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Although the Maxwell equations govern the propagation of EM waves at all frequencies, the methods required to generate, direct, analyse and detect radiation differ from band to band. This thesis is concerned with the development and demonstration of 'Quasi-optical' techniques for millimetre wavelengths, which involve the propagation of Gaussian profiled beams a few wavelengths across, and the realization of a general circuit approach to mm-wave measurement. Gaussian beam-mode analysis, which is used in later chapters to understand propagation of quasi-optical beams, is reviewed in chapter 1. Chapter 2 outlines the design, manufacture and testing of corrugated feed horns which generate fundamental Gaussian beam-modes. The design and manufacture of lenses which control the spreading of the beams and directional couplers which provide desirable signal processing functions in quasi-optical circuits is discussed in chapter 3. Chapter 4 traces the development of a Faraday isolator which operates in free-space and can suppress unwanted reflections in quasi-optical circuits. Chapter 5 discusses a reusable circuit board upon which systems can be easily and quickly constructed. A null reflectometer built using quasi-optical components is outlined in chapter 6 and reflection measurements from lenses and horns presented. Chapter 7 describes a corrugated feed horn/lens antenna used in a balloon-borne nw-wave cosmic background experiment. Finally, Chapter 8 demonstrates the use of quasi-optical components in a 115 GHz receiver circuit.

In this thesis, we proposed general forms of eigen-mode analysis for multilayer optical waveguides. This study discussed the periodic structure in transverse direction and used the slowly varying envelope approximation to approximate the wave function. Firstly, we presented a general method for analyzing the multilayer nonlinear optical waveguide structure by using modal theory. The nonlinear optical waveguide is a medium whose refractive index changes with the electric field intensity. The general method can also be degenerated into some other special cases for analyzing multilayer nonlinear optical waveguide. Secondly, a general method for analyzing the multilayer optical waveguides with photonic metamaterials characterized by simultaneously negative dielectric permittivity and magnetic permeability was studied. The research pointed out explicitly that the three-layer planar waveguide with photonic metamaterials could support forbidden regions. The complete set of modes of all possible solutions for the TE wave in photonic metamaterials optical waveguide was found. The transverse electric field distributions and dispersion relations in multilayer optical waveguides can be obtained by using these general forms. Finally, we used the general forms to design an all-optical mode converter which composed of a pair of multibranch optical waveguides. The analytical and numerical results show excellent agreement.

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Made available in DSpace on 2014-10-09T12:49:40Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:01:21Z (GMT). No. of bitstreams: 1 10192.pdf: 6833898 bytes, checksum: 366c211ea17c52eecbc22d5392203f97 (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP

Electric power systems are undergoing significant changes with the deployment of large-scale wind and solar plants connected to the transmission system and small-scale Distributed Energy Resources (DERs) and microgrids connected to the distribution system, making the latter an active system. A microgrid is a small-scale power system that interconnects renewable and non-renewable generating units such as solar photo-voltaic panels and micro-turbines, storage devices such as batteries and fly wheels, and loads. Typically, it is connected to the distribution feeders via power electronic converters with fast control responses within the micro-seconds. These new developments have prompted growing research activities in stability analysis and control of the transmission and the distribution systems. Unfortunately, these systems are treated as separated entities, limiting the scope of the applicability of the proposed methods to real systems. It is worth stressing that the transmission and distribution systems are interconnected via HV/MV transformers and therefore, are interacting dynamically in a complex way. In this research work, we overcome this problem by investigating the dynamics of the transmission and distribution systems with parallel microgrids as an integrated system . Specifically, we develop a generic model of a microgrid that consists of a DC voltage source connected to an inverter with real and reactive power control and voltage control. We analyze the small-signal stability of the two-area four-machine system with four parallel microgrids connected to the distribution feeders though different impedances. We show that the conventional PQ control of the inverters is insufficient to stabilize the voltage at the point-of-common coupling when the feeder impedances have highly unequal values. To ensure the existence of a stable equilibrium point associated with a sufficient stability margin of the system, we propose a new voltage control implemented as an additional feedback control loop of the conventional inner and outer current control schemes of the inverter. Furthermore, we carry out a modal analysis of the four-machine system with microgrids using Koopman mode analysis. We reveal the existence of local modes of oscillation of a microgrid against the rest of the system and between parallel microgrids at frequencies that range between 0.1 and 3 Hz. When the control of the microgrid becomes unstable, the frequencies of the oscillation are about 20 Hz. Recall that the Koopman mode analysis is a new technique developed in fluid dynamics and recently introduced in power systems by Suzuki and Mezic. It allows us to carry out small signal and transient stability analysis by processing only measurements, without resorting to any model and without assuming any linearization. / Ph. D. / Electric power systems are undergoing significant changes with the deployment of large-scale wind and solar plants connected to the transmission system and small-scale Distributed Energy Resources (DERs) and microgrids connected to the distribution system, making the latter an active system. A microgrid is a small-scale power system that interconnects renewable and non-renewable generating units such as solar photo-voltaic panels and micro-turbines, storage devices such as batteries and fly wheels, and loads. Typically, it is connected to the distribution feeders via power electronic converters with fast control responses within the micro-seconds. These new developments have prompted growing research activities in stability analysis and control of the transmission and the distribution systems. Unfortunately, these systems are treated as separated entities, limiting the scope of the applicability of the proposed methods to real systems. It is worth stressing that the transmission and distribution systems are interconnected via HV/MV transformers and therefore, are interacting dynamically in a complex way. In this research work, we overcome this problem by investigating the dynamics of the transmission and distribution systems with parallel microgrids as an integrated system . Specifically, we develop a generic model of a microgrid that consists of a DC voltage source connected to an inverter with real and reactive power control and voltage control. We show that the conventional PQ control of the inverters is insufficient to stabilize the voltage at the point-of-common coupling when the feeder impedances have highly unequal values. Furthermore, we carry out a modal analysis of the four-machine system with microgrids using Koopman mode analysis. Koopman mode analysis is a new technique developed in fluid dynamics and recently introduced in power systems by Suzuki and Mezic. It allows us to carry out small signal and transient stability analysis by processing only measurements, without resorting to any model and without assuming any linearization.

