Digital Commons Network^™

How Do Parents Influence Female Students' Engineering Trajectory?, Niloufar Bayati, Cameron Denson

Journal of Research in Technical Careers

Using the Parental Socialization Framework, this research provides a detailed analysis of how early STEM exposure, parental confidence in abilities, and gender-neutral upbringing contribute to the development of STEM identities among women. Employing a hermeneutic phenomenological approach, six undergraduate women engineering majors were interviewed in-depth about their parents' influence on their STEM pathways. The findings reveal that parents' high academic expectations, confidence in their daughters' abilities, verbal and non-verbal encouragement, and early STEM opportunities are pivotal in steering female participants toward engineering. The study also underscores the importance of creating a gender-neutral environment that allows girls to explore and develop …

From In-The-Head To In-The-World: Frameworks For Understanding And Applying Computational Thinking, Justin Olmanson, Gretchen K. Larsen, Azadeh Hassani

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In the five decades since Papert coined the term Computational Thinking (CT), it has become a core framework for thinking about learning, problem-solving, design, and creativity. Although CT is most commonly, and initially, associated with the cognitive orientations involved in coding and learning to code, it also includes situated and critical processes related to computational problem solving. Herein we unpack ways researchers in different fields and points in time have organized CT. We include creative coding as a uniquely generative lens for rethinking CT, outlining its potential as an expressive, constructionist, and culturally situated practice. In doing so, we explore …

Connecting The Montessori Philosophy Through Edtech, Olivia Chilvers

Electrical Engineering and Computer Science (MS) Theses

This thesis explores the evolving landscape of Educational Technology (EdTech) and examines how the Montessori educational philosophy is translated into digital learning environments. The study aims to identify design implications for children’s educational applications (apps) that seek to align with Montessori principles and what aspects of a Montessori-based application excel over a non-Montessori-based application. A qualitative thematic analysis was conducted using a custom-developed codebook to analyze user reviews posted by guardians of children on the Apple App Store. These reviews pertained to apps identified as Montessori-based, either through explicit labeling or meta-data. In addition to this review analysis, a user …

Experimental Study Of Process Parameter Effects On Internal Defects In Titanium Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia, Braden Mclain, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Wire-based laser metal deposition is an additive manufacturing process that can be used in the efficient manufacturing of complex structures. This paper utilizes a three-beam coaxial laser wire system to explore the effect of process parameters on the resultant deposition density. The reduction in or elimination of defects is important to the mechanical properties of the additively manufactured material and the widespread adoption of additive manufacturing processes. In this work, two-bead-wide walls were deposited under varying experimental conditions, including the traverse feed rate and workpiece illumination proportion. A method for calculating the bead pitch and layer height increment based on …

Interfacial Defect Properties Of High-Entropy Carbides: Stacking Faults, Shockley Partial Dislocations, And A New Evans-Polanyi-Semenov Relation, Samuel E. Daigle, Stefano Curtarolo, William G. Fahrenholtz, Jon Paul Maria, Douglas E. Wolfe, Eva Zurek, Donald W. Brenner

Materials Science and Engineering Faculty Research & Creative Works

Using first principles calculations, {111} intrinsic stacking fault (ISF) energies in groups IVB, VB, and VIB high-entropy transition metal carbides (HETMCs) are shown to be predictable from an optimized rule of mixtures based on the atomic arrangement near the stacking fault. A composition-independent linear relationship is demonstrated between the ISF energies and the unstable stacking fault (USF) energies along the (112¯){111} γsurface slip path. This relationship represents a new application of the Evans-Polanyi-Semenov principle by treating the ISF and USF energies as analogous to the heat of reaction and transition state barrier in chemical reactions. Further, a full defect energy …

Intermediate Stage Densification Kinetics Of High-Entropy Ceramics During Spark Plasma Sintering, Steven M. Smith, William G. Fahrenholtz, Greg E. Hilmas, Stefano Curtarolo

Materials Science and Engineering Faculty Research & Creative Works

The intermediate stage densification kinetics of (Hf, Nb, Ta, Ti, Zr) B2 and (Hf, Nb, Ta, Ti, Zr) C were studied using a Coble creep rate model. (Hf, Nb, Ta, Ti, Zr) B2 was synthesized by boro/carbothermal reduction and (Hf, Nb, Ta, Ti, Zr) C was synthesized by carbothermal reduction. Both ceramics were densified by spark plasma sintering at 1700–1850°C. The activation energies for densification were 575 ± 53 kJ/mol for the high-entropy boride and 646 ± 4 kJ/mol for the high-entropy carbide. The densification mechanisms were grain boundary diffusion for the high-entropy boride and lattice diffusion for the high-entropy …

