Digital Commons Network^™

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) (Residential Parcels) (Dated February 26, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Incorporating Latent Survival Trajectories And Covariate Heterogeneity In Time-To-Event Data Analysis: A Joint Mixture Model Approach, Fu-Wen Liang, Wenyaw Chan, Michael D Swartz, Bouthaina S Dabaja

Faculty, Staff and Student Publications

Background: Finite mixture models have been recently applied in time-to-event data to identify subgroups with distinct hazard functions, yet they often assume differing covariate effects on failure times across latent classes but homogeneous covariate distributions. This study aimed to develop a method for analyzing time-to-event data while accounting for unobserved heterogeneity within a mixture modeling framework.

Methods: A joint model was developed to incorporate latent survival trajectories and observed information for the joint analysis of time-to-event outcomes, correlated discrete and continuous covariates, and a latent class variable. It assumed covariate effects on survival times and covariate distributions vary across latent …

Escalating Hydrological Extremes And Whiplashes In The Western U.S.: Challenges For Water Management And Frontline Communities, Wenzhao Li, Surendra Maharjan, Joshua B. Fisher, Thomas Piechota, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Western U.S. is experiencing significant changes in its hydrological dynamics, marked by increased variability and rapid “whiplash” shifts between extreme drought and flood conditions. This study quantified these changes using a customized hydrological water year index, which correlated better with surface water storage in the basins than other drought/wetness indicators. Application of the index revealed heightened hydrological extremes and whiplash events post-2015 in all Western U.S. basins, with nearly 72% of stations facing critically dry conditions in 2021 and over 54% experiencing extreme wet conditions in 2023. Future projections indicate a decline of 8.5%–13.2% in non-extreme water year types …

Sustainability Planning For Waste Management In Midwestern Small Suburban Cities, Karen Frances Goodwin

Walden Dissertations and Doctoral Studies

Sustainability planning in small suburban cities, particularly as it relates to waste management programs, remains an underexplored area in scholarly research. Without long-term planning, these cities often react to issues in a fragmented manner rather than implementing proactive policies, negatively affecting public health and well-being. The purpose of this study was to examine sustainable waste management policy processes that enable sustainability planning in Midwestern small suburban cities. Using Jones et al.’s local adaptive capacity framework and Q-methodology, viewpoint patterns were analyzed to understand what motivates decision-makers to foster an environment conducive to sustainability planning. Thirty-one participants representing three local government …

Memory-Augmented Llm Agent For Predicting Locomotion Modes In Construction Activities, Ehsan Ahmadi

LSU Doctoral Dissertations

The construction industry faces significant challenges, including labor shortages, high physical demands, and safety risks, necessitating advanced assistive technologies like exoskeletons to enhance worker efficiency and reduce injuries. However, effective exoskeleton control in dynamic construction environments requires accurate locomotion prediction, a task complicated by the diversity of activities and reliance on supervised learning methods that struggle to generalize. This study investigates a multimodal approach to locomotion prediction, leveraging speech commands and visual data from smart glasses to enable adaptive and safe human-exoskeleton interaction. The research unfolds in two stages: the first develops a framework to evaluate the zero-shot capability and …

System Administration Practices And Experimentation, Nicholas Z. Young

Honors Program Theses and Projects

This undergraduate departmental honors capstone project experiments with and demonstrates System Administration practices that are used in enterprise environments. The skills and practices of System Administrators are crucial to maintain large-scale IT infrastructure. This project aimed to gain a deeper, practical understanding of the role of a System Administrator in an emulated environment. Through hands-on experimentation, this project addressed the responsibilities of a System Administrator, such as controlling user access, adding hardware, automating tasks, monitoring systems, overseeing and developing a backup strategy, maintaining local documentation, and security practices. This project demonstrated some of the complexities that lie in each of …

Modeling Molten Lithium Carbonate As Pollutant Absorbing Agent, Lucian G. Forestieri

Student Summer Scholars Manuscripts

Coal burning generates gaseous pollutants that are toxic to local environments and human health, namely hydrochloric acid and sulfur dioxide ( HCl and SO₂). Current methods for capturing these pollutants are flue gas desulfurization, which utilize solid or water- dissolved carbonates. This method, however, is inefficient mainly due to the product salts blocking further reactions. Molten carbonates may be a more efficient alternative. Experimental work cannot observe these reaction mechanisms, and the small number of current computational models do not match experimental properties. This work aims to develop a computational model of gaseous HCl scattering off the surface …

