Alzheimer's disease (AD) is the neurodegenerative disease responsible for the majority of dementia cases across the United States. Its pathology involves the accumulation of protein plaques in areas of the brain directly involved with learning and memory formation, causing cognitive impairments and loss of independence in everyday life. Deep brain stimulation (DBS) is a relatively young field in medicine that has gained a great deal of traction with its efficacious clinical outcomes in neurological diseases including Parkinson's disease, epilepsy, depression and obsessive-compulsive disorder. More recently, researchers have sought to discover the proper application of DBS to improve the formation of episodic memory to provide a comparable or superior therapy for AD. Many experiments have been performed using different electrical parameters, hardware, or locations stimulated in the brain, which produced mixed results for benefits in memory reinforcement. Of the various brain structures available to target, the Entorhinal Cortex (EC) has been shown to lead to numerous positive outcomes. Additionally, one study used a novel approach, applying DBS in response to the neural activity of the individual brain during memory encoding tasks, which produced improvements in memory performance. This proposal aims to use these modalities in concert - a closed-loop stimulation approach that monitors neural activity and targeting the EC - in AD dementia patients to act as an adjuvant therapy to current acetylcholinesterase inhibitor medications that provide weak efficacy when used alone. This will be conducted in a 2 year, multicenter, double-blind, randomized controlled clinical trial comparing treatment with dual therapy consisting of DBS and an acetylcholinesterase inhibitor, to those with acetylcholinesterase inhibitor monotherapy. Participants will have mild or moderate AD at baseline, evaluated using the Mini-Mental State Examination and their progress in both experimental arms will be recorded using the 13 item Alzheimer's Disease Assessment Subscale-Cognitive over a 2-year period. Investigators will study the primary outcome of delaying cognitive decline, with secondary effects involving the differences between age groups, stages of AD and how frequently stimulation was received in those within the DBS and standard therapy group. The results from this study have the potential to further improve future approaches involving DBS in the treatment of AD dementia, as the projected number of those affected by the disease continues to grow with advances in modern medicine.

Deep neural networks (DNNs) and deep learning approaches yield state-of-the-art performance in a range of machine learning tasks, including automatic speech recognition. The multi-layer transformations and activation functions in DNNs, or related network variations, allow complex and difficult data to be well modelled. However, the highly distributed representations associated with these models make it hard to interpret the parameters. The whole neural network is commonly treated a ``black box''. The behaviours of activation functions and the meanings of network parameters are rarely controlled in the standard DNN training. Though a sensible performance can be achieved, the lack of interpretations to network structures and parameters causes better regularisation and adaptation on DNN models challenging. In regularisation, parameters have to be regularised universally and indiscriminately. For instance, the widely used L2 regularisation encourages all parameters to be zeros. In adaptation, it requires to re-estimate a large number of independent parameters. Adaptation schemes in this framework cannot be effectively performed when there are limited adaptation data. This thesis investigates structured deep neural networks. Special structures are explicitly designed, and they are imposed with desired interpretation to improve DNN regularisation and adaptation. For regularisation, parameters can be separately regularised based on their functions. For adaptation, parameters can be adapted in groups or partially adapted according to their roles in the network topology. Three forms of structured DNNs are proposed in this thesis. The contributions of these models are presented as follows. The first contribution of this thesis is the multi-basis adaptive neural network. This form of structured DNN introduces a set of parallel sub-networks with restricted connections. The design of restricted connectivity allows different aspects of data to be explicitly learned. Sub-network outputs are then combined, and this combination module is used as the speaker-dependent structure that can be robustly estimated for adaptation. The second contribution of this thesis is the stimulated deep neural network. This form of structured DNN relates and smooths activation functions in regions of the network. It aids the visualisation and interpretation of DNN models but also has the potential to reduce over-fitting. Novel adaptation schemes can be performed on it, taking advantages of the smooth property that the stimulated DNN offer. The third contribution of this thesis is the deep activation mixture model. Also, this form of structured DNN encourages the outputs of activation functions to achieve a smooth surface. The output of one hidden layer is explicitly modelled as the sum of a mixture model and a residual model. The mixture model forms an activation contour, and the residual model depicts fluctuations around this contour. The smoothness yielded by a mixture model helps to regularise the overall model and allows novel adaptation schemes.

