These findings support the idea that KDP can be used by forecasters to build confidence in whether a given mesovortex might produce damage or not
Latina Women\u27s Health Conference: A Public Relations and Advertising Study
No full textLatina health requires greater attention and education in the United States. Previous research has highlighted disparities in Latino health outcomes. In order to combat this, public relations professionals can present health information in a culturally-relevant way to communicate for the betterment of the community. This paper analyses a public relations event in January 2025, in collaboration with a local community center El Centro de las Américas. The event promoted women\u27s health in Lincoln, Nebraska through inviting speakers familiar with the Latina language and culture, along with intentional planning decisions to invite women and care for them during the event
Biochemical Characterization of Mammalian Sodium Calcium Exchangers
No full textCa2+ is a widespread second messenger in mammalian cells. It is crucial
for various physiological processes. These include skeletal mineralization, cell
proliferation, muscle cell contraction, nerve transmission, hormonal secretion,
maintaining a regular heartbeat, and blood clotting. Na+/Ca2+ Exchangers (NCXs)
play a central role in regulating the concentration of intracellular Ca2+ homeostasis
through the high-capacity extrusion of Ca2+. In humans, three homologs of NCX
exist, each has multiple cytosolic regulatory domains. The NCXs can also function
in both monomeric and dimeric states. Dysfunction of NCXs has been associated
with various diseases, including heart disease, neurodegenerative disorders, and
cancer. This makes NCXs a highly promising therapeutic target. Despite extensive
physiological research on this protein, the molecular principles governing the
function and regulation of NCXs largely remain unknown due to limited structural
studies. This effort is further hindered by the significant challenge of expressing
and purifying both monomeric and dimeric NCXs. Using an improved mammalian
expression system developed in our lab, we successfully expressed both
monomeric and dimeric NCXs for all three homologs from both humans and rats,
which were analyzed by fluorescence-detection size exclusion chromatography
(FSEC). Additionally, we have expressed and purified 3C protease to facilitate the
subsequent structural studies by removing the fluorescence and purification tags
Literature Review of Culturally Relevant Tobacco Prevention Methods for AI/AN in the Northern Great Plains Region
No full textAmerican Indians and Alaska Natives (AI/AN) are the largest consumers of commercial tobacco (Centers for Disease Control and Prevention [CDC] 2020). In the Northern Great Plains region, Lung Cancer Mortality is the highest for this racial group, more than any other region. The objective of this paper was to build on responses to the initial interview-based study. To indirectly address cancer readiness, this review sought to find effective programming and research methods related to tobacco use prevention and cessation that are culturally relevant to the American Indian populations of the Northern Great Plains Region by reviewing existing literature. This review identified four main themes in the literature that are important for establishing research and programming that is culturally relevant. These themes are understanding the cultural significance of tobacco, incorporating spiritual, cultural, and physical representation, adopting a community-based and strengths-focused approach, and addressing youth tobacco use through early prevention and trauma-informed strategies
Applying DMS-MaPseq to Evaluate RNA-Ligand Binding
No full textRNAs play pivotal roles in the cell due to their structures. RNA disfunction is implicated in many diseases, including cancers and neurodegenerative disorders, making RNA a critical drug target. However, the flexibility of RNA, its anionic nature, limited chemical diversity, and nonfunctional sites pose significant challenges in drug design. Furthermore, the chemical space of known RNA-binders is limited to non-drug-like compounds. Recent studies have suggested that RNA is a viable drug target as pockets have been found that are comparable to those found in druggable proteins and various assays have found drug-like compounds that bind to RNAs. These recent findings suggest the existence of a chemical space of drug-like RNA binders. To enable the development of RNA targeted therapeutics, this chemical space must be characterized. However, current methods to detect RNA-ligand interactions are either limited in their throughput or in the chemical scaffolds and targets that can be evaluated. This study aims to introduce the application of DMS-MaPseq as a high-throughput approach to evaluate a larger chemical space for RNA binding. Results demonstrate that titrations are able to robustly detect and characterize the binding events, while individual comparisons of standard and high concentration conditions are complicated by experimental variance
ECHO Collective Learning Management System (LMS)
No full textECHO Collective is a non-profit founded during the start of the Covid-19 pandemic that provides opportunities and connections for refugee and immigrant women in the Lincoln area. ECHO Collective’s education program, The Refinery, selects a small group of entrepreneurial refugee and immigrant women for a 4-month business course twice every year.
Currently, assignments and lessons for the Refinery program are given to students in a paper notebook. Students can manually translate their books and reach out to instructors through WhatsApp if they have any questions on lessons or assignments and can look at the ECHO Collective homepage for information on events and other programs. As more students go through the Refinery program, this system becomes increasingly overwhelming for instructors. Additionally, the 4-month program limits the time for technology education, leaving women unsure how to grow their technology experience and confidence.
