Digital Commons Network^™

Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …

Waveguide-Assisted Single-Mode Fiber Bragg Gratings In A Highly Multimode Coreless Fiber Via Femtosecond Laser Inscription For Extreme Temperature Quasi-Distributed Thermal Sensing, Farhan Mumtaz, Koustav Dey, Bohong Zhang, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This research reports a potential quasi-distributed thermal mapping optical sensing system for extreme temperatures, leveraging femtosecond (fs) laser inscribed single-mode fiber Bragg gratings (FBGs) and a waveguide within coreless, highly multimode optical fiber, resulting in a single-mode structure. Unlike doped single-mode fibers, coreless fibers composed of silica rods prevent issues associated with dopant migration and ensure data accuracy. The strategic placement of point-by-point FBGs in a cascaded formation on the fs-laser inscribed waveguide facilitates localized multipoint sensing. The long-term stability of the proposed waveguide-assisted FBG system was assessed over 24 hours at elevated temperatures (1000°C), showing no hysteresis during heating …

Embeddable Optical Fiber Sensor For Simultaneous Strain And Temperature Monitoring, Amardeep Kaur, Sudharshan Anandan, Steve Eugene Watkins, Yinan Zhang, Kumbla Chandrashekhara, Hai Xiao

Electrical and Computer Engineering Faculty Research & Creative Works

We present an embeddable hybrid optical fiber sensor based on a cascaded extrinsic Fabry–Pérot interferometer (EFPI) and intrinsic Fabry–Pérot interferometer (IFPI) for simultaneous strain and temperature monitoring in high-performance composite materials. The sensor is fabricated using femtosecond laser micromachining and is embedded within bismaleimide composite laminates manufactured via an out-of-autoclave process. Experimental results demonstrate linear and decoupled responses to strain and temperature, with the EFPI showing minimal temperature sensitivity (1.7 pm/°C) and the IFPI exhibiting high temperature sensitivity (16.1 pm/°C). Strain sensitivities for both components were consistent at 0.6pm/με in embedded conditions. The sensor maintained structural integrity and stable spectral …

Distributed Temperature Sensing In The Spray-Cooled Shell Of A 150-Ton Dc Electric Arc Furnace Using Brillouin Optical Fiber Technology, Farhan Mumtaz, Yeshwanth Reddy Mekala, Koustav Dey, Rony Kumer Saha, Ogbole Collins Inalegwu, Manoj Kumar Pullagura, Bohong Zhang, Muhammad Roman, Nicholas Dionise, Zane Voss, Jeffrey D. Smith, Ronald J. O'Malley, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents the deployment and validation of a Brillouin - distributed temperature sensing (DTS) system for real-time thermal monitoring of the spray-cooled upper shell of a 150-ton direct current Electric Arc Furnace (DC EAF) at Big River Steel Plant, Osceola, AR, USA. A four-channel Brillouin DTS system from OZ Optics was employed, with one active channel instrumented using an in-house-fabricated Brillouin scattering-depressed single-mode optical fiber (SMF28e+). The 60 m optical fiber sensor was fabricated, with 20 m allocated for thermal measurement and 40 m used as lead-in fiber to isolate the interrogator from the furnace environment. The fiber was …

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …

Fixed-Time Consensus Tracking For Nonlinear Multi-Agent Systems Under Aperiodically Intermittent Control, Lei Xue, Tong Wu, Wenwen Jia, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article explores the problem of fixed-time consensus tracking (FT-CT) for nonlinear multi-agent systems utilizing the a periodically intermittent control (AIC) strategy. In contrast to existing control algorithms, the proposed algorithm utilizes the AIC strategy instead of the conventional continuous-time control strategy, effectively reducing the consumption of communication resources. Moreover, the problem of intermittent FT-CT is well handled by proposing the average control rate of the AIC strategy. Two theorems based on the cases of directed and undirected graphs are proposed, respectively. Finally, the validity of these results is confirmed through numerical simulations on a general nonlinear system and a …

Effect Of Process Parameters On Thermal Response Of An Oxy-Fuel Burner/Injector Panel In An Electric Arc Furnace Via Fiber Optic Sensors, Mobashir Ahmed, Rony Kumer Saha, Koustav Dey, Todd Sander, Jie Huang, Ronald J. O'Malley

