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Waves Generated by Moving Vessels and Cnoidal Wave Interactions with Either a Partially-submerged Porous Barrier or a Mixed Partially-submerged and Submerged Dual Porous-Barrier System
No full textThis dissertation presents its first topic on the development of predictive models for estimating moving vessel generated maximum wave heights at Sabine–Neches Waterway in Texas. Using the recorded wave and vessels’ sailing data, the empirical approach with the calibration and validation procedures is carried out to confirm those models’ applicability. The performance of each proposed model is evaluated with two statistical measures in defining model accuracy. For coastal protection consideration, the second part of study presented focuses on the theoretical investigation of the hydrodynamic interactions between cnoidal waves and two types of porous breakwaters. One is a partially submerged porous barrier and the other one is a dual-barrier system consisting of a complete submerged frontal porous wall and a partially submerged rear porous wall. For both breakwater systems, the unknown coefficients of the velocity potentials at each flow domain are analytically derived according to the least squares method by minimizing squared error functions formulated from the mixed matching conditions. The expressions of wave elevations and hydrodynamic forces on breakwaters are also derived to calculate the reflected and transmitted waves and impact forces for breakwaters’ performance evaluations. Solution validations are performed by comparing results of limiting cases with those from other published literatures. The physical variables, such as wave height, wave length, submerged or bottom-up vertical dimensions of breakwaters, gap between two breakwaters, and porous properties, that affect wave run-up, wave reflection and transmission, and wave forces on breakwaters are investigated. For a partially submerged porous barrier case, the results show that with an increase in submerged barrier depth, the transmission coefficient decreases, although the wave force increases. Longer wave-length waves have a better tendency to be transmitted towards downstream and impact slightly greater forces on the breakwaters. However, with the inclusion of porous properties into the barrier, both the transmission coefficient and receiving wave force are considerably reduced. By considering a dual porous-barrier system, similarly, with an increase in submerged vertical dimensions of both breakwaters, the reflection coefficient is substantially decreased. Due to the blockage effect provided by the frontal barrier, the wave force on the rear barrier can be reduced when comparing to those from a single barrier case. Again, the porous effect applied to both barriers can greatly lower the values of transmission coefficient and wave forces on both breakwaters. An interesting finding for the gap effect is that the maximum wave forces on either the frontal or the rear breakwater are shown to have periodic oscillations with the peak appearing at the gap arranged to be equal to a multiple of half wave length while the minimum values of the induced maximum forces occur when the frontal and rear breakwaters are placed separately with a gap of a odd multiple of quarter wave length
Threshold-based Association Analysis Frameworks for Continuous Variables
No full textAssociation analysis centers on finding interesting patterns in large datasets. Past work developed association-mining frameworks, which mine association rules, frequent sequences, graphs, and col-locations. However, most association analysis framework mine discrete variables and association analysis frameworks, which mine continuous variables, are lacking. This dissertation consists of three studies that focuses on the development of threshold-based association analysis frameworks for continuous variables. The first study introduces Norma, a novel association-mining framework tailored for continuous spatial variables analysis. Norma introduces the unique Continuous Variable Threshold (CVT) pattern, aiming to identify a pair of thresholds within the value domain of two continuous variables, revealing strong associations within a specified geographic area. For example, it may unveil a strong association between COVID-19 infection rates above 2% and poverty rates above 15% in New Mexico. Norma associates point-wise functions with each variable-e.g., a function that returns poverty rates for each location in New Mexico. It employs a novel interestingness function, which measures agreement with respect to hotspots where variable point-wise functions exceed associated thresholds. Norma also employs a grid-based spatial hotspot-growing algorithm to discover high-interestingness regions and pairs of thresholds that generate interestingness surpassing a predefined threshold. Furthermore, the framework introduces measures for assessing variable relatedness based on CVT associations. A comparative