Several catastrophic failures have occurred during the past two decades, both in engineered as well as non-engineered landfills. In addition, there are numerous instances of significant deformations, although not failure in the sense of significant and rapid downslope mass movement, which may cause sufficient damage to buried gas and leachate collection infrastructure. One such instance was observed in 1999 near the toe of a 75 m high 4H:1V slope at the Brock West Landfill in Ontario, Canada. Significant distortion of gas collection laterals was observed at this site. The present research is an in-depth study intended to examine deformation in landfills based on a detailed study of the mechanical properties of municipal solid waste. Four research objectives were defined based on identified shortcomings and knowledge gaps in the existing literature pertaining to mechanical properties of MSW viz; (a) to develop a method for obtaining intact samples of MSW and to examine the significance of using intact and recompacted samples in characterizing the stress-deformation behaviour of MSW; (b) to characterize MSW shear strength and Youngs modulus of elasticity from interpretation of triaxial test results and to determine the parameters of a non-linear elastic constitutive model as applied to MSW; (c) to measure the evolution of compressibility behaviour of MSW with degradation and verify the mechanism of secondary compression in waste; (d) to develop a simple design chart for predicting lateral deformations in landfills. A comprehensive research program was carried out to address various research objectives - field monitoring of deformations at the Brock West site; triaxial compression tests on large intact and recompacted samples of waste; simulating waste degradation in a large laboratory compression cell; analyzing stress-strain data from various published studies and a numerical modelling study. Interpretation of the effective stress paths followed during shearing in triaxial compression tests suggested that while recompacted samples may be sufficient to characterize shear strength parameters for use in stability analysis of landfill slopes, there might be a benefit in obtaining intact samples to evaluate the deformation characteristics of MSW. A hyperbolic model is proposed to describe the stress-deformation response of waste. The required parameters for this model were determined from evaluation of the results of numerous triaxial tests, both from this study and from the published literature. Observations from the long-term degradation test suggested that degradation has a significant effect on the compressibility of waste and further verifies the mechanism of secondary compression in waste. The coefficient of at-rest lateral pressure was observed to maintain an essentially constant value during combined compression and degradation.<p>The results obtained from the experimental work were combined with the findings of a stochastic numerical modelling study and a statistical evaluation of published data and used to propose a simple design chart for estimating the maximum lateral displacement in a landfill slope. The design chart was developed using results of a finite element parametric study in which the behaviour of the municipal solid waste was modeled using a non-linear elastic hyperbolic model. The design chart incorporates nonlinear variation in unit weight as well as Youngs modulus with depth. The predictions from the design chart were compared with the results of field monitoring of lateral displacement in the instrumented slope at the Brock West landfill and were found to be in good agreement.

The HIV-1 transactivator of transcription (Tat) is a protein essential for both viral gene expression and virus replication. Tat is an RNA-binding protein that, in cooperation with host cell factors cyclin T1 and cyclin-dependent kinase 9, regulates transcription at the level of elongation. Tat also interacts with numerous other intracellular and extracellular proteins, and is implicated in a number of pathogenic processes. The Tat protein is encoded by two exons and is 101 residues in length. The first exon encodes a 72-residue molecule that activates transcription with the same proficiency as the full-length protein. The physico-chemical properties of Tat make it a particularly challenging target for structural studies: Tat contains seven cysteine residues, six of which are essential for transactivation, and is highly susceptible to oxidative cross-linking and aggregation. In addition, a basic segment (residues 48-57) gives the protein a high net positive charge of +12 at pH 7, endowing it with a high affinity for anionic polymers and surfaces. In order to study the structure of Tat, both alone and in complex with partner molecules, we have developed a system for the bacterial expression and purification of polyhistidine-tagged and isotopically enriched (in 15N and 15N /13C) recombinant HIV-1 Tat1-72 (BH10 isolate) that yields large amounts of protein. These preparations have facilitated the assignment of 95% of the non-proline backbone resonances using heteronuclear 3-dimensional nuclear magnetic resonance (NMR) spectroscopy. Analysis by mass spectrometry and NMR demonstrate that the cysteine-rich Tat protein is unambiguously reduced and monomeric in aqueous solution at pH 4. NMR chemical shifts and coupling constants suggest that it exists in a disordered conformation. Line broadening and multiple peaks in the cysteine-rich and core regions suggest that transient folding occurs in two of the five sequence domains. NMR relaxation parameters were measured and analysed by spectral density and model-free approaches both confirming the lack of structure throughout the length of the molecule. The absence of a fixed conformation and the observation of fast dynamics are consistent with the ability of the Tat protein to interact with a wide variety of proteins and nucleic acid lending further support to the concept that Tat exists as an intrinsically disordered protein. / October 2007

