Digital Commons Network^™

Characterization Of The Thermally Driven Red Hue Effect In Coated And Uncoated Concrete Systems: Implications For Post-Fire Assessment In Wildland Urban Interface Communities, Juan C. Palominos Jr

Master's Theses

The increasing frequency and intensity of Wildland-Urban Interface (WUI) wildfires, such as the destructive 2025 Pacific Palisades Fire that destroyed over 6,000 structures, have underscored the urgent need for rapid post-fire safety assessment methodologies. This study sought to quantitatively characterize the Thermally Driven Red Hue Effect (TRHE), a unique, irreversible color shift observed in architectural coatings and concrete substrates, to determine its reliability as a permanent visual record of thermal exposure. Concrete substrates were formulated with three distinct coarse aggregates: gold granite (14.7% Fe), red cinder (22.4% Fe), and green rock (33.6% Fe) and coated with a 20 PVC waterborne …

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Multimodal Machine Learning For Soil Burn Severity Mapping Across California Wildfires, Sanjana Checker

Master's Theses

Accurate mapping of soil burn severity (SBS) is critical for post-fire watershed management, erosion risk assessment, and ecological recovery planning, yet traditional field-based approaches remain costly, time-intensive, and spatially limited. This thesis presents a machine learning pipeline for wall-to-wall SBS classification across California wildfires using multi-sensor satellite imagery, terrain derivatives, and bioclimatic covariates. Field-collected SBS observations (n = 2,180) from 52 wildfires occur- ring between 2013 and 2025, sourced from the U.S. Forest Service and CAL FIRE, were used to train and evaluate multiple classification architectures within a Google Earth Engine and Google Cloud-based prediction framework. After upsampling the unburned …

Thermally Induced Color Changes In Iron Oxide Pigments Used In Architectural Coatings, Han Diep

Master's Theses

The 2025 Palisades Fire was one of the most destructive wildfires in the history of Los Angeles, destroying thousands of structures and severely impacting the communities after. This widespread destruction demonstrated an urgent need for more effective wildfire prevention strategies. Architectural coatings do not only provide aesthetics and protection against environmental conditions but can also function as a thermal indicator when a fire breaks out. This study examines the thermally induced color transformation of iron oxide pigments, commonly used in earthtone paint, to provide information relevant to CAL FIRE for improved analysis of wildland-urban interface (WUI) fire behavior and mitigation …

Comparing Allometric Models To Machine Learning Models For Aboveground Biomass Estimation In Agroforestry Systems In Kenya, Samuel Irungu Kigotho, Kennedy Senagi, John Olukuru, David Masereti Makori, Elfatih M. Abdel-Rahman, Evans Omondi

All Peer-Reviewed Publications

This study compared traditional allometric models with machine learning (ML) techniques for accurately estimating aboveground biomass (AGB) in six Acacia species within Kenyan agroforestry systems. Using tree diameter at breast height (DBH) and total height as inputs, the research evaluated allometric models (Chave’s, Brown’s, and Henry’s) against ML models, including Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Regression (SVR). This research advances the field by benchmarking machine learning and classical allometric models at the species level within Kenyan agroforestry systems and employing SHapley Additive exPlanations (SHAP) for interpretability analysis. Model performance was validated using …

Invasion Patterns And Niche Dynamics Of The Pollinivorous Florida Calligrapher, Toxomerus Floralis (Diptera: Syrphidae) In The Afrotropical Region, Burgert Muller, John Midgley, Georg Goergen, Ali Al Jahdhami, Michelson Azo'o Ela, Terence Bellingan, Simon Cavaillès, Robert Copeland, Marc De Meyer, Martin Hauser, Allen Holmes, Ximo Mengual, Gabriel Nève, Menno Reemer, Jeff Skevington, Gunilla Ståhls, Eugène Sinzinkayo, John Smit, Axel Ssymank, Genevieve Theron, Kurt Jordaens

All Peer-Reviewed Publications

The rapid spread of Toxomerus floralis (Fabricius, 1798) (Diptera: Syrphidae) within the Afrotropical region is described. We characterise and compare the climatic niches of T. floralis in its native (Southern North America, Central America and South America) and invaded (Afrotropical Region) range to assess the potential for further expansion across Africa and beyond, and included future global climate models and socioeconomic pathways as projections. Occurrence data for native and invaded ranges were obtained from field sampling by authors, major collections of Afrotropical Syrphidae, collections records and occurrence data from the Global Biodiversity Information Facility (GBIF), including iNaturalist data. Single and …