Real-World Implementation Of A Noninvasive, Ai-Augmented, Anemia-Screening Smartphone App And Personalization For Hemoglobin Level Self-Monitoring, Robert G. Mannino, Julie Sullivan, Jennifer K. Frediani, Paul George, Jeremy Whitson, James Tumlin, L. Andrew Lyon, Erika A. Tyburski, Wilbur A. Lam

Engineering Faculty Articles and Research

Anemia, characterized by low blood hemoglobin (Hgb) levels, afflicts >2 billion individuals worldwide. Here, we report real-world data generated by a smartphone app that noninvasively screens for anemia using only “fingernail selfies.” App data for anemia screening were obtained from >1.4 million uses across the United States enabling geographic mapping of Hgb levels. Of those, 9,061 users also self-reported complete blood count Hgb levels for comparison, resulting in accuracy and performance that match gold standard laboratory testing and a sensitivity and specificity of 89% and 93%, respectively, when using an anemia cutoff of 12.5 g/dL. Geotagged data enabled construction of …

Integrating Artificial Intelligence In Orthopedic Care: Advancements In Bone Care And Future Directions, Rahul Kumar, Kyle Sporn, Joshua Ong, Ethan Waisberg, Phani Paladugu, Swapna Vaja, Tamer Hage, Tejas C. Sekhar, Amar S. Vadhera, Alex Ngo, Nasif Zaman, Alireza Tavakkoli, Mouayad Masalkhi

SKMC Student Presentations and Publications

Artificial intelligence (AI) is revolutionizing the field of orthopedic bioengineering by increasing diagnostic accuracy and surgical precision and improving patient outcomes. This review highlights using AI for orthopedics in preoperative planning, intraoperative robotics, smart implants, and bone regeneration. AI-powered imaging, automated 3D anatomical modeling, and robotic-assisted surgery have dramatically changed orthopedic practices. AI has improved surgical planning by enhancing complex image interpretation and providing augmented reality guidance to create highly accurate surgical strategies. Intraoperatively, robotic-assisted surgeries enhance accuracy and reduce human error while minimizing invasiveness. AI-powered smart implant sensors allow for in vivo monitoring, early complication detection, and individualized rehabilitation. …

Probing Binding And Allosteric Mechanisms Of The Kras Interactions With Monobodies And Affimer Proteins : Ensemble-Based Mutational Profiling And Thermodynamic Analysis Of Binding Energetics And Allostery Reveal Diversity Of Functional Hotspots And Cryptic Pockets Linked By Conserved Communication Network, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Guang Hu, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

KRAS, a historically "undruggable" oncogenic driver, has eluded targeted therapies due to its lack of accessible binding pockets in its active state. This study investigates the conformational dynamics, binding mechanisms, and allosteric communication networks of KRAS in complexes with monobodies (12D1, 12D5) and affimer proteins (K6, K3, K69) to characterize the binding and allosteric mechanisms and hotspots of KRAS binding. Through molecular dynamics simulations, mutational scanning, binding free energy analysis and network-based analyses, we identified conserved allosteric hotspots that serve as critical nodes for long-range communication in KRAS. Key residues in β-strand 4 (F78, L80, F82), α-helix 3 (I93, H95, …

Efficient Eeg Epilepsy Classification And Feature Selections Based On Hellinger Distance, Muhammed Sadiq

Theses and Dissertations

Accurate and efficient detection of epileptic seizures from EEG signals remains a critical challenge due to high-dimensional data, class imbalance, and the limitations of standard classifiers. This thesis introduces two novel models to address these challenges. The first model presents a new classifier based on the Hellinger Distance, specifically designed to enhance discriminative capability and robustness against imbalanced datasets. By integrating the Hellinger Distance Classifier with Particle Swarm Optimization (PSO) for feature selection, this model significantly improves classification performance while reducing computational complexity. Experimental evaluations on the Bonn dataset demonstrate an accuracy of 96.25%, an F1-score of 97.74%, a recall …

Gnns For Network Classification In Single Cell Rna Sequencing Data, Reid C. Sewell

Capstone Projects

A common technique when investigating a disease is to profile gene expression, as this gives unique insights into the functions of a cell. Gene expression data gathered from single cell RNA sequencing can be encoded into a gene co-expression network, which is a graph of potential relationships between different genes. One method for interpreting data encoded as a graph is to use a graph neural network, or GNN. This project designs and implements a GNN architecture to accomplish classification tasks on graph data. Then, given a dataset of gene co-expression networks made from multiple single cell RNA sequencing studies, the …

