Digital Commons Network^™

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Determination Of Tensile Strength Distribution Of Single Carbon Fibers At Microscale Gagelengths, Karan Deepak Shah

Theses and Dissertations

High performance carbon fibers are widely used as reinforcements in composite material systems for aerospace, automotive, and defense applications. The tensile strength of commercial fibers is significantly less than its theoretical limits. The composite systems are often overdesigned, thus any increase in the fiber tensile strength can yield significant cost and weight savings. Modification of fiber surface treatment (sizing) during manufacturing is a potential route to enhance fiber strength. Single fiber tensile testing at millimeter-scale is typically used to characterize the effect of sizing on the fiber strength. However, the longitudinal tensile failure of a composite system is a result …

Downwind-Upwind Flux Path Analysis Method For Model Reduction Performance Evaluations, Christian Robert Smith

Theses and Dissertations

Large, complex chemical kinetic models have long since been limited by the computational cost it takes to evaluate said model. Over time many reduction methods have been developed to combat this computational cost. However, very little has been done towards evaluating the limitations of reductions as a way of understanding the original model’s characteristics. This paper aimed to use a path flux analysis-based reduction algorithm to rapidly develop multiple reduced mechanisms for a 96 species FFCM-2 methane chemical kinetic model as well as an 858 species n-Dodecane chemical kinetic model. The goal of formulating these reduced mechanisms was to identify …

New Approaches On Source Coding For Quantum Stochastic Sources And Implementation Of Quantum Fanout Gate, Rabins Wosti

Theses and Dissertations

The accurate computation of advanced quantum algorithms like Shor’s integer factorization, quantum phase estimation (QPE), and the quantum Fourier transform (QFT) requires quantum circuits of considerable size and depth. It is difficult to achieve reliable computation with deep quantum circuits due to the limited coherence times of the current noisy quantum devices. The quantum fanout gate is known to be a powerful primitive for reducing the depth of many quantum circuits (Høyer and Špalek 2003; Gottesman and Chuang 1999). Shallow or constant-depth quantum circuits are desirable for both near-term and fault-tolerant quantum computations as they reduce noise and allow faster …

Towards Accurate First-Principles Modeling In Heterogenous Catalysis: Ethane Dehydrogenation And Hydrogenolysis Over Pt Catalysts, Mubarak Ayo Bello

Theses and Dissertations

First-principles modeling has become central to heterogeneous catalysis research, offering mechanistic insight and guiding catalyst design, yet conventional approaches often struggle to accurately describe complex catalytic systems due to methodological uncertainties, simplified assumptions, and the structural diversity of nanoparticle catalysts. This dissertation addresses these challenges using ethane dehydrogenation (EDH) and hydrogenolysis (EH) over platinum catalysts as model systems. The first study benchmarks density functional theory (DFT) functionals against the random phase approximation (RPA) for the EDH network on Pt(111), identifying cost-effective functionals and demonstrating the efficiency of BEEF-vdW ensembles for capturing functional uncertainty. The second study (addressed in prior work) …

Multiphysics Modeling, Analysis, And Design Of Ceramic Hollow Fiber Membranes For Oxygen Separation, Hamed Abdolahimansoorkhani

Theses and Dissertations

Oxygen plays a central role in numerous industrial processes. Several technologies have been reported for producing oxygen from air. Among them, oxygen transport membrane (OTM) technology—based on mixed-conducting, gas-tight ceramic membranes—has attracted significant attention due to its high oxygen selectivity, relatively low capital and operating costs, and versatility for both ex-situ and in-situ applications. Mathematical modeling of OTMs offers a powerful tool to investigate internal multi-physics transport phenomena, providing deeper insight into fundamental mechanisms while serving as a cost-effective approach for optimizing membrane stack designs.

After a comprehensive introduction, in the first part of this dissertation (chapter 2), a comprehensive …

A Building Block Approach To Certification By Analysis Applied To A Ditching Analysis, Preliminary Studies, Sean Taylor

Theses and Dissertations

Extended Twin-Engine Operations (ETOPS) certification ensures safe trans-oceanic operation of transport category aircraft. A critical aspect of ETOPS certification is compliance with ditching regulations. The importance of ditching analysis has grown significantly and come under greater scrutiny because of the ‘Miracle on the Hudson’ incident. For transport category aircraft certified under 14 CFR 25 regulations, compliance with ditching requirements, rests on two major components. First, demonstrating acceptable aircraft dynamic behavior during the ditching event and second, ensuring the airframe can withstand the loads generated because of water impact.

