Digital Commons Network^™

Genomic Determinants Of Response And Resistance To Pirtobrutinib In Relapsed/Refractory Chronic Lymphocytic Leukemia, Jennifer R Brown, Bastien Nguyen, Sai Prasad Desikan, Helen Won, Shady I Tantawy, Samuel C Mcneely, Narasimha Marella, Hetal S Randeria, Lauren M Hanson, Andrew Parker, Salomé Calado Botelho, Jennifer A Woyach, Krish Patel, Constantine S Tam, Toby A Eyre, Chan Y Cheah, Nirav N Shah, Paolo Ghia, Wojciech Jurczak, Minna Balbas, Binoj Nair, Paolo Abada, Chunxiao Wang, Denise Wang, Lindsey E Roeker, Varsha Gandhi, William G Wierda

Faculty, Staff and Student Publications

Pirtobrutinib, a noncovalent, reversible Bruton tyrosine kinase inhibitor (BTKi), demonstrated efficacy in patients with chronic lymphocytic leukemia (CLL), resistant to covalent BTKi (cBTKi). We analyzed genomic correlations with response and resistance to pirtobrutinib in relapsed/refractory (R/R) patients with CLL pretreated with cBTKi enrolled in the phase 1/2 BRUIN trial. DNA sequencing was performed on peripheral blood mononuclear cells at baseline, on treatment, and at progressive disease (PD). Common alterations at baseline included mutations in BTK (43%), TP53 (38%), SF3B1 (25%), NOTCH1 (23%), ATM (19%), XPO1 (11%), PLCG2 (9%), BCL2 (8%), and 17p deletion (28%). Common baseline BTK mutations included C481S …

The Impact Of True Crime Podcasts On Cold Case Investigations And Victims' Advocacy, Kyle Gamache, Karlie Rice, Ashley Allen, Willem Pontbriand

Arts & Sciences Faculty Publications

True crime has long captivated public interest, evolving from sensationalized accounts in the Middle Ages to the widespread popularity of modern podcasts. This qualitative study explores the ethical complexities of true crime media by examining how it intersects with criminal investigations, public perception, and victim advocacy. Through in-depth interviews with law enforcement officers, victim advocates, and true crime content creators, the study investigates differing attitudes toward the role of podcasts in active and cold cases. Using Colaizzi’s (1978) phenomenological method, data were analyzed to uncover shared and divergent themes across professional roles. Law enforcement participants voiced concerns over web- sleuthing …

Meta-Analysis Of The Health Effects Of Gas Cooking In Homes, P. Jacob Bueno De Mesquita, Núria Casquero-Modrego, Erik Pontes

Arts & Sciences Faculty Publications

Background: Given existing evidence linking indoor gas combustion with potential health effects, we aimed to quantify from epidemiologic field studies the health impacts associated with residential gas cooking and unvented heating.

Methods: We evaluated and synthesized results from peer-reviewed epidemiologic studies that isolated associations between exposure to residential gas cooking and/or unvented heating and an unrestricted range of health outcomes. We focused on studies conducted since 2000 that cited at least one of five, well-regarded studies. We evaluated relevant studies and computed pooled effect estimates, where at least three studies contributed data, using random effect meta-analysis models with inverse-variance weighting. …

Standard Textualism, James A. Macleod

Articles

For as long as legal scholars have been writing about the rules-versus-standards distinction, textualism has been understood to produce characteristically rule-like law. This Article argues for the opposite view. Far from generating the “law of rules” that Scalia famously envisioned, the rule of modern textualism produces a law of standards—much more so than anybody, proponent of textualism or critic, appears to have recognized.

Two aspects of today’s textualism produce this result. The first is its emphasis on ordinary language and communication. Modern textualism typically produces standards because ordinary language and communication are typically standard-like. The second is modern textualism’s drive …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner

Doctoral Dissertations

Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …

Exploring New Poly-Anion Based Materials For Lithium – Ion Battery Cathodes, Sutapa Bhattacharya

Doctoral Dissertations

The escalating global demand for sustainable energy storage solutions has driven intensive research into novel electrode materials. Polyanion-based cathode materials have emerged as promising candidates due to their structural stability, safety, and voltage tunability enabled by the inductive effect of polyanionic groups. This research explores the synthesis, crystal structure, and electrochemical performance of new polyanion-based cathode materials featuring vanadium, molybdenum, and iron within phosphate and selenite frameworks.

