Digital Commons Network^™

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

On-Site Water Management Field Sampling Plan (Fsp), 2025 Update, Mark Thompson, Rampart Solutions

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Thriving In The Age Of Ai: Navigating Ai Identity Threat Through Ai Job Crafting, Yuming He

Theses and Dissertations in Business Administration

As artificial intelligence (AI) technologies like GenAI tools increasingly reshape the workplace, employees increasingly face threats to their work identity. Grounded in the identity threat response model and job crafting theory, this study investigates how AI identity threat influences employee AI job crafting behaviors and how these behaviors, in turn, affect vitality and learning. Using survey data from 521 full-time employees who actively engage with AI tools, the results indicate that AI identity threat stimulates both AI approach job crafting and AI avoidance job crafting. AI approach crafting enhances both vitality and learning, while AI avoidance crafting only supports vitality. …

Specialization Or Diversification? Creators’ Strategies On User-Generated Content Platforms, Ziwei Ye

Theses and Dissertations in Business Administration

Recent advancements in digital platforms have reshaped content creation and distribution. User-generated content (UGC), created and shared by internet users, is transforming entertainment, communication, and information sharing. The rise of UGC has fueled the growth of the "creator economy"—an ecosystem of creators, users, and advertisers facilitated by platforms such as YouTube and TikTok. While prior research has primarily explored how UGC platforms incentivize content quantity and quality, this study advances the literature by examining how creators' content strategies influence consumer attention and how platform mechanisms shape this relationship, offering new insights into the interplay between creator behavior and platform design. …

Advancing Fake News Detection With Graph Neural Network And Deep Learning, Haji Gul, Feras Al-Obeidat, Muhammad Wasim, Adnan Amin, Fernando Moreira

All Works

In the modern era of digital technology, the rapid distribution of news via social media platforms substantially contributes to the propagation of false information, presenting challenges in upholding the accuracy and reliability of information. This study presents an updated approach that utilizes graph neural networks (GNNs) alongside with advanced deep learning techniques to improve the identification of false information. In contrast to traditional approaches that primarily rely on analyzing text and assessing the credibility of sources, our methodology utilizes the structural information of news propagation networks. This allows for a detailed comprehension of the interconnections and patterns that are indicative …

Building Narratives And Probing Concepts: Preparing Materials For Co-Design With Autistic Livestreamers, Terrance Mok, Tyson Hartley, Anthony Tang, Adam Mccrimmon, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Based on ten semi-structured interviews with autistic Twitch streamers, we introduce a series of scenario-based design narratives coupled with technology design concepts as a starting point for co-design discussion about autistic streaming. This work builds on prior thematic analysis of the unique intersection between autism and livestreaming. Our user-centered scenarios highlight the needs, goals, and challenges of autistic individuals in livestreaming contexts. By using evocative narratives, the scenarios serve to facilitate empathy and deeper engagement with the needs of autistic users, and help facilitate and support co-creative dialogues and discussions about new technology designs. We contribute this starting point for …

Hvi: A New Color Space For Low-Light Image Enhancement, Qingsen Yan, Yixu Feng, Cheng Zhang, Guansong Pang, Kangbiao Shi, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang

Research Collection School Of Computing and Information Systems

Low-Light Image Enhancement (LLIE) is a crucial computer vision task that aims to restore detailed visual information from corrupted low-light images. Many existing LLIE methods are based on standard RGB (sRGB) space, which often produce color bias and brightness artifacts due to inherent high color sensitivity in sRGB. While converting the images using Hue, Saturation and Value (HSV) color space helps resolve the brightness issue, it introduces significant red and black noise artifacts. To address this issue, we propose a new color space for LLIE, namely Horizontal/Vertical-Intensity (HVI), defined by polarized HS maps and learnable inten sity. The former enforces …

Large Language Models For Logical Fallacy Detection, Nicole Anne Hui-Ying Teo, Donghao Huang, Erik Cambria, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Identifying logical fallacies is essential for maintaining log-ical reasoning and reducing false information in a variety of domains, such as the media, law, and education. We present an extensive study on the use of large language models (LLMs) for logical fallacy detection and provide a comparative overview of model performance across various fallacy classes. We evaluate the logical fallacy detection capabilities of multiple state-of-the-art models (LLaMA, Qwen, Gemma, Phi) utilizing accuracy, precision, recall, and F1-score as assessment measures. Accord-ing to our findings, our models do well on simple fallacies like “circular reasoning,” but they have trouble with more interpretive reasoning …