Historically, original equipment manufacturers (OEMs) relied on comparisons to existing aircraft with …

Recognizing The Unexpected: Deep Learning Across Complex Environments, Ge Song

Theses and Dissertations

Ensuring the security, trustworthiness, and operational integrity of modern autonomous and cyber-physical systems presents a critical challenge. While widely utilized in various engineering applications, such as intelligent transportation and industrial manufacturing, these systems require robust monitoring frameworks to identify unexpected anomalies in real-time, thereby maintaining operational safety and efficiency. This dissertation develops advanced deep learning methodologies for anomaly detection and health monitoring, with a particular emphasis on semisupervised reconstruction-based approaches that identify anomalies in complex environments using models trained only with normal operational patterns.

Building on this theme, the first study focuses on analyzing pedestrian behavior and detecting anomalies at …

Implicit Neural Representation For Image Reconstruction, Canyu Zhang

Theses and Dissertations

Image reconstruction seeks to restore corrupted images and recover visual content that has been lost or degraded. Such degradation may result from low resolution, occlusion, masking, or shadow interference. This problem has become an increasingly significant research topic, as visual information plays a central role in almost every aspect of modern life. Neural network based approaches have recently emerged as highly effective solutions for this task. In particular, convolutional neural networks and transformer based architectures have demonstrated remarkable success in producing visually convincing reconstructions. However, these models remain constrained in several important ways, one of the most critical being that …

Development Of A Strategy To Neutralize Ccl8 Activity And Ablate Ccl8 Cellular Targets, Bernardo Chavez

Theses and Dissertations

The chemokine CCL8 (monocyte chemoattractant protein-2) is a versatile signaling molecule involved in tumor progression, immune cell recruitment, and therapeutic resistance. Through activation of receptors including CCR1, CCR2B, and CCR5, CCL8 promotes leukocyte trafficking, epithelial–mesenchymal transition, and the establishment of immunosuppressive tumor microenvironments. In breast cancer and inflammatory diseases, elevated CCL8 levels correlate with poor clinical outcomes, making it a promising therapeutic target.

A strategy was developed to block CCL8 activity and selectively ablate CCL8 receptor expressing cells. A neutralizing monoclonal antibody, 1G3E5, was identified from a panel of murine candidates based on high affinity CCL8 binding. Sequencing revealed two …

Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Maxwell Aghoghovbia

Theses and Dissertations

Sodium superionic conductors are key to the development of all-solid-state sodium batteries. Discovery of new superionic conductors has traditionally relied on insights from material defect chemistry and the transition/hopping theory, while the role of lattice vibrations, i.e., phonons, remains underexplored. We identify key lattice dynamics signatures that govern ionic conductivity by analyzing the phonon mean squared displacement (MSD) of Na⁺ ions. By high-throughput screening of a dataset of 3903 Na-containing structures, we establish a strong positive correlation between phonon MSD and diffusion coefficients, providing a quantitative correlation between lattice dynamics and ion transport. To accelerate this discovery, we incorporate …

Spectral Modeling Of Electromagnetic Radiation From Power Converters, Regan A. Varner

Theses and Dissertations

Switching power converters are increasingly utilized in contemporary electronics. They are becoming more compact and operate at higher frequencies, which contributes to radiated electromagnetic interference (EMI). This EMI is important to quantify for electromagnetic compatibility of the converters with other nearby systems. In this thesis, analytical models have been developed for both ideal and non-ideal switching waveforms, employing piecewise functions to describe time-domain waveforms, with their corresponding frequency spectra derived and compared to empirical spectra. The results demonstrate that the comparisons with measured frequency data exhibit agreement with the analytical models up to approximately 25 MHz. Additionally, our analysis indicates …

Calculating Surface Current Velocities From Video Generated From A Near Forward-Facing Camera, Colby James Weeks

Theses and Dissertations

This work presents a camera system for estimating surface currents. A combined camera and IMU system provide high resolution images and high precision orientation information, respectively. This eliminates the need for leveling and enables forward looking operation. The hardware stack includes a Lucid Vision Triton TRT162S monochrome camera, an SBG Ellipse D with dual antenna GNSS for precise pose, and an Nvidia Jetson Orin for acquisition and processing. The Ellipse D provides a hardware trigger at 10 Hz to time stamp each frame and to synchronize images with inertial measurements.