A caracterização das flutuações dos resíduos da proteína em torno do seu estado nativo é essencial para estudar mudanças conformacionais, interação proteína-proteína e interação proteína-ligante. Tal caracterização pode ser capturada pelo modelo de rede gaussiana (GNM). Este modelo tem sido modificado e novas propostas têm surgido nos últimos anos. Nesta Tese, apresentamos um estudo sobre como melhorar o GNM e exploramos o seu desempenho em predizer os fatores-B experimentais. Modelos de redes elásticas são construídos a partir das coordenadas experimentais dos levando em consideração pares de átomos de C? distantes entre si até um dado raio de corte Rc . Estes modelos descrevem as interações entre os atómos por molas com a mesma constante de força. Desenvolvemos um método baseado em simulações numéricas com um campo de forças simplificado para atribuir pesos a estas constantes de mola. Este método considera o tempo em que dois átomos de C? permanecem conectados na rede durante o desenovelamento parcial, estabelecendo assim uma forma de medir a intensidade de cada ligação. Examinamos dois diferentes campos de forças simplificados e exploramos o cálculo desses pesos a partir do desenovelamento das estruturas nativas. Nós comparamos o seu desempenho na predição dos fatores-B com outros modelos de rede elástica. Avaliamos tal desempenho utilizando o coeficiente de correlação entre os fatores-B preditos e experimentais. Mostramos como o nosso modelo pode descrever melhor os fatores-B / The characterization of the fluctuations in protein residues around its native state is essential to study conformational changes, protein binding interaction and protein-protein interaction. Such characterization can be captured by simple elastic network models as the Gaussian Network Model (GNM). This model has been modified and new proposals have emerged in recent years. In this Thesis we propose an extended version of GNM, namely wGNM. Elastic network models are built on the experimental C? coordinates,and they only take the pairs of C? atoms within a given cutoff distance Rc into account. These models describe the interactions by elastic springs with the same force constant to predicted the experimental B-factors, providing insights into the structure-function properties of proteins. We have developed a method based on numerical simulations with a simple coarse-grained force field, to attribute weights to these spring constants. This method considers the time that two C? atoms remain connected in the network during partial unfolding, establishing a means of measuring the strength of each link. We examined two different coarse-grained force fields and explored the computation of these weights by unfolding native structures. We compare the B-factors predicted by different elastic network models with the experimental ones employing the correlation coefficient between these two quantities. We show that wGNM performs better and consequently provides better evaluation of the B-factors

Conformational selection is the idea that proteins traverse positions on the conformational space represented by their potential energy landscape, and in particular positions considered as local energy minima. Conformational selection a useful concept in ligand binding studies and in exploring the behavior of protein structures within that energy landscape. Often, research that explores protein function requires the generation of conformational ensembles, or collections of protein conformations from a single structure. We describe a method of conformational ensemble generation that uses joint-constrained rigid-body dynamics (an approach that allows for explicit consideration of rigidity) and the elastic network model (providing structurally derived directional guides for the rigid-body model). We test our model on a selection of unbound proteins and examine the structural validity of the resulting ensembles, as well as the ability of such an approach to generate conformations with structural overlaps close to the ligand-bound versions of the proteins.