Climate-Driven Stochastic Modelling Of Crimean-Congo Haemorrhagic Fever Transmission In Uganda, P. G. Kpatchana, J. Aduda, K. M. Agboka

All Peer-Reviewed Publications

Crimean-Congo haemorrhagic fever (CCHF) is a climate-sensitive tick-borne zoonosis that remains a significant public health concern in Uganda, where temperature and vapour pressure deficit influence tick ecology and consequently disease transmission. This study aimed to develop and analyse a climate-driven stochastic model for CCHF transmission among ticks, livestock, and humans under environmental variability in Uganda. A compartmental transmission model was formulated and extended into a stochastic differential equation framework by incorporating multiplicative environmental noise. Climate-dependent tick recruitment, development, and mortality were parameterized using district-level temperature and vapour pressure deficit data to capture spatial heterogeneity in transmission risk. Theoretical analyses based …

Spatiotemporal Pah Patterns In Size-Fractionated Particles (Pm>10-Pm0.1) From Northern Thailand Biomass Burning Via Sentinel-2, Phakphum Paluang, Watinee Thavorntam, Sarawut Sangkham, Phuchiwan Suriyawong, Hisam Samae, Thaneeya Chetiyanukornkul, Masami Furuuchi, Worradorn Phairuang

Research outputs 2022 to 2026

Biomass burning, particularly from forest fires and crop residue burning during the dry season, is a major source of particulate pollution across many Asian countries. However, accurately identifying these emissions remains challenging due to uncertainties in burned area estimation and the limited availability of country-specific emission factors. This study quantified the spatiotemporal distribution of emissions from biomass burning using satellite imagery. Burned areas were classified using a random forest (RF) algorithm implemented on the Google Colaboratory (Colab) platform. The RF model showed strong performance, with a kappa coefficient of 0.85 and an average accuracy of 0.81. Emission estimates for the …

The Association Between Ethical Ai Use And Well-Being Among Young Adults In The Uae: A Structural Equation Modeling Approach, Areej Elsayary, Zeina Hojeij, Lames Abdul Hadi

All Works

This study examines the association between ethical AI use and young people’s emotional, social, and psychological well-being in the United Arab Emirates (UAE), where the number of hours spent on GenAI serves as a moderator. Framed within the Theory of Planned Behavior and aligned with the Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) and SDG 13 (Climate Action), this research examines how responsible digital engagement is associated with both individual mental health and broader digital sustainability. A Structural Equation Modeling approach assessed how ethical AI behaviors are associated with well-being. A total of 204 participants, predominantly …

Applications Of Prior And Novel Computational Tools In Mental Health Treatment, And Their Potential To Uncover The Explanatory Gap, Ambika Vyas

University Honors Theses

The explanatory gap is a widely discussed concept in scientific and philosophical literature. In neuroscience, the solution to the explanatory gap is highly sought out, but the general consensus is that it is unsolvable. Numerous articles discuss the explanatory gap alongside computational tools and how these tools could aid neuroscientists in uncovering the mental health explanatory gap. However, significant developments in machine learning have been made since 2020, coinciding with the rise in Large Language Models (LLMs). This thesis is a literature review on computational methods, tools, and devices developed and utilized by researchers to improve how mental health disorders …

Public Acceptance Of Meat-Reduction Policies Across Cultures: Comparing Singapore And Switzerland, Bianca Wassmann, Shu Tian Ng, Mark Chong, Angela K. Y. Leung, Michael Siegrist

Research Collection Lee Kong Chian School Of Business

Purpose – As meat-reduction policies are discussed across the globe, many are met with public resistance. Cultural values may help explain this pushback, yet their role in shaping support for food policy remains poorly understood. This study is the first to apply cultural cognition theory to food policy by examining how cultural worldviews shape the acceptance of meat-reduction interventions in Singapore and Switzerland—two economically developed countries with contrasting cultural profiles. Design/methodology/approach – In an online survey, participants (Singapore: n = 357; Switzerland: n = 495) rated their acceptance of 11 meat-reduction interventions (e.g. taxes, subsidies, labelling). We then analysed to …