A camera calibration step estimates the intrinsic camera parameters and …

Towards Robust Bmocz Schemes For Non-Coherent Wireless Communication, Anthony Joseph Perre

Theses and Dissertations

Non-coherent communication has emerged as a promising approach to address several challenges at the physical layer. A particular scheme called binary modulation on conjugate-reciprocal zeros (BMOCZ) uses the zeros (i.e, roots) of a polynomial to convey information bits. In this thesis, we strive to improve the reliability of BMOCZ in various scenarios. In particular, we utilize machine learning (ML) methods to determine the parameters for BMOCZ and improve upon the decoding performance. Moreover, we introduce a smooshed BMOCZ variant to combat typical impairments encountered within wireless communications, including timing offsets (TOs) for noncoherent orthogonal frequency division multiplexing (OFDM). Through numerical …

Computational Analogies In The Era Of Large Language Models, Amarakoon Mudiyanselage Thilini Wijesiriwardene

Theses and Dissertations

Analogical reasoning is an important part of human cognition requiring the integration of abstract reasoning, pattern recognition, and background knowledge. Despite significant advances in language modeling, the capacity of current methods to accurately identify, model, and evaluate analogies remains fundamentally underexplored.

Analogies enable individuals to perceive deep similarities between superficially different situations. Effective analogy-making requires integrating knowledge about the external world with abstract reasoning and pattern recognition capabilities. While current language models (LMs), trained on massive textual corpora using autoregressive or masked objectives, achieve impressive performance across Natural Language Processing (NLP) tasks such as text generation, summarization, and classification, their …

Multi-Layer Decision Making For Long-Term Autonomous Mission Based On Dual Process Theory, Shruti Jadhav

Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly used in precision agriculture, where extended autonomous operation is required for monitoring, intervention, and field management. However, achieving long-term autonomy remains challenging due to battery constraints, environmental uncertainty, and the need to balance exploration with event-driven tasks. To address these challenges, a multi-layer decision-making framework inspired by Dual Process Theory (DPT) is developed. The framework combines reactive return-tobase strategies, exploratory navigation, and directional bias from prior missions, with a conflict-monitoring mechanism that adapts system behavior based on real-time conditions. The approach is implemented in a simulated agricultural grid environment, demonstrating improved adaptability and coverage …

A Qualitative Study Of Middle School Teachers’ Experiences Integrating Computer Coding Into Mathematics Classrooms, George William Austin Iii

Theses and Dissertations

As computers become more accessible in schools nationwide, teachers are embracing them to impact achievement positively (Brudno, 2013; Cetin, 2016). As a result, computer coding instruction has gained attention as a strategy for providing students with skills that will serve them both pre and post-graduation (Burke & Kafai, 2013; Yadav et al., 2016; Ng, 2017). Computer coding is the process of providing instructions for a computer to follow. In 2017, the South Carolina State Board of Education approved Computer Science and Digital Literacy standards for all K-8 public schools in the state of South Carolina (South Carolina Department of Education, …

Reduced Order Simulator Of A Nuclear Thermal Propulsion System, Jackson Taylor Zazzaro

Theses and Dissertations

This thesis presents the development of a reduced-order simulator for a nuclear thermal propulsion (NTP) system, designed to capture the key thermo-fluid and performance characteristics of such systems while maintaining computational efficiency. The primary objective of this work is to develop and demonstrate a modular simulation framework capable of modeling the coupled physics of an NTP reactor, nozzle, and orbital transfer system. The simulator integrates a reduced-order thermal-fluid model of the reactor, a simplified nozzle model, and an orbital transfer model, providing a comprehensive yet computationally efficient representation of the propulsion process. By employing reduced-order modeling techniques, the simulator achieves …

Multi-Perspective Feature Learning For Facial Expression Recognition In The Wild, Xiangyu Hu

Theses and Dissertations

With the rapid progress of deep learning, Facial Expression Recognition (FER) has seen substantial improvements in performance, particularly “in the wild” meaning real world conditions. Despite these advances, most existing methods extract features from facial images as the sole emotional cues, which limits the model’s ability to capture the full complexity of human emotional expressions.

