Digital Commons Network^™

Design And Fabrication Of Petri Dish Optimized For High-Frequency Acoustic Microscopy Using 3d Printing, Tuna Pesen, Beyza Ceren Eren, Arda İnanç, Bora Akgün

Turkish Journal of Physics

High-frequency imaging in acoustic microscopy requires the use of Petri dishes with thin and acoustically transparent bottoms to minimize signal attenuation and distortion. Commercially available options suitable for this purpose are often expensive or limited in compatibility with custom setups. Here, we present a cost-effective and easily customizable alternative developed in our laboratory, consisting of a 3D-printed frame combined with commercially available stretch film. The stretch film serves as an ultrathin (8 µm thickness) base that supports efficient high-frequency acoustic transmission, enabling clear and reliable imaging. Beyond acoustic microscopy, the adaptable design is also compatible with other modalities such as …

Properties Of Enjoyable Mathematical Contexts From The Student Perspective, Emilie Nadine Hendrickson

Theses and Dissertations

Researchers continue to grapple with how to meaningfully engage students in mathematical content. Many students report disengagement due to perceptions that mathematics is difficult, irrelevant, boring, or anxiety-inducing. This study sought to understand how students interpret and respond to different mathematical problem contexts, with particular attention to the reasons students describe certain problems as enjoyable or unenjoyable. Using semi-structured interviews, this research examined student responses to a variety of mathematical problem types primarily across affective engagement. Students reflected on specific problem contexts and explained which features supported or hindered their enjoyment and engagement. Students described that contexts were enjoyable have …

Ai And The Music Industry: Its Current Status And A Speculative Projection Of Its Evolutionary Trajectory, Rhett D. Morris, Clayton Rosati, Stefan Fritsch

Honors Projects

Music serves as one of society's biggest cultural outlets, allowing millions to share in what used to be a uniquely human form of expression. The commodification of music has built a huge industry full of companies and platforms that have used technology and property laws to shape music's relationship with the public. This study aims to look into the future to see how AI and its implementation could affect the structure of the music industry. To look into the future, this piece establishes two of the most pressing kinds of AI technology for the music industry and looks to contextualize …

Toroidal Plasmonic Nanodimers For Enhanced Near-Infrared Emission In Heterostructured Inp Quantum Dots, Arda Gülücü, Emre Ozan Polat

Turkish Journal of Physics

Near-infrared (NIR) emitters operating in the 650--900 nm spectral range are highly attractive for imaging and sensing in turbid media. However, cadmium-free InP-based quantum dots (QDs) often exhibit limited brightness owing to nonradiative recombination pathways and inefficient photon outcoupling. In particular, heterostructured InP QDs may possess band alignments that induce partial spatial separation of charge carriers, thereby reducing the electron-hole wavefunction overlap. This characteristic modifies the intrinsic recombination dynamics and increases the sensitivity of their emission to the surrounding photonic environment. Here, we investigate silver toroidal plasmonic nanoantenna dimers (Ag TPNDs) using finite-difference time-domain (FDTD) simulations as a geometry-tunable platform …

Radiation Pressure And Membrane Dynamics In Cavity Optomechanics: Interaction Hamiltonian And Quantization, Mahmut Can Özuygur

Turkish Journal of Physics

Cavity optomechanics explores the interaction between light confined in optical cavities and mechanical oscillators, primarily driven by radiation pressure forces. These interactions enable significant advances in precision measurements, quantum information processing, and tests of fundamental quantum mechanics. This paper presents a detailed analysis of membrane vibration and radiation pressure force within a cavity optomechanical system. The membrane's equation of motion is derived, the radiation pressure force is evaluated within the Lorentz force formalism, and the corresponding interaction Hamiltonian is formulated. Quantization of the resulting Hamiltonian enables the investigation of quantum phenomena, including entanglement generation and quantum state transfer, and provides …

Observational Constraints On The Structure-Induced Dark Energy Model, Ali̇ Kazim Çamlibel

Turkish Journal of Physics

A new phenomenological dark energy model, originally associated with large-scale structure formation and proposed as a solution to the fine-tuning and coincidence problems related to the cosmological constant, was analyzed within the framework of General Relativity in a Friedmann-Robertson-Walker spacetime and its model parameters were estimated using cosmic chronometers and recent DESI data. It turns out that the proposed model can serve as an alternative evolving dark energy model with a novel equation of state function. Given the form of this phenomenological energy density ansatz, which rises with the nonlinear structure growth in the universe and declines as cosmic voids …

Extreme Heat And Its Impact On Public Transit Ridership In Nyc, Craig Denton

Theses and Dissertations

This thesis explores the connection between extreme heat events and public transit ridership patterns in New York City, with a particular emphasis on low-income communities. It investigates the intersection of socioeconomic factors and heat-related challenges, analyzing how extreme temperature periods influence overall transit use and why certain routes or neighborhoods experience greater declines in ridership during these events.

