The hepatitis delta virus (HDV), composed of ~1,700nt, is the smallest circular RNA pathogen known to infect humans. Understanding the mode of replication of HDV implies on investigating the host proteins that bind to its genome. The polypyrimidine tract-binding protein-associated splicing factor (PSF), an HDV interacting protein, was found to interact with the carboxy terminal domain (CTD) of RNA polymerase II (RNAPII), and to facilitate the interaction of RNA transcripts with the CTD of RNAPII. Both PSF and RNAPII were found to interact with both polarities of the terminal stem loop domains of HDV RNA, which possess RNA promoter activity in vitro. Furthermore, PSF and RNAPII were found to simultaneously interact with HDV RNA in vitro. Together, the above experiments suggest that PSF acts as a transcription factor during HDV RNA replication by interacting with both the CTD of RNAPII and HDV RNA simultaneously. PSF knockdown experiments were performed to indicate that PSF is required for HDV RNA accumulation. Mutagenesis experiments of PSF revealed that HDV RNA accumulation might require the N terminal domain, and the RNA recognition motifs RRM1 and RRM2. I propose that the RRM1 and RRM2 domains might interact with HDV RNA, while the N-terminal domain might interact with the CTD of RNAPII for HDV RNA accumulation. Together, the above experiments provide a better understanding of how an RNA promoter might be recognized by RNAPII.

This dissertation explores methods of reducing the oversampling ratio (OSR) of both delta-sigma modulators and incremental data converters. The first reduced-OSR architecture is the high-order cascaded delta-sigma modulator. These delta-sigma modulators are shown to reduce the in-band noise sufficiently at OSRs as low as 3 while providing power savings. The second low OSR architecture is the high-order cascaded incremental data converter which possesses signal-to-quantization noise ratio (SQNR) advantages over equivalent delta-sigma modulators at low OSRs. The final architecture is the time-interleaved incremental data converter where two designs are identified as potential methods of increasing the throughput of low OSR incremental data converters. A prototype chip is designed in 0.18um CMOS technology which can operate in three modes by simply changing the resetting clock phases. It can operate as an 8-stage pipeline analog-to-digital (A/D) converter, an 8th-order cascaded delta-sigma modulator, and an 8th-order cascaded incremental data converter with an OSR of 3.

The main objective of this study was to describe the overflow of freshwater onto the sea ice surface in the Mackenzie Delta and to investigate the hydraulic behaviour of the upwelling and strudel events. This study was performed from the analysis of data collected during field investigations, from satellite images and from experimental laboratory studies. A forecasting method using the water level in the Mackenzie River was formulated to predict the overflow initiation about five days before its occurrence. The physical modelling of a strudel flow through a circular hole established a relation between the overflow depth and the discharge coefficient. Velocity measurements of the free-surface vortex using an Acoustic Doppler Velocimeter found that velocities at the vortexs core were influenced by its vorticity. Finally, predictions of maximum strudel scour, which are of great importance for the determination of burial depth of pipelines, were predicted from published impinging jet experiments. / Water Resources Engineering

