Digital Commons Network^™

Emergent Collective Reproduction Via Evolving Neuronal Flocks, Nam H. Le, Michael Levin, Richard A. Watson, Josh Bongard, Christopher L. Buckley

Northeast Journal of Complex Systems (NEJCS)

This study advances the understanding of evolutionary transitions in individuality (ETIs) through a novel artificial life framework, VitaNova, which integrates self-organization and natural selection to simulate the emergence of complex, reproductive groups. By dynamically modeling individual agents within an environment shaped by predators and spatial constraints, VitaNova reveals mechanisms by which simple agents evolve into cohesive units exhibiting collective reproduction. The findings highlight the synergy between self-organized behaviors and adaptive evolutionary strategies as fundamental drivers of ETIs. This approach deepens our understanding of higher-order biological individuality and offers a new empirical pathway for investigating ETIs, extending current theoretical frameworks.

An Action Research Study On Ai Video Vs. Written Feedback: Enhancing Undergraduate Academic Writing And Critical Thinking, Sandra Baroudi, Nida Mubeen, Suha Karaki

All Works

This action research explores how AI-assisted feedback formats influence students’ academic writing and critical thinking, a gap particularly relevant in the digital learning landscape. This study involved 40 undergraduate Emirati students divided into two groups, receiving either AI-generated video or written feedback across three assignments. Using a quantitative design, data were gathered using standardized critical thinking and academic writing skills rubrics. Additionally, students completed post-surveys to capture their perceptions, engagement levels and use of AI tools in the learning process. Results showed written feedback significantly improvemed critical thinking (M = 2.80, SD = 0.75) compared to video feedback (M = …

The Astrobiological Figure Of Humboldt As Pioneer In The Rock Varnish Research, Jose Jordan-Soria

Homage to Alexander von Humboldt: Travels to and from Spain Throughout the Centuries / Homenaje a Alexander von Humboldt: Viajes hacia y desde España de todos los siglos

From Humboldt is particularly interesting -and little know- his description of mineral coatings on rocks 200 years ago, reported in his book Personal Narrative of Travels to the Equinoctial Regions of the New Continent during the years 1799-1804, co-written with Aimé Bonpland, for which is considerate the father of rock coating research. On June 5th 1799 set sail from A Coruña -Spain- to Cumaná -Venezuela- beginning five years of expedition. While they explored the Orinoco River system, in th eriver basin waterfalls, Humboldt observed the presence of dark coating depositions. He ascertained a manganese-rich accretion, reporting similar structures in other …

Modeling, Analysis, And Prediction Of Covid-19 Dynamics With Interacting Subpopulations And Implicit Behavior Using Physics-Informed Neural Networks, Naima Aubry-Romero, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Spora: A Journal of Biomathematics

In this paper, we consider an extended SEIR compartmental model that incorporates young and old interacting subpopulations, allowing for cross-group transmission dynamics. Implicit behavioral changes are included to determine the influence of social behavior on coronavirus transmission dynamics. The basic reproduction number, the average number of secondary cases of infection produced by a single primary case, is derived for both the explicit and implicit model using the next-generation matrix method. We solve the associated differential equation systems and estimate useful parameters in the explicit model using physics-informed neural networks (PINNs). Our results point to how the PINNs approach offers an …

Detecting Ionospheric Disturbances Using High Frequency Coastal Radar Transmissions From The West Coast Of The United States, Riley N. Troyer, Kenneth Obenberger, Michael Negale, Eugene Dao, Zsolt Balint, Eric Burnside, Kris Robinson, Jeffrey M. Holmes, Pavel Inchin, Jonathan Snively

Space Dynamics Laboratory Publications

Coastal radar system are located around the world and many happen to transmit at frequencies capable of skywave propagation via the ionosphere. Therefore, they can be detected hundreds to thousands of kilometers away. This paper demonstrates the opportunity to detect 39 Coastal Ocean Dynamics Application Radar transmitters located on the western coast of the United States using three HF radio receivers in Utah and New Mexico. It also illustrates the possibility to use the phase and Doppler measurements of these signals to derive displacements of the refracting ionospheric layer up to meter resolution for the 2023 annular solar eclipse, an …

Fisheries Science Update - Pilbara Fishing Competition Science 2020 To 2024 - July 2025, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Science Updates

Key Points:

• Pilbara recreational fishing competitions are helping to track the sustainability of pelagic species like Spanish mackerel.
• Over 500 pelagic fish have been sampled at Pilbara fishing competitions over 5 years.
• This information goes towards DPIRD’s assessment of Spanish mackerel and monitoring the large pelagic resource in the North Coast Bioregion.