Digital Resurrection Of Thonis-Heracleion: Technological Advances In Underwater Archaeology And A Speculative Ai-Driven Reconstruction Methodology, James Hutson, Passent Chahine

Faculty Scholarship

This article synthesizes past archaeological research on the submerged Egyptian city of Thonis-Heracleion, critically reviewing excavations and technological interventions deployed since its rediscovery by Franck Goddio and the IEASM team. Situated approximately 10 meters beneath Aboukir Bay near Alexandria, the city represents a significant nexus of Greek and Egyptian cultural heritage, vividly documented in classical sources such as Herodotus and Strabo. Prior excavations have recovered temple complexes, colossal statues, ritual artifacts, and an extensive array of ancient shipwrecks, mapping only a fraction of the extensive site. These investigations utilized pioneering geophysical methods, including multibeam sonar, side-scan sonar, and photogrammetry, establishing …

Watersmart Farms - Desalination: Inventory And Analysis, Ela Wendell, Abdulla Rasheed, Sharmina Begum, Vaibhav Patel, Goruck Soubans, John K. Ruprecht

Natural resources commissioned reports

A drying climate means traditional water supply resources of farms in southern Western Australia are frequently unable to meet agricultural production demands. However, extensive, untapped sources of brackish or moderately saline water ( <   20,000mg/L total dissolved solids (TDS) are present in nearly all agricultural areas experiencing water shortages. In response, a small, yet increasing, number of farms have privately financed and installed small-scale desalination units to treat locally sourced, salt-impaired water. This approach not only provides a new source of freshwater to the farm portfolio, but is unaffected by changing climatic and weather conditions. Since the majority of the early adopters of on-farm desalination draw the salt-impaired water from groundwater bores, the technology implementation also mitigates local salinization of agricultural land due to groundwater rise, while decreasing reliance on the heavily subsidized, centralized water supply schemes operated by Water Corporation (WC).

The WaterSmart Farms Desalination (WSFD) project was undertaken to assess the nature and performance of existing, small-scale, on-farm desalination systems, including their economics, sustainability, availability, and weaknesses; and to assess these decentralized systems’ applicability and uncertainties for broader application on farms throughout southern Western Australia. The project was undertaken by three major partners, WA Department of Primary Industries and Region Development (DPIRD), WC, and the Harry Butler …

Nonlinear Physics Of Parity-Broken Fluids, Sudheesh Srivastava

Dissertations, Theses, and Capstone Projects

This thesis explores parity-breaking mechanisms, nonlinear wave phenomena, and localization transitions across different physical contexts. First, we examine modulation instability in parity-breaking systems, deriving modified nonlinear Schr¨odinger equations that reveal direction dependent instabilities. Next, we investigate wave turbulence, demonstrating numerically that parity-breaking dispersion significantly alters turbulent cascades and modifies their statistical properties. Lastly, we analyze localization in quasiperiodic tight- binding model based on polariton condensate lattice. Collectively, these studies illustrate the universal role of symmetries and nonlinear interactions in shaping macroscopic behaviors, facilitating interdisciplinary insights.

How Argentina Won The 2022 Fifa Men's World Cup: A Data Story, Aniruddha Parthasarathy

Dissertations, Theses, and Capstone Projects

This project analyzes Argentina’s 2022 FIFA Men’s World Cup win using open-source football (soccer) data. The project evaluates the team’s performance at a micro-level across three domains: without possessing the ball, possessing the ball and the team’s in-game management tactics. A statistical framework, i.e., multiple linear regression modeling, was used to identify the five key defensive actions influencing the Argentinian team’s intensity of pressure applied, and visualized by heatmaps and time-segmented plots. More specifically, an Expected Threat (xT) analysis quantified the threat or danger from passes and progressive carries (moving the ball at least 10 meters), revealing that Lionel Messi’s …

On The Design Of A Framework For Large-Scale Exploratory Graph Analytics, Oliver Andres Alvarado Rodriguez

