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Effects Of Processing And Microstructure On The Oxidation Of Zrb2-Sic In Co2, Marharyta Lakusta, Jeremy L. Watts, William G. Fahrenholtz, David W. Lipke May 2025

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 …

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Intermediate Stage Densification Kinetics Of High-Entropy Ceramics During Spark Plasma Sintering, Steven M. Smith, William G. Fahrenholtz, Greg E. Hilmas, Stefano Curtarolo May 2025

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 …

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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 May 2025

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 …

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Advancing Marine Animal Movement Studies Using An Open Innovation Framework, Jacob Levenson May 2025

Advancing Marine Animal Movement Studies Using An Open Innovation Framework, Jacob Levenson

Graduate Doctoral Dissertations

This dissertation investigates the application of open innovation to migratory marine animal movement studies, addressing critical challenges in understanding, managing and ultimately conserving highly mobile and migratory species (HMMS). The species examined herein, including manta rays, sea turtles, and marine mammals, face threats including habitat disruption and behavioral changes to adapt to anthropogenic stressors. Traditional monitoring techniques, while valuable, are often costly, limited in scale, and protected by proprietary intellectual property, all of which decrease accessibility. Ambitious conservation goals, such as protecting 30% of the ocean by 2030, require more data that are indubitably sharable and thus will need to …

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New Mathematical Approaches To Ultra-Cold Atoms, Joanna Ruhl May 2025

New Mathematical Approaches To Ultra-Cold Atoms, Joanna Ruhl

Graduate Doctoral Dissertations

This dissertation addresses three main themes: cold atoms, integrability, and number theory. In this dissertation we present novel approaches to four models, each of which touches on at least two of the three themes. At the intersection of cold atoms and integrability, we present a Lagrange bracket formalism that allows for exact computation of initial quantum fluctuations of soliton breathers which previously could only be estimated numerically, and the advance in software tools developed in Python to facilitate studies of two-dimensional disc breathers. At the intersection of integrability and number theory, we present a propagator for the Newman-Moore, or triangular …

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Criminal Activity Monitoring System: Targeting Africans And East Asian Communities In Dubai, Hamdan Kalantar May 2025

Criminal Activity Monitoring System: Targeting Africans And East Asian Communities In Dubai, Hamdan Kalantar

Theses

This dissertation investigates crime patterns among African and East Asian communities in Dubai, focusing on geographic hotspots, temporal trends, victim demographics, and the use of machine learning for predictive crime modeling. The research addresses the challenges faced by these communities, including labor exploitation, financial fraud, and human trafficking, within the socio-economic context of a rapidly growing urban city. Building on existing studies of urban crime, this research aimed to explore the spatial, temporal, and demographic dynamics of crimes and assess the potential of predictive models to assist law enforcement in crime prevention and resource allocation. A mixed-methods approach was employed, …

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Energy Forecasting Inaccuracies And Their Direct Impact On Grid Performance, Rashed Khalid Alboom May 2025

Energy Forecasting Inaccuracies And Their Direct Impact On Grid Performance, Rashed Khalid Alboom

Theses

Accurate energy forecasting is critical for the stability, efficiency, and cost-effectiveness of modern power grids, particularly as renewable energy sources like solar and wind become more prominent. The variability of these sources presents challenges for traditional forecasting models, which struggle with non-linearity, external dependencies, and evolving grid conditions. These limitations lead to operational inefficiencies, grid instability, and increased financial risks. This study investigates the effectiveness of traditional statistical models, advanced machine learning techniques, and hybrid forecasting approaches to enhance prediction accuracy and grid performance. Using real-world datasets from Kaggle, including historical energy generation, consumption, pricing, and weather variables, this research …

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Determining Sustainable Urban Renewal: A Case Of Quantifying Sustainability For Adaptive Reuse Within Mumbai’S Textile Mill Sector, Arundhati Rajesh Kawlekar May 2025

Determining Sustainable Urban Renewal: A Case Of Quantifying Sustainability For Adaptive Reuse Within Mumbai’S Textile Mill Sector, Arundhati Rajesh Kawlekar