Utilizing existing literature, NYC-specific transit and climate datasets, and the broader context of transit equity, this research aims to inform strategies that strengthen climate resilience within urban transportation systems. The study’s findings are intended to support policy development and planning initiatives that …

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.

Changes In Water Quality And Microbiota Over Two Years In Florida Hard Clam (Mercenaria Mercenaria) Hatcheries, Bonnie Getter

Electronic Theses and Dissertations 2020 - Present

This thesis characterized the water quality and bacterial communities in nine hard clam hatcheries over two production years through weekly or biweekly water quality and chemistry monitoring, monthly bacterial plating in the second year of production, and select 16S microbiome sampling at select hatcheries to address production bottlenecks and support the reliable production of high-quality seed for Florida’s growing hard clam aquaculture industry. Logistic regression models showed that water source was distinguished by pH, salinity, alkalinity, and nitrite, whereas geographic location was distinguished by temperature, salinity, nitrate, and calcium; temperature, dissolved oxygen, salinity, and alkalinity distinguished seasons. Vibrio bacteria differed …

From Homogeneous To Heterogeneous Adaptive Bounded-Confidence Opinion Dynamics On Networks, Sally Hafez, Fatma R. Farag, Amira S. N. Tawadros

Northeast Journal of Complex Systems (NEJCS)

Adaptive bounded-confidence models (ABCMs) elucidate the coevolution of agent states and network structure via local interactions and rewiring mechanisms. Traditional formulations assume uniform interaction parameters, leading to distinct regime shifts encompassing fragmentation, polarization, and consensus. A symmetric heterogeneous extension of the adaptive bounded-confidence model is introduced, in which interaction parameters vary according to whether agents belong to the same or different groups. The model retains the original update and rewiring protocols but integrates within-group and between-group confidence bounds alongside tolerance thresholds. Initially, the classic homogeneous model is replicated to establish a reference point. Subsequently, the heterogeneous extension is assessed under …

A Stabilized Weighted Interior Penalty Method For Thermal Convection Model In Heterogeneous Porous Media, Yuanyuan Hou, Qianqian Ding, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

In this article, we propose and analyze a stabilized weighted interior penalty method for solving the thermal convection problems in heterogeneous porous media. We first transform the thermal convection model into the pressure primal form with homogeneous Neumann boundary condition and develop a symmetric weighted interior penalty method to handle the discontinuous Darcy number and automatically adjust the penalty coefficient corresponding to the varying permeability. Then we recover the velocity by a stabilized method and incorporate it into the energy equation to obtain the temperature. The stability and convergence rates of the numerical solutions are rigorously proved and verified by …

Alaska Earthquake Center Quarterly Review October-December 2025, Heather Mcfarland, Beth Grassi, Austin Holland, Nate Murphy, Elisabeth Nadin, Carolyn Parcheta, Michael West

Alaska Earthquake Center Reports

This series of technical quarterly reports from the Alaska Earthquake Center (AEC) includes detailed summaries and updates on Alaska seismicity, the AEC seismic network and stations, fieldwork, our online presence, public outreach, and lists publications and presentations by AEC staff. Multiple AEC staff members contributed to this report.

Painting A Scene: 3d Painterly Rendering From Curves To Rebelle, William M. Luttrell

All Theses

Stylized 3D rendering has seen much development and success over the past few years. From Spider-Man: Across the Spider-Verse to The Bad Guys, many studios have developed tools to incorporate stylistic elements from graphic novels, comic books, watercolor paintings, and more into their productions. This stylization process incorporates the pacing, visual style, and themes from the source medium into the animated work, allowing a much greater freedom of expression for artists and directors.

Inspired by these films as well as the needs of the short film Kate Shelley and the Bridge of Darkness currently in production, This paper presents …

Evaluation Of High Temperature Thermal Energy Storage At A Field Site, Samuel R. Jennings

All Theses

A pilot-scale high-temperature thermal energy storage site has been developed at Clemson University and began operation in April 2025. High-temperature heat transfer fluid is circulated through a hexagonal array of borehole heat exchangers, which are installed up to 35 ft deep in the subsurface. The thermal energy is stored in the ground and is extracted by circulating the heat transfer fluid at a lower temperature. This test was expected to last more than six months and there was no way to evaluate the temperature data being measured. Since only temperature was being monitored, it was difficult to predict when key …