case study against traditional correlation methods are presented using county-level COVID-19 infection rates and nineteen other socio-economic variables from the continuous United States, and demonstrate how Norma can be used to explore association among subset of values related to spatial continuous variables. The second study introduces thresholds to classical correlation analysis; it proposes a novel generalization of classical correlation, called threshold correlation, and assesses the merit of threshold correlation analysis in a case study which centers on understanding the relationship between temperature and relative humidity in locations in five different cities. In contrast to classical correlation, threshold correlation restricts observations for which the correlation is computed using pairs (th1, th2) of thresholds and introduces four forms of threshold correlations named High/High, Low/Low, High/Low, Low/High correlations, excluding observations whose values are above/below the thresholds th1 and th2 before computing the correlation of the remaining observations. The third study proposes a novel, density-based framework called Sirius for identifying global and regional co-location patterns regarding sets of continuous variables. The goal is to identify sets of continuous variables where continuous variables with values from the wings of their statistical distribution are co-located. Sirius employs an value-weighted density estimation to estimate the strength of a co-location pattern for a given location; this is done by combining z-scores of value-weighted non-parametric density functions, measuring the degree of highness/lowness of a continuous variable in a given location. Global co-location patterns can then be identified by measuring their area under the particular colocation measure curve. Regional co-location patterns can be obtained by identifying regions where the co-location measure curve is above a user-defined threshold. Finally, we demo and evaluate Sirius for a US dataset containing COVID-19 infection rates and seven other continuous variables for the state of Virginia
Development of a Low-Cost PCB-Based High-Frequency AC Susceptometer for Magnetic Materials Characterization
No full textThis thesis presents the development and performance evaluation of femtoMag, a novel, cost-effective high-frequency AC susceptometer designed to characterize magnetic materials up to 200 MHz. Leveraging a low-cost printed circuit board (PCB) design and commercially available high-frequency electronics, femtoMag addresses limitations in conventional susceptometry by enabling measurements of magnetic powders and thin films without requiring specific geometries or extensive sample preparation. The design employs a PCB-based low-inductance single-turn coil, which enhances the sensor's performance at higher frequencies compared to traditional multi-turn coil designs. Electromagnetic properties of the system were modeled using ANSYS HFSS simulations, while physical components were created with Autodesk Fusion 360 and DipTrace. Performance validation was conducted using reference samples with known permeability values, showing close agreement with conventional measurement methods. This work highlights femtoMag's simplicity, cost-efficiency, and reliability in providing accurate magnetic characterization data, establishing it as a powerful tool for diverse magnetic material studies, particularly in cases where sample quantities or geometries are limited
Polymeric Delivery with Dual Drug Payloads for Hepatocellular Carcinoma (HCC) Therapy
No full textHepatocellular carcinoma (HCC) is the primary type of liver cancer. Systemic therapy is the preferred treatment strategy when patients are not eligible for surgery. In recent years, multitargeted tyrosine kinases and checkpoint inhibitors have attracted attention to HCC therapy. Despite target therapy and immunotherapy showing effective effects in HCC patients, chemotherapy is still a preferred option for most patients due to economic considerations and feasibility for patients at advanced stages. However, chemoresistance is still a significant challenge for the treatment of HCC patients. To overcome drug resistance, the combination of chemotherapeutic drugs targeting multiple signaling pathways might be a feasible option. Previous studies demonstrated that combining cyclopamine (CPA) and paclitaxel (PTX) exhibits promising anticancer effects against pancreatic cancer. A polymeric micellar drug delivery system was developed to improve solubility and anticancer efficacy and reduce toxicity of CPA and PTX. However, a comprehensive analysis of this delivery system has not yet been conducted. This project combined cyclopamine (CPA) with paclitaxel (PTX) to treat HCC. The toxicity, pharmacokinetics, and anticancer effects of this micellar system were evaluated in this project. The combination effect of CPA and PTX against HCC cells was investigated in vitro. Additionally, the central composition design (CCD) method facilitated the optimization of the formulation. Three formulations were selected to evaluate stability at different storage conditions. A toxicity study was conducted to determine the optimal formulation for further research. Before anticancer efficacy studies, toxicity studies in healthy male and female FVB mice were performed to find the maximum tolerated dose in mice. Results indicated that there was a difference in toxicity and PK of CPA and PTX between females and males. Healthy female mice were more tolerant to higher doses of M-CPA/PTX than male mice. Also, at the same dosing level, male mice presented significantly higher blood concentrations of CPA and lower clearance than female mice. This could be related to their different expression levels of drug metabolism enzymes, body fat, organ perfusion, and blood volume. Before conducting the efficacy study, toxicological and pharmacokinetic differences between diseased and healthy mice were investigated. Healthy mice were more tolerant to M-CPA/PTX than c-myc-driven HCC-bearing mice. In diseased mice, concentrations of PTX were higher than in healthy mice, which suggested that HCC compromised liver function and that dose adjustment was needed to reduce toxicity in diseased mice. This micellar system could significantly prolong animal survival and suppress tumor growth. Besides the difference in efficacy between sexes, it was found that females tend to benefit more from the treatment. Conclusion: Overall, our pre-clinical studies strongly indicated that the polymeric delivery system significantly improved the anticancer efficacy and reduced the toxicity of the CPA/PTX combination
Fog Causality, Reversibility, Forming Mechanisms, and Causal Relationships between Fog and Turbulence
No full textThe presence of fog significantly impacts transportation safety, agriculture, and day-today activities. Enhanced prediction models could significantly benefit society by minimizing the adverse effects of fog. However, predicting fog remains challenging due to limited understanding of its formation, duration, and dissipation. Turbulent kinetic energy (k) and relative humidity RH have known connections to the fog life-cycle, but these connections need to be quantified and implemented in prediction models. To address this, the Fog and Turbulence Interactions in the Marine Atmosphere (FATIMA) campaign was conducted in the Nova Scotia region in July of 2022. Over the month of July, many fog events were identified with various formation mechanisms on Sable Island. In this research, techniques from time series analysis and continuous wavelet transforms (CWT) are used to explore the reversibility and causality of fog events, and to what extent this causality can be inferred from turbulent time series variables. The approach involves examining cross-scale and time correlations to establish a statistical identity for fog-generating events, enhancing prediction accuracy. Intensity, the reciprocal of visibility, is used as a surrogate for fog, and k and RH and are explored as variables that can help formation and cause dissipation. This method reveals cascades at fine time resolutions, which are indicative of the multi-scale nature of fog events. A statistical, quantifiable, correlation between fog intensity, k, and RH is also found in this study. This research provides valuable insights into the underlying mechanisms of fog occurrence, paving the way for improved fog prediction and response strategies
Investigating the Role of Physical and Chemical Weathering and Sorting for Downstream Fining of Sediment in Kangerlussuaq, Greenland
No full textIn channelized flow, sediment fines downstream as a result of abrasion, hydrodynamic sorting, and chemical weathering. While chemical weathering is typically limited in high-latitude environments, glacierized catchments can behave differently. Alpine glaciers, for example, exhibit chemical weathering rates comparable to, or exceeding, the global average. The substantial yield of freshly weathered sediment from retreating glaciers, which is comprised of grains that are physically abraded and strained, readily reacts with meltwater through dissolution. Thus, meltwater flux is the primary control on chemical weathering in glacierized catchments. With the rise in high-latitude meltwater discharge, driven by increased atmospheric temperatures, these processes may impact the character of sediment exported by glaciers. This research explores the mechanisms and impacts of downstream fining in a glacierized catchment located in Southwest Greenland. Specifically, we hypothesize that downstream fining in this catchment is a function of abrasion, hydrodynamic sorting, and grain-scale dissolution, explaining the observed fining trends from source-to-sink. Our study site, Kangerlussuaq, hosts a braided river system that emerges from three land-terminating lobes of the Greenland Ice Sheet. At the ice margin, referred to as the sediment 'source', we observed terminal moraines comprised