Phosphomimetic Substitution Of Serine Residue Ser260 With Aspartate Suggests Regulation Of Activity Of Human Cytosolic Malate Dehydrogenase By Phosphorylation, Charles Pelagalli '25, Luke Tischio, Kathleen Cornely

Chemistry & Biochemistry Faculty Publications

Human cytosolic malate dehydrogenase (MDH1) is a key enzyme involved in the malate-aspartate shuttle of eukaryotic cells, and which catalyzes the reaction of oxaloacetate to malate. As MDH1 is responsible for maintaining redox homeostasis by regeneration of NAD+ for glycolysis, its regulation is of particular interest in pharmaceutical applications, specifically in treating cancer cells that proliferate quickly and hence rely greatly on glycolysis. While the regulation of MDH1 by the phosphorylation of key residues has been previously documented, work still remains in identifying the specific residues involved in regulation of the enzyme by phosphorylation. In this study, we used …

Examining The Accuracy Of The Omni Data In Representing Geomagnetic Storm Observations Near Earth And The Effect On Global Modeling, James T. Davis

2025 Spring Honors Capstone Projects - Archive

The accuracy of OMNI dataset being propagated to bow shock nose and used to represent geomagnetic storms is a known issue. Inaccuracies of this data bring erroneous results in scientific endeavors therefore establishing the importance of accuracy and consistency. This case study examines the accuracy of the OMNI data and data near-Earth in representing geomagnetic storms with different drivers on global simulations. This research will include examples of global magnetosphere simulations, such as SWMF, driven with two storms driven by coronal mass ejections, and one driven by a high-speed stream using OMNI data and data near-Earth to illustrate potential variations …

The Evolution And Impact Of Blog Analysis Tools: A Study Of Blogtracker's Comprehensive Approach To Digital Discourse Analysis, Oyindamola Koleoso

Theses and Dissertations

This study presents BlogTracker, a comprehensive web-based platform designed to address the growing complexities of analyzing the modern blogosphere. We detail BlogTracker's evolution from earlier blog analysis tools, highlighting its innovative integration of features including real-time data collection, advanced content analysis, sentiment analysis, influence tracking, and narrative analysis. At the core of our contribution is a robust content extraction system that achieves 91.33% accuracy across diverse blog formats, providing a reliable foundation for all analytical functions. This extraction system effectively distinguishes between primary content and peripheral elements, ensuring high-quality inputs for downstream analysis regardless of source blog structure. The platform's …

Institutions, Indigenous Peoples, And The Structure Of Power In Columbia River Basin Salmon Governance, Christopher Michael Page

Dissertations and Theses

As broad patterns of behavior influenced by norms and rules, institutions structure many aspects of modern society through coordination and the distribution of power. Due to the importance of common-pool natural resources to many aspects of society, they usually involve competition and lie at the intersection of multiple institutions. This combination of institutions, power disparities, and a competitive interest is what scholars have referred to as a "field." Fields can be complex, and the coordination among interests is generally done through a form of governance involving a wide array of laws, regulations, and actors. When at least one of these …

Draft Final 2025 Residential Metals Abatement Program (Rmap) Non-Residential Daycare Soil Sampling: Field Sampling Plan (Fsp) Submittal #15 [Mini Scholars Discovery Academy, Hands On Learning Childcare, Kidz Konnection, Young Explorers, & University On Princeton], Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Modeling Cross-Platform Narrative Templates: A Temporal Knowledge Graph Approach, Ridwan Amure

Theses and Dissertations

Over the past decade, social media platforms have rapidly evolved in scale, functionality, and user engagement, encouraging individuals to maintain active presences across multiple networks. This complex, interconnected ecosystem has also enabled information actors to exploit cross-platform dynamics to amplify the reach of their content and strategically target diverse audiences. Recognizing the persistence and adaptability of such actors, this research emphasizes the need for robust models that can effectively capture and analyze cross-platform narrative diffusion. To this end, we propose a framework that utilizes temporal knowledge graphs to model the evolution and relationships among narratives across platforms. We extract temporal …

Hierarchical Log Bayesian Neural Network For Enhanced Aorta Segmentation, Delin An, Pan Du, Pengfei Gu, Jian-Xun Wang, Chaoli Wang

