Lyconadin A (1) is a structurally unique Lycopodium alkaloid with antitumor properties, isolated from the club moss Lycopodium complanatum. We are developing a synthetic route to 1 based on a novel 7-exo-trig/6-exo-trig acyl radical cascade cyclization. The synthesis of model acyl radical cascade precursor 23 will be presented. Key features of this synthesis include the suppression of competing elimination during the alkylation of a hindered phenethyl bromide and the use of a lactone as a precursor to a compound bearing two differentially protected primary alcohols. An account of our studies on the model acyl radical cascade cyclization (23 to 24 above) will also be given, including a stereochemical analysis of the product. Our findings have been applied to develop a more detailed stereoselective synthetic plan for Lyconadin A (1).

This thesis studies CP violation in the decay of the Ξ− hyperon, also known as the cascade baryon, which decays in the sequence Ξ− → Λπ− → pπ−π−. A difference between the angular distribution of this decay sequence and the angular distribution of the charge conjugate decay sequence ͞Ξ+ →͞Λπ+ → ͞pπ+π+, after taking into account the inversion of the momenta due to the parity operation, is indicative of CP violation. The decay sequence is described by three asymmetry parameters: αΞ, αΛ and φΞ, while the charge conjugate decay's sequence is described by: ͞αΞ, ͞αΛ and ͞φΞ. A measure of CP violation is given by the CP violating observables: AΞ, AΛ and ΦΞ. The aim of this thesis is to study how the normalised statistical uncertainties in the asymmetry parameters and in the CP violating observables depend on the magnitude of the polarisation vector (polarisation) of the cascade and the anticascade. This was done by simulating 1.0×107 Ξ− → Λπ− → pπ−π− and  ͞Ξ+ →͞Λπ+ → ͞pπ+π+ decays for different values of polarisation of the cascades using Monte Carlo, and then utilising maximum likelihood estimation and error propagation to estimate the uncertainties in the parameters and in the observables. It was shown using the methods of this thesis that the normalised statistical uncertainties in the asymmetry parameters and the CP violating observables decreased whenever the polarisation was increased, although with diminishing returns. In the region of 10% − 50% polarisation, the decrease in the uncertainties was substantial. An increase from 10% to 50% polarisation lowered all of the uncertainties by 76% − 80%. In the region of 50% − 100% polarisation, the decrease in the uncertainties was slightly less. An increase from 50% to 100% polarisation lowered the uncertainties in αΞ,  ͞αΞ and AΞ by roughly 33%, in αΛ,  ͞αΛ and AΛ by roughly 40%, and in φΞ,  ͞φΞ and ΦΞ it went down by 53%. It was also shown that, if one were to produce 60% polarised cascades and use the method of this thesis, it would require a sample of 1.1×1011 − 1.3×1011 Ξ− → Λπ− → pπ−π− and  ͞Ξ+ →͞Λπ+ → ͞pπ+π+ decays to reach the precision in the observables of the order given by the Standard Model. However, if one wished to match the uncertainty given by the most recent and best measurement of the observables, using 60% polarised cascades, one would only need a sample of 5.7×104 − 8.6×104 for each decay sequence.

Experimental tests on a transonic annular rig are time-consuming and expensive, so it is desirable to use experimental results to validate a computational model which can then be used to extract much more information. The purpose of this work is to create a numerical model that can be used to simulate many different scenarios and then to apply these results to experimental data.; In the modern world, gas turbines are widely used in aircraft propulsion and electricity generation. These applications represent a massive use of energy worldwide, so even a very small increase in efficiency would have a significant beneficial economic and environmental impact. There are many ways to optimize the operation of a gas turbine, but a fundamental approach is to increase the turbine inlet temperature to increase the basic thermodynamic efficiency of the turbine. However, these temperatures are already well above the melting temperature of the components. A primary cooling methodology, called film cooling, creates a blanket of cool air over the surface and is an effective way to help protect these components from the hot mainstream gasses. This paper focuses on the effect of the film holes upstream of the first row of blades in the turbine because this is the section that experiences the highest thermal stresses. Many factors can determine the effectiveness of the film cooling, so a complete understanding can lead to effective results with the minimum flow rate of coolant air. Many studies have been published on the subject of film cooling, but because of the difficulty and expense of simulating turbine realistic conditions, many authors introduce vast simplifications such as low speed conditions or linear cascades. These simplifications do not adequately represent the behavior of a turbine and therefore their results are of limited use. This study attempts to eliminate many of those simplifications. The test rig used in this research is based on the NASA-GE E³ design, which stands for Energy Efficient Engine. It was introduced into the public domain to provide an advanced platform from which open-literature research could be performed.