A well-accepted idea in geomorphology is that landforms control the type and distribution of biological habitat. However, the linkages between geomorphology and ecology remain poorly understood. In rivers, the geomorphic template controls the hydraulic environment, partly shaping the river ecosystem. But what processes shape the geomorphic template? Here, I examine how two hillslope processes dominant in the Oregon Coast Range, debris flows and deep-seated landslides, affect valley floor width and channel slope, key components of the geomorphic template in riverine ecosystems. I then investigate how patterns in potential salmon habitat differ between streams dominated by deep-seated landslides and streams dominated by debris flows. I show that terrain influenced by deep-seated landslides exhibits (1) valley widths that are more variable throughout the network but less locally variable, (2) more variable channel slopes, and (3) more potential salmon habitat as well as significantly more connectivity between habitat types.

Continuous or semi-continuous reproduction is the norm in deep-sea animals, with exceptions explained by seasonal pulses of surface-derived phytodetritus. Chemosynthesis-based ecosystems such as cold seeps have an independent nutritional supply and are often thought of as decoupled from surface productivity. This thesis explores reproductive patterns of four bathymodiolin mussel species from 14 cold seeps (320 to 3300 m depth) in the Gulf of Mexico (2014) and the northwestern Atlantic (2015). Using paraffin histology, I determined maturity stages for male and oocyte sizes for female mussels. All species at all sites reproduced periodically and synchronously, with geographic synchrony among sites. This suggests that mussels rely on a site-independent cue such as seasonal phytodetrital flux to synchronize reproduction, providing evidence for a stronger coupling between surface productivity and chemosynthesis-based fauna than previously expected. Mature oocytes were of similar size for all species at all depths, suggesting that egg size is phylogenetically constrained.

Made available in DSpace on 2014-06-11T19:33:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2001-05-28Bitstream added on 2014-06-13T19:44:10Z : No. of bitstreams: 1 terada_hh_dr_arafo.pdf: 1658352 bytes, checksum: 431bfc18fcfd164c8330b1a2453bcd71 (MD5) / Este estudo cefalométrico prospectivo foi desenvolvido com o propósito de descrever os resultados de uma das estratégias de correção da mordida profunda. Foram selecionados 19 indivíduos, com faixa etária entre 11 e 15 anos, apresentando más-oclusões de Classe II, Divisão 1, com mordida profunda de no mínimo 4 milímetros. Desses, 9 indivíduos serviram como grupo controle e os outros 10 foram tratados com a mecânica de intrusão da técnica de Ricketts (arco base). Foram colocados implantes metálicos de referência intra-mandibulares, para sobreposições de traçados, em todos os componentes da amostra. Telerradiografias cefalométricas, em norma lateral, para a avaliação do comportamento dos incisivos inferiores, e em 45 graus, para a avaliação dos primeiros pré-molares e primeiros molares inferiores, foram tomadas no início do tratamento e após o nivelamento da curva de Spee do arco inferior para o grupo experimental, e após aproximadamente 6 meses no grupo controle. Os resultados na região de incisivos inferiores indicaram que houve intrusão dos incisivos inferiores e também um deslocamento horizontal para lingual dos três pontos estudados (borda incisal, centro de resistência e ápice radicular). Não houve deslocamento vertical (extrusivo) nos primeiros pré-molares e nos primeiros molares causados pelo tratamento. Os primeiros pré-molares demonstraram uma inclinação para distal com o fulcro próximo ao ápice, apesar de nenhum acessório ter sido colocado nesses dentes. Na região de molares, houve uma inclinação distal da coroa e mesial de raiz, com o fulcro desse movimento próximo ao centro de resistência. / The purpose of this prospective study was to avaliate the results of treatment strategie for deep overbite correction. Nineteen Class II, Division 1, with deep overbite individuals (age 11 to 15 years) were selected. Nine cases were used as a control group and the others were trated with the bioprogressive technique (Ricketts) for correction of vertical malocclusion. Metallic implants were used for superimpositions. Lateral cephalometric radiographs were used for evaluation of lower incisors. Forty five degrees cephalometric radiographs were used for evaluation of lower first bicuspids and first molars. These radiographs were taken before and immediately after leveling of lower arch and about 6 months later for the control group. The results showed that the technique produced highly significant incisor intrusion and a lingual movement of three points inverstigated (incisal edge, center of resistence and root apex). There was no vertical displacement (extrusion) on lower first bicuspid and first molar. A distal inclination was observed on lower first bicuspid, despite of any bracket has been fixed on it. Lower first molars crowns showed a distal movement and the root showed a mesial movement, with center of rotation near the fulcrum.