Adaptation Planning To Mitigate Flood Risk: Bellevue, Nebraska As A Case Study, Michael Nti Ababio

Community and Regional Planning Program: Theses

Flooding remains one of the most pressing natural hazards in the United States, with increasing frequency and intensity driven by climate change. This thesis explores the adaptation planning strategies employed to mitigate flood risks in Bellevue, Nebraska, a city significantly impacted by the 2019 floods in eastern Nebraska. Using a mixed-methods approach, the study combines quantitative analysis of flood vulnerability with a critical review of local planning policies using documents, zoning ordinances and institutional frameworks. Spatial analytical tools such as Global Moran’s I and Hot Spot Analysis (Getis-Ord Gi*) were used to detect clustering of inundated buildings during the 2019 …

Dataset Description, Bradley M. Ratliff

Model Desert Terrain Monochromatic DoT Dataset

Polarimetric dataset containing data collected within the Automated Remote Sensing Solar Simulation Lab at the University of Dayton. The data were collected using a visible monochromatic division-of-time imaging polarimeter. A model desert terrain model was constructed and imaged for eight different scenarios consisting of different model panel and vehicle targets. The dataset is parameterized across different sensor, scene, and illumination geometries that mimic outdoor solar irradiance conditions.

From Palimpsest To Prompt: Rewriting Shakespeare, Creative Authorship, And The Generative Logics Of Large Language Models In Contemporary Theatre, Michael Harding, James Hutson

Faculty Scholarship

This article examines the convergence of creative authorship, adaptation, and generative artificial intelligence within contemporary theatre, taking Michael Harding‘s Awake, Young King as a central case study. Through the rewriting of Shakespearean drama, Harding‘s creative process demonstrates how theatrical meaning emerges through ongoing negotiation among playwright, performer, and audience, with scripts historically subject to revision, improvisation, and reinterpretation. Concerns regarding copyright, intellectual property, and the role of AI in the performing arts are reframed as extensions of enduring debates over originality and authorship, rather than novel threats. Tracing the evolution from The Rise of James VI to Awake, Young King, …

Water Current, Volume 57, No. 2, Summer 2025

Water Current Newsletter

No abstract provided.

Soil Health In Nebraska: Exploring Practitioners' Needs And Insights From A Long-Term Organic Farm, Ingrids Isabel Mata Vigil

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Soil health is foundational to sustainable agriculture, environmental resilience, and long-term food security. Yet, the adoption of soil health assessments remains limited, often perceived as too technical, costly, or difficult to implement in real-world contexts. To better understand these challenges, the first chapter presents findings from a statewide survey of 41 soil health practitioners in Nebraska, including farmers, extension educators, NRCS staff, and conservation professionals. Respondents highlighted the need for simpler, more accessible, and context-specific tools for soil health assessment that help practitioners make informed decisions aligned with their management goals. Complementing these insights, the second chapter includes an independent, …

Quantum Simulation Of Molecular Dynamics Processes─A Benchmark Study Using A Classical Simulator And Present-Day Quantum Hardware, Tamila Kuanysheva, Brian K. Kendrick, Lukasz Cincio, Dmitri Babikov

Chemistry Faculty Research and Publications

We explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this …

Catching A Fever: A Comparison Of Vachellia Xanthophloea Populations In The Limpopo And Luvuvhu River Floodplains Of The Makuleke Contractual Park, Kianie B. David

School of Natural Resources: Dissertations, Theses, and Student Research

This study investigates patterns of stand structure regeneration, growth characteristics, and coarse woody debris (CWD) patterns in Vachellia xanthophloea (fever tree) stands within the Makuleke Contractual Park (MCP), a semi-arid savanna system in northern Kruger National Park (KNP), South Africa. Fieldwork was conducted across two stand types: a monospecific fever tree stand in Rietbok Vlei and a mixed-species stand in the Western Nhlangaluwe Floodplain where fever tree is established with Faidherbia albida (ana tree). Data were collected from 20 total 1/4-acre (1,011 m²) circular plots between both stands in 2024 and 2025, including seedling root collar diameter (RCD), …

