This thesis documents a collection of experimental investigations in which a differentially-heated annulus was used to investigate the effects of topography on the atmospheric and oceanic circulation. To this end a number of experiments were devised, each using a different topographic base to study a different aspect of the impact of topography, motivated by the most notable outstanding questions found in a review of the literature, namely exploring the effects of topographic resonance, blocking via partial barriers, and azimuthally differential-heating via thermal topography. First of all, whilst employing sinusoidal wavenumber-3 topography to extend the experimental parameter space of a similar study, namely Read and Risch (2011), a new regime within a region of structural vacillation was encountered. Denoted as the ‘stationary-transition’ regime, it featured periodic oscillations between a dominant stationary wavenumber-3 flow and axisymmetric or chaotic flow. An investigation into topographic resonance followed, keeping the wavenumber-3 base, but with a sloped lid to add a beta effect to the annulus. This acted to increase the occurrence of stationary waves, along with the ‘stationary-transition’ regime, which was discovered to be a near-resonant region where nonlinear topographic resonant instability led to a 23 to 42 ‘day’ oscillatory structure. The base was then replaced with an isolated ridge, forming a partial barrier to study the difference between blocked and unblocked flow. The topography was found to impact the circulation at a level much higher than its own peak, causing a unique flow structure when the drifting flow and the topography interacted in the form of an ‘interference’ regime at low Taylor Numbers, as well as forming an erratic ‘irregular’ regime at higher Taylor Numbers. Lastly, this isolated ridge was replaced by flat heating elements covering the same azimuthal extent, in order to observe whether thermal topography could be comparable to mechanical topography. These azimuthally-varying heating experiments produced much the same results as the partial barriers study, despite the lack of a physical peak or bottom-trapped waves, suggesting that blocking is independent of these activities. Evidence of resonant wave-triads was noted in all experiments, though the component wavenumbers of the wave-triads and their impact on the flow was found to depend on the topography in question.

<p>In order to understand how the brain functions, under normal as well as pathological conditions, it is important to study the mechanisms underlying information integration. Depending on the nature of an input arriving at a synapse, different strategies may be used by the neuron to integrate and respond to the input. Naturally, if a short train of high-frequency synaptic input arrives, it may be beneficial for the neuron to be equipped with a fast mechanism that is highly sensitive to inputs on a short time scale. If, on the contrary, inputs arriving with low frequency are to be processed, it may be necessary for the neuron to possess slow mechanisms of integration. For example, in certain working memory tasks (e. g. delay-match-to-sample), sensory inputs may arrive separated by silent intervals in the range of seconds, and the subject should respond if the current input is identical to the preceeding input. It has been suggested that single neurons, due to intrinsic mechanisms outlasting the duration of input, may be able to perform such calculations. In this work, I have studied a mechanism thought to be particularly important in supporting the integration of low-frequency synaptic inputs. It is mediated by a cascade of events that starts with activation of group I metabotropic glutamate receptors (mGlu1/5), and ends with a membrane depolarization caused by a current that is mediated by canonical transient receptor potential (TRPC) ion channels. This current, denoted I_TRPC, is the focus of this thesis.</p><p>A specific objective of this thesis is to study the role of I_TRPC in the integration of synaptic inputs arriving at a low frequency, < 10 Hz. Our hypothesis is that, in contrast to the well-studied, rapidly decaying AMPA and NMDA currents, I_TRPC is well-suited for supporting temporal summation of such synaptic input. The reason for choosing this range of frequencies is that neurons often communicate with signals (spikes) around 8 Hz, as shown by single-unit recordings in behaving animals. This is true for several regions of the brain, including the entorhinal cortex (EC) which is known to play a key role in producing working memory function and enabling long-term memory formation in the hippocampus.