Made available in DSpace on 2014-06-11T19:27:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2004-06-29Bitstream added on 2014-06-13T19:36:14Z : No. of bitstreams: 1 nunes_vfm_me_arafo.pdf: 1730181 bytes, checksum: 4ab25e53f6d17c054131c11164a011c6 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este estudo cefalométrico prospectivo foi desenvolvido com o propósito de descrever os resultados de uma das estratégias de intrusão de caninos. Foram selecionados 19 indivíduos, com faixa etária entre 11 e 15 anos, apresentando más-oclusões de Classe II, Divisão 1, com mordida profunda mínima de 4 milímetros. Desses, 9 indivíduos serviram como grupo controle e os outros 10 foram tratados inicialmente com a mecânica de intrusão da técnica de Ricketts (arco base). Foram colocados implantes intra-mandibulares, para sobreposição de traçados, em todos os componentes da amostra. Teleradiografias cefalométricas, em norma lateral, para a avaliação do comportamento dos incisivos inferiores, e em 45 graus, para avaliação dos caninos inferiores, foram tomadas no início do tratamento e após a intrusão dos caninos no arco inferior para o grupo experimental, e após aproximadamente 6 meses no grupo controle. Os resultados na região dos incisivos inferiores indicaram que houve uma leve vestibularização deste dentes, sem provocar extrusão. Os resultados nos caninos inferiores demonstraram que houve intrusão nos três pontos estudados (ponta de cúspide, centro de resistência e ápice radicular) e uma inclinação para distal do centro de resistência e ápice radicular. / The purpose of this prospective study was to evaluate the results of treatment strategies for canines intrusion. Nineteen Class II, Division 1, with deep overbite individuals (age 11 to 15 years) were selected. Nine cases were used as a control group and the others were treated with the bioprogressive technique (Ricketts) for canine intrusion. Metallic implants were used for superimpositions. Lateral cephalometric radiographs were used for evaluation of lower incisors. Forty-five degrees cephalometric radiographs were used for evaluation of canines. These radiographs were taken after lower incisors intrusion and immediately after canines intrusion and about 6 months later for the control group. The results showed that the technique produced highly significant canines intrusion and a distal movement of center of resistence and root apex. There was no vertical displacement (extrusion) on lower incisors and a vestibular inclination was observed.

Autoregressive models factorize a multivariate joint probability distribution into a product of one-dimensional conditional distributions. The variables are assigned an ordering, and the conditional distribution of each variable modelled using all variables preceding it in that ordering as predictors. Calculating normalized probabilities and sampling has polynomial computational complexity under autoregressive models. Moreover, binary autoregressive models based on neural networks obtain statistical performances similar to that of some intractable models, like restricted Boltzmann machines, on several datasets. The use of autoregressive probability density estimators based on neural networks to model real-valued data, while proposed before, has never been properly investigated and reported. In this thesis we extend the formulation of neural autoregressive distribution estimators (NADE) to real-valued data; a model we call the real-valued neural autoregressive density estimator (RNADE). Its statistical performance on several datasets, including visual and auditory data, is reported and compared to that of other models. RNADE obtained higher test likelihoods than other tractable models, while retaining all the attractive computational properties of autoregressive models. However, autoregressive models are limited by the ordering of the variables inherent to their formulation. Marginalization and imputation tasks can only be solved analytically if the missing variables are at the end of the ordering. We present a new training technique that obtains a set of parameters that can be used for any ordering of the variables. By choosing a model with a convenient ordering of the dimensions at test time, it is possible to solve any marginalization and imputation tasks analytically. The same training procedure also makes it practical to train NADEs and RNADEs with several hidden layers. The resulting deep and tractable models display higher test likelihoods than the equivalent one-hidden-layer models for all the datasets tested. Ensembles of NADEs or RNADEs can be created inexpensively by combining models that share their parameters but differ in the ordering of the variables. These ensembles of autoregressive models obtain state-of-the-art statistical performances for several datasets. Finally, we demonstrate the application of RNADE to speech synthesis, and confirm that capturing the phone-conditional dependencies of acoustic features improves the quality of synthetic speech. Our model generates synthetic speech that was judged by naive listeners as being of higher quality than that generated by mixture density networks, which are considered a state-of-the-art synthesis technique.