Despite being one of the largest aquifers of its type in Australia, the Burdekin River Delta (BRD) is an area that has received comparatively little research on its groundwater resources. This study conceptualises the hydrogeology of the BRD and characterises the relationships between the stratigraphic elements and the physical and chemical components of the groundwater system that influence the major governing processes. Importantly, a large amount of spatial and temporal groundwater information exists in database form, which enables an integrated conceptual model of the BRD aquifer to be developed from the key hydrogeological and hydrogeochemical relationships. Conceptualisation of the BRD aquifer is achieved by categorising four main aspects of the groundwater resource: 1. Surface characterisation; 2. Geologic characterisation; 3. Hydrogeologic characterisation; and 4. Groundwater System characterisation. The BRD is a large cuspate delta comprising a complex stratigraphy of Pleistocene to Holocene sediments of fluvial, deltaic and marine origin to a maximum depth of about 150 metres. The lower Pleistocene sediments lie predominantly below sea level and are typified by laterally discontinuous sands, silts and clays that have formed in response to fluctuating sea levels. The upper Pleistocene boundary is differentiated from the overlying Holocene sediments by a formerly exposed surface of semiconsolidated oxidised sandy clays and gravel. By contrast, the Holocene sediments comprise loose, uncompacted sequences of fluvial channel sands, interdistributary floodplain silts and marine incursions of estuarine clays and mangrove muds. The anastomosing array of fluvial sand bodies of former Burdekin River channels and levees is the setting for the main shallow aquifer units. Aquifer units of the lower Pleistocene sediments are in hydraulic connection with the Holocene units, effectively categorising the whole BRD as a single unconfined aquifer. Hydraulic gradients from both sides of the river divide the BRD into two broad flow regimes. Interpreted flow zones based on hydrograph patterns further subdivide the flow system based on seasonal recharge response to elevated river heights and flooding, and response to long-term rainfall patterns associated with La Niña episodes of the Southern Oscillation. Stable isotope data (2H and 18O) indicate that the dominant isotopic signature of groundwater throughout the BRD corresponds with intense rainfall activity, however high deuterium-excess values indicate that significant evaporation occurs prior to recharge. This infers dominant recharge by the Burdekin River that drains a massive catchment extending hundreds of kilometres inland. Direct recharge via rainfall infiltration is largely dependant on soil texture. More conductive soils are associated with the major levee systems that comprise the main shallow aquifers. Two evolutionary hydrogeochemical paths exist for the north and south sides of the river, and are constrained by the interpreted flow zones. In the south side, groundwater enters the main aquifer from river recharge and leakage out of weathered granite outcrops (exposed bedrock). Mineral hydrolysis and evaporative concentration of salts initially evolve groundwater in the weathered granite to a combination of Na-Cl and Na-HCO3 type. Leakage through clay-rich hillwash and marginal sediments causes reverse cation-exchange reactions where excess Na replaces Ca and Mg on ion-exchange surfaces. This leads to the formation of Mg,Ca-Cl type groundwaters into the southern parts of the main aquifer (supersaturated with respect to calcite and dolomite). Discharge towards the coast is characterised by seawater mixing where salinity increases with corresponding evolution to Na-Cl type waters. Recharge waters from the Burdekin River are fresh (<250mS/cm) Ca-HCO3 type, undersaturated with respect to calcite, and are easily distinguishable from the ion-exchange groundwater. In the north, only one smaller outcrop of bedrock exists, which hosts similar mineral hydrolysis reactions and base-exchange reactions. An absence of associated Na-Cl type waters means that reverse-cation exchange reactions are negligible, and so water types are predominantly Na-HCO3 type. Aquifer sands in the north are more widespread than in the south, so the fresh Ca-HCO3 recharge waters tend to dominate the overall groundwater composition, with Na-HCO3 types limited to the exposed bedrock areas. Towards the coastline, groundwater mixes with seawater towards Na-Cl type waters, similar to that observed in the south. The mangrove mud sequences that flank the coastline of the BRD are associated with high-Fe and low-pH groundwater formed by the oxidation of Fe-sulphides such as pyrite). SO4 is a product of this reaction, but does not achieve abnormally high concentrations, possibly due to the presence of sulphate-reducing bacteria. Carbonate dissolution is a possible side effect of acid sulphate generation, with possible gypsum dissolution as a secondary source of SO4. This study tested an alternative method to characterising groundwater to determine if the spatial extent of hydrogeochemical processes could be defined and comparable results achieved. This method involved discriminating discrete statistical groups of ionic ratios based on their cumulative frequency distribution. The statistical groups are bounded by critical values that distinguish different chemical processes, referred to as hydrogeochemical indicators. Various tested ionic ratios produced analogous indicators, proving their reliability as a valid method for the characterisation of groundwater chemistry. The significance of this research underlies the importance of groundwater use in the BRD as a primary source of irrigation supplies. Land use expansion and unregulated pumping pose a risk to future groundwater quality and sustainable volumes. The understanding of the relationship between the main geologic elements and the subsequent hydrogeochemical processes provides a scientific basis for conceptualising the groundwater resource. This establishes a framework for initiating future groundwater management options.