Draft Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System – First Quarter 2026, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System – Fourth Quarter 2025, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final Bpsou Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final 2022 Unreclaimed Sites Sampling: Ur-07 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final 2023 Unreclaimed Sites Sampling: Ur-31 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final 2024 Unreclaimed Sites Sampling: Ur-46 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Butte Priority Soils Operable Unit (Bpsou) Unreclaimed (Ur) Sites New And Mahoney (Ur-23) Construction Completion Report (Ccr), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Deployment-Aware Deep Learning For Computer Vision: Efficient Architectures From 3d Segmentation To Mixed Reality, Bahar Uddin Mahmud

Dissertations

Deep learning has become the dominant approach for solving vision-centric problems; however, its successful deployment in real-world applications remains limited by high computational cost, data dependency, and insufficient integration with practical and human-centered environments. While state-of-the art deep learning models often achieve impressive performance in controlled settings, they frequently fail to generalize or operate efficiently under deployment constraints such as limited resources, complex data modalities, and real-time interaction requirements. These limitations motivate the need for a deployment-oriented deep learning framework that balances accuracy, efficiency, and practical usability.

This dissertation investigates the design and deployment of efficient deep learning architectures for …

Happycal: Designing Text And Image-Based Supports For Savouring Positive Work Experiences, Molly Stewart, Minghao Cai, Anthony Tang, Sam Liu, Chris Mosunic, Sowmya Somanath

Research Collection School Of Computing and Information Systems

Savouring positive work experiences can promote positive affect and well-being at work, yet there is limited guidance on how digital applications can support workers to engage in savouring. We developed HappyCal, a work-focused savouring application offering two forms of savouring support: text-based, a common modality in workplace reflection tools, and images, a largely unexplored approach in work-related savouring. We conducted an exploratory qualitative study where participants (N=36) used HappyCal over five days and engaged in savouring through either a text-only modality (n=17) or text input paired with image output (n=19). We found that (1) participants in both groups reported heightened …

“Alexa, Do Not Say That In Front Of My Boss!” A Cross-Cultural Comparison Of User And Ai Preferences For Privacy-Aware Smart Speaker Interactions Across Contexts, Lynne Warin, Emily Aurelia, Anthony Tang, Emily Aurelia, Delphine Reinhardt

Research Collection School Of Computing and Information Systems

Due to their limited ability to reason about the social context in which they are used, smart speakers pose significant privacy risks by responding in ways that may violate people's implicit social boundaries. We conducted a cross-cultural vignette study (N = 944) in Germany and Singapore to investigate how situational factors—specifically social context (bystander relationships and closeness), physical context (location), and interaction context (topic and deceptive intent)—regulate user preferences for smart speaker responses. Our results demonstrate that these factors are superior predictors of response preferences than dispositional user traits (i.e., intrinsic personal traits). We identify two distinct social dynamics: a …

Gc-Ms-Based Comparative Analysis Of Compounds In Host Plants And Insect Gut Extracts, Rita Dill, Kimberly Smith, Shelia Okoth, Xavier Cheseto, Anne Osano

All Peer-Reviewed Publications

Background/Objectives: Herbivorous insects feed on plant tissues to obtain nutrients necessary for growth and development while simultaneously ingesting diverse plant secondary metabolites. Understanding the fate of these compounds during digestion is important for advancing knowledge of insect nutritional physiology and diet-associated biochemical processes. This study aimed to comparatively profile metabolites in host plants and corresponding insect gut extracts to generate insights into compound transfer and compositional changes within these systems. Methods: Gas Chromatography-Mass Spectrometry (GC-MS) metabolomics was combined with Ultraviolet-Visible (UV–Vis) quantification of total phenols and flavonoids to compare host plant tissues and insect gut extracts in three systems: fall …

Climate Change Reduces Pollination Services And Sunflower Yields Across Europe And Northern Africa, Stella Gachoki, Clémence Riva, Danilo Bevk, Yamina Haider, Noureddine Adjlane, Ioannis Manthos, Bojan Stipešević, Zlatko Puškadija, Marin Kovačić, Leonidas Charistos, Fani Hatjina, Fabrice Requier

All Peer-Reviewed Publications

Sunflower (Helianthus annuus) productivity is highly dependent on pollinators, yet the effects of climate on pollination services and crop yield remain poorly understood. In this study, we investigate how temperature gradients influence flower-visiting communities, pollination services, and sunflower productivity across Europe and Northern Africa. We conducted standardized two-year (2022 and 2023) pollination exclusion experiments across 36 sunflower fields spanning a broad climatic gradient, from temperate regions in Slovenia to arid conditions in Algeria. We found that sunflower production (seed set, seed number, and oil content) relied heavily on insect pollination. However, this benefit declined with rising temperatures, likely due to …