Complex filters are multi-input, multi-output networks designed to discriminate based upon the relative phase difference between input signals. Complex filters find application in modern wireless systems for single sideband transmission and image-reject reception. This thesis presents one active complex filter implementation using two operational amplifiers per stage, termed “type-II” topology. The “type-II” originates from the passive RC-CR polyphase topology presented by Gingell in his 1973 paper, “Single sideband modulation using sequence asymmetric polyphase networks.” This new topology gains several advantages over existing complex filter implementations, namely “cascadability” (multiple sections placed in series to create a higher-order response) without altering the characteristics of each individual stage. In addition to describing the derivation of the topology and its performance relative to existing topologies, this thesis investigates the passband characteristics of a general higher-order filter and provides a passband-centric design approach through derivations of closed form expressions for passband gain and bandwidth. The thesis includes a five-stage design example using this approach in addition to an implementation, its characterization, and its comparison to the derived expressions and simulations.

This thesis presents an active Complex Filter implementation that that creates a transfer function with with a single real pole and a complex zero. The two-input/two-output network developed in in this thesis responds differently based upon upon the relative phase difference of of the two inputs. If a negative ninety-degree phase difference occurs between the two inputs, the filter will exhibits a bandstop response. While a positive ninety-degree phase difference exhibits a bandpass response. This topology is relatesd to to Gingell’s RC-CR polyphase topology but because of of the use of of op-amps, can be cascadedd without without suffering loading effects. This thesis will focusfocuses primarily on on the bandstop response characteristics of of the filter. In a several stage cascade, each stage contributes a notch to broaden the attenuation bandWhen several sections are cascaded, multiple notches will be created from each stage that forms a broader attenuation band. Closed form design equations were were derived to to give expressions for for the “attenuation floor”. These equations can be used by a designer to predict the attenuation provided by by a cascaded system. The closed form expressions derived in in this thesis are used to implement an example five-stage topology that that operates from from 147 Hz to to 3.34 KHz. The thesis also investigates the robustness of of multi-stage cascades to to component variations. Monte Carlo analysis is used to determines the effects of of cascading the filter in in different orders, component tolerances, and a comparison to to an idealized polyphase RC-CR topology.

Humans have caused grave ecological and economic damage worldwide through the introduction of invasive species. Understanding the factors that influence community susceptibility to invasion are important for controlling further spread of invasive species. Predators have been found to provide biotic resistance to invasion in both terrestrial and marine systems. However, predators can also have the opposite effect, and facilitate invasion. Therefore, recovery or expansion of native predators could facilitate the spread of invasive species. Needles et al. (2015) demonstrated that the threatened southern sea otter (Enhydra lutris nereis) facilitated the invasion of an exotic bryozoan, Watersipora subatra. However, the underlying mechanism was not fully understood. We tested the hypothesis that sea otter predation on Romaleon antennarium crabs indirectly facilitated the abundance of W. subatra. To do this, we collected weekly data on sea otter foraging and quantified the abundance of crabs in the sea otter diet. We also conducted a caging experiment, where we experimentally manipulated crab densities and limited otter access using exclusion cages on pier pilings in Morro Bay, CA. We used photoQuad image processing software to calculate the abundance of W. subatra on PVC panels within each treatment group. We found that crabs were the second most abundant prey item in Morro Bay, comprising 25.1% of the otter diet. Through the caging experiment, we found that W. subatra abundance significantly increased as crab densities decreased. Our results indicated that sea otters indirectly facilitated the invasion of W. subatra by reducing R. antennarium crab densities and sizes. Removal of crabs may release W. subatra from the disturbance caused by crab foraging behavior. Understanding the impacts of top predators in invaded ecosystems has important management implications, as recovery of predator populations could unintentionally benefit some non-native species. Therefore, management should focus first on prevention and second on early detection and eradication of invasive species likely to benefit from predator recovery.