Electrical and Computer Engineering Faculty Research & Creative Works

Modern oxy-fuel burner/injectors in electric arc furnaces (EAFs) play a critical role in scrap melting, liquid steel refining, and slag foaming. However, varying operational modes, combined with dynamic process conditions, such as arcing and slag behavior, can expose the injector panel surface to intense thermal conditions that can compromise efficiency and safety. Conventional monitoring techniques, including cooling water temperature measurements and thermocouples, fail to capture localized thermal anomalies due to their limited spatial resolution and susceptibility to electromagnetic interference. In this study, four high-resolution Rayleigh backscattering-based fiber optic sensors, interrogated via optical frequency domain reflectometry, were embedded in top and …

Resolving Stiffness Trade-Offs In Simultaneous Pressure And Vibration Sensing Using A Corrugated-Tube Fiber-Optic Sensor, Yizheng Chen, Yan Tang, Jie Huang, Qi Zhang, Biyao Shi, Zewei Wu

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes and experimentally demonstrates a corrugated-tube-based fiber-optic sensor capable of measuring pressure, vibration, or both simultaneously. To address the limited sensitivity of conventional diaphragm-based designs, the sensor incorporates an optimized corrugated tube that balances the conflicting stiffness requirements for pressure and vibration measurements. The corrugated tube, acting as a mechanical transducer, is integrated with an extrinsic fiber-optic Fabry–Perot interferometer (EFPI). The EFPI cavity is formed between a reflective surface at the sealed end of the corrugated tube and the cleaved end face of an optical fiber fixed within a mounting assembly. In this configuration, displacement of the corrugated …

Nash Equilibrium Strategies For Multicluster Pursuit–Evasion Game With Disturbances: A Prescribed-Time Convergence Approach, Lei Xue, Xian Yu, Yongbao Wu, Jian Liu, Changyin Sun, D. C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article investigates the problem of prescribed-time Nash equilibrium (NE) seeking for a multicluster pursuit–evasion game (PEG) subject to external disturbances. To mitigate the impact of disturbances and reach the NE within a user-defined prescribed time, a prescribed-time disturbance observer (PTDO) is devised to estimate and compensate for them. Based on this observation, a novel control algorithm is developed, which facilitates collaboration among multiple pursuers to capture multiple evaders within the prescribed time. It is theoretically demonstrated that the designed algorithm ensures prescribed-time convergence to the NE of the multicluster PEG with disturbances. Finally, numerical simulations are conducted to verify …

Real-Time Multiregional Market-To-Market Congestion Management Through Exchange Of Relief Cost Curve, Haotian Chen, Yonghong Chen, Jose Daniel Lara, Jarrad Wright, Matthew Bossart, Sebastian De Jesus Machado, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a novel method for multiregional market-to-market (M2M) coordinated congestion management. It identifies shortcomings in existing M2M approaches, where Regional Transmission Organizations (RTOs) exchange shadow prices and relief requests to optimize congestion relief allocations across interconnected regions. Two methods are proposed to enhance flow and price convergence. The first method proposes that both Regional Transmission Organizations (RTOs) use state-estimator flows directly to determine relief requirements, eliminating delays and potential oscillations caused by using market flows calculated from the prior period under existing M2M approach. The second method involves exchanging transmission relief cost curves, enabling each RTOs to integrate …

Corrections To: Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems (Ieee Transactions On Instrumentation And Measurement (2026) 75 (1–12) Doi: 10.1109/Tim.2026.3676091), Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In the above article [1], a wording ambiguity appears in Proposition 4 regarding the description of the missing at random (MAR) mechanism. The published sentence states that the probability of observing the kth sample depends on the realized measurement value. This wording may be interpreted as dependence on the current unobserved value y[tk], which could suggest a missing not at random (MNAR) mechanism. The intended MAR mechanism is that the observation probability for the kth sample depends only on previously observed measurement information, such as y[tk-1], and not on the current unobserved value y[tk]. Therefore, the corrected wording clarifies that …

Multi-Agent Reinforcement Learning Driven Package Pdn Design Automation, Haran Manoharan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