of poorly sorted, coarse and fine sediment. The sediment 'sink' is defined as the marine fjord waters, where the river constructs a delta and an extensive, sinuous turbidity current channel. Within a distance of approximately 40 kilometers, the sediment composition undergoes a size transition, shifting to predominantly well-sorted, medium- to fine-grained sand in the submarine channel with clays to silty clays on its flanks. To test our hypothesis, we collected sediment samples for grain size and mineralogical analyses, as well as water samples for cation and anion analysis, along with pH and temperature measurements. We applied models for sediment fining driven by abrasion, sorting, and dissolution to assess the influence of each in this system. We find that the abrasion model cannot explicitly determine if abrasion is the dominant control of downstream fining in the system, but we do not doubt its prevalence in impacting grain size from source to sink. Grain-scale chemical weathering, or dissolution, could be significant for some mineralogies if the residence times of sediment in the Qinnguata Kuusua braid plain are long enough to allow dissolution to take place. Sorting is found to likely be the dominant process exerting control over downstream fining trends observed in the system, with only minor discrepancies between the model prediction and the observed data
An Investigation of Anti-Proliferative Mechanisms of Novel Liver X Receptor Inverse Agonists in Pancreatic Cancer
No full textPancreatic cancer is the third leading cause of cancer-related deaths in the United States, with the worst 5-year survival. Significant challenges include late diagnosis due to inadequate screening tests and ineffective treatment options. Liver X Receptors (LXRs) are ligand-modulated transcription factors that regulate fatty acid metabolism and cholesterol transport. LXRs are overexpressed in pancreatic cancer, and targeting LXR with small molecule ligands has emerged as a promising therapeutic strategy. However, existing LXR ligands are limited by adverse effects. A screen of a focused library of drug-like molecules identified novel LXR ligand GAC0001E5 (1E5) that exhibited anti-proliferative effects in human pancreatic ductal adenocarcinoma (PDAC) cell lines. 1E5 repressed LXR target gene expression and reduced cellular LXRb levels, acting as an LXR “degrader.” Mechanistic studies revealed disruption of glutamine metabolism upon 1E5 treatment, but the consequence of LXR degradation and its connection with anti-proliferative effects has not been explored. This study aims to determine the mechanism of inhibitory effects of novel LXR inverse agonists in pancreatic cancer cells. In Chapter 1, we treated human PDAC cells with well-known LXR ligands that could activate or inhibit LXR. Interestingly, blocking LXR was insufficient to inhibit cell proliferation as SR9238, a potent LXR inhibitor, did not exert any anti-proliferative effects. However, we noted that novel ligands 1E5 and KD-95 reduced cellular LXRb levels, whereas SR9238 and GW3965 increased LXRb protein levels. This observation suggested that a reduction in cellular LXRb protein may be sufficient to exert anti-proliferative effects. Moreover, LXR knockdown presented anti-proliferative effects in PDAC cells. In Chapter 2, time-course studies in cycloheximide-treated cells indicated that 1E5 and KD-95 decreased protein stability, whereas GW3965 and SR9238 had the opposite effect. Inhibition of proteasomal degradation and autophagy abolished the impact of 1E5 and KD-95 in a cell line-dependent manner. Furthermore, RNA-seq analysis of 1E5-treated PDAC cells implied the involvement of aggrephagy and RING-type E3 ligases in LXRb degradation. These findings suggest that the novel ligands may impart anti-proliferative effects by disrupting LXRb protein stability via autophagy and proteasomal pathways
Lightweight, Post-Quantum Secure Cryptography Based on Ascon: Hardware Implementation in Automotive Applications
No full textWith the rapid growth of connected vehicles and the vulnerability of embedded systems against cyber attacks in an era where quantum computers are becoming a reality, post-quantum cryptography (PQC) is a crucial solution. Yet, by nature, automotive sensors are limited in power, processing capability, memory in implementing secure measures. This study presents a pioneering approach to securing automotive systems against post-quantum threats by integrating the Ascon cipher suite---a lightweight cryptographic protocol---into embedded automotive environments. By combining Ascon with the Controller Area Network (CAN) protocol on an Artix-7 Field Programmable Gate Array (FPGA), we achieve low power consumption while ensuring high performance in post-quantum-resistant cryptographic tasks. The Ascon module is designed to optimize computational efficiency through bitwise Boolean operations and logic gates, avoiding resource-intensive look-up tables and achieving superior processing speed. Our hardware design delivers significant speed improvements of 100 times over software implementations and operates effectively within a 100 MHz clock while demonstrating low resource usage. Furthermore, a custom digital signal processing block supports CAN protocol integration, handling message alignment and synchronization to maintain signal integrity under automotive environmental noise. Our work provides a power-efficient, robust cryptographic solution that prepares automotive systems for quantum-era security challenges, emphasizing lightweight cryptography’s readiness for real-world deployment in automotive industries