Theses

This study explores adaptive reuse as a sustainable approach to urban development in Mumbai, India, focusing on the revitalization of a heritage textile mill site. It investigates how historical significance and evolving community needs can shape design decisions, while assessing sustainability through Life Cycle Analysis (LCA) and energy efficiency metrics. Mumbai’s defunct textile mills, once central to its industrial growth, now pose challenges to urban vitality. Through a literature review, the paper examines their historical, social, and cultural relevance and the decline of the mill industry. Adaptive reuse emerges as a key strategy to reimagine these structures, offering an environmentally …

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Through Legitimate Dissent, The Supreme Court Repairs Itself, Afnaan A. Qureshi May 2025

Through Legitimate Dissent, The Supreme Court Repairs Itself, Afnaan A. Qureshi

Theses

The decisions of the Supreme Court of the United States, along with its reasoning, influence the direction and scope of historical events. Through an analysis of landmark dissents from four of the worst Supreme Court decisions, Curtis’ dissent in Dred Scott v. Sandford (1857), Harlan’s dissent in Plessy v. Ferguson (1896), Holmes’ dissent in Abrams v. United States (1919), and Murphy’s dissent in Korematsu v. United States (1944), we can take steps towards catalyzing its self repair by stepping away from digital echo chambers and engaging in legitimate dissent. The four cases marked turning points in the efforts to protect …

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A Prototype High Power Dc-Dc Converter For Regulating Generator Output Voltage In A Series Hybrid Electric Vehicle, Alex Currie May 2025

A Prototype High Power Dc-Dc Converter For Regulating Generator Output Voltage In A Series Hybrid Electric Vehicle, Alex Currie

Theses

As fully electric and hybrid electric vehicles become more commonplace, a strong incentive for innovation in electric powertrain technology has been created. Though the instantaneous power available from an electric motor may appeal to consumers of powersports vehicles, this has been an area with relatively little advancement towards electric architectures. One primary concern of electrifying such a platform is the need for large battery packs that tend not to perform well in the harsh weather conditions often seen in powersports such as snowmobiling. As such, hybrid electric architectures may prove to be a successful middle ground between fossil fuels and …

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Uvm Based Verification Of Ee621 Risc Processor Module, Collin Neidel May 2025

Uvm Based Verification Of Ee621 Risc Processor Module, Collin Neidel

Theses

In the process of digital design, the majority of efforts are focused on verification. This is because a proper verification environment can help engineers discover bugs that otherwise would have flown under the radar. On the other hand, a poorly designed verification environment could fail to fully confirm the device’s functionality and leave the customer with a buggy mess. For obvious reasons, this should be avoided at all costs, hence the emphasis on functional verification and validation efforts. Throughout time, the complexity of the average design under test (DUT) has increased dramatically, making verification a significant challenge for today’s verification …

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A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold May 2025

A Bert-Resnet Cross-Attention Fusion Network And Modality Utilization Assessment For Multimodal Sentiment Classification, Ronen G. Gold

Theses

This study explores the growing field of Multimodal Sentiment Analysis (MSA), focusing on understanding how advanced fusion techniques can improve sentiment prediction in social media contexts. As platforms like X and TikTok continue to expand and facilitate sharing sentiment through digital media, there is an increasing need for neural network architectures that can accurately interpret sentiment across modalities. We implement a model using BERT for textual features and ResNet for visual features. A cross-attention fusion module aligns the modalities for joint representation. We conduct experiments on the MVSA-Single and MVSA-Multiple datasets, which contain over 5,000 and 17,000 labeled text-image pairs. …

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Glue Laminated Timber: A New Way Of Framing The Residential Architecture Of Upstate New York To Improve Thermal Performance & Energy Use Intensity, Griffin Jones May 2025

Glue Laminated Timber: A New Way Of Framing The Residential Architecture Of Upstate New York To Improve Thermal Performance & Energy Use Intensity, Griffin Jones

Theses

This thesis addresses the issue present within the current construction techniques for the residential architecture of Upstate New York. Modern platform framing has long been the dominant fashion for constructing homes in the United States, however the nature of this construction is instilled with the issue of thermal bridging, where the wood studs and structure allow heat to escape due to gaps in the continuous insulation. This study proposed a new way of framing residential architecture for the upstate region of New York, relying on glue-laminated timber (GLT) to replace dimensional sawn lumber. GLT has increased structural strength and stability …

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Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang May 2025