A parametric study was performed to observe and quantify the effect of varying turbulence intensities on separation and performance in a compressor cascade at low Reynolds numbers. Tests were performed at 25° and 37.5° stagger angle, negative and positive angles of incidence up until the point of full stall, Reynolds numbers from 6 x 104 to 12.5 x 104, and turbulence intensities from approximately 0.7% – 8%. Additionally, oil flow techniques were combined with static tap data to visualize the boundary layer characteristics at various test conditions. The overall performance of the cascade was presented and evaluated through mass-averaged total pressure loss coefficients. The results of the study showed that the best efficiency (lowest pressure loss coefficient) was determined by separation characteristics for any angle of attack. While adding turbulence generally delayed separation, in some cases, adding turbulence to a separated airfoil resulted in decreased performance. Very similar separation characteristics were observed for the full range of Reynolds numbers and stagger, with the higher stagger setting giving slightly better performance. It was shown that a large percentage of total pressure losses can be recovered by applying the appropriate turbulence intensity at any angle of attack, which is relevant to possibilities for active control of such flows. / Master of Science

An investigation of ion flow control was performed to determine the effect of a positive, DC corona discharge on the boundary layer profile along a flat plate and to examine its ability to prevent separated flow in a low-speed compressor cascade. Flat plate tests were performed for two electrode configurations at free-stream velocity magnitudes of 2.5, 5, 7.5, and 10 m/s. Boundary layer velocity profile data was taken to measure the performance of the electrode pairs. Ion flow control was also tested in the compressor cascade for a stagger angle of 25° at angles of attack equal to 6° and 12°. The cascade tests were performed at free-stream velocities of 5 and 10 m/s. Static tap data was used to characterize separated flow behavior and the effect of ion flow control on flow reattachment. A computational model was developed using the commercial CFD software Fluent. This model simulates ion flow control as a body force applied to the flow through user-defined functions. The study showed that the corona discharge has the ability to increase near-wall velocities and reduce the thickness of the boundary layer for flow over a flat plate. Ion flow control successfully prevented trailing edge separation in a compressor cascade for angles of attack of 6° and 12°; however, the flow control scheme was not able to prevent leading edge separation for angle of attack equal to 12°. The ion flow control CFD model accurately predicted flow behavior for both the flat plate and cascade experiments. The numerical model was able to simulate the boundary layer velocity profiles for flat plate tests with good accuracy, and was also able to predict the flow behavior over a compressor blade. The model was able to show the trends of separated and reattached flow over the blade surface. / Master of Science