A concentric pneumatic nebulizer (CPN) and a custom designed flow focusing nebulizer (FFN) are characterized. As will be shown, the classical Nukiyama-Tanasawa and Rizk-Lefebvre models lead to erroneous size prediction for the concentric nebulizer under typical operating conditions due to its specific design, geometry, dimension and different flow regimes. The models are then modified to improve the agreement with the experimental results. The size prediction of the modified models together with the spray velocity characterization are used to determine the overall nebulizer efficiency and also employed as input to a new Maximum Entropy Principle (MEP) based model to predict joint size-velocity distribution analytically. The new MEP model is exploited to study the local variation of size-velocity distribution in contrast to the classical models where MEP is applied globally to the entire spray cross section. As will be demonstrated, the velocity distribution of the classical MEP models shows poor agreement with experiments for the cases under study. Modifications to the original MEP modeling are proposed to overcome this deficiency. In addition, the new joint size-velocity distribution agrees better with our general understanding of the drag law and yields realistic results. / PhD

Oil from flaxseed (Linum usitatisssimum L.) contains hydrophobic cyclic peptides or cyclolinopeptides (CLs) comprising eight or nine amino acids. These bioactive compounds have potential therapeutic applications and may be used as scaffolds for increased utility. Two steps were undertaken to increase the potential utility of these compounds. Initially multigram quantities of flax CLs were highly enriched from flax oil. Subsequently new synthetic procedures were developed for modification of the CLs through the methionine group (Met). Finally, the utility of the modified CLs was tested in a number of applications. CLs were recovered from a crude oil extract that contain five CLs (CLA, CLC, CLE, CLJ and CLK). Oxidation of this mixture reduced the complexity of the mix to just three CLA, CLJ and CLK. CLJ and CLK were enriched then characterized by NMR and MS-MS methods. CLs containing methionine sulfoxide groups (Mso), CLC and CLE were isolated from crude mixture then selectively reduced to afford Met containing analogs: CLB and CLE'. The Met of modified CLs was used as a point for attachment of tags and couplers for various applications. Cyclic peptide modification through Met groups has not been reported previously. Synthetic methods were devised to introduce activating functional groups such as -CN, -COOH, -OH and -NH2 to the sulfur atom of Met. The modified CL conjugates were characterized using spectrometric techniques including 1D and 2D NMR spectrometry, as well as mass spectrometry. After activation the CLs were covalently linked to molecules or materials of interest including fluorescence tags (coumarin), affinity chromatography media and bovine serum albumin (BSA) for production of polyclonal antibodies. Fluorescence studies were performed in methanol, ethanol, dimethylformamide and acetonitrile to study the solvent effect. CLs attached to solid affinity matrix showed specific binding to apolipoprotein A1 after incubation with chicken serum. These CLs also act as hapten and have been used to couple BSA to produce polyclonal antibodies. Met modification was a satisfactory approach to produce a range of useful peptide products where more conventional methods of molecule attachment are not available.