The scope of this work focuses on computationally modeling compounds with protein structures. While the impetus of drug discovery is the innovation of new therapeutic molecules, it also involves distinguishing molecules that would not be an effective drug. This can be achieved by inventing new tools or by refining old tools. Virtual screening (VS, also called docking), the computational modeling of a molecule in a receptor structure, is a staple in predicting a molecule's affinity for an intended target. In our Virtual Target Screening system (also called inverse-docking), VS is used to find high-affinity targets, which can potentially explain absorption, distribution, metabolism, and excretion (ADME) of a molecule of interest in the human body. The next project, low-mode docking (LD), attempts to improve VS by incorporating protein flexibility into traditional docking where a static receptor structure has potential to produce poor results due to incorrectly predicted ligand poses. Finally, VS, performed mostly on small molecules, is scaled up to cyclic peptides by employing Monte Carlo simulations and molecular dynamics to mimic the steps of small molecule VS. The first project discussed is Virtual Target Screening (also called inverse-docking) where a small molecule is virtually screened against a library of protein structures. Predicting receptors to which a synthesized compound may bind would give insights to drug repurposing, metabolism, toxicity, and lead optimization. Our protocol calibrates each protein entry with a diverse set of small molecule structures, the NCI Diversity Set I. Our test set, 20 kinase inhibitors, was predicted to have a high percentage of kinase "hits" among approximately 1500 protein structures. Further, approved drugs within the test set generally had better rates of kinase hits. Next, normal mode analysis (NMA), which can computationally describe the fundamental motions of a receptor structure, is utilized to approach the rigid body bias problem in traditional docking techniques. Traditional docking involves the selection of a static receptor structure for VS; however, protein structures are dynamic. Simulation of the induced fit effect in protein-ligand binding events is modeled by full articulation of the approximated large-scale low-frequency normal modes of vibration, or "low-modes," coupled with the docking of a ligand structure. Low-mode dockings of 40 cyclin dependent 2 (CDK2) inhibitors into 54 low-modes of CDK2 yielded minimum root-mean-square deviation (RMSD) values of 1.82 – 1.20 Å when compared to known coordinate data. The choice of pose is currently limited to docking score, however, with ligand pose RMSD values of 3.87 – 2.07 Å. When compared to corresponding traditional dockings with RMSD values of 5.89 – 2.33 Å, low-mode docking was more accurate. The last discussion involves the rational docking of a cyclic peptide to the murine double minute 2 (MDM2) oncoprotein. The affinity for a cyclic peptide (synthesized by Priyesh Jain, McLaughin Lab, University of South Florida), PJ-8-73, in MDM2 was found to be within an order of magnitude of a cyclic peptide from the Robinson Lab at the University of Zurich in Switzerland. Both are Β-hairpin cyclic peptides with IC50 values of 650 nm and 140 nm, respectively. Using the co-crystalized structure of the Robinson peptide (PDB 2AXI), we modeled the McLaughlin peptide based on an important interaction of the 6-chloro-tryptophan residue of the Robinson peptide occupying the same pocket in MDM2 as the tryptophan residue by the native p53 transactivation helical domain. By preserving this interaction in initial cyclic peptide poses, the resulting pose of PJ-8-73 structure in MDM2 possessed comparable active site residue contacts and surface area. These protocols will aid medical research by using computer technology to reduce cost and time. VTS utilizes a unique structural and statistical calibration to virtually assay thousands of protein structures to predict high affinity binding. Determining unintended protein targets aids in creating more effective drugs. In low-mode docking, the accuracy of virtual screening was increased by including the fundamental motions of proteins. This newfound accuracy can decrease false negative results common in virtual screening. Lastly, docking techniques, usually for small molecules, were applied to larger peptide molecules. These modifications allow for the prediction of peptide therapeutics in protein-protein interaction modulation, a growing interest in medicine. Impactful in their own ways, these procedures contribute to the discovery of drugs, whether they are small molecules or cyclic peptides.

Conformational selection is the idea that proteins traverse positions on the conformational space represented by their potential energy landscape, and in particular positions considered as local energy minima. Conformational selection a useful concept in ligand binding studies and in exploring the behavior of protein structures within that energy landscape. Often, research that explores protein function requires the generation of conformational ensembles, or collections of protein conformations from a single structure. We describe a method of conformational ensemble generation that uses joint-constrained rigid-body dynamics (an approach that allows for explicit consideration of rigidity) and the elastic network model (providing structurally derived directional guides for the rigid-body model). We test our model on a selection of unbound proteins and examine the structural validity of the resulting ensembles, as well as the ability of such an approach to generate conformations with structural overlaps close to the ligand-bound versions of the proteins.