The Aggregation Of Microplastics By Enhancing Extracellular Polymeric Substance Production In Pseudoalteromonas Sp. Ncimb 2021 To Improve Removal Efficiencies In Environmental Matrices, Janelle L. Mercer

All Theses

Microplastics (MP) are ubiquitous in the natural environment and are a growing threat due to their small size and durability. Plastics are released into the environment through improper waste management, wastewater treatment outfalls, industrial spills, agricultural runoff, and landfills. These particles breakdown into secondary MP through degradation pathways. MP, less than 5 mm, require intricate removal techniques from water systems. Filtration techniques, though viable and effective, have implementation constraints due to high cost, maintenance demands, and filter fouling. By integrating coagulation and flocculation processes prior to filtration, MP removal efficiencies can increase, while minimizing operational challenges during filtration. Extracellular polymeric …

Differential Effects Of Generative Artificial Intelligence On Formative And Summative Assessment Performance: A Quasi-Experimental Longitudinal Study, Md Istiak Morsalin

Master's Theses

Generative artificial intelligence has unsettled a core assumption of course assessment: that scores on unsupervised work reflect what students can do unassisted. This study tests whether the widespread availability of ChatGPT altered student performance differently on formative versus summative assessments in Business Analytics and Foundations, a required undergraduate quantitative-methods course taught by one instructor across nine cohorts. In a quasi-experimental longitudinal design, the Fall~2022 cohort ($n = 90$), the last to finish before ChatGPT's public release, serves as a control against eight post-ChatGPT cohorts spanning Spring~2023 through Summer~2025 ($N = 646$). Outcomes were drawn from McGraw-Hill Connect records using matched …

Success Of New Ideas In Online Platforms: An Idea Network Perspective, Yimei Zhou, Qian Tang, Vincent Z.W. Mack Mack, Shao Yi Liaw

Research Collection School Of Computing and Information Systems

On online platforms, new ideas often emerge by recombining existing ones within idea networks. Unlike traditional knowledge networks, idea networks represent curated, meaning-based associations among ideas, offering a distinct lens on recombination. Drawing upon a hypergraph perspective, we investigate how new idea success depends on their structural and content attributes, and how collaborative participation shapes these attributes. Using data from an ideation platform, we find that both structural embeddedness and bridging benefit new idea success. Content diversity has no direct effect, but it amplifies the benefits of bridging while constraining those of embeddedness. Both crowd contributions and ideator expertise strengthen …

Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh

Research Collection Library

No abstract provided.

Advancing Sdg 9 Through Ai-Powered Waste Diversion, Ally Murphy

Goal 9: Industry, Innovation and Infrastructure

No abstract provided.

Spring Ai 2026 Workshop And Speaker Series Report, Gregory Blike, Hannah (Nyingi) Brown, Dora (Dawn) Nguyen, Rami Huu Nguyen, Ajanee Igharo, Frayni Calderon, Moumita Saha, Chengjie Zheng

Paul English Applied Artificial Intelligence (AI) Institute Publications

The AI Workshop and Speaker Series was organized by the Student Advisory Council of the Paul English Applied Artificial Intelligence Institute at the University of Massachusetts Boston with the guidance of Distinguished Professor of Computer Science Wei Ding to create a practical and student-centered AI learning space. The Spring 2026 series included workshops on LinkedIn Optimization, Data Mining, GitHub, Prompt Engineering, Machine Learning of Structured Data, and Applied LLMs with Responsible AI Use in Research, while the broader speaker series introduced students to AI career development, generative AI and LLMs for cybersecurity, transportation security, political sciences, and AI in biomedicine. …

Sem-Pdpl: Semantic Exposure Graphs For Privacy-Law-Informed Risk Assessment Of Public Social-Media Data, Heba Ismail

All Works

Public social-media content often contains self-disclosed personal attributes that appear low-risk in isolation but become privacy-relevant when linked across posts, platform accounts, or user-level traces. Existing research has advanced privacy-sensitive content detection, de-anonymization analysis, social-media research ethics, and privacy-compliance workflows; however, limited work operationalizes how personal-data disclosures combine structurally and how these structures can be translated into auditable governance actions. This paper proposes SEM-PDPL, a computational, privacy-law-informed risk-assessment framework for modeling public social-media exposure as semantic exposure graphs and mapping graph patterns to controls aligned with the United Arab Emirates Personal Data Protection Law (PDPL) and compatible with GDPR principles. …

Developing Solvent Tolerant Microbial Membranes: Lipid Extraction And Laurdan Fluorescence Approaches For Biofuel Optimization, Gladstone Anku

