Digital Commons Network^™

Searching Smarter, Connecting Better, Abby Veiman

University of Nebraska-Lincoln Libraries: White Papers

In Searching Smarter, Connecting Better, Abby Veiman reflects on her experience as a data-driven researcher to reimagine the future of research libraries. Drawing from her work as an Ameritas Research Assistant in Actuarial Science and Risk Management, she highlights how modern research is increasingly digital, analytical, and dependent on technological infrastructure rather than physical materials. Veiman argues that libraries must continue evolving beyond access to databases by strengthening technological capacity, supporting responsible AI integration, and providing clearer guidance on the effective and ethical use of emerging research tools. She emphasizes the need for libraries to serve as trusted institutions …

Phosphorus Adsorption And Desorption Characteristics On Micronutrient Doped Biochar, Moe Kikuchi '27

Annual Student Research Poster Session

The increasing global demand for food necessitates efficient agricultural practices; however, the overuse of phosphorus (P) fertilizers presents a major environmental concern. Advanced materials, including biochar, offer promising strategies for mitigating these effects. Biochar, a carbonaceous material derived from biomass, can be functionalized with micronutrients such as magnesium (Mg) or iron (Fe) to enhance its P adsorption and retention characteristics so that the ion-doped biochar could serve as a sustained nutrient release fertilizer besides improving soil health. This study investigated the adsorption and desorption behavior of dissolved P (200 µM/g and 400 µM/g) in three types of biochars: raw (BC), …

The Feelit System: Application Content-Aware Perspectives And Challenges On Understanding User Likes In Social Network Posts, Konstantinos Theocharidis, Hady W. Lauw, Panagiotis Karras

Research Collection School Of Computing and Information Systems

In a series of our prior works, we study influence and subscription maximization problems in social networks that are based on posts having influential content; as content we consider a set of features where each feature corresponds to a specific social network page, whereas influence and subscription relate to gaining the postlike and subscription-to-brand page of targeted users, respectively; subscription is conceptually achieved as repetitive influence on users. So, both influence and subscription depend on content that gains the likes of users; however, to be realistic, modeling and estimating such likes is a complex problem that has not been adequately …

Cellscout: Visual Analytics For Mining Biomarkers In Cell State Discovery, Rui Sheng, Zelin Zang, Jiachen Wang, Yan Luo, Zixin Chen, Yan Zhou, Shaolun Ruan, Huamin Qu

Research Collection School Of Computing and Information Systems

Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define specific cell states. However, difficulties arise from the co-discovery process of cell states and biomarkers: biologists often use dimensionality reduction to visualize cells in a two-dimensional space. Then they usually interpret visually clustered cells as distinct states, from which they seek to identify unique biomarkers. However, this assumption is often this assumption often fails to hold due to internal inconsistencies in a cluster, making the process trial-and-error and highly uncertain. Therefore, biologists urgently need effective …

Prisrv+: Privacy And Usability-Enhanced Wireless Service Discovery With Fast And Expressive Matchmaking Encryption, Yang Yang, Guomin Yang, Yingjiu Li, Pengfei Wu, Rui Shi, Minming Huang, Jian Weng, Hwee Hwa Pang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The evolution of decentralized identity (DID) and self-sovereign identity (SSI) frameworks, as endorsed by W3C Verifiable Credentials (VC) and eIDAS 2.0, underscores the need for secure, efficient, and privacy-preserving credential management. However, existing credential systems often depend on centralized issuers, lack efficient aggregation mechanisms, or fail to ensure unlinkability across authentication sessions. To address these challenges, we propose DISC (Decentralized Identity System with Self-Sovereign Credential Aggregation), a novel credential system that enables multi-authority credential issuance, user-controlled credential aggregation, and unlinkable authentication. DISC allows users to aggregate credentials from multiple issuers while maintaining constant-size authentication tokens and supporting batch verification for …

Prompt Tuning Without Labeled Samples For Zero-Shot Node Classification In Text-Attributed Graphs, Sethupathy Parameswaran, Suresh Sundaram, Yuan Fang