Recent developments in material joining, specifically arc-welding, have increased in scope and extended into the aerospace, nuclear, and underwater industries where complex geometry and hazardous environments necessitate fully automated systems. Even traditional applications of arc welding such as off-highway and automotive manufacturing have increased their demand in quality, accuracy, and volume to stay competitive. These requirements often exceed both skill and endurance capacities of human welders. As a result, improvements in process parameter feedback and sensing are necessary to successfully achieve a closed-loop control of such processes. <br ><br /> One such feedback parameter in gas-metal arc welding (GMAW) is acoustic emissions. Although there have been relatively few studies performed in this area, it is agreed amongst professional welders that the sound from an arc is critical to their ability to control the process. Investigations that have been performed however, have been met with mixed success due to extraneous background noises or inadequate evaluation of the signal spectral content. However, if it were possible to identify the salient or characterizing aspects of the signal, these drawbacks may be overcome. <br ><br /> The goal of this thesis is to develop methods which characterize the arc-acoustic signal such that a relationship can be drawn between welding parameters and acoustic spectral characteristics. Three methods were attempted including: Taguchi experiments to reveal trends between weld process parameters and the acoustic signal; psycho-acoustic experiments that investigate expert welder reliance on arc-sounds, and implementation of an artificial neural network (ANN) for mapping arc-acoustic spectral characteristics to process parameters. <br ><br /> Together, these investigations revealed strong correlation between welding voltage and arc-acoustics. The psycho-acoustic experiments confirm the suspicion of welder reliance on arc-acoustics as well as potential spectral candidates necessary to spray-transfer control during GMA welding. ANN performance shows promise in the approach and confirmation of the ANN?s ability to learn. Further experimentation and data gathering to enrich the learning data-base will be necessary to apply artificial intelligence such as artificial neural networks to such a stochastic and non-linear relationship between arc-sound and GMA parameters.

This dissertation addresses the issue of noise in quantum information processing devices. It is common knowledge that quantum states are particularly fragile to the effects of noise. In order to perform scalable quantum computation, it is necessary to suppress effective noise to levels which depend on the size of the computation. Various theoretical proposals have discussed how this can be achieved, under various assumptions about properties of the noise and the availability of qubits. We discuss new approaches to the suppression of noise, and propose experimental protocols characterizing the noise. In the first part of the dissertation, we discuss a number of applications of teleportation to fault-tolerant quantum computation. We demonstrate how measurement-based quantum computation can be made inherently fault-tolerant by exploiting its relationship to teleportation. We also demonstrate how continuous variable quantum systems can be used as ancillas for computation with qubits, and how information can be reliably teleported between these different systems. Building on these ideas, we discuss how the necessary resource states for teleportation can be prepared by allowing quantum particles to be scattered by qubits, and investigate the feasibility of an implementation using superconducting circuits. In the second part of the dissertation, we propose scalable experimental protocols for extracting information about the noise. We concentrate on information which has direct practical relevance to methods of noise suppression. In particular, we demonstrate how standard assumptions about properties of the noise can be tested in a scalable manner. The experimental protocols we propose rely on symmetrizing the noise by random application of unitary operations. Depending on the symmetry group use, different information about the noise can be extracted. We demonstrate, in particular, how to estimate the probability of a small number of qubits being corrupted, as well as how to test for a necessary condition for noise correlations. We conclude by demonstrating how, without relying on assumptions about the noise, the information obtained by symmetrization can also be used to construct protective encodings for quantum states.

No description available.