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 …

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Development Of A Probabilistic Interaction Rule And Failure Pressure Model For Pipelines With A Colony Of Corrosion Defects, Kiswendsida J. Kere, Qindan Huang May 2025

Development Of A Probabilistic Interaction Rule And Failure Pressure Model For Pipelines With A Colony Of Corrosion Defects, Kiswendsida J. Kere, Qindan Huang

Civil and Environmental Engineering Faculty Research and Publications

The interaction effect originating from a defect colony can pose a higher pipeline failure risk than the case when such possible interaction is not considered. Recognizing the limitations in existing models that can lead to inaccurate pipeline integrity assessment, the goal of this study is to develop a probabilistic interaction rule and predictive burst failure pressure model for pipelines with a colony of corrosion defects. First, a comprehensive database of burst failure pressure for pipes with a colony of corrosion is established that encompasses a wide range of influencing factors (e.g., spacing, defect sizes, and material properties) on the defect …

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Polypharmacy As A Treatment Barrier In Autism Spectrum Disorder, Ahmed Aly May 2025

Polypharmacy As A Treatment Barrier In Autism Spectrum Disorder, Ahmed Aly

Rowan-Virtua Research Day

The purpose of the study is to assess the prevalence of polypharmacy in current literature in the Autism Spectrum Disorder (ASD) population. It is hypothesized to find patients with ASD over prescribed compared to the neurotypical counterparts.

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Effects Of Novel Dopamine D4 Receptor-Targeted Compounds On Locomotor Activity And Anxiety-Like Behavior In Male And Female Sprague Dawley Rats, Samantha Alyse Walkow, Noah A. Ivak, Daniel Chandler, John Tkaczynski, Thomas M. Keck, Comfort A. Boateng, Eleni Papadopoulos, Barry D. Waterhouse, Rachel L. Navarra May 2025

Effects Of Novel Dopamine D4 Receptor-Targeted Compounds On Locomotor Activity And Anxiety-Like Behavior In Male And Female Sprague Dawley Rats, Samantha Alyse Walkow, Noah A. Ivak, Daniel Chandler, John Tkaczynski, Thomas M. Keck, Comfort A. Boateng, Eleni Papadopoulos, Barry D. Waterhouse, Rachel L. Navarra

Rowan-Virtua Research Day

The consequences of modulating subtypes of G protein coupled dopamine receptors are broadly studied for their role in decision making behavior, specifically in situations involving uncertain risk and reward. The actions of dopamine D4 receptors (D4Rs) on these complex processes are the least understood, particularly due to a lack of available compounds with suitable selectivity for D4Rs. Further, current research often fails to evaluate how modulating specific dopamine receptor subtypes may affect locomotor activity and anxiety-like behavior as confounding factors prior to assessing their function in behavioral assays of higher order decision making. The goal of the current study was …

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A Review Of Sutures And The Prospective Applications Of Nanofiber Technology In Suture Engineering, Hanna Brancaccio, Dominique Hassinger, Vincent Beachley May 2025

A Review Of Sutures And The Prospective Applications Of Nanofiber Technology In Suture Engineering, Hanna Brancaccio, Dominique Hassinger, Vincent Beachley

Rowan-Virtua Research Day

Introduction: Suturing is a method to close surgical or traumatic wounds to promote healing. The ideal suture should have high tensile strength that loses strength at the same rate as the healing tissue gains strength, be easy to handle and form secure knots, induce minimal inflammation, and stretch/recoil according to wound contraction. While there are suture materials available for use in various procedures that fulfill most requirements, no one suture possesses every desirable characteristic, and limitations are still prevalent. Nanofiber geometry has a well-known ability to modulate cell morphology, attachment, gene expression, extracellular matrix production, and macrophage polarization in …

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An Analysis Of Dc-Dc Converter Efficiencies, Carley Visser May 2025

An Analysis Of Dc-Dc Converter Efficiencies, Carley Visser

Theses

With the increase in technology used in everyday life, the need for DC-DC converters has continued to increase. The efficiency of these converters is an essential parameter as an increase in a few percent can increase battery life by hours. There are several different factors that effect the efficiency of converters ranging from temperature, component selection, quiescent current and more. In this paper, a series of eleven DC-DC converters will be designed and tested in order to observe how the efficiencies and other parameters compare to the values provided in this datasheet. For this investigation two different PCBs were designed, …