The design of package-level power delivery networks (PDNs) has become increasingly challenging as modern high-performance systems demand higher currents. Existing PDN design flows treat ball map assignment, stackup selection, and power plane routing as separate, largely manual steps, leading to long iteration times and limited scalability. This work proposes a unified and automated package PDN design framework based on multi-agent reinforcement learning (MARL). Each power domain is modeled as an agent, with specialized agents responsible for ball map assignment, routing layer selection, and power plane synthesis. A central controller coordinates agent decisions using a global reward that captures electrical and …

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …

Enhancing Explainable Ai For Medical Imaging: Improved Lime Interpretation With Influence Mapping, Abiha Tahsin Chowdhury, Dhanush Bavisetti, Daniel B. Hier, Rahul Dubey, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

The integration of artificial intelligence (AI) into medical imaging is progressing rapidly. It is essential for these AI tools to be transparent, interpretable, and explainable to gain the trust of clinicians and regulators. Current state-of-the-art explainable AI (XAI) techniques in imaging includes Local Interpretable Model-Agnostic Explanations (LIME), Shapley Additive Explanations (SHAP), and Gradient-weighted Class Activation Mapping (Grad-CAM). Recent studies have shown that LIME often suffers from inconsistency and unreliability which limits their utility in sensitive fields like medical imaging. This paper proposes Influence Map based Explanation (IME), an enhanced variant of the original LIME framework, that aggregates multiple runs to …

Event-Based Predefined-Time Synchronization For Complex Networks With Deception Attacks: An Asynchronously Intermittent Strategy, Lei Xue, Jiong Yu, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article studies the practical predefined-time synchronization (PPTS) for complex networks (CNs) under deception attacks based on the asynchronously intermittent event-triggered control (AIE-TC). Notably, AIE-TC effectively integrates the advantages of asynchronously intermittent control (AIC) and event-triggered control, where AIC provides each subsystem node with independent control and rest intervals. Besides, all synchronization errors of the CNs converge to an adjustable neighborhood within the predefined time by designing a bounded time-varying function into the controller. Moreover, this article considers that the transmission network is subjected to stochastic deception attacks modeled by a Markov process, which captures the state-driven dynamic transition characteristics …

Effect Of Sample Properties On Short-Circuited Waveguide Measurements For Materials Characterization, Alexander Hook, Jared Sinkey, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Microwave materials characterization measurements can be performed using a number of well-established approaches. One such approach, the filled transmission line approach featuring a short-circuited rectangular waveguide (SC-RWG) sample holder, is known to have sample placement restrictions related to measurement viability. This work focuses on this approach and addresses the measurement restrictions within the context of sample length and dielectric properties. The complex reflection properties, S11, of a sample placed in a SC-RWG sample holder are studied to quantitively define when a sample must be offset from the SC-end. The impact of the sample holder is also studied from a measurement …

Femtosecond-Laser-Inscribed Cladding Fiber Bragg Gratings: Architectures, Design Trade-Offs And Future Sensing Opportunities, Koustav Dey, Rex E. Gerald, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Femtosecond (fs) laser inscription enables fiber Bragg gratings (FBGs) to be positioned beyond the fiber core, including within the cladding, thereby expanding control over modal interactions and directional sensing. These cladding fiber Bragg gratings (CLFBGs) extend FBG functionality through interactions with core, cladding, and evanescent fields. Their operation does not involve fundamentally different grating physics; rather, core-mode, cladding-mode, and coupled-mode responses depend on power distribution, modal overlap with the laser-inscribed refractive-index modulation (RIM), grating position, fiber geometry, modal excitation, and interrogation configuration. This Perspective reviews advances in CLFBG fabrication, optical characteristics, sensing mechanisms, and applications. Cladding-waveguide-assisted, evanescent-field-coupled, and direct cladding-mode-excitation …

Consumer Responses To Ethical And Privacy Concerns In Ai Chatbots: Evidence From Offensive Language, Gender Bias, And Digital Privacy, Jikhan Jeong

Economics Faculty Research & Creative Works

Due to the rapid innovation of artificial intelligence (AI) and big data, AI chatbots have become increasingly influential computational social systems (CSS) in everyday life. However, the expansion of interactions between AI chatbots and consumers has raised significant ethical and privacy concerns. Using data from an online survey, this study empirically examines how consumer concerns about AI ethics and privacy influence their intention to use AI chatbots. These concerns are categorized into three types: 1) offensive language (generated by AI chatbots or users); 2) gender-biased language (from either source); and 3) digital privacy violations. The findings suggest that prior experience …