In reality, facial expressions are composed of diverse and multi-perspective information, including appearance-based cues and geometric structural deformations due to activations of facial muscles. Depending exclusively on one type of representation may fail to exploit the complementary nature of these cues, an issue that becomes …

Enhancing Two-Phase Heat Spreading: Development And Performance Evaluation Of Hermetically Sealed Hybrid Heat Sinks, Walker Ryan Champion

Theses and Dissertations

Modern, high-performance technology presents challenges for thermal management based on power density. To cool heat fluxes to this degree, conventional liquid-cooled heat sinks are utilized because air cooling becomes insufficient (>100 𝑊/𝑐𝑚² ). This study introduces a hybrid heat sink that integrates liquid cooling with a dropwise-enhanced vapor chamber, contains a hermetic seal, and achieves high thermal performance with low energy consumption. The temperature hotspots, thermal resistances, gravitational/pin effects, temperature uniformity, and coefficient of performance were investigated. Experimental results demonstrate a high cooling capacity of 600 W over a 6.25 𝑐𝑚² heating area with a low cooling …

High Prevalence Of Abnormal Baseline Lung Function In Pediatric And Young Adult Hematopoietic Stem Cell Transplant Recipients: A Report From The Transpire Study, Jane Koo, Richard Cooper, Stephanie L Edwards, Adam Lane, Sara Katherine Loveless, Lauren Strecker, Kelly E Lake, Kasiani C Myers, Christopher Towe, Jessica Patti, Laura L Walkup, Kathryn A Wikenheiser-Brokamp, Margaret L Macmillan, Philip Lacher, Tamara Griffin, Merve Tekman, Gabriel Salinas Cisneros, Kevin Wu, Matthew S Zinter, Fernando A Urrego, K Scott Baker, Matthew F Abts, Sheri Ballard, Jason L Freedman, Alexander Caraballo, Lisa R Young, Maureen B Josephson, Julian L Allen, Devaney M Camburn, Erin E Doherty, Mashid Sababi Azamian, Martha Arredondo, Manuel Silva-Carmona, Leslie E Lehmann, Wai Wong, Jonathan M Gaffin, William Mcalpine, Mona Li, Samuel B Goldfarb, Jason C Woods, Stella M Davies

Faculty, Staff and Students Publications

Background: Pulmonary complications are a major cause of morbidity and mortality in pediatric and young adult hematopoietic stem cell transplant (HSCT) recipients. The impact of preexisting lung dysfunction on posttransplant outcomes remains understudied.

Methods: In a multi-institutional prospective cohort of 444 patients (≤24 years) undergoing allogeneic HSCT at eight centers, baseline lung function was categorized as normal or abnormal using clinical history, imaging, pulmonary function tests (PFTs), and pulmonologist review. Spirometry and diffusion capacity were assessed at baseline, Day 100, 1 year, and 2 years post-HSCT.

Results: Baseline pulmonary dysfunction was present in 224 patients (50.4%), including impaired spirometry (46.4%), …