Novel selenite-based materials, such as LiFe(SeO₃)₂ and Li₀.₂₅V₂O₃(SeO₃)₂, were synthesized and characterized, revealing stable electrochemical cycling associated with Fe2+/Fe3+ and V⁴⁺/V⁵⁺ transitions. Additionally, a systematic investigation was conducted on molybdenum phosphate compounds, including …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

Trust-Aware Algorithms For Stackelberg Ground Vehicle Routing, Doris Evelyn Meredith Brown

Doctoral Dissertations

Despite decades of research focused on reducing ground vehicle traffic congestion, urban traffic networks worldwide continue to experience traffic flows that lead to increased network travel times, largely resulting from the routing decisions of individual vehicles. To address this challenge, this work leverages a Stackelberg game framework to model the interaction between a vehicle agent and a routing authority as a leader–follower game, in which the routing authority proposes routing interventions to which the agent responds. This research contributes to existing traffic mitigation literature by exploring the role of trust in route decision-making and providing trust-aware algorithms that influence vehicle …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …

Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt

Doctoral Dissertations

This research focuses on the processing and properties of zirconium carbide-based materials to promote their use in extreme environment aerospace applications, including nuclear thermal propulsion and hyper sonics. Several carbide systems including ZrC, ZrC-Mo cermets, (Zr, Nb)C, and a high entropy carbide were developed. The ZrC-Mo cermet was studied extensively to understand the effect of starting carbide grain size on the final microstructure, composition, elastic moduli, hardness, fracture toughness, room and elevated temperature flexural strength, thermal diffusivity, electrical resistivity, thermal expansion coefficient, and thermal conductivity. It was shown that heat transport in the cermets was dominated by the ZrC phase …

Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan

Doctoral Dissertations

The rapid increase in power density and stringent power-integrity requirements in modern System-on-Chip (SoC) platforms have made Power Delivery Network (PDN) design an increasingly complex, multi-stage challenge. Critical decisions must be made both during pre-layout planning, such as stackup configuration, power-plane geometry, and early decoupling capacitor (decap) budgeting, and during post-layout refinements. Traditional heuristic and evolutionary optimization techniques struggle with scalability, require extensive manual iteration, leading to long runtimes and limited adaptability across varying board configurations. To address these challenges, this work proposes a unified reinforcement-learning-driven framework for automated PDN synthesis and decap optimization that spans both pre-layout and post-layout …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …

Fabrication And Characterization Of A High Strength Novel Aluminum Alloy For Implementation With Directed Energy Deposition, Rachel Boillat-Newport

Doctoral Dissertations

"Additive manufacturing (AM) is of significant interest due to the ability to fabricate 3D components layer-by-layer. Compared with traditional manufacturing methods, AM allows for the direct fabrication of complex, intricate parts without the need for extensive machining, reducing manufacturing time and tooling costs and minimizing material waste. Aluminum alloys are highly desired for implementation via AM due to their high strength-to-weight ratios; however, there are several challenges that complicate the situation and hinder the use of aluminum alloys. One of the most challenging issues is that the desired high-strength alloys are not compatible with AM processing methods. A method to …

Critical Parameters Controlling Oxide Scale Formation And Hydro-Descaling Efficiency During Steelmaking, Tochukwu Princewill Ojiako

Doctoral Dissertations

In modern steelmaking, cast slabs are exposed to high-temperature oxidizing environments during secondary cooling, reheating, and hot rolling, resulting in the formation of multilayer oxide scales on the steel surface. These scales interact with mold-flux residues originating from the casting process (CC). The morphology, chemistry, and adhesion of oxide scale strongly influence its removability during high-pressure hydraulic descaling and ultimately determine the surface quality of hot-rolled products. However, the mechanistic relationship between oxide scale evolution, scale-steel interfacial structure, and hydraulic descaling performance remains poorly understood.

This dissertation investigates oxide scale formation, modification, and removal in low-carbon thin-slab steels produced by …

Probability Of Detection For Corrosion-Induced Mass Loss And Yield Strain In Metal Structures Using Fe-C Coated Long Period Fiber Gratings Sensors And Electroresistive Strain Gauges, Ying Zhuo

Doctoral Dissertations

"Graphene-based, Fe-C coated long-period fiber grating (LPFG) sensors individually reveal a causal relation between LPFG wavelength change and Fe-C mass loss. Their correlation parameters vary significantly between the sensors mainly because hydrophobic multilayer graphene and graphene oxide make sensor fabrication inconsistent. This study explores MXene-based, Fe-C coated LPFG sensors due to MXene’s inherent hydrophilic property in the presence of surface functional groups such as hydroxyl and oxygen and the probability of detection (POD) for mass loss from Fe-C coated LPFG sensors when deployed at a fixed location. A novel fabrication process incorporating Piranha solution pretreatment is proposed to ensure uniform …

Accelerating Circular Economy Transition For A Sustainable Built Environment: A Systems-Based Framework, Radwa Walid Yassin Eissa