The Design Studio team’s solution is a customized learning management web application designed for the multi-cultural needs of the Refinery’s students. While ECHO Collective had investigated learning management systems such as Canvas and Google Classroom, they found that these solutions were not designed for users with low tech literacy and were too expensive. To counter this, the Design Studio team built a custom solution that limits user confusion by removing unnecessary or irreversible actions. For all actions a user can take, the LMS also provides clear directions. With this solution, ECHO Collective’s Refinery students can build their confidence in technology
AI-Powered Sport Storytelling from Event Data
No full textHudl helps teams and players reach their full potential, and the Hudl Fan Platform is meant to do the same for fans. While fans can find streams, tickets, and rosters on the site, there’s often no context or story to get them excited about the game. As a result, fans struggle to stay engaged, family members miss key moments, and players don’t get the recognition they deserve. With the rise of AI and access to rich game data, our team saw an opportunity to fix this. We built a system that uses large language models (LLMs) to automatically generate pregame articles. These summaries help tell the story of each matchup, highlight key stats, and guide fans to streams and tickets, bringing more energy and attention to every game.
We chose to focus on a more defined scope to ensure we could deliver high-quality work with greater depth and precision. This year, we focused on pregame articles for Boys Varsity Basketball. Overall, the team experienced success in generating pre-game articles while also discovering roadblocks that would prevent the widespread rollout of pre-game content. At this point, we have an understanding of what is needed and how to implement widespread AI content generation across the Hudl Fan platform
AI Shopping Assistant
No full textBuckle, Inc. is a leading retailer of high-quality casual apparel, footwear, and accessories for fashion–conscious men and women. Headquartered in Kearney, Nebraska, the company currently operates over 440 stores in more than 40 states. Buckle prioritizes providing the best possible guest experience through individual customer services.
Through this project, Buckle aims to optimize the shopping experience by integrating our natural language search solution into their existing internal applications. This will allow internal users to help customers find the perfect product for any occasion.
The Design Studio team developed a model powered by Retrieval Augmented Generation (RAG) to enhance the search experience. This allows users to find products using natural language instead of a typical keyword search. Current solutions may show the user products that aren’t contextually relevant to their search, which is not effective. For example, a search for “winter vibes” won’t return scarves because “winter” isn’t a keyword in the product name for scarves.
We used Anthropic’s Claude Sonnet model to create lists of words (‘tags’) that describe each of the provided products’ features. We created these tags to enhance the model’s knowledge about the Buckle products and give it context so the model can make the best recommendation. This solution improves the clothing shopping experience by allowing for more flexibility when looking for the perfect product. Instead of needing to use rigid keywords to find a specific clothing item, a user can use natural language to find products that fit any occasion
Project DepEx: Depreciation Exploration and Visualization
No full textProject DepEx delivered a scalable, automated solution for Conagra Brands to analyze and visualize asset depreciation across its extensive manufacturing network. By leveraging Python for data transformation and Power BI for interactive visualization, the team streamlined a previously manual, fragmented process into a unified, dynamic dashboard. This tool consolidates over 10 million data points from more than 100,000 assets and provides clear, actionable insights by fiscal period, facility, brand, and asset type. The solution enables Conagra to reduce analysis time by over 97%, enhance financial planning, and support more informed capital investment decisions that drive long-term value creation
Methane Mitigation and Its Effects on Energy Utilization in Lactating Dairy Cattle
Get PDFImproved methane (CH4) mitigation strategies are needed to achieve the greenhouse gas emission goals of the dairy industry. The first experiment was conducted to evaluate the effects of feeding black cumin (Nigella sativa) seed oil and acetate (BCA) on CH4 production and whole-animal energy utilization. Twelve dry Jersey cows were used in a 2-period crossover design study with 28d periods. The BCA treatment was compared to a control diet with corn oil. Both BCA and corn oil were added to the base diet as a top dress. Results from this study did not show any difference in CH4 production or energy utilization between treatments.
The second experiment was conducted to evaluate the effects of feeding increasing inclusion rates of an algae feed additive containing bromoform (ALB) on CH4 production and whole-animal energy utilization. Twelve lactating Jersey cows were arranged in a quadruplicated 3×3 Latin square design consisting of 3 periods with 28d each. Treatments were randomly assigned and consisted of 0CTRL (base diet with 0% ALB), 0.46LOW (base diet with 0.46% ALB), and 0.93HIGH (base diet with 0.93% ALB). Increasing inclusion of ALB linearly decreased CH4 production. No differences were observed in dry matter intake (DMI) or energy corrected milk (ECM).
Advisor: Paul J. Kononof