Effects Of Processing And Microstructure On The Oxidation Of Zrb2-Sic In Co2, Marharyta Lakusta, Jeremy L. Watts, William G. Fahrenholtz, David W. Lipke

Materials Science and Engineering Faculty Research & Creative Works

Oxidation kinetics and oxide scale microstructures were compared for ZrB2-30 vol% SiC composites fabricated by hot press sintering of powders and by pressure less sintering of additively manufactured billets. Oxidation in CO₂ was conducted at temperatures up to 1400 °C with durations up to 900 h. All specimens exhibited parabolic oxidation kinetics. Materials with similar composition but different processing histories exhibited differences in oxidation behavior that become evident at extended durations (200–900 h) and higher temperatures (1200–1400 °C). Oxidation rates generally increased with grain size, e.g., at 1000 °C for 200 h, oxide scale thickness increased from 36 to …

Storytelling In Undergraduate Engineering Courses As Inclusive Curriculum: Improving Students’ Sense Of Belonging, Identity, And Persistence, Brooke Heller

Boise State University Theses and Dissertations

The engineering field experiences high attrition rates and a historical lack of diversity in the United States. Sense of belonging and identity have been shown to impact persistence, especially for people from historically marginalized communities. This three-paper dissertation is focused specifically on this phenomenon in academia and methods of contributing to improving and progressing conditions. To pivot to a new paradigm in which people from diverse backgrounds feel welcome and valued, there is a need for more inclusive practices in the field, particularly in the form of curriculum in academia. Inclusion has been shown to improve outcomes for students from …

Uncertainty Quantification Of Turbulent Premixed Flames, David L. Brown

Honors Theses

This thesis presents an uncertainty quantification (UQ) study of turbulent premixed flames, focusing on the impact of uncertainties in operating conditions on the normalized consumption speed. Namely, temperature, pressure, and equivalence ratio are the operating conditions that are under study. Due to significant computational demands associated with direct MC methods for UQ, surrogate modeling techniques including Polynomial Chaos Expansion (PCE), Stochastic Collocation (SC), and Gaussian Process (GP) are evaluated based on efficiency and accuracy. Through this study, PCE is identified as the optimal surrogate model due to its accuracy and significantly reduced computational costs. PCE is subsequently applied to investigate …

A Simplified Thermal And Battery Model For Off-Grid Solar Air Conditioning In Florida’S Hurricane Context, Steven A. Sanford

Honors Theses

Florida’s hurricane-prone climate often leaves residents without power and at risk of dangerous indoor heat conditions. This thesis examines whether an off-grid, solar-powered air conditioning system can feasibly maintain safe indoor temperatures over a one-week outage period during peak hurricane season. A simplified, lumped-capacitance thermal model and an energy-based (Coulomb-counting) battery state of charge (SoC) approach were developed in MATLAB to simulate a DC-powered air conditioner (the DC48 unit) in a single-zone space. Historical weather and solar irradiance data from Vero Beach, Florida, represent the hot and humid conditions typical of post-hurricane scenarios. The model uses an on/off plus deadband …

The Effect Of Catalyst Choice On Biodiesel Yield And Quality Using Waste Cooking Oil As A Feedstock, Neka Long

Honors Theses

Biodiesel is one current area of interest as a replacement for traditional diesel fuel. Benefits of biodiesel include that it can be derived from renewable resources, and it possesses properties similar to that of traditional diesel fuel. Biodiesel is often produced through a catalyzed transesterification process, which involves the use of a catalyst to aid in the conversion of triglycerides into alkyl esters. A method called the transesterification double step process (TDSP) was researched and used in this project due to the success seen using this method for the conversion of waste cooking oil to biodiesel. In this project, four …

A Causal Model Of Performance Shaping Factors For Human Reliability Analysis In Manufacturing., Prameet Ranjan Jha

Electronic Theses and Dissertations

Human reliability analysis is a critical component of probabilistic risk assessment, aimed at predicting and mitigating human errors in complex systems. This dissertation develops a novel approach to human reliability analysis in manufacturing by integrating structural equation modeling and Bayesian networks to improve the estimation of human error probabilities. Traditional human reliability assessment methods, such as the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) and the Technique for Human Error Rate Prediction (THERP), provide structured techniques for estimating human error probabilities. However, these methods often fail to capture the complex interdependencies among performance shaping factors (PSFs), limiting their applicability in …

Exploring User Sentiment On Social Issues Via Neural Network Transfer Learning In Digital Communities, Ananya R. Vangoor

Electrical Engineering and Computer Science Undergraduate Honors Theses

Understanding public sentiment on social issues is crucial for gauging the stance of the general population. Traditionally, surveys have been a common approach for this. However, to capture more candid opinions, social media provides a rich source of unadulterated opinions. By analyzing social media statements, we can gain insights into the perspectives of specific groups. More specifically, we will investigate the attitudes of the public into the relationship between hard work and success in the workplace.