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Sustainable Retrofits: The Balance Between Energy Efficiency And Embodied Energy, Alexander Narvaez May 2025

Sustainable Retrofits: The Balance Between Energy Efficiency And Embodied Energy, Alexander Narvaez

Theses

This thesis looks at how to balance energy efficiency with embodied energy in small commercial retrofits, focusing on restaurant buildings. Rather than tearing down older buildings and starting from scratch—something that wipes out all the embodied energy already invested—retrofitting can improve performance while preserving what's already there. Using EnergyPlus for operational energy modeling and the Athena Impact Estimator for embodied energy analysis, this study compares different retrofit scenarios. These include retrofitting one, two, or all three major assemblies (walls, roofs, and floors) to see how each combination affects total emissions over time. The results show that not all retrofits are …

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Forecasting Load At Residential, Industrial, And Commercial Stations For Dubai Electricity And Water Authority: A Machine Learning Approach To Managing Generation During Peak And Off-Peak Times Over The Coming Years, Mohammad Anoohi May 2025

Forecasting Load At Residential, Industrial, And Commercial Stations For Dubai Electricity And Water Authority: A Machine Learning Approach To Managing Generation During Peak And Off-Peak Times Over The Coming Years, Mohammad Anoohi

Theses

In Dubai, with the rapid growth of energy demand, efficient demand side management is necessary to optimize the distribution of electricity, reduce peak loads, and improve grid stability. Traditional DSM strategies are based on historical data and reactive control mechanisms that cannot adapt to evolving consumption patterns. This research uses Machine Learning techniques to enhance DSM in residential, commercial, and industrial sectors by developing predictive models that forecast energy demand based on seasonal variations. The dataset used was from Dubai Electricity and Water Authority (DEWA), covering the consumption patterns across Summer, Winter, Transition from Winter to Summer, and Transition from …

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Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji May 2025

Beyond The Badge: Predicting Military Employee Attrition In The Police Force, Alia Abdulla Alhajji

Theses

This study explores the issue of employee attrition within the military police force, with a focus on predicting which employees are at risk of leaving. Attrition in law enforcement is costly and disruptive, especially in roles that require long training periods and operational readiness. The research specifically targets the internal organizational factors influencing turnover in military police environments and aims to leverage machine learning models to support the early identification of high-risk individuals. Guided by the CRISP-DM framework, the study followed a structured process across six stages: business understanding, data exploration, preparation, modeling, evaluation, and insight generation. A simulated dataset …

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Using Generative Ai For Tutoring Data Science, Yusra Khalid May 2025

Using Generative Ai For Tutoring Data Science, Yusra Khalid

Theses

A large increase in the use of Generative AI has been observed in the last few years. Data science is also a rapidly growing field with a high demand for skilled professionals. The goal of this thesis is to explore the potential of Generative AI, specifically ChatGPT, in facilitating data science education. The focus is on how ChatGPT can be used as a tutor to help solve practical exercises. The capabilities of Generative AI were explored along with the comparison of a few different models in terms of data science. Exploratory analysis was conducted to compare Generative AI models and …

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Classification Of Linear Systems Of Equations For Quantum Computing Implementation, Mark Danza May 2025

Classification Of Linear Systems Of Equations For Quantum Computing Implementation, Mark Danza

Theses

Drawing nearer to an error-corrected era of quantum computing, it is necessary to understand the suitability of certain post-NISQ algorithms for practical problems. One of the most promising, applicable, and yet difficult to implement in practical terms is the Harrow, Hassidim and Lloyd (HHL) algorithm for linear systems of equations. An enormous number of problems can be expressed as linear systems of equations, from machine learning to fluid dynamics to electrical circuit analysis. However, in most cases, HHL will not be able to provide a practical, reasonable solution to these problems. This work seeks to determine whether problems can be …

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Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli May 2025

Sales Opportunities Lead Qualification In B2b Market, Hajar Hussain Ahli

Theses

This thesis addresses the challenge of inefficient lead qualification in the business-to-business (B2B) market by applying machine learning techniques to predict the likelihood of winning a sales opportunity. Using a real-world dataset of over 78,000 records and 17 variables, the study aims to improve how sales teams identify and prioritize high-conversion leads. A thorough data preparation process was conducted, including handling of missing values, outlier detection, and under-sampling to resolve class imbalance between won and lost opportunities. After thorough data cleaning, preprocessing, and under-sampling to address class imbalance, five machine learning models were developed: Logistic Regression, Random Forest, Neural Network, …