Research Collection School Of Computing and Information Systems

Node classification is a fundamental problem in information retrieval with many real-world applications, such as community detection in social networks, grouping articles published online and product categorization in e-commerce. Zero-shot node classification in text-attributed graphs (TAGs) presents a significant challenge, particularly due to the absence of labeled data. In this paper, we propose a novel Zero-shot Prompt Tuning (ZPT) framework to address this problem by leveraging a Universal Bimodal Conditional Generator (UBCG). Our approach begins with pre-training a graph-language model to capture both the graph structure and the associated textual descriptions of each node. Following this, a conditional generative model …

Fortifying The Seams Between C/C++ And Rust: Characterizing Bugs In Interop Tools, Xuemeng Cai, Jiakun Liu, Cunyang Liu, Lingfeng Bao, Yijun Yu, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Rust has become increasingly popular in recent years due to its safety and high performance. Despite these advantages, Rust projects rarely start from scratch in practice, and many Rust-based systems instead use hybrid programming, where Rust interoperates with existing C/C++ code. To reduce the manual effort involved in this interoperation (interop) process, several interop tools have been proposed to facilitate hybrid programming between Rust and C/C++. However, the challenges and limitations of these tools remain largely unexplored, leaving developers unclear about the future directions and users unclear about the appropriate usage scenarios. To fill the gap, we mined 320 bugs …

Mm-Attackg: A Multimodal Approach To Attack Graph Construction With Large Language Models, Yongheng Zhang, Xinyun Zhao, Yunshan Ma, Haokai Ma, Yingxiao Guan, Guozheng Yang, Yuliang Lu, Xiang Wang

Research Collection School Of Computing and Information Systems

Cyber Threat Intelligence (CTI) parsing aims to extract key threat information from massive data, transform it into actionable intelligence, enhance threat detection and defense efficiency, including attack graph construction, intelligence fusion, and indicator extraction. Among these research topics, Attack Graph Construction (AGC) is essential for visualizing and understanding the potential attack paths of threat events from CTI reports. Existing approaches primarily construct the attack graphs purely from the textual data to reveal the logical threat relationships between entities within the attack behavioral sequence. However, they typically overlook the specific threat information inherent in visual modalities, which preserves key threat details …

Obstructive Sleep Apnea Prediction: A Comprehensive Review And Comparative Study, Thi Khanh Chi Huynh, Amonae Dabbs-Brown, Anna Jurek-Loughrey, James Mulhall, Tuan Dung Pham, Ngoc Phu Doan, Viet Hung Tran, Zichi Zhang, Xuan Hoang Nguyen, Yimeng An, Peixin Li, Phi Hung Nguyen, Thi Linh Hoang, Xinming Shi, Hans Vandierendonck, Sebastien Bailly, Jean-Louis Pépin, Thai Son Mai

Research Collection School Of Computing and Information Systems

Obstructive Sleep Apnea (OSA) is a highly prevalent sleep disorder linked to considerable public health burdens and comorbidities. However, its heterogeneous presentation and the limited accessibility of traditional diagnostic tools such as polysomnography (PSG) lead to widespread underdiagnosis. As a result, artificial intelligence (AI) approaches, including machine learning (ML) and deep learning (DL) models, have attracted attention as an alternative pathway to detection. This paper first provides a comprehensive review of AI-driven OSA diagnosis, covering different diagnosis problems, input-data types, data biases, pre-processing techniques, and model performance. We then leverage the largest clinical dataset used in OSA prediction to date, …

Analysis Method Of Impact Of Complex Electromagnetic Signals On Measurement Errors In Single-Phase Electric Energy Meters, Hongtao Shen, Chong Li, Hao Wang, Juchuan Guo, Penghe Zhang, Cong Wang

Journal of Electric Power Science and Technology

In complex electromagnetic environments, the diverse array of electromagnetic interference signals with varying modulation schemes leads to degraded performance in single-phase electric energy meters. With the random and dynamic characteristics of complex electromagnetic signals, a parametric model is established for m-sequence dynamic test signals. Subsequently, a structured measurement model for single-phase electric energy meters and a mathematical model for the impact of electromagnetic signals on single-phase electric energy meter errors are developed. The impact of electromagnetic signals on random interference in electric energy meters is then simulated. Finally, through simulation and experimental tests, the impacts of electromagnetic signals on measurement …