Using a neural network trained on tweets from X, formerly known as Twitter, we can categorize each tweet as either pro-luck or pro-meritocracy. But …

Predictive Modeling Of Electro-Optic Modulators Under Electromagnetic Interference, Hasan Ahmed

Optical Science and Engineering ETDs

In this age of electronic warfare, directed energy research is of utmost importance to ensure national security, robust military defense systems and gain a competitive edge in research worldwide. This thesis explores the intentional directed energy impacts on electro-optic devices by developing analytical predictive models through experimental data validation. An electro-optic modulator known as Mach-Zehnder modulator (MZM) is used to understand the implications of intentional EMI. A low frequency RF signal is injected in the MZM to create an EMI environment. The MZM behavior changes due to EMI during a pseudo-random bit sequence signal modulation were studied through analyzing receiver …

Plansyncc - A Construction Document Translation Software, Easton Richard Abreo, Ashton Lee Gandrup, Javier Solis

Construction Management

PlanSyncc was born from shared construction internship experiences, where the team observed significant language barriers between supervisors and tradesmen, leading to miscommunication, inefficiencies, and safety risk. Motivated by this problem, PlanSyncc developed an AI-powered translation software to bridge the gap by translating construction documents in real-time. To bring PlanSyncc to life, the team divided the project into three key deliverables: a Minimum Viable Product (MVP), a business plan, and a pitch deck. The MVP involved creating two Python-based translation codes, one for specifications and another for complex construction plans using tools like PyMuPDF, Tesseract, mtranslate, and others. The business plan …

Hierarchical Frameworks For Scaling-Up Multi-Agent Coordination, Minghong Geng

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning has emerged as a powerful framework for developing collaborative behaviors in autonomous systems. However, existing MARL methods often struggle with scalability in terms of both the number of agents and decision-making horizons. My research focuses on developing hierarchicalapproaches to scale up MARL systems through two complementary directions: structural scaling by increasing the number of coordinated agents and temporal scaling by extending planning horizons. My initial work introduced HiSOMA, a hierarchical framework integrating self-organizing neural networks with MARL forlong-horizon planning, and MOSMAC, a benchmark for evaluating MARL methods on multi-objective MARL scenarios. Building on these foundations, my recent …

Modelling Virus Filtration And Virus Reduction By An Advanced Multilayer Model: Retention Distribution And The Effect Of Product Aggregates, Hironobu Shirataki, Remo Leisi, Junji Hdaka, S. Rancil Wickramasinghe

Chemical Engineering Faculty Publications and Presentations

Robust virus reduction and high permeability are characteristic properties of virus filters, which are modeled as having an asymmetric multilayer membrane structure with a pore size distribution. In this study, an advanced heterogeneous multilayer model for the multicomponent solution containing viruses, protein monomers and aggregates, has been developed to reproduce the filtration behavior, virus reduction, and virus/protein retention distribution in the virus filter with asymmetric membrane structure. Calculations based on the multilayer membrane structure with consideration of the effect of aggregate size and concentration numerically reproduce the experimental results that virus LRV (log reduction value) decreases when a large number …

A Framework For Quantifying The Benefits Of Electric Vehicle Infrastructure Development, Donya Negahbani

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Under the Biden Administration’s Justice40 Initiative, a significant portion of benefits derived from federal clean transportation investments is required to be directed to disadvantaged communities. Meeting this mandate necessitates a transparent and reproducible approach that quantifies various dimensions of value and allocates them equitably. This dissertation presents a flexible framework specifically tailored for the deployment of electric vehicle charging infrastructure in Nebraska, effectively translating equity goals into rigorous spatial and economic analyses. The framework first identifies multiple distinct categories of benefit that reflect the societal value of charging access: energy savings, economic opportunities, environmental quality enhancements, and public health improvements. …

Computationally Guided Liquid Crystal-Based Competitive Binding Sensing Platform For Optical Detection Of Spike Protein, Homa Ghaiedi, Shubham Pandey, Sophia Ezendu, Tibor Szilvasi, Karthik Nayani