Computer Science Faculty Publications

Accurate segmentation of the aorta and its associated arch branches is crucial for diagnosing aortic diseases. While deep learning techniques have significantly improved aorta segmentation, they remain challenging due to the intricate multiscale structure and the complexity of the surrounding tissues. This paper presents a novel approach for enhancing aorta segmentation using a Bayesian neural network-based hierarchical Laplacian of Gaussian (LoG) model. Our model consists of a 3D U-Net stream and a hierarchical LoG stream: the former provides an initial aorta segmentation, and the latter enhances blood vessel detection across varying scales by learning suitable LoG kernels, enabling self-adaptive handling …

Clinical Value Of Chatgpt For Epilepsy Presurgical Decision-Making: Systematic Evaluation Of Seizure Semiology Interpretation, Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R. Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J. Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu

Engineering Faculty Articles and Research

Background: For patients with drug-resistant focal epilepsy, surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, electroencephalography (EEG), magnetic resonance imaging (MRI), and intracranial EEG (iEEG). However, interpreting seizure semiology is challenging because it heavily relies on expert knowledge. The semiologies are often inconsistent and incoherent, leading to variability and potential limitations in presurgical evaluation. To overcome these challenges, advanced technologies like large language models (LLMs)—with ChatGPT being a notable example—offer valuable tools for …

Interpreting Spatial And Temporal Variations In Global Air Quality Using A Chemical Transport Modeling Framework, Deepangsu Chatterjee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Air quality is a major health concern. Exposure to fine particulate matter (PM2.5) and nitrogen oxides (NOx = NO + NO2) is a leading mortality risk factor across the world. Numerous cohort studies conducted over the past two decades have identified strong associations between ambient air pollution and human mortality, highlighting the adverse health effects of PM2.5 and NO2 exposure. My thesis includes three studies that contribute to a better understanding of air quality. In many regions, including South Asia, elevated emissions from various sectors and sparse ground monitoring are significant challenges. The concurrent development and use of the high-performance …

Turn-On Fluorescent Glucose Transport Bioprobe Enables Wash-Free Real-Time Monitoring Of Glucose Uptake Activity In Live Cells And Small Organisms, Monica Soma Hensley, David Hutchings, Abdelrahman Ismail, Marina Tanasova

Michigan Tech Publications

The direct link between sugar uptake and metabolic diseases highlights the iminent need for molecular tools to detect and evaluate alterations in sugar uptake efficiency as approaches to identify disease-relevant metabolic alterations. However, the strict requirements of facilitative glucose transporters regarding substrate binding and translocation pose challenges for developing effective fluorescence molecular probes. Based on the state-of-the-art understanding of glucose recognition by facilitative transporters (GLUTs), we designed a glucopyranoside mimic - GluRho - that delivers the “turn-on” rhodamine B to live cells via glucose transport, including major transporters GLUTs 1-4. The high binding affinity achieved through the secondary interaction between …

Should Physicians Take The Rap? Normative Analysis Of Clinician Perspectives On Responsible Use Of 'Black Box' Ai Tools, Ben H Lang, Kristin Kostick-Quenet, Jared N Smith, Meghan Hurley, Rita Dexter, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

Background: Increasing interest in deploying artificial intelligence tools in clinical contexts has raised several ethical questions of both normative and empirical interest. One such question in the literature is whether "responsibility gaps" (r-gaps) are created when clinicians utilize or rely on such tools for providing care, and if so, what to do about them. These gaps are particularly likely to arise when using opaque, "black box" AI tools. Compared to normative and legal analysis of AI-generated responsibility gaps in health care, little is known, empirically, about health care providers views on this issue. The present study examines clinician perspectives on …

Machine Learning Course: A 15-Week Interactive Curriculum With Code And Case Studies, Pegah Khosravi

Open Educational Resources

This open-access machine learning course is a comprehensive 15-week curriculum developed and published on GitHub with full Google Colab compatibility. It combines theoretical concepts with hands-on Python coding, real-world datasets, and structured projects covering regression, classification, clustering, deep learning, transformers, and multimodal AI. The course is designed for students, educators, and researchers interested in applied machine learning, including biomedical applications. It includes explainable AI components and ethical discussions to align with modern AI standards. The course is maintained by BioMind AI Lab at CUNY.