Stratifying Lung Adenocarcinoma Risk With Multi-Ancestry Polygenic Risk Scores In East Asian Never-Smokers, Batel Blechter, Xiaoyu Wang, Juncheng Dai, Christiana Karsonaki, Jianxin Shi, Kouya Shiraishi, Jiyeon Choi, Keitaro Matsuo, Tzu-Yu Chen, Rayjean J Hung, Kexin Chen, Xiao-Ou Shu, Young Tae Kim, Parichoy Pal Choudhury, Jacob Williams, Maria Teresa Landi, Dongxin Lin, Wei Zheng, Zhihua Yin, Baosen Zhou, Jiucun Wang, Wei Jie Seow, Lei Song, I-Shou Chang, Wei Hu, Li-Hsin Chien, Qiuyin Cai, Yun-Chul Hong, Hee Nam Kim, Yi-Long Wu, Maria Pik Wong, Brian Douglas Richardson, Shilan Li, Tongwu Zhang, Charles Breeze, Zhaoming Wang, Bryan A Bassig, Jin Hee Kim, Demetrius Albanes, Jason Yy Wong Sm, Min-Ho Shin, Lap Ping Chung, Yang Yang, Hong Zheng, Hongji Dai, Yasushi Yatabe, Xu-Chao Zhang, Young-Chul Kim, Neil E Caporaso, Jiang Chang, James Chung Man Ho, Yataro Daigo, Yukihide Momozawa, Yoichiro Kamatani, Masashi Kobayashi, Kenichi Okubo, Takayuki Honda, H Dean Hosgood, Hideo Kunitoh, Shun-Ichi Watanabe, Yohei Miyagi, Shingo Matsumoto, Hidehito Horinouchi, Masahiro Tsuboi, Ryuji Hamamoto, Koichi Goto, Atsushi Takahashi, Akiteru Goto, Yoshihiro Minamiya, Megumi Hara, Yuichiro Nishida, Kenji Takeuchi, Kenji Wakai, Koichi Matsuda, Yoshinori Murakami, Kimihiro Shimizu, Hiroyuki Suzuki, Motonobu Saito, Yoichi Ohtaki, Kazumi Tanaka, Tangchun Wu, Fusheng Wei, Mitchell J Machiela, Yeul Hong Kim, In-Jae Oh, Victor Ho Fun Lee, Gee-Chen Chang, Kuan-Yu Chen, Wu-Chou Su, Yuh-Min Chen, Adeline Seow, Jae Yong Park, Sun-Seog Kweon, Yu-Tang Gao, Jianjun Liu, Ann G Schwartz, Richard Houlston, Ivan P Gorlov, Xifeng Wu, Ping Yang, Stephen Lam, Adonina Tardon, Chu Chen, Stig E Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, Bu-Tian Ji, H-Erich Wichmann, David C Christiani, Gad Rennert, Susanne M Arnold, Paul Brennan, James Mckay, John K Field, Michael P A Davies, Sanjay S Shete, Loïc Le Marchand, Geoffrey Liu, Angeline S Andrew, Lambertus A Kiemeney, Shan Zienolddiny-Narui, Kjell Grankvist, Angela Cox, Fiona Taylor, Jian-Min Yuan, Philip Lazarus, Matthew B Schabath, Melinda C Aldrich, Hyo-Sung Jeon, Shih Sheng Jiang, Chung-Hsing Chen, Chin-Fu Hsiao, Zhibin Hu, Laura Burdett, Meredith Yeager, Amy Hutchinson, Belynda Hicks, Jia Liu, Sonja I Berndt, Wei Wu, Junwen Wang, Yuqing Li, Jin Eun Choi, Kyong Hwa Park, Sook Whan Sung, Chang Hyun Kang, Wen-Chang Wang, Jun Xu, Peng Guan, Wen Tan, Chong-Jen Yu, Gong Yang, Alan Dart Loon Sihoe, Yi Young Choi, In Kyu Park, Hsiao-Han Hung, Roel C H Vermeulen, Iona Cheng, Junjie Wu, Fang-Yu Tsai, John K C Chan, Jihua Li, Hsien-Chih Lin, Jie Liu, Bao Song, Norie Sawada, Taiki Yamaji, Kathleen Wyatt, Hongxia Ma, Meng Zhu, Yifan Wang, Tianchen Qi, Xuelian Li, Yangwu Ren, Ann Chao, Motoki Iwasaki, Junjie Zhu, Guoping Wu, Chih-Yi Chen, Chien-Jen Chen Scd, Pan-Chyr Yang, Victoria L Stevens, Joseph F Fraumeni, Kuang Lin, Robin G Walters, Zhengming Chen, Nilanjan Chatterjee, Olga Y Gorlova, Christopher I Amos, Hongbing Shen, Chao Agnes Hsiung, Stephen J Chanock, Nathaniel Rothman, Takashi Kohno, Qing Lan, Haoyu Zhang

Faculty, Staff and Students Publications

Background: Lung adenocarcinoma (LUAD) in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve LUAD risk prediction.

Methods: PRSs were developed using genome-wide association study summary statistics from East Asian (8,002 cases; 20,782 controls) and European (2,058 cases; 5,575 controls) populations. Single-ancestry models included PRS-25, PRS-CT, and LDpred2; multi-ancestry models included LDpred2+PRS-EUR128, PRS-CSx, and CT-SLEB. Performance was evaluated in independent East Asian data from the …

Bcaas Newsletter Fall 2025, Bcass

BCAAS Newsletter

No abstract provided.

A Comparative Evaluation Of Two Subharmonic-Aided Pressure Estimation (Shape) Analysis Methods, Hailee Mayer, Priscilla Machado, Trang Vu, Annalisa Berzigotti, Jaume Bosch, Elton Dajti, Antonina Antonenko, Kirk Wallace, Flemming Forsberg

Department of Radiology Faculty Papers

Pressure measurement in clinical practice is a valuable tool for diagnostic evaluation, especially in diseases such as portal hypertension. Currently, portal pressures are measured by invasive hepatic vein catheterization, posing risks to patients, and limiting how often measurements can be obtained. Subharmonic-aided pressure estimation (SHAPE) is an ultrasound-based technique that leverages ultrasound contrast agents (UCAs) to estimate changes in hydrostatic pressure. UCAs act as nonlinear oscillators when exposed to high enough acoustic pressures (typically > 200 kPa) and produce significant energy components ranging from subharmonics to higher harmonics. Tissues do not generate significant subharmonic components, thus making it the optimal component …