Peer-To-Peer Electricity Trading Method Considering Supply-Demand Relationship Tariffs And Tariff Time Period Division, Renjun Zhou, Xin Peng, Jingjie Huang, Xiaojiao Tong

Journal of Electric Power Science and Technology

A two-layer optimization model of a leader-follower game is constructed for peer-to-peer electricity trading between distributed energy power stations and industrial parks. The profit maximization of the distributed energy station is taken as the goal in the upper layer, with decision variables including tariff time period division, tariff pricing, and the charging/discharging power of on-site energy storage equipment. The difference between electricity supply and demand is used as the state variable, and a certain range of difference is used to determine the valley and peak price periods. A tariff response coefficient is designed, which depends on the demand response effect …

Iowa Waste Reduction Center Newsletter, February 2026, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Cedar Rapids Linn County SWA Wins Award
--- Energy Savings Made Simple: What is An Energy Audit?
--- New IEDA Grant Helps Rural Grocers Power Up
--- Dan Nickey Gets Thermography Certified
--- You’re Invited to UNI Day of Service
--- Minor Source Emission Inventory
--- IStorm 26
--- Industry News

Coe Annual Technical Review 2025, Jianshun Zhang, Bing Dong

SyracuseCoE

No abstract provided.

Duration And Properties Of The Embedded Phase Of Star Formation In 37 Nearby Galaxies From Phangs-Jwst, Lise Ramambason, Mélanie Chevance, Jaeyeon Kim, Francesco Belfiore, J. M. Diederik Kruijssen, Andrea Romanelli, Amirnezam Amiri, Médéric Boquien, Ryan Chown, Daniel A. Dale, Simthembile Dlamini, Oleg V. Egorov, Ivan Gerasimov, Simon C.O. Glover, Kathryn Grasha, Hamid Hassani, Hwihyun Kim, Kathryn Kreckel, Hannah Koziol, Adam K. Leroy, José Eduardo Méndez-Delgado, Justus Neumann, Lukas Neumann, Hsi An Pan, Debosmita Pathak, Karin Sandstrom, Sumit K. Sarbadhicary, Eva Schinnerer, Jiayi Sun, Jessica Sutter, David A. Thilker, Leonardo Ubeda

Physics and Astronomy Faculty Publications

Light reprocessed by dust grains emitting in the infrared enables the study of the physics at play in dusty embedded regions, where ultraviolet and optical wavelengths are attenuated. Infrared telescopes such as JWST have made it possible to study the earliest feedback phases, when stars are shielded by cocoons of gas and dust. Comprehending this phase is crucial for unravelling the effects of feedback from young stars that leads to their emergence and the dispersal of their host molecular clouds. Here we show that the transition from the embedded to the exposed phase of star formation is short (< 4 Myr) and sometimes almost absent (< 1 Myr) across a sample of 37 nearby star-forming galaxies covering a wide range of morphologies, from massive barred spirals to irregular dwarfs. The short duration of the dust-clearing timescales suggests a predominant role of pre-supernova feedback mechanisms in revealing newborn stars, confirming previous results on smaller samples and allowing, for the first time, a statistical analysis of their dependencies. We find that the timescales associated with mid-infrared emission at 21 μm, tracing a dust-embedded feedback phase, are controlled by a complex interplay between giant molecular cloud properties (masses and velocity dispersions) and galaxy morphology. We report relatively longer durations of the embedded phase of star formation in barred spiral galaxies, while this phase is significantly reduced in low-mass irregular dwarf galaxies. We discuss tentative trends with gas-phase metallicity, which may favor faster cloud dispersal at low metallicities.