Chemical Engineering Faculty Publications and Presentations

A liquid crystal (LC)-based sensing platform for the rapid optical detection of SARS-CoV-2 ' s spike protein's receptor binding domain (RBD) domain is introduced. This platform utilizes a thermotropic LC, hosted on metal-cation decorated substrates, onto which the spike protein can competitively bind. Density functional theory (DFT) calculations guide the experiments that reveal a homeotropic-to-planar transition in the LCs upon exposure to SARS-CoV-2 spike-decorated yeast, providing a basis for sensitive virus detection. The sensor's reversibility/specificity is confirmed through antibody-induced orientation recovery of the LCs initial orientation. Strikingly, the sensor can detect approximate to 2000 copies of the spike protein per …

Preclinical Development Of Genome Editing To Treat Duchenne Muscular Dystrophy By Exon Skipping, Made Harumi Padmaswari, Shilpi Agrawal, Christopher E. Nelson

Biomedical Engineering Faculty Publications and Presentations

Duchenne muscular dystrophy (DMD) is caused by loss-of-function mutations to the gene encoding dystrophin. Restoring the reading frame of dystrophin by removing internal out-of-frame exons may address symptoms of DMD. Therefore, the principle of exon skipping has been at the center stage in drug development for Duchenne muscular dystrophy (DMD) over the past two decades. Antisense oligonucleotides (AONs) have proven effective in modulating splicing sites for exon skipping, resulting in the FDA approval of several drugs using this technique in recent years. However, due to the temporary nature of AON, researchers are actively exploring genome editing as a potential long-term, …

Performance Evaluation Of Highly Modified Asphalt-Based Binders In High Friction Surface Treatment: Comparative Study With Epoxy-Based System, Alireza Roshan, Magdy Abdelrahman, Mohyeldin Ragab

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are frequently used to increase skid resistance and reduce collisions, particularly in crash-prone zones, including horizontal curves and intersections. Epoxy-based binders traditionally have been the sole option for HFSTs, but their drawbacks, such as high costs and compatibility challenges, have led to the search for substitute binders, including asphalt-based options. This study investigates the comparative performance of highly modified asphalt-based binders, including polymer-modified, mastic, and highly modified emulsions, in HFST applications using two aggregate types, Calcined Bauxite (CB) and Rhyolite with different gradations, with an emphasis on their frictional properties, durability, and resistance to polishing. …

Cooperative And Bifunctional Ga-Ca-Cr2o3@Cao Structured Monoliths As Versatile Platform For Reactive Capture Of Co2 And Its Subsequent Conversion To Ethylene, Khaled Baamran, Ali A. Rownaghi

Chemical and Biochemical Engineering Faculty Research & Creative Works

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO₂ to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr₂O₃ metal oxides as the catalyst for the reactive capture of CO₂ and its subsequent conversion to C₂H₄ via the oxidative dehydrogenation of C₂H₆ (CO₂-ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C₂H₄ selectivity. …

Tumor-Specific Surface Marker–Independent Targeting Of Tumors Through Nanotechnology And Bioorthogonal Glycochemistry, Hyesun Hyun, Bo Sun, Mostafa Yazdimamaghani, Albert Wielgus, Yue Wang, Stephanie Ann Montgomery, Tian Zhang, Jianjun Cheng, Jonathan S. Serody, Andrew Z. Wang

Chemical and Biochemical Engineering Faculty Research & Creative Works

Biological targeting is crucial for effective cancer treatment with reduced toxicity but is limited by the availability of tumor surface markers. To overcome this, we developed a nanoparticle-based (NP-based), tumor-specific surface marker–independent (TRACER) targeting approach. Utilizing the unique biodistribution properties of NPs, we encapsulated Ac4ManNAz (Maz) to selectively label tumors with azide-reactive groups. Surprisingly, while NP-delivered Maz was cleared by the liver, it did not label macrophages, potentially reducing off-target effects. To exploit this tumor-specific labeling, we functionalized anti–4-1BB Abs with dibenzo cyclooctyne to target azide-labeled tumor cells and activate the immune response. In syngeneic B16F10 melanoma and orthotopic 4T1 …

Picosecond Laser Ranging At 1.5 Μm Using Dispersive Interferometry, Behzad Boroomandisorkhabi, Xiangrui Su, Mina Esmaeelpour