This thesis presents the results of an experimental, numerical and analytical study to develop a design method to calculate shear resistance of flanged ferrocement beams with vertical mesh reinforcements in the web. Two groups of full-scale testing were conducted comprising of three I beams and four U beams. The I beams had the same geometry and reinforcement arrangements, but differed in the matrix strength or shear span to depth ratio. The U beams differed in web and flange thickness, reinforcement arrangements, matrix strength and shear span to depth ratio. The experimental data were used for validation of finite element models which had been developed using the ABAQUS software. The validated models were subsequently employed to conduct a comprehensive parametric study to investigate the effects of a number of design parameters, including the effect of matrix strength, shear span to depth ratio, cross sectional area, length of clear span, volume fraction of meshes and amount of rebar. The main conclusion from the experiments and parametric studies were: shear failure may occur only when the shear span to depth ratio is smaller than 1.5; the shear strength may increase by increasing the matrix strength, volume fraction of meshes, cross sectional area and amount of rebar. The main type of shear failure for I beams was diagonal splitting while for U beams it was shear flexural. Based on the results from the experimental and numerical studies, a shear design guide for ferrocement beams was developed. A set of empirical equations for the two different failure types and an improved strut-and-tie were proposed. By comparison with the procedures currently in practice, it is demonstrated that the methodology proposed in this thesis is likely to give much better predictions for shear capacity of flanged ferrocement beams.

During July 1974, two reversed deep seismic sounding (DSS) profiles extending about 75 km were recorded in the Explorer Ridge region of the northeastern Pacific, one parallel and the other perpendicular to the ridge. A two-ship operation was used to record near-vertical incidence to wide-angle reflected waves and refracted waves with penetration from the ocean bottom to the upper mantle. Signals from six individual hydrophones suspended at 45 m depth from a 600 m cable trailed behind the receiving ship were recorded in digital form. The shooting ship detonated charges ranging from 2.3 kg to 280 kg and recorded the direct arrival plus the WWVB time code. Processing of the data recorded at distances beyond 4 km included demultiplexing, stacking, and filtering. Before the data were presented in record section form, traveltime corrections were made for topography and shot distance, and amplitude corrections were made for amplifier gain, charge size, and spherical spreading. The interpretation procedure consisted of two steps. A homogeneous, layered velocity-depth model was initially constructed from first arrival traveltime data. The p-A curve corresponding to this model was then altered until an amplitude fit was obtained using synthetic seismograms. Weichert-Herglotz integration of the resultant p-A curve produced the final velocity-depth model. This traveltime and amplitude interpretation required the introduction of velocity gradients into the model. The profile run across the ridge showed no anomalous behaviour as the ridge was crossed; the profile on the Juan de Fuca plate, paralleling the ridge, exhibited traveltime branch offsets and delays. These have been interpreted as due to faulting with a. vertical component of offset of about 5 km. The reversed upper mantle velocities are 7.8 and 7.3 km/s in directions perpendicular and parallel to the ridge. Anisotropy is proposed to explain these different velocities. Compared with crustal sections from other ridge areas, the data require a thick "layer 3" (up to 7 km) near the ridge crest. The total depth to the base of the oceanic crust varies between 10 and 12 km except in the faulted region. The results of this study favor the hypothesis that Explorer Ridge is presently an inactive spreading center. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

This dissertation examines the idea that ethnographically reported relationships between artifact classes and faunal food resource remains can be detected in an archaeological context. A detailed site report is presented for Deep Bay (DiSe 7), including analyses of the artifact and faunal assemblages, and quantitative techniques are employed to search for associations between faunal and artifact variables in this site. The results of four analyses are compared, and the recurring associations of variable pairs are interpreted in the light of ethnographic and ecological data. The various lines of evidence relevant to the most likely season of site occupation are also examined. It is concluded that some of the ethnographically reported food resource procurement patterns can successfully be detected in the archaeological record. Evidence is presented that suggests the existence of food resource procurement systems centered around herring, deer, sea mammal, and migratory waterfowl. The site was most likely occupied during the late winter and early spring, primarily for deer hunting and herring fishing, and secondarily for sea mammal and waterfowl hunting. The acquisition of molluscs is considered to be a given. This subsistence pattern appears to have varied little over the past 2000 years. It is also concluded that the same techniques could be used profitably for similar studies in the future. / Arts, Faculty of / Anthropology, Department of / Graduate