Recent developments in material joining, specifically arc-welding, have increased in scope and extended into the aerospace, nuclear, and underwater industries where complex geometry and hazardous environments necessitate fully automated systems. Even traditional applications of arc welding such as off-highway and automotive manufacturing have increased their demand in quality, accuracy, and volume to stay competitive. These requirements often exceed both skill and endurance capacities of human welders. As a result, improvements in process parameter feedback and sensing are necessary to successfully achieve a closed-loop control of such processes. <br ><br /> One such feedback parameter in gas-metal arc welding (GMAW) is acoustic emissions. Although there have been relatively few studies performed in this area, it is agreed amongst professional welders that the sound from an arc is critical to their ability to control the process. Investigations that have been performed however, have been met with mixed success due to extraneous background noises or inadequate evaluation of the signal spectral content. However, if it were possible to identify the salient or characterizing aspects of the signal, these drawbacks may be overcome. <br ><br /> The goal of this thesis is to develop methods which characterize the arc-acoustic signal such that a relationship can be drawn between welding parameters and acoustic spectral characteristics. Three methods were attempted including: Taguchi experiments to reveal trends between weld process parameters and the acoustic signal; psycho-acoustic experiments that investigate expert welder reliance on arc-sounds, and implementation of an artificial neural network (ANN) for mapping arc-acoustic spectral characteristics to process parameters. <br ><br /> Together, these investigations revealed strong correlation between welding voltage and arc-acoustics. The psycho-acoustic experiments confirm the suspicion of welder reliance on arc-acoustics as well as potential spectral candidates necessary to spray-transfer control during GMA welding. ANN performance shows promise in the approach and confirmation of the ANN?s ability to learn. Further experimentation and data gathering to enrich the learning data-base will be necessary to apply artificial intelligence such as artificial neural networks to such a stochastic and non-linear relationship between arc-sound and GMA parameters.

This dissertation addresses the issue of noise in quantum information processing devices. It is common knowledge that quantum states are particularly fragile to the effects of noise. In order to perform scalable quantum computation, it is necessary to suppress effective noise to levels which depend on the size of the computation. Various theoretical proposals have discussed how this can be achieved, under various assumptions about properties of the noise and the availability of qubits. We discuss new approaches to the suppression of noise, and propose experimental protocols characterizing the noise. In the first part of the dissertation, we discuss a number of applications of teleportation to fault-tolerant quantum computation. We demonstrate how measurement-based quantum computation can be made inherently fault-tolerant by exploiting its relationship to teleportation. We also demonstrate how continuous variable quantum systems can be used as ancillas for computation with qubits, and how information can be reliably teleported between these different systems. Building on these ideas, we discuss how the necessary resource states for teleportation can be prepared by allowing quantum particles to be scattered by qubits, and investigate the feasibility of an implementation using superconducting circuits. In the second part of the dissertation, we propose scalable experimental protocols for extracting information about the noise. We concentrate on information which has direct practical relevance to methods of noise suppression. In particular, we demonstrate how standard assumptions about properties of the noise can be tested in a scalable manner. The experimental protocols we propose rely on symmetrizing the noise by random application of unitary operations. Depending on the symmetry group use, different information about the noise can be extracted. We demonstrate, in particular, how to estimate the probability of a small number of qubits being corrupted, as well as how to test for a necessary condition for noise correlations. We conclude by demonstrating how, without relying on assumptions about the noise, the information obtained by symmetrization can also be used to construct protective encodings for quantum states.

Modern storage systems are complex. Simple direct-attached storage devices are giving way to storage systems that are flexible, network-attached, consolidated and virtualized. Today, storage systems have their own administrators, who use specialized tools and expertise to configure and manage storage resources. As a result, database administrators are no longer in direct control of the design and configuration of their database systems' underlying storage resources. This introduces problems because database physical design and storage configuration are closely related tasks, and the separation makes it more difficult to achieve a good end-to-end design. For instance, the performance of a database system depends strongly on the storage layout of database objects, such as tables and indexes, and the separation makes it hard to design a storage layout that is tuned to the I/O workload generated by the database system. In this thesis we address this problem and attempt to close the information gap between database and storage tiers by addressing the problem of predicting the storage (I/O) workload that will be generated by a database management system. Specifically, we show how to translate a database workload description, together with a database physical design, into a characterization of the I/O workload that will result. Such a characterization can directly be used by a storage configuration tool and thus enables effective end-to-end design and configuration spanning both the database and storage tiers. We then introduce our storage layout optimization tool, which leverages such workload characterizations to generate an optimized layout for a given set of database objects. We formulate the layout problem as a non-linear programming (NLP) problem and use the I/O characterization as input to an NLP solver. We have incorporated our I/O estimation technique into the PostgreSQL database management system and our layout optimization technique into a database layout advisor. We present an empirical assessment of the cost of both tools as well as the efficacy and accuracy of their results.