Background: Every country has seen an increase in motorcycle accidents over the years due to social and economic differences as well as regional variations in transportation circumstances. One common mode of transportation for those in the middle class is a motorbike.  Every motorbike rider is legally required to wear a helmet when driving a bike. However, some people on bikes used to ignore their safety, which resulted in them violating traffic rules by driving the bike without a helmet. The policeman tried to address this issue manually, but it was ineffective and proved to be quite challenging in practical circumstances. Therefore, automating this procedure is essential if we are to effectively enforce road safety. As a result, an automated system was created employing a variety of techniques, including Convolutional Neural Networks (CNN), the Haar Cascade Classifier, the You Only Look Once (YOLO), the Single Shot multi-box Detector (SSD), etc. In this study, YOLOv3 and Haar Cascade Classifier are used to compare motorcycle helmet and license plate detection.  Objectives: This thesis aims to compare the machine learning algorithms that detect motorcycles’ license plates and helmets. Here, the Haar Cascade Classifier and YOLO algorithms are used on the US License Plates and Helmet Detection datasets to train the models. The accuracy is obtained in detecting the helmets and license plates of the motorcycles and analyzed.  Methods: The experiment method is chosen to answer the research question. An experiment is performed to find the accuracy of the models in detecting the helmets and license plates of motorcycles. The datasets utilized for this are from Kaggle, which included 764 pictures of two distinct classes, i.e., with and without a helmet, along with 447 unique license plate images. Before training the model, preprocessing techniques are performed on US License Plates and Helmet Detection datasets. Now the datasets are divided into test and train datasets where the test data set size is considered to be 20% and the train data set size is 80%. The models are trained using 80% pre-processed training datasets and using the Haar Cascade Classifier and YOLOv3 algorithms. An observation is made by giving the 20% test data to the trained models. Finally, the prediction results of these two models are recorded and the accuracy is measured by generating a confusion matrix.   Results: The efficient and best algorithm for detecting the helmets and license plates of motorcycles is identified from the experiment method. The YOLOv3 algorithm is considered more accurate in detecting motorcycles' helmets and license plates based on the results.  Conclusions: Models are trained using Haar Cascade and YOLOv3 algorithms on US License Plates and Helmet Detection training datasets. The accuracy of the models in detecting the helmets and license plates of motorcycles is checked by using the testing datasets. The model trained using the YOLOv3 algorithm has high accuracy; hence, the Neural network-based YOLOv3 technique is thought to be the best and most efficient.

Modern societies are fully dependent on critical infrastructures networks to support the economy, security, and prosperity. Energy infrastructure network is of paramount importance to our societies. As a pillar of the economy, it is necessary that energy infrastructure networks continue to operate safely and be resilient to provide reliable power to other critical infrastructure networks. Nonetheless, frequent large-scale blackouts in recent years have highlighted the vulnerability in the power grids, where disruptions can trigger cascading failures causing a catastrophic regional-level blackout. Such catastrophic blackouts call for a systemic risk assessment approach whereby the entire network/system is assessed against such failures considering the dynamic power flow within. However, the lack of detailed data combining both topological and functional information, and the computational resources typically required for large-scale modelling, considering also operational corrective actions, have impeded large-scale resilience studies. In this respect, the research in the present dissertation focuses on investigating, analyzing, and evaluating the vulnerability of power grid infrastructure networks in an effort to enhance their resilience. Through a Complex Network Theory (CNT) lens, the power grid robustness has been evaluated against random and targeted attacks through evaluating a family of centrality measures. The results shows that CNT models provide a quick and potential indication to identify key network components, which support regulators and operators in making informed decisions to maintain and upgrade the network, constrained by the tolerable risk and allocated financial resources. Furthermore, a dynamic Cascade Failure Model (CFM) has been employed to develop a Physical Flow-Based Model (PFBM). The CFM considers the operational corrective actions in case of failure to rebalance the supply and demand (i.e., dispatch and load shedding). The CFM was subsequently utilized to construct a grid vulnerability map function of the Link Vulnerability Index (LVI), which can be used to rank the line maintenance priority. In addition, a Node Importance Index (NII) has been developed for power substations ranking according to the resulting cascade failure size. The results from CNT and CFM approaches were compared to address the impact of considering the physical behavior of the power grid. The comparison results indicate that relying solely on CNT topology-based model could result in erroneous conclusions pertaining to the grid behavior. Moving forward, a systemic risk mitigation strategy based on the Intentional Controlled Islanding (ICI) approach has been introduced to suppress the failure propagation. The proposed mitigation strategy integrated the operation- with structure-guided strategies has shown excellent capabilities in terms of enhancing the network robustness and minimizing the possibility of catastrophic large-scale blackouts. This research demonstrates the model application on a real large-scale network with data ranging from low to high voltage. In the future, the CFM model can be integrated with other critical infrastructure network systems to establish a network-of-networks interaction model for assessing the systemic risk throughout and between multiple network layers. Understanding the interdependence between different networks will provide stakeholders with insight on enhancing resilience and support policymakers in making informed decisions pertaining to the tolerable systemic risk level to take reliable actions under abnormal conditions. / Thesis / Doctor of Philosophy (PhD)