</p><p>Although there is strong evidence suggesting that I_TRPC is important for neuronal communication, I have not encountered a systematic study of how this current contributes to synaptic integration. Since it is difficult to directly measure the electrical activity in dendritic branches using experimental techniques, I use computational modeling for this purpose. I implemented the components necessary for studying I_TRPC, including a detailed model of extrasynaptic glutamate concentration, mGlu1/5 dynamics and the TRPC channel itself. I tuned the model to replicate electrophysiological in vitro data from pyramidal neurons of the rodent EC, provided by our experimental collaborator. Since we were interested in the role of I_TRPC in temporal summation, a specific aim was to study how its decay time constant (τ_decay) is affected by synaptic stimulus parameters.</p><p>The hypothesis described above is supported by our simulation results, as we show that synaptic inputs arriving at frequencies as low as 3 - 4 Hz can be effectively summed. We also show that τ_decay increases with increasing stimulus duration and frequency, and that it is linearly dependent on the maximal glutamate concentration. Under some circumstances it was problematic to directly measure τ_decay, and we then used a pair-pulse paradigm to get an indirect estimate of τ_decay.</p><p>I am not aware of any computational model work taking into account the synaptically evoked I_TRPC current, prior to the current study, and believe that it is the first of its kind. We suggest that I_TRPC is important for slow synaptic integration, not only in the EC, but in several cortical and subcortical regions that contain mGlu1/5 and TRPC subunits, such as the prefrontal cortex. I will argue that this is further supported by studies using pharmacological blockers as well as studies on genetically modified animals.</p> / QC 20101005

This study employed multiple assessments, including sleep/resting waking EEG (visual scoring and power spectral analysis) and psychomotor vigilance task, to access effects of varying pulse-modulated microwaves (such as: 'talk', 'listen' and 'standby' mode signals) emitted from a standard mobile phone. The idea was prompted by a finding that the pulse modulation frequencies of mobile phone signals correspond to the frequencies of brain delta and alpha waves. Thereby it is possible the brain is able to recognize and respond to the low-frequency components of the mobile phone signals. Supporting evidence comes from repetitively reported EEG alpha and spindle effects of the 2, 8 and 217-Hz pulsed microwave exposure. Furthermore, brain imaging (EEG and PET) studies reveal 'low-frequency pulse-modulated waves' rather than the 'microwave frequency carrier waves' is the sine qua non for inducing these brain physiological effects [Huber et al., 2002, 2005; Regel et al., 2007a]. On the other hand, recent converging evidence, from molecular, behavioural and electrophysiological level, have shown that brain plasticity is a continuous process from waking to sleep and, sleep, a well-defined physiological condition, is 'shaped' by the waking experiences. The latter findings suggest certain sleep EEG features may characterize levels of cortical plasticity during wakefulness. The work presented in this thesis was inspired by these studies and aimed to understand how the real mobile phone signals with different low-frequency pulsing components [such as 'talk' (8, 217 Hz pulsed), 'listen' (2, 8, 217 Hz pulsed) and 'stand by' mode < 2 Hz pulsed)] change human brain electrical activities from waking to sleep. We approached this question based on EEG analysis in two domains: (1) EEG visual scoring; (2) EEG spectral analysis from relaxed waking to the deeper stages of non-NREM sleep. We also looked at the effects on the psychomotor vigilance performance. Results suggest 'talk' and 'Iisten/standby' modes have inverse effects on the distinctive thalamo-cortical oscillation modes and may thus impart inverse effects on their sleep structures. The implications of this study are of practical importance as it suggests the thalamo-cortical oscillations can be modulated by synchronizing rTMS/tDCS/DBS and sleeplwaking EEG. This concept may be applied to modulate the brain oscillation modes for enhancing sleep-dependent brain plastiCity or information processing.