A Comparison of Control Methods for Spacecraft Maneuvering With Run Time Assurance
No full textIn the vast subject of aerospace systems, safety is a critical factor in mission completion within the controls field. Controllers designed using data-based approaches like artificial intelligence must uphold the same levels of safety expected from modern controllers, such as Linear Quadratic Regulators. This is accomplished with the application of Run Time Assurance, which ensures the system states will remain within a predefined safe set of values, no matter the potentially dangerous control actions from the primary controller. This research compares control approaches for a deputy spacecraft conducting proximity operations to safely egress from near a chief spacecraft to a predefined relative parking orbit. This trajectory is described in a linearized relative motion reference frame and is calculated from a variety of modern control methods: Linear Quadratic Regulation, Linear Quadratic Integration, and Linear Quadratic Tracking. The initial conditions are chosen to force an unsafe trajectory to demonstrate how the use of Run Time Assurance ensures the system remains within the set of safe states. The two Run Time Assurance methods utilized are an active set invariance filter and a switching backup controller, both of which use a control barrier function to determine the safe set of values for the affected outputs with differing approaches of implementation. Three different scenarios are investigated to prove the safety bounds are not violated, each with a new situation addressed complete with new specific initial conditions. The results demonstrate that each modern controller is fully capable of implementing Run Time Assurance methods, while displaying varying levels of success based on the calculation-based values of the summation of control output and the rendezvous time
Impact of Whiteness on Undergraduate Mathematics Identity Scale: Theoretical Foundation, Scale Development, and Validation
No full textBackground: Historically, mathematics has been considered a race and gender-neutral subject. More recently, scholars are using critical, conceptual lenses to interrogate race and gender inequities in mathematics teaching and learning spaces. One such lens is the Framework for Understanding Whiteness in Mathematics Education, which is composed of three interrelated dimensions: institutional, labor, and identity. To date, a scale to operationalize this framework has not been developed. Purpose: The purpose of this research is to develop and test a scale that operationalizes the mathematics identity dimension of the Framework for Understanding Whiteness in Mathematics Education framework. Three research questions guiding this work are: (1) What are the results of the reliability and validity procedures of the first iteration of the Impact of Whiteness on Undergraduate Mathematics Identity (IWUM) Scale? (2) How many factors and items describe the final, fully developed IWUM Scale? (3) What are the results of the reliability procedures of the final, fully developed iteration of the IWUM Scale? Methods: This study employs a three-phase model for scale development grounded in QuantCrit principles. In phase one, 14 scale items were developed and pre-tested with 28 target users, four content experts, and 16 undergraduate STEM students. Data included written feedback and cognitive interviews. In phase two, revised survey items were administered to 126 undergraduate STEM students. In phase three, Exploratory Factor Analysis was conducted. Findings: For the first research question, unacceptable Cronbach’s alpha and fair to moderate Fleiss’ kappa were reported for the initial survey items. During phase one, there was also unsatisfactory face validity of the scale items. The final scale can be described as six factors and 20 items where after large-scale implementation, an acceptable Cronbach’s alpha was reported. Conclusion: After further development and large-scale implementation, an acceptable Cronbach’s alpha was reported. The final scale can be described as six factors and 20 items. The findings from this three-phase study reveal improvement in the survey items between the initial scale items and the final scale items. The findings also indicate the usability of this scale within undergraduate STEM spaces and room for continued development of the scale