Doctoral Dissertations

"The Circular Economy (CE) has gained momentum as a transformative framework for steering the construction value chain towards greater sustainability. However, this transition requires shifts in production and consumption patterns, adoption of circular business models, and the replacement of linear practices. Despite growing interest, CE adoption in construction faces persistent challenges, including sectoral fragmentation, lack of integrated governance frameworks, and limited coordination among stakeholders. This dissertation aims to accelerate the CE transition in the built environment through a multi-scale, interdisciplinary approach spanning five modules: (1) Module 1 develops a construction value chain-structured portfolio of CE strategies and assesses their implementation; …

Milankovitch Paleoclimatic Signals In Upper Permian–Lower Triassic Fluvial-Lacustrine Records, Bogda Mountains, Greater Turpan-Junggar Intracontinental Rift Basin, Nw China, Wentao Zhang

Doctoral Dissertations

"The objective of this study is to understand whether Milankovitch climatic and/or tectonic processes influenced the sedimentation of the upper Permian–Lower Triassic fluvial-lacustrine cyclic deposits in Bogda Mountains, greater Turpan-Junggar intracontinental rift basin, Xinjiang Uygur Autonomous Region, NW China. This study carried out gamma analysis, gamma and astronomical tuning, and spectral analysis on the Wutonggou, Jiucaiyuan, and Shaofanggou low-order cycles of the South and Central Taodonggou, South and North Tarlong, Dalongkou, and Zhaobishan sections. Stable and positive gamma values support the assumption of facies-dependent sedimentation rates for non-marine facies. The sedimentation rates range from 0.04 to 2.43 m/kyr, and 0.21 …

Analytical And Empirical Data-Driven Risk-Governance Design Across The Different Phases: Creating Informed Policy Adjustments For The Transportation Project Lifecycle, Mariam A. Elazhary

Doctoral Dissertations

"Transportation infrastructure is a critical foundation for economic productivity, yet agencies still face challenges in translating the expanding transportation datasets into defensible, phase-specific risk-governance tools. This dissertation addresses this gap by developing analytical and empirical, data-driven approaches to support risk governance across the transportation project lifecycle. Module 1 uses a panel model with bid-letting data to examine how out-of-state contractor participation affects pre-award competition and to derive entry-governance rules. Module 2 analyzes nonfatal injury data through iterative multiple linear regression and fatality data through association-rule change mining to identify multi-factor safety-risk configurations and develop adaptive safety-governance provisions. Module 3 develops …

Bond Graph And Extended Generalized Average Method With Applications In Cyber-Physical Systems And Power Electronics, Arnold Anthony Fernandes

Doctoral Dissertations

"This research examines two applications of control theory. The first application considers the bond graph (BG) modeling technique, which is used to develop the MATLAB structural analysis toolbox (MATSAT), an open-source toolbox for sensor placement and qualitative system analysis that considers the observability and fault-detection capabilities of multi-domain cyberphysical systems. The toolbox provides information on redundant sensors, guiding the system designer in cost and security trade-offs. The toolbox uses traditional BG causality assignment procedures. Additionally, MATSAT provides optimal causality assignment methods that perform significantly better at assigning causality to BGs with increased junctions, sources, and simple meshes, without encountering causality …

Lidar-Based Point-Cloud Human Modeling: Pose Estimation, Body-Parts Segmentation, 6g Localization, And Applications, Omar Rinchi

Doctoral Dissertations

"The human body represents a rich source of physiological and behavioral information, where precise analysis of anatomy, body parts, 3D pose, and motion enables cross-disciplinary precision applications. This dissertation formulates this challenge as a human modeling problem, where proposed algorithms convert the human body into a three-dimensional digital twin capturing anatomical structure and pose. These representations are further analyzed using additional algorithms to enable precision applications. To realize this vision, LiDAR sensing is adopted due to its privacy-preserving nature, robustness to lighting conditions, color-blind sensing characteristics, and decreasing cost.

Human modeling using LiDAR is challenging due to sparse, irregular, and …

Quantifying, Forecasting, And Mitigating Construction Labor And Material Challenges In A Dynamic Global Economy Using Econometrics And Deep Learning, Ahmed Gamal Elsayed Mohamed Shiha

Doctoral Dissertations

"The construction industry contributes to the global economy, yet its cost management practices remain constrained by labor shortages and material price volatility. These challenges are intensified by economic disruptions, geopolitical tensions, and trade policy shifts. Despite a growing body of literature, five knowledge gaps remain unaddressed: (1) the absence of dynamic, and localized measures of construction labor shortages; (2) limited empirical investigation of macroeconomic leading indicators of labor shortages; (3) underutilization of deep learning (DL) algorithms in forecasting local construction labor earnings; (4) the limited treatment of structural breaks in existing construction material price forecasting models; and (5) the lack …