Dissertations

Large-scale exploratory graph analytics merges data science with high-performance computing to extract critical insights from network-representable data. Data scientists routinely analyze data from the natural, social, and computing sciences by representing it as networks, or graphs, where objects become vertices and their relationships become edges. This representation allows data scientists to add graph analytics to their toolbox. However, designing tools for large-scale exploratory graph analytics is challenging due to the complexities of graph algorithms, such as high communication in distributed systems and large memory demands. These challenges can lead to overly complex software, which limits usability and development to a …

Fact-Checking As A Multi-Step Process: From Ambiguity Resolution To Claim Validation, Wenbo Wang

Dissertations

The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. Fact-checking—the process of verifying claims against credible evidence—has emerged as a critical safeguard against misinformation. Yet, the task is fraught with challenges: claims are often ambiguous, context-dependent, or composed of multiple intertwined assertions, while automated systems struggle to replicate the nuanced reasoning of human experts. This dissertation addresses these challenges by reimagining fact-checking as a multi-step, knowledge-guided process that systematically resolves ambiguity, decomposes complexity, and validates claims through structured reasoning. Additionally, the proposed …

Field Journal: The Excluded Middle, Carrie E. Kouts

Masters Theses

What does it look like to engage with organisms and landscapes at the periphery of anthropocentric value structures? How does one break the internalized myth that the “built” environment is excluded from the natural world? When does a hyper-mobile and hyper-commodified society confront the exponential crisis of animal death? Within this series of journal entries, field notes, collection observations, weird prose, and sensory musings, one will find questions on the nature of being human and the complex narratives of care we encounter in a world shared with more-than-humans. Each handwritten vignette and photograph from daily life weaves a non-linear and …

A Novel Framework For Dynamic Graph Representation Learning With Mamba, Ashish Pandey

Theses

Dynamic graph embedding is a key technique for modeling temporal dependencies in evolving networks. While transformer-based models perform well, their quadratic complexity limits scalability on long graph sequences. This thesis compares transformer approaches with the Mamba architecture-a linear-complexity state-space model—for temporal graph embedding.

Two frameworks are proposed: DG-Mamba and GDG-Mamba. DG-Mamba uses standard GCN-based spatial encoding, while GDG-Mamba incorporates domain-aware edge features using Graph Isomorphism Network with Edge Convolution (GraphGINE). Experiments on UCI, Reality Mining, Slashdot, Bitcoin-OTC, and SBM datasets show that Mamba-based models match or exceed transformer performance, especially on graphs with high temporal variability.

The thesis also applies …

Artificial Intelligence And Astronomy: Lab Manual For Generative Ai-Based Learning Activities, Vasiliy Znamenskiy

Open Educational Resources

This laboratory manual introduces an innovative approach to teaching astronomy by integrating generative artificial intelligence (AI) tools into hands-on educational activities. Aimed at undergraduate and general education students, the manual guides learners through interactive exercises that involve evaluating AI-generated text responses, creating scientifically inspired images, and producing short educational videos about astronomical phenomena. By engaging with platforms such as ChatGPT, Gemini, DALL·E, and InVideo, students develop critical thinking skills, enhance their digital literacy, and deepen their understanding of space science. The method emphasizes inquiry-based learning, creativity, and scientific communication, preparing students to become thoughtful users of AI in academic and …

Photojournalism In The Age Of Deepfakes: The Role Of Media Literacy And Ethical Standards In Restoring Trust In Visual Reporting, Ionnnis Kontos, Katerina Chryssanthopoulou, Ioannis Galanopoulos-Papavasileiou

All Works

This article explores the impact of deepfake technology on photojournalism, highlighting its role in undermining trust in visual media. As deepfakes allow for the creation of highly realistic manipulated content, they pose significant challenges regarding the authenticity of journalistic imagery and erode the authority of visual truthfulness. The widespread use of deepfakes has led to a decline in public confidence in the credibility of news, raising concerns about the future of photojournalism in an era of digital deception. As a solution to regaining viewers’ trust, this article suggests a twofold approach: First, it emphasizes the importance of media literacy in …

Advanced Machine Learning Techniques For Social Support Detection On Social Media, Olga Kolesnikova, Moein Shahiki Tash, Zahra Ahani, Ameeta Agrawal, Raúl Monroy, Grigori Sidorov