Rain, Rain, Go Away: Geoengineering And The Illusion Of Control, Hannibal Newsome

The Lender Center for Social Justice

In this article, Newsom critiques geoengineering proposals by examining how they reflect a human impulse to exert control over nature; a control that may be illusory. The piece argues that while geoengineering is increasingly touted as a solution to climate change, it brings with it ethical, ecological, and political risks that are often underappreciated, including unintended side effects, issues of governance, and moral hazard. The author calls for more caution, rigorous oversight, and humility in considering geoengineering as part of climate policy.

Ten Tips For Legal Empiricists, Jordana R. Goodman, Christa J. Laser

Northwestern Journal of Technology and Intellectual Property

This essay offers practical tips from leading legal empirical researchers to assist new scholars who are entering the field. Topics include developing meaningful research questions, designing robust survey methodologies, balancing qualitative and quantitative approaches, ensuring data transparency, fostering interdisciplinary collaboration, and navigating ethical considerations in empirical work. Drawing from their own unique challenges and successes, these scholars illuminate what they wished they would have known going into empirical research and the pitfalls to avoid.

Although many examples focus on intellectual property law, the principles outlined here are broadly applicable to all legal empirical scholarship. This essay aims to serve as …

Alicia Alonso’S Giselle: A Cuban Dancer’S Journey Into Romantic Ballet And Modern Dramaturgy | La Giselle Di Alicia Alonso: Il Viaggio Di Una Ballerina Cubana Nel Balletto Romantico E Nella Drammaturgia Moderna, Lester Tomé

Dance: Faculty Books

This article examines the trajectory of Cuban ballerina Alicia Alonso as both performer and restager of Giselle. After offering a historical overview of Romantic ballet in nineteenth-century Cuba, the study traces Alonso’s transformation into one of the most acclaimed figures in the performance history of Giselle. The text considers her interpretation of the eponymous role in the United States, Cuba and beyond, beginning with her 1943 debut as Giselle with Ballet Theatre in New York, and highlights the interplay between her performances and stagings of the piece. It charts the evolution of Alonso’s productions of Giselle from the first time …

Message In A Bottleneck: Supply Chain Disruptions And Manufacturing Output In The United States, Raja N. Kali, Gu K. Jingping, Erica J. Neuyou

Economics Faculty Publications and Presentations

We examine the effect of container shipping disruptions on US manufacturing output before and during the Covid-19 pandemic. We augment maritime trade with a global production network model, where the reliability of container logistics is critical for the on-time and full availability of inputs and the delivery of output to foreign markets. We combine a US container shipping reliability dataset with input-output and trade data to construct a novel supply chain disruption index that captures the integration of upstream and downstream linkages of the US manufacturing sector into the global supply chain. Our findings suggest that a one-unit shock leads …

Advances In Encapsulated Phase Change Materials For Integration In Thermal Management Applications, Muhammad Ghufran, David Huitink

Mechanical Engineering Faculty Publications and Presentations

Encapsulated phase change materials (ePCMs) have the potential to emerge as a key solution for efficient thermal management in various applications. This review paper explores the recent advancements in ePCMs for thermal energy storage and thermal management. We start with a basic overview of the PCMs and then performance enhancements of PCMs through the encapsulation, critical parameters for encapsulation, various encapsulation methods, and their evaluation are discussed. This review also discusses key properties and proposed figure of merit for ePCMs, impact of encapsulation on thermophysical properties, performance evaluation of ePCMs, thermal management needs, and the role of PCMs. The paper …

Innovation Interrupted: Legal And Institutional Risks Of Undermining Public-Private Partnerships, Jennifer S. Fan, Xuan-Thao Nguyen

Articles

Part I traces the development of the Bayh–Dole Act and discusses public–private partnership collaboration. Part II focuses on intellectual property generation by universities, illustrating the benefits of public– private partnership. Then Part III highlights the Trump administration’s federal funding cuts to universities that jeopardize the established public–private partnerships. Finally, Part IV details the consequences of how federal funding cuts impact the venture capital sector and the legal architecture of innovation, eroding the United States’ standing in the innovation race.