Towards The Next Generation Of Storage Stack For Nand Flash Memory-Based Systems, Ziyang Jiao

Dissertations - ALL

The explosive growth of data has led to increased attention on NAND flash-based solid-state drives (SSDs), which offer high performance, low power consumption, and significant capacity per unit volume when compared to traditional hard-disk drives (HDDs). However, as NAND flash memory density continues to scale, modern SSDs suffer from what is known as fail-slow symptoms, and their performance degrades over time as they wear out. In this dissertation, we focus on understanding and addressing the performance, reliability, and sustainability challenges of modern flash-based storage systems by modeling key metrics, analyzing the design tradeoffs between these metrics, and optimizing existing storage …

Harnessing Llms To Detect Hate Speech, Weibin Cai

Theses - ALL

Hate is a sentiment, while hate speech refers to the expression of hate in a form that targets and attacks specific groups, such as race, religion, or gender. With the rise of the internet and social media, hate speech has spread rapidly, gaining wide exposure and posing threats to individual well-being, the profits of major tech companies, and social stability. As a result, both industry and academia have turned their attention to the study of hate speech. One of the most active areas is hate speech detection, which involves training models to predict whether a given piece of content is …

Chemical Reversal Of Beta-Lactam Resistance And Induction Of Hyper-Susceptibility In Pseudomonas Aeruginosa By Limiting Horizontal Gene Transfer Under Beta-Lactam Stress, Aimee Iradukunda

Dissertations - ALL

The emergence of antibiotic resistance poses a significant threat to global health, with certain bacterial strains evolving to resist multiple drugs. Urgent action is necessary to develop new antibacterial agents that effectively target these resistant strains; however, no new classes of antibiotics have been approved in recent decades. This research employs innovative biological tools to identify and highlight factors influencing resistance dynamics. Additionally, this study refines the novel approach by utilizing adjuvants to chemically repurpose existing antibiotics and improve their effectiveness against antibiotic-resistant strains. Pseudomonas aeruginosa, recognized for its adaptability, persistent infections—especially in cystic fibrosis patients—and widespread antibiotic resistance, serves …

Diel Patterns Of Biogeochemical Indicators In Tidally-Dominated Creeks, Juliana Calderone

Honors Theses

Marshes and swashes are vital environments as a controlling barrier between land affected by various pollutants and the ocean. Eutrophication and the effects of this process can be detrimental for the areas experiencing it. I am interested in ways areas that have little contact with human interactions compare to areas that are heavily urbanized, and whether either of these locations is at a higher risk for eutrophication. Using spectrophotometry and fluorometry, I analyzed samples collected from the relatively undeveloped and restricted-access locations of Waities Island Beach and Dunn Sound monthly for dissolved nutrients, and chlorophyll. At the time of sampling, …

Identification And Preclinical Assessment Of Novel Therapeutic Modalities In Environmental Exposure-Induced Lung Disease, Aaron D. Schwab

Theses & Dissertations

Environmental lung diseases are preventable respiratory conditions either caused or made worse by inhaled environmental exposures. Contemporarily, environmental lung diseases are most associated with workplace exposures given specific occupational processes aerosolize inflammatory agents that can be inhaled at high concentrations. Although a considerable amount is known regarding immunoglobulin (Ig)E-mediated responses to environmental exposures, little is known about non-IgE mediated respiratory conditions resulting from lipopolysaccharide (LPS)-enriched organic dust exposure(s). Chronic respiratory diseases such as asthma, hypersensitivity pneumonitis, chronic obstructive pulmonary disease (COPD), and pulmonary fibrosis have all been identified as environmental lung diseases caused or exacerbated by such environmental dusts. Therapeutic …

Multi-Modal Mri For The Pre-Clinical Evaluation Of Hiv-Linked Changes In The Central Nervous System, Gabriel Gauthier

Theses & Dissertations

Though the inception of anti-retroviral therapy (ART) has fundamentally changed the life expectancy of human immunodeficiency virus (HIV) patients, accessibility and outcomes vary enormously along demographic lines. Even for people living with HIV (PLWH) with perfect access and adherence to anti-retroviral drugs (ARVs), modern treatment plans are fundamentally unable to secure complete viral remission for patients. The cause of this perpetual infection is the persistence of viral reservoirs in the central nervous system (CNS), hidden beyond the reach of modern ARVs, leaving patients to deal with lifelong medication side-effects and risks of developing HIV-associated neurodegenerative disorders (HAND). Despite improving outcomes …