Lysine Demethylase 4a Is A Centrosome-Associated Protein Required For Centrosome Integrity And Genomic Stability, Pratim Chowdhury, Xiaoli Wang, Richard I Han, Manga Motrapu, Ashley G Boice, Yuya Nakatani, Sofia Vargas-Hernandez, Julia F Love, Claude Chew, Sandra L Grimm, Dereck Mezquita, Frank M Mason, Elisabeth D Martinez, Cristian Coarfa, Cheryl L Walker, Anna-Karin Gustavsson, Ruhee Dere

Faculty, Staff and Students Publications

Centrosomes play a fundamental role in nucleating and organizing microtubules in the cell and are vital for faithful chromosome segregation and maintenance of genomic stability. Loss of structural or functional integrity of centrosomes causes genomic instability and is a driver of oncogenesis. Here we identify lysine demethylase 4A (KDM4A), an epigenetic 'eraser' of chromatin methyl marks, as a centrosome-localized protein, visualized at the nanometer-scale resolution. We additionally uncovered that KDM4A demethylase enzymatic activity is required to maintain centrosome homeostasis and integrity; a previously unknown functionality unlinked to altered expression of genes regulating centrosome number. We find that KDM4A interacts with …

Amino Acids And Lean Mass Accretion In Preterm Neonates, Antonio C Ramos Dos Santos, Marta L Fiorotto, Teresa A Davis

Faculty, Staff and Students Publications

Purpose of review: This review evaluates recent evidence on how total protein and energy intake, amino acid composition, and nutrient delivery modality influence protein synthesis in preterm neonates, with the goal of informing nutritional strategies to support optimal lean mass accretion and growth.

Recent findings: Preterm neonates exhibit anabolic resistance to feeding due to impaired insulin and amino acid signaling in skeletal muscle. Enteral nutrition, especially fortified human milk, supports better lean mass accretion and neurodevelopment than parenteral nutrition. Intermittent bolus feeding and pulsatile leucine supplementation during continuous feeding further enhance mTORC1-dependent translation initiation signaling and protein synthesis efficiency in …

Feral Horses And Native Ungulates: Evaluating The Potential For Competition In Predator–Prey Communities Of Alberta’S Upper Foothills, Birch Gano

Graduate Student Theses, Dissertations, & Professional Papers

Feral herbivores are expanding in range and numbers globally, yet their community-level effects in ecosystems are poorly resolved. We evaluated whether feral horses reshape predator–prey–vegetation dynamics in Alberta’s Upper Foothills, Canada, through two pathways; i) potential exploitative competition for forage and ii) apparent competition via shared predators. We combined fecal DNA metabarcoding with remote wildlife cameras to quantify diets, spatiotemporal co-occurrence, and the role of horses in carnivore diet. We analyzed 241 ungulate scats (feral horses, elk, bighorn sheep, cattle, moose, and deer), 96 combined camera-years at 23 sites, and 190 carnivore scats (wolves, cougars, coyotes, bears) from 2023–2025. The …

Searching For Nooks And Crannies: Geometric And Mechanistic Perspectives On Transformer Language Model Interpretability, Anna Marbut

Graduate Student Theses, Dissertations, & Professional Papers

Large language models (LLMs) have demonstrated remarkable linguistic capabilities, but the internal mechanisms driving their performance and behavior remain poorly understood. This dissertation investigates the interpretability of transformer-based language models from two complementary perspectives: the geometric organization of model internals in encoder-only models, and the mechanisms underlying safety behavior in decoder-only generative models.