Municipality Of Bayamón V. Exxon Mobil Corp. (2025): Bringing Racketeering Charges For Climate Justice, Ilinca C. Johnson

Pace Environmental Law Review

Environmental justice communities should have their climate change damages heard in the courtroom. One means to increase environmental justice claims is through claims under the federal Racketeer Influence and Corrupt Organizations (RICO) Act. Using Municipality of Bayamón v. Exxon Mobil Corp. (2025) as a model, this Article suggests a novel RICO case strategy to pursue climate damages for marginalized communities. Fundamentally, environmental justice RICO claims involve careful case design based on the climate-related damages a marginalized community has faced because of the long-term deception by fossil fuel actors upon those communities. Pursuing such claims forwards the intersectional issues faced by …

Intervention Levers For Stunting Reduction In Indonesia: Evidence From The 2023 Indonesian Health Survey Data, Iwan Ariawan, Hafizah Jusril, Zahra Izza Afifa, Azka Fitri, Elmarizha Sekar Utami, Mikail Hasan, Dwi Puspasari

Kesmas

Stunting remains the largest public health challenge among macro-nutrition problems in Indonesia, affecting almost a quarter of children under five in 2023. The prevalence is considered high according to the World Health Organization standard. This study analyzed 15 aggregated provincial variables from the 2023 Indonesian Health Survey using Structural Equation Modeling (SEM), focusing on determinants of stunting among children under two to identify primary intervention levers. Findings indicated that intervention urgency should focus on the first 1,000 days, particularly the steep increase in stunting prevalence observed in the 12–24-month age range. While the highest prevalence is in Eastern provinces (e.g., …

Parameter Density Estimation For Cardiac Electrophysiology Models Using Data Consistent Deep Learning, Michael Luo

Dissertations

Mathematical models of biological rhythms and excitable systems can provide insights into mechanisms underlying cardiac electrical dynamics. However, estimating the parameters of these models from experimental observations is often difficult due to noise, heterogeneity, and unobserved variables. For example, in an electrocardiogram (ECG) recording, information about the electrical properties of different regions of the heart is compressed into a single voltage trace. Additionally, variability within these signals may contain important information about population heterogeneity, regional differences in electrophysiology, and time-dependent modulation.

This dissertation develops, explores, and evaluates methods that perform feature-based distributional inference for complex nonlinear dynamical systems. The objective …

Re: Approval Letter For The Draft Final 2026 Butte Priority Soils Operable Unit (Bpsou) Type B Borrow Material Submittal #3 (Dated May 6, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Streamlined Biomedical Image Processing Pipelines, Jiehyun Kim

Graduate Doctoral Dissertations

This dissertation focuses on advancing carotid artery analysis through a series of visualizations and deep learning tools for calcified plaque assessment and related biomedical imaging tasks. Accurate plaque evaluation is essential, but current workflows depend on slow, clinician-dependent manual review. To address these limitations, this work introduces the CACTAS framework, a set of tools and methods that enable fast and reliable plaque segmentation for clinicians.

The first study, the CACTAS-Tool, provides a web-based labeling tool that enables clinicians to label plaque directly in three dimensions through a streamlined one-click interface. This tool significantly reduces the effort required to generate high-quality …

Computer-Aided Development Of Novel Antioxidants, Rita Bernadett Vlocsko

Graduate Doctoral Dissertations

Physiological redox homeostasis is a fine balance between prooxidants and antioxidants that are integrated elements of several reduction-oxidation mechanisms at molecular, organellar, cellular and tissue levels. When this equilibrium is disrupted and prooxidants become dominant, the body relies on endogenous and exogenous antioxidants to counterbalance the dysregulation and ultimately prevent the progression of oxidative stress. Reactive species (reactive oxygen species, reactive nitrogen species, or reactive sulfur species) are significant contributors to prooxidant activity. Over the years, substantial knowledge has been accumulated regarding their origin and roles in disease development, leading to the discovery and development of antioxidants that effectively target …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2026 Revised Draft Final Backfill And Cover Soil Quality Assurance Project Plan (Qapp) (Dated May 13, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.