Bioenergy Crop Production: Implications For Grassland Bird Communities In Southwestern Nebraska, Grace E. Schuster

School of Natural Resources: Dissertations, Theses, and Student Research

Biofuel and bioenergy systems are components of most climate stabilization pathways to reduce greenhouse gas emissions and limit global warming. Currently, corn (Zea mays) is the predominant feedstock used for bioenergy production in the United States. However, widespread production of this monoculture crop has resulted in many negative environmental impacts. The most notorious impact has been the loss of grassland habitat due to agriculture expansion which has had detrimental effects on wildlife that depend on grassland habitat. One such group, grassland birds, has faced steeper, more consistent, and more widespread declines than any other avian guild. Therefore, strategies …

Strategies For Thoughtful Dissemination Of Climate Change Knowledge: A Blueprint For Scientists In The Heart Of The Empire, Christopher Cronk

Nepal: Geoscience in the Himalaya

This interdisciplinary research investigates how climate change education, Indigenous knowledge systems, journalism, and anthropology intersect in shaping environmental awareness and action, focusing primarily on Nepal and drawing parallels with Indigenous Peoples of Turtle Island (North America). Stationed in Kathmandu, I conducted interviews with climate educators, journalists, anthropologists, and activists to explore how scientific and local knowledge are communicated and acted upon. Findings highlight the strong awareness of climate change in Nepal, the systemic barriers to effective mitigation and adaptation, and the potential of community-led initiatives like the Community Forest Program. Anthropological insights proved crucial in linking human experience to environmental …

Electrochemistry Behind Pfas: Mechanistic And Analytical Approach For Sensing And Degradation Strategies, Jonathan Josue Calvillo Solis

Open Access Theses & Dissertations

Understanding the fundamental electrochemistry of perfluoroalkyl substances (PFAS) is key to developing effective water remediation and sensing strategies. This work explores the thermodynamics and kinetics of perfluorooctanoic acid (PFOA) electroreduction, focusing on C-F bond cleavage. These insights were applied to design a highly sensitive electrochemical sensor for detecting trace levels of PFOA in water. This dissertation focuses on the electrochemical investigation of the reduction reaction of PFOA in aqueous and organic media employing different electrode materials. This exploration allows to understand the defluorination reaction of PFAS to further propose potential strategies for water treatment and PFOA electrosensing. Through electrochemical, spectroscopical …

Chat With The ’For You’ Algorithm: An Llm-Enhanced Chatbot For Controlling Video Recommendation Flow, Shuo Niu, Dikshith Vishnuvardhan, Venkata Sai Reddy Punnam

Computer Science

The rise of short-form video platforms like TikTok, driven by algorithmic recommendations, fosters immersive flow experiences. While users value personalization and engagement, they also seek greater agency over their For You recommendations. This paper designs, prototypes, and evaluates TKGPT, an LLM-enhanced conversational interface that helps users articulate their interests and understand recommendations. Through qualitative interviews and a user study, we examine how the TKGPT influences algorithmic folk theories and the sense of agency. Findings show that users primarily use TKGPT to seek relevant videos, explain preferences, and exert control over the algorithm. The resulting For You videos better reflect user …

Aircraft Bird Strike Risk Prediction Using Machine Learning And Analytic Hierarchy Process, Jason Anthony Powell

Doctoral Dissertations and Master's Theses

To address the limitations of Next Generation Radar-based bird strike forecasting, this study modeled 12 spatiotemporal weather features from the National Oceanic and Atmospheric Administration alongside bird strike risk using Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), XGBoost regression tree, and Bayesian network algorithms. Five years of bird strike data from four geographically diverse airfields served as the target risk variable, categorized as low, moderate, or severe based on Department of the Air Force risk models. The ensemble model, which combines the LSTM-RNN and XGBoost regression algorithms, yielded the most accurate forecasts, achieving 80% to 93% accuracy across all airfields, …

Crosssections, Summer 2025, University Of Northern Iowa. Department Of Physics.