Computer Science Faculty Publications and Presentations

The widespread use of social media highlights the need to understand its impact, particularly the role of online social support. In this study, we present a dataset of YouTube comments, initially comprising 66,272 entries, which was refined to 42,695, with a subset of 10,000 comments selected for detailed analysis without additional filtering. The dataset is annotated for three classification tasks: (1) distinguishing supportive from non-supportive comments, (2) determining whether the support is directed at an individual or a group, and (3) further categorizing group support into six subtypes (Nation, LGBTQ, Black Community, Women, Religion, and Other). To address data imbalances …

Large-Scale Groundwater System Characterization Using Pressure Responses To Barometric Perturbations Caused By The 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption, Anhua He, Yang Liu, Fan Zhang, Huamei Zhang, Ramesh P. Singh, Yanzhang Wang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Hunga Tonga-Hunga Ha'apai volcanic erupted on 15 January 2022, causing Lamb waves to propagate throughout the global troposphere. However, reports on volcanic eruptions–pressure fluctuations and water level dynamics are lacking. We quantified the propagation processes of Lamb waves induced by the Tonga volcanic eruption. Barometric pressure data collected at 1-min intervals at 485 meteorological stations in China showed that the eruption induced an atmospheric pressure event with an amplitude of ∼2 hPa over an hour and a wave speed of 295 m/s. Concomitant groundwater levels were available at 338 wells to find the barometric response to the volcanic event. The …

Agent-Based Modeling: Introduction And Actuarial Applications, Rick Gorvett

Mathematics and Economics Faculty Working Papers

Agent-based modeling (ABM) has become an important and valued approach to modeling complex systems. In this paper, I advocate for actuaries to recognize the complex systems-nature of socioeconomic and risk processes and for ABM models to become a regular resource in our actuarial toolkits. These models allow for the observation of potential macro-behavior emerging from the underlying agent-level micro-activity and characteristics. Therefore, ABM models can provide significant insight into the quantification of risk and the identification of optimal strategies. This paper is an introduction and guide to ABM models, and it includes several case studies to illustrate their utility.

2025 Revised Draft Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Wildlife Road Mortalities During Covid-19 Pandemic-Related Lockdown In South Texas: A Comparative Survey, Bradley Evan Beer, Kevin W. Ryer, Md Saydur Rahman, John H. Young Jr., Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Mortalities of wildlife caused by collisions with vehicles along roads are increasing in prevalence, threatening the existence of various species and populations. The COVID-19 pandemic-related lockdown provided an opportunity to gain a better understanding of how wildlife vehicle mortality occurrences change in response to anthropogenic variables and how varying survey methods influence obtaining mortality data. In this study, data were collected in three observation periods: pre-lockdown (PreL), during lockdown (DL), and post-lockdown (PostL) in south Texas. There were 194 wildlife mortalities recorded during weeks 4–27 of 2020. Results of this study showed that road mortality survey counts did not change …

Mechanisms And Equation Improvement For Gas Seepage In Coal Seams Around Boreholes Subjected To High-Pressure Co2 Foam Fracturing, Pang Mingkun, Zhang Tianyu, Pan Hongyu, Song Xianfeng, Wu Shan, Zhang Tianjun

Coal Geology & Exploration

Objective The special low-porosity, low-permeability structures of high-gas-content coal seams restrict efficient gas drainage. To address this issue, this study accurately determined the seepage parameters of annularly fractured coals around boreholes subjected to CO₂ foam fracturing to enhance both the design accuracy of boreholes for gas pre-drainage from coal seams and gas drainage efficiency. Methods Using an independently developed apparatus for gas seepage experiments on fractured coals around boreholes, this study investigated the coals with pores and fractures distributed in an annular pattern around boreholes from the perspective of varying initial pore structures. Specifically, this study analyzed the evolutionary …

Diffusion Mechanisms Of Power-Law Grouts In Water-Rich Sand Layers During Permeation Grouting, Xie Bao, Cheng Hua, Wang Xuesong, Li Mingjing, Liu Xiangyang, Han Xueyu

Coal Geology & Exploration

Objective This study aims to clarify the spherical diffusion patterns of power-law grouts in water-rich sand layers during permeation grouting and their influential factors. To this end, permeation grouting experiments were conducted to gain insights into the quantitative impacts of varying grouting parameters on grout diffusion.Methods Using model experiments on spherical diffusion during permeation grouting, this study analyzed the macroscopic diffusion morphologies and microscopic infilling effects of grouts, as well as the trends of permeation and soil pressures during grouting. Then, based on the spherical diffusion equations for permeation grouting that consider multi-effect coupling, this study analyzed the factors …