Holographic Duality From Howe Duality, Anatoly Dymarsky, Johan Henriksson, Brian Mcpeak

Physics and Astronomy Faculty Publications

We discuss the holographic correspondence between 3d “Chern-Simons gravity” and an ensemble of 2d Narain code CFTs. Starting from 3d abelian Chern-Simons theory, we construct an ensemble of boundary CFTs defined by gauging all possible maximal subgroups of the bulk one-form symmetry. Each maximal non-anomalous subgroup is isomorphic to a classical even self-dual error-correcting code over ℤ_p × ℤ_p, providing a way to define a boundary “code CFT.” The average over the ensemble of such theories is holographically dual to Chern-Simons gravity, a bulk theory summed over 3d topologies sharing the same boundary. In the case of …

Evaluating Groundwater-Surface Water Interactions At Selected Streams In The Mississippi River Valley Alluvial Aquifer, Usa, And Comparison To Regional Potentiometric Surfaces, Joshua Michael Blackstock, Oladipo S. Obembe, Aaron Shew, Phillip Hays, Phillip R. Owens, Christopher D. Delhom

Geosciences Faculty Publications and Presentations

Field measurements of groundwater-surface water interactions (GWSW) are critical for quantifying stream leakage, but are often limited in availability. In the Mississippi River Valley alluvial aquifer (MRVAA), USA, GWSW interactions are often inferred through interpolated potentiometric surfaces, which can provide information on GWSW changes through time, but are often limited in spatial resolution. Field measurements of GWSW interactions were conducted at several locations and compared with potentiometric surfaces using objectively calculated cell sizes. The potentiometric surfaces showed similar regional-scale groundwater-flow patterns irrespective of grid cell size. Field measurements of GWSW interactions exhibited a broader range of gaining and losing conditions …

Belknap And Carroll Counties 4-H Presents Event Packet 2026, Mikayla Cerney

UNH Cooperative Extension

No abstract provided.

The Role Of Spatial Abilities In Stem Learning And The Influence Of Individual Differences, Styliani Malkogeorgou

Masters

Students’ decisions to pursue education and careers in Science, Technology, Engineering, and Mathematics (STEM) are shaped by an interplay of cognitive, social, and motivational factors. Spatial ability is among the most reliable predictors of STEM success, yet less is known about how it relates to students’ STEM attitudes and aspirations, and whether visuospatial working memory (VSWM) explains this relationship. This study tested the hypotheses that (a) stronger spatial abilities and VSWM would be associated with more positive STEM attitudes and stronger STEM aspirations, and (b) VSWM would mediate the relationship between spatial abilities and STEM attitudes/aspirations, while examining the influence …

Artificial Neural Network Model For Predicting Fatigue Endurance Limit Of Hot Mix Asphalt Using Uniaxial Tension–Compression Tests, Prashanta Kumar Acharjee, Mayzan Isied, Mena I. Souliman, Sameer Jung Karkl, Tanvir Ahmed, Gokhan Saygili

Civil Engineering Faculty Publications and Presentations

Fatigue is one of the major distresses occurring in asphalt concrete pavement. Repeated traffic loading causes escalated structural damage which results in the formation of cracks. There is a strain level below which the Hot Mix Asphalt goes under fatigue failure, and it is called endurance limit. In this study, a predictive model is developed to predict endurance limit strain values by using artificial neural network. Uniaxial tension-compression fatigue test results conducted under NCHRP Project 9–44 A were utilized in the model development process. An equation is also extracted from the model along which gives the exact values as the …

Variation In Food Web Reliance On Green And Brown Energy Pathways Across Ecosystem Gradients, James W. Sturges, W. Ryan James, Ryan J. Rezek, Rolando O. Santos, Mack White, Gina A. Badlowski, Shakira Trabelsi, Jordan Massie, Justin S. Lesser, Joel C. Trexler, James Nelson, Jennifer S. Rehage

Marine Science

Aquatic food webs typically include highly coupled fast, ‘green’ energy pathways driven by algae or phytoplankton and slower, ‘brown’ energy channels driven by detritus and terrestrial plants. Quantifying how much energy biological communities obtain from each of these pathways is essential, particularly across multiple interconnected food webs over large areas, because energy dynamics are known to influence ecosystem structure and function. Despite their importance, few studies track variance in energy channel contributions to food webs across interconnected habitats during distinct hydrologic seasons. In this study, we used tri-isotope Bayesian mixing models to quantify seasonal contributions of energy pathways to consumers …

Biob 591.05: Ecological Models And Data, Robert O. Hall

University of Montana Course Syllabi, 2026-2030

No abstract provided.