CrossSections

Contents:

A Message from the Department Head, Dr. Paul Shand --- 1
Department Happenings --- 3
Faculty Profile - Takeshi Yasuda --- 7
Student Profile - Brandon Schmidt --- 8
Student Research --- 9
Student Focus --- 10
Physics Education --- 13
Alumni Profile - Roger Burkhart --- 14
Alumni News - Sterling Hartman --- 16
New Physics --- 17

In Situ Thrust Measurement Of Fish During Locomotion; Test Case: Sharks, Braedon Payne, Bryan A. Keller, Daniel Weihs, Roi Gurka

Physics and Engineering Science

We present a novel method of measuring thrust of aquatic animals using in situ video data of swimming motions. To demonstrate its utility, the method was applied to several large elasmobranch species, which are typically highly challenging to measure. Using motion tracking software, we analyzed video footage of wild and captive sharks to track their instantaneous position and speed. In order to estimate the force output, we used the tail/body motion based on the swimming modes of the fish to calculate the water displaced by this motion during locomotion. Using Newton 3rd law, we have calculated the instantaneous force exerted …

Status Of The Western Australian Pastoral Rangelands 2024: Total Vegetative Cover, Cover Risk And Pasture Condition, Department Of Primary Industries And Regional Development, Western Australia

Natural resources published reports

The Department of Primary Industries and Regional Development (DPIRD) monitors and reports on the vegetation condition of pastoral rangelands in Western Australia. Two levels of reporting are provided: every 5 years a full report (this report) details the state, trend and risk of decrease of vegetation condition in the pastoral rangelands using information derived from remotely sensed and on-ground data; in the intervening years, short reports are provided based on remotely sensed data.

This full report is based on remotely sensed vegetation cover data, rainfall data, livestock data and station-level rangeland condition assessment (RCA) data available in November 2024. Data …

Electrocatalytic Degradation Of Methylene Blue Using Graphene Oxide, Antimony Oxide, And Graphene Oxide-Supported Antimony Oxide Ink-Based Electrodes, Maria Irene Myers Armas

Theses and Dissertations

This study investigates the electrocatalytic degradation of methylene blue (MB) using copper mesh electrodes coated with graphene oxide (GO), antimony oxide (Sb₂O₃), and their composite (GO/Sb₂O₃). These materials were evaluated across a pH range of 2 to 8 using sodium sulfate as the supporting electrolyte. UV-Vis spectroscopy at 665 nm confirmed dye degradation, with removal efficiencies reaching up to 95% at pH 2. However, degradation decreased at higher pH, with 40 – 60% removal at pH 8, depending on the electrode. Kinetic analyses revealed optimum performance under acidic conditions. GO/Sb₂O₃ electrodes demonstrated the most consistent and effective performance across all …

Sequential Data Modeling Of Influenza A Via Traditional, Dwt-Gpr Hybrid, And Deep Learning Architectures, Edmund Fosu Agyemang

Theses and Dissertations

Influenza A is responsible for 290,000 to 650,000 respiratory deaths a year, though this estimate is an improvement from years past due to improved sanitation, healthcare practices, and vaccination programs. In this study, we perform a comparative analysis of traditional, deep-learning and discrete wavelet (DWT)-Gaussian Process (GP) hybrid models to predict Influenza A outbreaks. Using historical data from January 2009 to December 2023, we compared the performance of traditional ARIMA and ETS models, four variants of DWT-GPR models and six distinct deep learning architectures: Simple RNN, LSTM, GRU, BiLSTM, BiGRU and Transformer. The results reveal a clear superiority of all …

Spatio-Temporal Modeling & Goodness Of Fit Testing For Ecological Fire Data, Jedidiah Olof Lindborg

Theses and Dissertations

An analysis of fire data sets resulting from controlled burns was performed. Spatio-temporal models were applied to the data sets to determine which covariates are significant in predicting fire temperature. The data sets were censored and only contain temperatures above 300C, due to a limitation in the measuring device. To handle the censoring, an extrapolation was used to reconstruct the temperatures below 300C. Models were created and run for a data set with the extrapolated temperatures and a data set with all censored temperatures removed. Several aspects of the model were evaluated, such as the chosen hyperparameters, the spatial covariance …