An Improved Mp-Nmo Correction Method Based On Multiparameter Fitting And Its Application, Yang Xiaohui, Yu Pengfei, Zhang Jiawei

Coal Geology & Exploration

Objective and Methods Normal moveout (NMO) correction is a core step in seismic data processing. However, the conventional NMO correction method tends to cause wavelet stretching when processing wide-angle or large-offset seismic data, leading to degraded stacking quality and distorted amplitude variation with offset (AVO) attributes. Although the matching pursuit (MP)-NMO correction method can mitigate the stretching effect, it will cause lateral discontinuity due to overlapping seismic events. Therefore, this study developed an improved MP-NMO correction method based on multiparameter fitting. Specifically, during MP decomposition, cubic polynomial fitting was applied to the amplitude, frequencies, and phases of wavelets from the …

Discovery Of Drug Transporter Inhibitors Tied To Long Noncoding Rna In Resistant Cancer Cells; A Computational Model -In Silico- Study, Mohanad Diab, Amel Hamdi, Feras Al-Obeidat, Wael Hafez, Ivan Cherrez-Ojeda, Muneir Gador, Gowhar Rashid, Sana F. Elkhazin, Mahmad Anwar Ibrahim, Tarek Farag Ismail, Samar Sami Alkafaas

All Works

Chemotherapeutic resistance is a major obstacle to chemotherapeutic failure. Cancer cell resistance involves several mechanisms, including epithelial-to-mesenchymal transition (EMT), signaling pathway bypass, drug efflux activation, and impairment of drug entry. P-glycoproteins (P-gp) are an efflux transporter that pumps chemotherapeutic drugs out of cancer cells, resulting in chemotherapeutic resistance. Several types of long noncoding RNA (lncRNAs) have been identified in resistant cancer cells, including ODRUL, MALAT1, and ANRIL. The high expression level of ODRUL is related to the induction of ATP-binding cassette (ABC) gene expression, resulting in the emergence of doxorubicin resistance in osteosarcoma. lncRNAs are observed to be regulators of …

Dsa-Api: Data Standardization Automation Using Ai-Powered Apis, Andrew Asher Turner

Master's Theses

The common factor with current implementations of Artificial Intelligence (AI) is data. Companies are constantly looking for new ways to analyze data, but it comes in various formats: Text, Comma Separated Value (CVE), JavaScript Object Notation (JSON), Extensible Markup Language (XML), and Excel. How can AI be adapted to standardize formats for data analysis, integration, and digestion efficiently? Published research acknowledged that Machine Learning (ML) and AI can provide an automated method to speed up this process and limit the human decision-making error. With the advancement in AI, Application Programming Interfaces (APIs) prompt the idea that they can take in …

Who Should Take Responsibility For Artificial Intelligence Actions And Outcomes? Perception Of Auditors As Users Of Ai Systems, Hanh Hoang Le

Doctoral Dissertations

As artificial intelligence (AI) systems become increasingly embedded in auditing processes, questions arise regarding how professional auditors perceive and allocate responsibility for AI-assisted decisions. This study investigates the effects of AI explainability and auditors’ perceived autonomy on perceived responsibility in the context of audit decision-making. Drawing on theories of moral responsibility and professional judgment, the study employs a 2x2 experimental design using hypothetical audit scenarios to manipulate levels of AI explainability and auditors’ autonomy. Hierarchical regression analysis reveals that perceived autonomy statistically significantly increases auditors’ perception of responsibility for AI-assisted decisionmaking, whereas AI explainability is not a significant predictor. Additionally, …

Fired And Fractured: An Analysis Of Broken Ceramics, Evan Mcguire

Honors Projects

How does the construction of a ceramic object affect how it breaks? How does the force applied affect this break? These questions are based on my first-hand observations of the multitude of ceramic fragments found in different states of decay at archaeological sites. To answer these questions, I created samples that imitate ancient ceramics and then broke them in different ways. I then analyzed the fracture surfaces and looked for evidence of weak points in the objects. Pieces that were hit by a blunt force, such as a hammer, had radial fractures that formed along paths that had clusters of …