Electrical and Computer Engineering Faculty Research & Creative Works

Precise displacement measurement is essential for engineering, industrial, and scientific purposes. Ultrafast laser techniques are preferred for real-time applications due to their single-shot measurement capability and high resolution. To create a high-performance and cost-effective system with less complexity, capable of achieving real-time measurement with high micrometer spatial resolution, we have used a picosecond pulsed laser at the telecommunication wavelength of 1.5 μm in combination with dispersive interferometry. The instantaneous frequency measurement took place using the time-stretch technique incorporating dispersion compensating fiber induced chirp. Results using a 7-picosecond laser at 1.5 μm with a 10 MHz repetition rate are presented. Frequency …

Sensor Data Fusion For Air Quality Monitoring, Mirna Hesham

Theses and Dissertations

Since traditional air quality monitoring methods often rely on geographically sparse and costly air quality monitoring stations, image-based air quality method- ologies are recently offering a compelling alternative that utilizes images from sources like satellites, traffic cameras, and even smartphones to monitor pollution levels by using estimation models, image-processing techniques, and deep-learning models. In this thesis, we first conduct a systematic review, in which we categorize and discuss the existing literature work. Moreover, we introduce a novel, multi- modal dataset designed to address the limitations of existing datasets, which are restricted in size, geographical coverage, and fixed-scene imagery, impeding the …

Compartmental Disaggregation: Bridging Simulation And Sampling Methods For Synthetic Population Data Generation, Dylan Mack

McKelvey School of Engineering Graduate Student Theses & Dissertations

As agent-based models (ABMs) grow increasingly widespread in public health, their associated challenges have become all the more significant. Lauded for their ability to capture population heterogeneity, nonlinear dynamics, and emergent behaviors, disease ABMs are also computationally expensive and often require detailed inputs that describe each agent at the individual-level, known as synthetic population data. Current approaches for synthetic population data generation generally fall into one of two categories: sampling or simulation. These methods are both feasible only under restricted conditions and suffer from challenges surrounding data availability and computing power. This thesis proposes compartmental disaggregation, an intermediate method for …

Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang

Faculty Publications

This paper presents a novel path planning method for real-time robotic path planning in a dynamic environment involving moving obstacles. It combines on a holistic platform a global approach to rapidly generate initial paths of prominent diversity and a heuristic approach to enable local path refinement for enhanced computational efficiency, exploration, and robustness. The global approach innovates a formulation that treats a path planning problem with a visibility graph as a Markov decision process and decomposes the process into many subproblems. A new evolutionary dynamic programming approach (EDP) is proposed to solve these subproblems in an iterative manner using …

Predicting Which Genes Will Respond To Transcription Factor Perturbation, Eric L. Jia

McKelvey School of Engineering Graduate Student Theses & Dissertations

A fundamental issue in mapping regulatory networks between transcription factors and their target genes is the poor overlap between the set of genes bound by a given transcription factor (TF), and the set of genes that are differentially expressed after knocking out or overexpressing the same TF. We began with the hypothesis that to predict whether a gene will respond to perturbation of a TF, it is important to not only consider whether that TF is bound at the gene’s promoter, but also whether other TFs bind at the same promoter.

In this work, we propose a novel modeling procedure …

A Neuroimmune Circuit Mediates Chemo Brain Pathology, Daniel Ahmadi

McKelvey School of Engineering Graduate Student Theses & Dissertations

Chemotherapeutic agents, while effective in targeting malignant tumors, often reduce the patients’ quality of life by inducing fatigue, pain, and motivational deficits. These symptoms are collectively referred to as “chemo brain.” The mechanisms underlying these adverse effects, and specifically whether fatigue and motivational impairments share a common etiology, remain poorly understood. The neural–immune substrates of these symptoms remain obscure, in part because standard preclinical regimens either bypass key systemic signals or introduce local toxicity confounds. Here, I establish and validate a three‑day, low‑dose intravenous cisplatin protocol that avoids peritoneal inflammation and severe renal injury yet produces robust, reversible fatigue and …

Reducing Measurement Error In Three-Point Bend Test Using Linear Gradient Correction Model, Juan J. Becerra-Garcia

McKelvey School of Engineering Graduate Student Theses & Dissertations

Endovascular devices like catheters feature non-uniform flexural rigidity (EI) profiles (flexi- ble tip, stiff shaft) crucial for navigation and pushability. Standard three-point bend analysis (assuming uniform stiffness) yields inaccurate apparent rigidity (B0) for these graded devices, especially in transition zones. This inaccuracy hinders device comparison, clinical selection, and predictive modeling. This thesis develops and validates a correction model for three-point bend tests aimed at improving local flexural rigidity accuracy for devices with varying stiffness, particularly those exhibiting transition zones similar to logistic profiles. The model assumes a linear gradient in rigidity (B(x) = Bm(1 + 2mx/L)) across the test span …