The objective of this doctoral thesis is to study three different innovative noise control techniques in ducts namely: acoustic metamaterials, porous absorbers and microperforates. There has been a lot of research done on all these three topics in the context of duct acoustics. This research will assess the potential of the acoustic metamaterial technique and compare to the use of conventional methods using microperforated plates and/or porous materials.  The objective of the metamaterials part is to develop a physical approach to model and synthesize bulk moduli and densities to feasibly control the wave propagation pattern, creating quiet zones in the targeted fluid domain. This is achieved using an array of locally resonant metallic patches. In addition to this, a novel thin slow sound material is also proposed in the acoustic metamaterial part of this thesis. This slow sound material is a quasi-labyrinthine structure flush mounted to a duct, comprising of coplanar quarter wavelength resonators that aims to slow the speed of sound at selective resonance frequencies. A good agreement between theoretical analysis and experimental measurements is demonstrated. The second technique is based on acoustic porous foam and it is about modeling and characterization of a novel porous metallic foam absorber inside ducts. This material proved to be a similar or better sound absorber compared to the conventional porous absorbers, but with robust and less degradable properties. Material characterization of this porous absorber from a simple transfer matrix measurement is proposed.The last part of this research is focused on impedance of perforates with grazing flow on both sides. Modeling of the double sided grazing flow impedance is done using a modified version of an inverse semi-analytical technique. A minimization scheme is used to find the liner impedance value in the complex plane to match the calculated sound field to the measured one at the microphone positions. / <p>QC 20160923</p>

A teoria da perturbação baseada em múltiplas escalas temporais é usada neste trabalho para estudar as interações não lineares entre ondas na atmosfera no contexto das equações primitivas no plano beta-equatorial em coordenadas isobáricas. As ondas equatoriais de Rossby, mista Rossby-gravidade, gravidade-inerciais e Kelvin, com diferentes estruturas verticais, são obtidas como soluções de ordem dominante. A partir da condição de solvabilidade do problema de ordem superior, foi obtido um modelo assintótico reduzido que governa a interação fracamente não linear entre as ondas numa determinada tríade ressonante. A conservação da energia total para a solução de ordem dominante do modelo de equações original implica que a soma dos coeficientes de interação numa tríade ressonante qualquer deve ser nula. Usando um método gráfico, foram encontradas algumas tríades ressonantes envolvendo ondas baroclínicas equatorialmente confinadas e ondas de Rossby barotrópicas possuindo significativa influência em médias e altas latitudes. Duas tríades ressonantes receberam especial atenção devido ao significativo acoplamento entre os modos e à possível relação desses modos com alguns aspectos observados acerca dos fenômenos de baixa freqüência na atmosfera. A primeira tríade é composta por uma onda de Rossby barotrópica possuindo o segundo modo meridional interagindo ressonantemente com uma onda mista de Rossby-gravidade com a estrutura vertical do primeiro modo baroclínico, ambas possuindo o mesmo número de onda zonal, por meio de um modo geostrófico zonalmente simétrico (k = 0) possuindo a mesma estrutura vertical da onda mista e o modo meridional n = 1. A segunda tríade é constituída por uma onda mista de Rossby-gravidade com número de onda-2, uma onda de Kelvin com número de onda-1, ambas associadas ao primeiro modo baroclínico, e uma onda de Rossby barotrópica com número de onda-3 e modo meridional n = 2. A integração das equações reduzidas para essas duas tríades ressonantes mostra que para as amplitudes iniciais dos modos caracterizando magnitudes típicas de anomalias atmosféricas observadas, os modos na primeira tríade, em geral, trocam energia na escala intra-sazonal, enquanto os modos na segunda tríade trocam energia na escala intra-sazonal ou numa escala semi-anual, dependendo da amplitude inicial do modo de Rossby barotrópico. São discutidas as implicações dos resultados para a dinâmica da interação trópicos-extratrópicos na escala de baixa-freqüência do espectro dos movimentos atmosféricos. / The asymptotic perturbation theory based on multiple scales in time is used to investigate the nonlinear interactions among equatorial waves in an equatorial beta-plane adiabatic primitive equation atmospheric model in isobaric coordinates. The equatorial Rossby, mixed Rossby-gravity, Kelvin and inertio-gravity waves, with several vertical