From Sparse Feedback To Sequential Decision-Making: Learning Safety Constraints With Weak Supervision, Siow Meng Low

Dissertations and Theses Collection (Open Access)

Real-world decision-making often involves safety constraints that are implicit, non-Markovian, or difficult to specify directly. Standard reinforcement learning (RL) approaches typically assume access to fully specified cost functions and constraint budgets—assumptions that limit their applicability in domains where such structure must instead be inferred from data. This dissertation develops a sequence of methods for learning safety-relevant structure from weak supervision, such as sparse binary feedback on trajectory segments, and using these signals to guide planning and policy optimization.

The first part of the dissertation introduces a sample-efficient method for planning in continuous Markov Decision Processes (MDPs) using deep reactive policies. …

Cradle: Empowering Foundation Agents Towards General Computer Control, Weihao Tan, Et. Al.

Research Collection School Of Computing and Information Systems

Despite their success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encapsulations of environments with manually designed observation and action spaces. To handle this issue, we propose the General Computer Control (GCC) setting to restrict foundation agents to interact with software through the most unified and standardized interface, i.e., using screenshots as input and keyboard and mouse actions as output. We introduce Cradle, a modular and flexible LMM-powered framework, as a preliminary attempt towards GCC. Enhanced by six key modules, Information Gathering, Self-Reflection, Task Inference, Skill Curation, Action …

Rattler Python, Samer Jabor

Systems Manuals - 2026

The Rattler Python project is an interactive game-based learning system that intends to teach the basic concepts of Python programming through guided instruction, gameplay challenges, and review-based assessments. The document contains a proposal for this system consisting of problem definition, background research, existing solutions, and the proposed product, together with the system scope, assumptions, and the organization of the remainder of this document.

A Neuro-Symbolic Ai Approach To Scene Understanding In Autonomous Systems, Ruwan Tharanga Wickramarachchige Don

Theses and Dissertations

Effectively understanding scenes requires a unified representation of scene data and background knowledge. A neuro-symbolic AI approach to scene understanding leverages such a unified representation to enable advanced expression, inference, and labeling of scenes, improving the perception of autonomous systems.

Scene understanding remains a central challenge in the machine perception of autonomous systems. It requires the integration of multiple sources of information, background knowledge, and heterogeneous sensor data to perceive, interpret, and reason about both physical and semantic aspects of dynamic environments. Current approaches to scene understanding primarily rely on computer vision and deep learning models that operate directly on …

Graph Convolutional Networks Enable Fast Hemorrhagic Stroke Monitoring With Electrical Impedance Tomography, J. Toivanen, V. Kolehmainen, A. Paldanius, A. Hänninen, A. Hauptmann, Sarah J. Hamilton

Mathematical and Statistical Science Faculty Research and Publications

Objective: To develop a fast image reconstruction method for stroke monitoring with electrical impedance tomography with image quality comparable to computationally expensive nonlinear model-based methods. Methods: A post-processing approach with graph convolutional networks is employed. Utilizing the flexibility of the graph setting, a graph U-net is trained on linear difference reconstructions from 2D simulated stroke data and applied to fully 3D images from realistic simulated and experimental data. An additional network, trained on 3D vs. 2D images, is also considered for comparison. Results: Post-processing the linear difference reconstructions through the graph U-net significantly improved the image quality, resulting in images …

An Efficient Detection And Deep Clustering Based Pipeline For Reliable Rodent Ultrasonic Vocalization Analysis, Sabah S. Anis

Theses and Dissertations

Ultrasonic vocalizations (USVs) are critical for understanding rodents' emotional states and social behaviors. However, manual analysis of USVs is time-consuming, subjective, and prone to errors. This thesis presents an automated pipeline that addresses these challenges by performing efficient USV detection and clustering. The proposed approach significantly reduces the time and effort needed to analyze USV data while improving accuracy and reproducibility.

To address this gap, we introduce ContourUSV, a five-step pipeline for USV detection. First, it begins with generating spectrograms from audio recordings, which are then pre-processed to enhance the contrast between USVs and background noise. Key steps include median …