M 105.01: Contemporary Mathematics, J. Michael Sulock

University of Montana Course Syllabi, 2026-2030

No abstract provided.

M 132.02: Numers And Operations For Elementary School Teachers, Frederick Peck

University of Montana Course Syllabi, 2026-2030

No abstract provided.

M 171.02: Calculus I, Molly Sager

University of Montana Course Syllabi, 2026-2030

No abstract provided.

From Classroom To Field: Rural Teachers’ Integration Of Science And The Outdoors, Steph N. Dean, Julieanne A. Wenner

Publications

This study explored how rural educators in the US use outdoor environments to enhance science instruction, addressing the educational marginalization of rural students. Using rural cultural wealth as a theoretical framework, we investigated how rural teachers integrate local nature-based resources and students’ out-of-school experiences into science learning. We conducted interviews and observations with rural teachers, using reflexive thematic analysis as our qualitative approach. Three key themes emerged that highlight the ways our participants use the outdoor environment to teach science: (a) harness rural community partnerships, (b) engage students through relational teaching, and (c) design learning opportunities that honor students as …

Slow Education, Sit Spot, And Holistic Well-Being: A Narrative Case Study In Secondary Science Education, Steph Dean, Jim Lane, Paul Bocko, Albert Gilbert, Devan A. Jones

Publications

The demands of a test-dominant education system point towards the need for students to have opportunities for unhurried learning engagements, a movement known as slow education. The purpose of this study was to examine the long-term influence of Sit Spot–a recurrent, structured time to reflect outdoors–on students’ holistic well-being. Using a narrative case study approach, we interviewed a secondary field ecology teacher and seven of his former students to understand the impact of high school Sit Spot experiences during a semester-long science class. Three primary outcomes emerged: (1) enduring impact on the whole person, (2) engagement with affect, and (3) …

Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Bruce I. Dvorak, David M. Admiraal, Pavel Shrestha

Nebraska Department of Transportation: Research Reports

The Nebraska Department of Transportation (NDOT) must manage sediment, and pollutant loads from roadway runoff to meet stormwater regulations. The SAFL Baffle, a hydrodynamic separator used by NDOT, depends on reliable estimates of total suspended solids (TSS) and particle size distribution (PSD). However, limited data exists for Nebraska roadways. In this study stormwater runoff was monitored at four NDOT-maintained sites, two in Lincoln and two in Beatrice, over 1.5 years to characterize TSS and PSD and to evaluate SAFL Baffle performance using the SHSAM model. Results showed large variability across sites and seasons. Median TSS ranged from 158 to 580 …

A Runtime-Adaptive Transformer Neural Network Accelerator On Fpgas, Ehsan Kabir, Jason D. Bakos, David Andrews, Miaoqing Huang

Electrical Engineering and Computer Science Faculty Publications and Presentations

Transformer neural networks (TNN) excel in natural language processing (NLP), machine translation, and computer vision (CV) without relying on recurrent or convolutional layers. However, they have high computational and memory demands, particularly on resource constrained devices like FPGAs. Moreover, transformer models vary in processing time across applications, requiring custom models with specific parameters. Designing custom accelerators for each model is complex and time-intensive. Some custom accelerators exist with no runtime adaptability, and they often rely on sparse matrices to reduce latency. However, hardware designs become more challenging due to the need for application-specific sparsity patterns. This paper introduces ADAPTOR, a …

M 221.01: Introduction To Linear Algebra, Emily F. Stone

University of Montana Course Syllabi, 2026-2030

No abstract provided.

M 584.01: Topics In Combinatorics And Optimization - The Probablistic Method, Cory T. Palmer

University of Montana Course Syllabi, 2026-2030

No abstract provided.