In Part I, we address the challenge of measuring geometric properties in high-dimensional latent spaces, proposing and evaluating alternative measures of data spread that improve upon commonly used metrics. We then apply these measures alongside quantization-based metrics to examine the relationship between latent space geometry and downstream …

Continental Violence And The "Oregon Question": George Frederick Ruxton And The Nineteenth-Century Pacific Northwest, Rory Orion Johnson

Graduate Student Theses, Dissertations, & Professional Papers

This paper builds on recent efforts to depict Indigenous polities across North America in their international relations with European and Euro-American colonists and their centralized governments. It examines George Frederick Ruxton, a private English citizen and former army lieutenant, as he developed his response to the U.S.-British Oregon dispute while living in London in early 1846. He concluded that continental warfare was imminent and took overt steps to influence British policy, which he believed could halt U.S. expansion and definitively resolve the “Oregon Question.”

Comprehensive Characterization Of Volatile Organic Compounds And Particulate Matter Emissions From Residential Wood Combustion And Their Impacts On Indoor And Outdoor Air Quality, Damien Tyler Ketcherside

Graduate Student Theses, Dissertations, & Professional Papers

Residential wood combustion (RWC) is a major wintertime source of fine particulate matter (PM2.5) and a potentially important source of volatile organic compounds (VOCs). Yet, uncertainties remain regarding its contribution to ambient air pollution, its representation in anthropogenic emissions inventories, and its direct impacts on indoor air quality via fugitive emissions. This dissertation investigates VOC and PM2.5 emissions from RWC activities, using in situ measurements of gas- and particle-phase pollutants in indoor and outdoor environments.

Chapter 2 presents ambient field observations of 24 volatile organic compounds (VOCs), carbon monoxide (CO), ozone (O3), and fine particulate matter (PM2.5) in the intermountain …

Flight Control And Costs In Unsteady And Turbulent Airflows In Ringneck Doves (Streptopelia Risoria), Rémy Alexandre Delplanche

Graduate Student Theses, Dissertations, & Professional Papers

The aerosphere is a highly dynamic environment where turbulence (irregular, chaotic changes in airflow velocity) and unsteady airflows (variations in flow velocity with time at a given spatial point, e.g. gusts) are ubiquitous [1,2]. These airflows are known to perturb man-made aircraft [3,4], and are thus expected to challenge biological fliers such as birds. However, birds display remarkable flight control in turbulent and gusty conditions, suggesting that they have evolved mechanisms to resist aerial perturbations. This in-flight stability is broadly attributed to wing morphing, the capacity for wing shape and orientation to be altered during flight, yet how morphable wings …

An Institutional And Policy Analysis Of Climate Adaptation In Dhaka, Bangladesh: An Examination Of Urban Heat Island Mitigation Strategies, Tamanna Binte Mesbah

Graduate Student Theses, Dissertations, & Professional Papers

This thesis examines the institutional capacity for Urban Heat Island (UHI) mitigation in Dhaka, Bangladesh, focusing on governance structures, institutional arrangements, and implementation effectiveness. An analytical framework is applied to assess the capacity of key urban institutions including Rajdhani Unnayan Kartripakkha (RAJUK), Dhaka North City Corporation (DNCC), Dhaka South City Corporation (DSCC), and the Department of Environment (DoE) across dimensions of leadership, resources, coordination, and learning capacity. The study also examines governance dynamics such as inter-agency coordination, knowledge exchange, and mobilization capacity as they relate to the planning and implementation of heat mitigation strategies. Through semi-structured expert interviews the research …

Phase 1 Trial Of Withania Somnifera Leaf Extract (Rh324) In Advanced Non-Small Cell Lung Cancer Including [18f]Fdg Pet/Ct As A Short-Term Metabolic Biomarker To Assess Efficacy: A Novel Model For Assessment Of Complimentary Therapies In Early Phase Human Clinical Trials, Jin Uk Heo, Santosh Rao, Herbert B Newton, Afshin Dowlati, Raymond F Muzic, Arash Kardan

Faculty, Staff and Students Publications

Background: Withania somnifera (WS), commonly known as ashwagandha, has been used in the traditional medical system of India. It has shown significant activity against numerous solid tumor varieties in pre-clinical in vitro and in vivo studies. This study focuses on RH324 (ReHeva Biosciences, Columbus, OH), a pharmaceutical-grade formulation derived from WS, which has received FDA allowance for clinical development as a botanical drug in the treatment of cancer.

Methods: A phase 1 open label dose ranging study of oral RH324 in advanced non-small cell lung cancer (NSCLC) was conducted. The primary endpoint of the study was assessment of short-term safety …