Electronic Theses and Dissertations

The high demand for sustainable energy has increased interest in advanced biofuels, though production is limited by solvent toxicity to microbial hosts. This study investigated the role of lipid composition in modulating membrane fluidity and solvent tolerance using Bacillus subtilis as a model organism. Five strains were cultured, and membrane lipids were extracted and analyzed using thin-layer chromatography and gas chromatography–mass spectrometry; however, inconsistent results limited compositional characterization. To address this problem, reconstituted vesicles composed of phosphatidylglycerol (PG) and phosphatidylethanolamine (PE) were used as model membranes. Membrane fluidity was assessed using Laurdan fluorescence spectroscopy by measuring generalized polarization (GP) values …

Imaging Oxygen Near Implanted Medical Devices Through Tissue With X-Ray And Ultrasound Modulated Luminescence Chemical Imaging, Vigjna Abbaraju

All Dissertations

Oxygen plays a crucial role in stem cell maintenance, tissue regeneration, disease progression, and treatment efficacy. For example, understanding oxygen dynamics within implanted medical devices, such as bone scaffolds, is essential for successful tissue regeneration and can serve as an early indicator of infection. The existing oxygen sensing and imaging techniques are often limited by narrow imaging depth, low spatial resolution in vivo resulting in poor understanding of oxygen dynamics in tissue microenvironments. This dissertation describes the development of implantable sensors using X-ray scintillators and thermochromic leuco dye paired with phosphorescent oxygen dye (PtTFPP) to image oxygen using X-ray luminescent …

Structure And Dynamics Of Associative Polymers Under Quiescent State And Flow, Rosita Sivaraj

All Dissertations

Associative polymers, including ionizable polymers, are widely used in membranes, coatings, fuel cells, energy storage, and other advanced soft materials. Their properties are governed by ionic aggregation and associative interactions, which influence chain mobility, phase behavior, self-assembly, interdiffusion, and flow response. This dissertation employs large-scale molecular dynamics (MD) simulations to investigate the structure, dynamics, phase behavior, interdiffusion, and extensional flow response of ion-containing and associative polymer systems under quiescent and nonequilibrium conditions.

The influence of molecular architecture is first examined by comparing ring and linear associative polymers using the Kremer–Grest bead-spring model. In linear chains, their closed-loop architecture reduces interchain …

Can Kinematics Specify Tool Use Affordances?, Tyler Duffrin

All Dissertations

Object properties such as length, shape, and heaviness, as well as affordance-based properties such as strike-with-ability and poke-with-ability, can be perceived via dynamic touch as functions of inertia tensor invariants. The primary question addressed here was whether people can perceive these same power and precision properties for purely virtual objects, which lack dynamic physical forces. The Kinematic Specification of Dynamics (KSD) principle asserts that missing dynamics are lawfully specified by kinematic (visual) motion patterns, such that kinematic information alone may support successful interactions with virtual objects. In three experiments, we investigated (1) whether virtual reality (VR) users could calibrate to …

Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu

Research Collection School Of Computing and Information Systems

Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challenging in data-scarce settings. While Large Language Models (LLMs) perform well in few-shot NLP tasks, they are not well-suited for time-series data and are computationally expensive for both training and inference. In this work, we propose a novel EARD framework that combines an autonomous agent and an LLM-based detection model, where the agent acts as a reliable decision-maker for \textit{early time point determination}, while the LLM serves as a powerful \textit{rumor …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar

Master's Theses

Three-dimensional cameras provide direct geometric measurements, but their cost, weight, power requirements, and calibration constraints can limit their use in various lightweight or large-scale sensing systems. A potential alternative is to use conventional two-dimensional RGB cameras together with geometric reconstruction models that infer a partial three-dimensional representation from images. This thesis evaluates that possibility for next-best-view (NBV) selection through Sentinel, an occlusion-centered system for static, object-centric scenes with known camera poses and intrinsics. Sentinel converts source RGB observations into pseudo-geometry using monocular depth or point-map predictions, combines those predictions with camera-ray evidence, identifies occluded unknown regions, and selects a candidate …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

Domain Adaptation Of Facial Age Estimation For Law Enforcement Mugshot Repositories, Jorge Alejandro Pacheco Roque

Open Access Theses & Dissertations

Facial age estimation supports law enforcement via image-based, age-filtered queries, age-progressive re-identification, and bulk record labeling, where prediction accuracy determines if the resulting decisions can be trusted. State-of-the-art models excel on web imagery but incur higher error on mugshots due to domain shift between the professionally lit, filtered, and posed web photographs used during pre-training and the uniform backgrounds, uncooperative expressions, and decades of evolving capture technology found in mugshot collections. We address this gap by adapting SwinFace - a state-of-the-art multi-task Swin Transformer with public code and pretrained weights, trained on color face imagery for face recognition, facial expression …