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Instrapix – An Image-Based Digital Audio Workstation Design, Dan Qiao May 2025

Instrapix – An Image-Based Digital Audio Workstation Design, Dan Qiao

Theses

InstraPix, a UI project designed by Dan Qiao, is groundbreaking image-and-audio conversion software and a digital audio workstation (DAW). enables bidirectional conversion between images and sound, opening new creative possibilities. With powerful image processing tools, it allows users to directly use pictures as audio sources, shaping unique sonic compositions. InstraPix also supports sound presets, VST plugins, and note editing, allowing seamless integration with other instruments. This all-in-one audio workstation could mark the beginning of a new era where music can be created entirely from images. Assigning images significant importance in audio production and minimizing the middle steps, it breaks the …

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A Remote Sensing-Based Evaluation Of Road And Electricity Infrastructure Expansion Effects On Development In Sub-Saharan Africa, Tunmise Ibukun Raji May 2025

A Remote Sensing-Based Evaluation Of Road And Electricity Infrastructure Expansion Effects On Development In Sub-Saharan Africa, Tunmise Ibukun Raji

Theses

Sub-Saharan African countries consistently rank low on human development indicators despite decades of international aid and domestic investment. To address these challenges, governments across the region are allocating substantial portions of their national budgets to infrastructure expansion, viewing it as a catalyst for accelerated socio-economic development. However, given severely constrained budgets, these nations often face trade-offs between infrastructure development and investment in other important sectors such as healthcare and education. This highlights the need for infrastructure investments to deliver their anticipated benefits. This dissertation examines the relationship between infrastructure development and socio-economic development in Sub-Saharan Africa, with a particular focus …

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Developing Meld-Accelerated Molecular Dynamics Protocols To Simulate The Binding Of The P53-Derived Ligand To The Mdm-2, X Protein, Maria Ciko May 2025

Developing Meld-Accelerated Molecular Dynamics Protocols To Simulate The Binding Of The P53-Derived Ligand To The Mdm-2, X Protein, Maria Ciko

Theses

In this study, we focus on developing computational methods to predict protein-ligand binding affinities, with applications in peptide drug discovery. Molecular Dynamics (MD) simulations can capture the complex conformational behavior of proteins, but their high computational cost limits their efficiency. MELD, or Modeling Employing Limited Data, is a Bayesian approach that integrates external information to accelerate sampling of low- energy, high-probability conformations. Building on previous work by Morrone et al., which successfully applied MELD to P53-MDM2 complexes, we hypothesize that we can effectively compute the relative binding affinities while reducing steric clashes and mitigating the effect of slowed diffusion on …

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Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi May 2025

Data-Driven Prediction Of Vehicle Residual Value In The Uae Automotive Industry, Meera Al Hashmi

Theses

In this master’s thesis, machine learning methods are applied to predict the residual value of a vehicle, focusing on the problem of estimating the vehicle’s price after sale. The research addresses some of the most important drivers of depreciation which include market segmentation, country, region-specific details, transmission type, and some numerical values obtained through factor analysis. This is very important to the automotive industry, leasing businesses, and financial institutions. The data was collected from the open-source online marketplace Dubizzle and contains 25 variables and 62,922 cases. The initial data posed notable challenges as there were non-standardized feature values, incomplete data …

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Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako May 2025

Predicting The Probability Of Crime Related Danger In Los Angeles, Joshua Oghenetega Okpako

Theses

This thesis examines the use of advanced machine learning to predict crime danger in Los Angeles, where 2023 violent crime rates (503 per 100,000) surpass the national average (363.8 per 100,000). Rooted in theories like social disorganization and victim vulnerability, it addresses the lack of combined victim-centric modeling by focusing on three questions: (1) Do blended ensemble models outperform individual models in predicting crime danger? (2) Can unsupervised learning techniques enhance supervised models’ accuracy through label generation or augmentation? (3) How can we interpret accurate machine learning models' decision-making processes? Using historical crime data from Los Angeles (2020–2025) and various …

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