Identity verification or biometric recognition systems play an important role in our daily lives. Applications include Automatic Teller Machines (ATM), banking and share information retrieval, and personal verification for credit cards. Among the biometric techniques, authentication of speakers by his/her voice is of great importance, since it employs a non-invasive approach and is the only available modality in many applications. However,the performance of Automatic Speaker Verification (ASV) systems degrades significantly under adverse conditions which cause recordings from the same speaker to be different.The objective of this research is to investigate and develop robust techniques for performing automatic speaker recognition over various channel conditions, such as telephony and recorded microphone speech. This research is shown to improve the robustness of ASV systems in three main areas of feature extraction, speaker modelling and score normalization. At the feature level, a new set of dynamic features, termed Delta Cepstral Energy (DCE) is proposed, instead of traditional delta cepstra, which not only greatly reduces thedimensionality of the feature vector compared with delta and delta-delta cepstra, but is also shown to provide the same performance for matched testing and training conditions on TIMIT and a subset of the NIST 2002 dataset. The concept of speaker entropy, which conveys the information contained in a speaker's speech based on the extracted features, facilitates comparative evaluation of the proposed methods. In addition, Frequency Modulation features are combined in a complementary manner with the Mel Frequency CepstralCoefficients (MFCCs) to improve the performance of the ASV system under channel variability of various types. The proposed fused system shows a relative reduction of up to 23% in Equal Error Rate (EER) over the MFCC-based system when evaluated on the NIST 2008 dataset. Currently, the main challenge in speaker modelling is channel variability across different sessions. A recent approach to channel compensation, based on Support Vector Machines (SVM) is Nuisance Attribute Projection (NAP). The proposed multi-component approach to NAP, attempts to compensate for the main sources of inter-session variations through an additional optimization criteria, to allow more accurate estimates of the most dominant channel artefacts and to improve the system performance under mismatched training and test conditions. Another major issue in speaker recognition is that the variability of score distributions due to incompletely modelled regions of the feature space can produce segments of the test speech that are poorly matched to the claimed speaker model. A segment selection technique in score normalization is proposed that relies only on discriminative and reliable segments of the test utterance to verify the speaker. This approach is particularly useful in noisy conditions where using speech activity detection is not reliable at the feature level. Another source of score variability comes from the fact that not all phonemes are equally discriminative. To address this, a new score re-weighting technique is applied to likelihood values based on the discriminative level of each Gaussian component, i.e. each particular region of the feature space. It is found that a limited number of Gaussian mixtures, herein termed discriminative components are responsible for the overall performance, and that inclusion of the other non-discriminative components may only degrade the system performance.

Identity verification or biometric recognition systems play an important role in our daily lives. Applications include Automatic Teller Machines (ATM), banking and share information retrieval, and personal verification for credit cards. Among the biometric techniques, authentication of speakers by his/her voice is of great importance, since it employs a non-invasive approach and is the only available modality in many applications. However,the performance of Automatic Speaker Verification (ASV) systems degrades significantly under adverse conditions which cause recordings from the same speaker to be different.The objective of this research is to investigate and develop robust techniques for performing automatic speaker recognition over various channel conditions, such as telephony and recorded microphone speech. This research is shown to improve the robustness of ASV systems in three main areas of feature extraction, speaker modelling and score normalization. At the feature level, a new set of dynamic features, termed Delta Cepstral Energy (DCE) is proposed, instead of traditional delta cepstra, which not only greatly reduces thedimensionality of the feature vector compared with delta and delta-delta cepstra, but is also shown to provide the same performance for matched testing and training conditions on TIMIT and a subset of the NIST 2002 dataset. The concept of speaker entropy, which conveys the information contained in a speaker's speech based on the extracted features, facilitates comparative evaluation of the proposed methods. In addition, Frequency Modulation features are combined in a complementary manner with the Mel Frequency CepstralCoefficients (MFCCs) to improve the performance of the ASV system under channel variability of various types. The proposed fused system shows a relative reduction of up to 23% in Equal Error Rate (EER) over the MFCC-based system when evaluated on the NIST 2008 dataset. Currently, the main challenge in speaker modelling is channel variability across different sessions. A recent approach to channel compensation, based on Support Vector Machines (SVM) is Nuisance Attribute Projection (NAP). The proposed multi-component approach to NAP, attempts to compensate for the main sources of inter-session variations through an additional optimization criteria, to allow more accurate estimates of the most dominant channel artefacts and to improve the system performance under mismatched training and test conditions. Another major issue in speaker recognition is that the variability of score distributions due to incompletely modelled regions of the feature space can produce segments of the test speech that are poorly matched to the claimed speaker model. A segment selection technique in score normalization is proposed that relies only on discriminative and reliable segments of the test utterance to verify the speaker. This approach is particularly useful in noisy conditions where using speech activity detection is not reliable at the feature level. Another source of score variability comes from the fact that not all phonemes are equally discriminative. To address this, a new score re-weighting technique is applied to likelihood values based on the discriminative level of each Gaussian component, i.e. each particular region of the feature space. It is found that a limited number of Gaussian mixtures, herein termed discriminative components are responsible for the overall performance, and that inclusion of the other non-discriminative components may only degrade the system performance.

Thesis (M.S. - Geosciences)--University of Arizona. / Includes bibliographical references.

Thesis (M. S. - Landscape Architecture)--University of Arizona, 2000. / Includes bibliographical references (leaves 175-187).

Thèse (Ph. D.)--Université Laval, 2007. / Thèse en cotutelle, Département d'histoire, Faculté des Lettres, Université Laval, Québec et Université de Nice Sophia Antipolis, Nice, France. Bibliogr.: f. [404]-432. Publié aussi en version électronique dans la Collection Mémoires et thèses électroniques.

Thesis (m.s.)--University of Kentucky, 2004. / Title from document title page (viewed Jan. 7, 2005). Document formatted into pages; contains xiv, 475p. : ill. Includes abstract and vita. Includes bibliographical references (p. 469-473).