An Energy-Stable Mixed Cg-Dg Scheme For A Full Shliomis Phase Field Model Of Two-Phase Ferrofluid Flows, Mahdi Gharehbaygloo

Doctoral Dissertations

"Ferrofluids are magnetic nanoparticle suspensions whose motion couples surface tension, flow field, magnetostatics, and magnetization dynamics. This dissertation develops, analyzes, and validates an energy-stable finite element method for a two-phase ferrofluid model that couples the Cahn-Hilliard equations with the full Shliomis model of single-phase ferrofluids, retaining its damping torque term, magnetic torque term, and magnetic stress term.

The spatial discretization is a mixed continuous Galerkin (CG) and discontinuous Galerkin (DG) formulation. It uses continuous ��2 elements for the phase field, chemical potential, velocity, and magnetostatic potential, discontinuous ��2 elements for the magnetization, and discontinuous ��1 elements for the pressure. The …

Innovative Methods In Intact Rock Deformation Detection, Ali Abdullah M Alzahrani

Doctoral Dissertations

"An accurate assessment of intact rock deformation is imperative in engineering activities carried out either in or above rock masses. However, instruments used for post-peak deformation are easily debonded and cannot record the whole process of post-peak deformation required in the failure modeling of rocks. This dissertation focuses on the investigation of the performance of two non-contact measuring systems (Laser Displacement Sensor (LDS) and Inductive Proximity Sensor (IPS)) compared to the contact type instrument (conventional Strain Gauge System (SGS)) in monitoring intact rock deformations. Subsequently, an IPS was installed in a high-pressure triaxial testing system before investigating its performance in …

Harnessing Coherent-Wave Control For Sensing Applications In Scattering Media, Pablo Xavier Jara Palacios

Doctoral Dissertations

"Diffuse electromagnetic waves are widely used for non-invasive sensing and imaging in complex scattering media such as biological tissues. A fundamental limitation of such techniques is the scarcity of detected photons: as the source-detector separation increases to access deeper regions of the medium, the signal strength decays rapidly, leading to poor signal-to-noise ratio and limited sensitivity. This dissertation addresses this challenge through a combination of theory and computation.

We show that coherent control of the incident optical wavefront can compensate for the scarcity of detected photons that limits conventional diffuse optical imaging, typically performed in the near-infrared spectral region. By …

Language Acquisition And Emergent Literacy In The 21st Century, Albert H. White Jr.

Open Touro Created

2026

Grounded in contemporary scholarship and pedagogical research, this work employs an integrated, multidisciplinary approach to 21st-century literacy instruction while prioritizing diversity, equity, and inclusion. Through its multimodal, universally accessible design—featuring interactive components, multimedia elements, and curated links to the New York State Department of Education Standards and Instruction Website—the resource facilitates critical engagement with content and alignment with state-mandated learning standards. Supplementary materials for pre-service teacher preparation and professional development are embedded throughout, enabling educators to customize and repurpose content for their specific contexts. Developed in partnership with Touro University and Colleges, this OER supports the continuous professional development …

From Germination To Transformation: Policy Studies In China Over The Past Half-Century (1970s–2020s), Shuai Cao, Ping Xu, Hongtao Yi, Ling Zhu

Political Science Faculty Publications

Over the past half-century, policy studies in China have undergone a remarkable evolution. This paper seeks to provide a comprehensive analysis of the field's development by tracing its origins and transformations over time. We introduce a time-based and multifaceted framework that delineates the evolution of policy studies in China into four distinct phases: germination (1978 to mid-1990s), burgeoning (late 1990s to 2012), normalization (2013 to 2022), and transformation (2023 to present). We first analyze the evolution of each phase in terms of historical contexts, disciplinary development, policy research (including policy domains, theoretical advancements, and methodological approaches), and intellectual engagement with …

Empirical-Based Model Of Spatio-Temporal Errors, Godwin Naaba Ndaa

Masters Theses

This research develops an empirical model to characterize spatial-temporal InSAR errors and improve the accuracy of deformation time-series analysis. Using standardized Sentinel-1 HyP3 products and MintPy, the study quantifies how correlated noise affects velocity precision and validates the results against continuous GNSS velocities.

Residual velocities are near-Gaussian, with σ ~0.92–2.04 cm/yr and ~1 cm/yr on average. Variograms show power-law spatial structure with a non-zero nugget implicating troposphere and decorrelation while errors drop exponentially with more acquisitions; spatial uncertainty is strongly affected by unwrapping errors, coherence, and tropospheric noise, not simply troposphere.

A comparative assessment of on-demand cloud processing with other …