structures, are obtained as the leading-order solution. From the solvability condition of the problem, a reduced model governing the weakly nonlinear interaction of the waves in a particular resonant triad was obtained. The total energy conservation of the leading-order solution of the original model equations implies that the sum of the coupling coefficients in any resonant triad must be zero. Using a graphical approach, we determined some resonant triads involving equatorially trapped baroclinic waves and barotropic Rossby waves having large mid-latitude amplitude. Two particular interactions deserve special attention because of their strong coupling and their possible relation to observed features in the atmospheric circulation. One is characterized by a first baroclinic mode structure mixed Rossby-gravity wave interacting with a barotropic Rossby wave with the second gravest meridional mode, both having the same wavenumber, through a zonally symmetric geostrophic mode with the same vertical structure as the Yanai wave and having the n = 1 meridional mode. The other triad is composed of a zonal wavenumber-1 Kelvin wave, a zonal wavenumber-2 mixed Rossby-gravity wave, both with the first baroclinic mode vertical structure, and a barotropic zonal wavenumber-3 Rossby wave having the second gravest meridional mode. The barotropic Rossby waves in these two triad interactions have significant projection onto middle and higher latitudes. The integration of the triad equations for these particular interactions shows that, for the initial mode amplitudes characterizing typical magnitudes of atmospheric flow perturbations, the modes in the first triad usually exchange energy on intraseasonal time-scales, while the modes in the second triad exchange energy on either intraseasonal or semi-annual time-scale, depending on the initial condition. The implications of the results for the dynamics of tropics-extratropics interaction on low-frequency time-scales are discussed.

O presente trabalho descreve o projeto de modelos neurais pulsados em tecnologia CMOS. Foram projetados dois modelos: um neurônio baseado em condutâncias e um neurônio do tipo integra e dispara. O primeiro gera impulsos elétricos similares aos potenciais de ação gerados pelo neurônio biológico. Mediante simulação, foram observadas as seguintes características: disparo do impulso quando se atinge a tensão de limiar, hiperpolarização após o potencial de ação, retorno passivo à tensão de repouso, presença de período refratário e relação sigmoide entre a frequência de disparo e a intensidade do estímulo. Da mesma maneira, foi reproduzida a curva mínima duração x amplitude de estímulo típico dos neurônios biológicos. O segundo realiza a codificação de uma grandeza analógica na fase relativa dos impulsos elétricos gerados. Os impulsos gerados pelo circuito estão afastados em relação a um sinal periódico, em um intervalo que apresenta uma dependência logarítmica de uma corrente de entrada. John Hopfield propus esse tipo de codificação para explicar o reconhecimento de padrões com independência de escala, realizado pelo cérebro humano. No decorrer da pesquisa, foi necessário desenvolver algumas expressões analíticas para o projeto de circuitos de baixa frequência em CMOS, não encontradas na literatura estudada. As expressões estão baseadas na equação da corrente do transistor MOS proposta no modelo conhecido como Advanced Compact Mosfet (ACM). O projeto, implementação e testes de um transcondutor linearizado, e os resultados das simulações dos modelos neurais projetados, demonstram a validade das expressões desenvolvidas. / This work describes the design of pulsed neural models in CMOS technology. Two models were designed: a conductance based neuron and an integrate and fire neuron. The first generates electrical impulses similar to action potentials generated by the biological neuron. Through simulation, the following characteristics were observed: pulse trigger after reaching threshold voltage, hyperpolarization after the action potential, passive return to resting potential, presence of refractory period and sigmoid relationship between the firing rate and the stimulus intensity. Likewise, the curve minimal duration vs stimulus amplitude typical of biological neurons was reproduced. The second one performs the encoding of an analog input in the relative phase of electrical impulses. The impulses generated by the circuit are delayed with respect to a reference periodic signal, in a range that has a logarithmic dependence on an input current. John Hopfield proposed this type of encoding to explain the scale independent pattern recognition performed by the human brain. During the research, it was necessary to develop some analytical expressions for the design of low-frequency circuits in CMOS, not found in the literature studied. The expressions are based on the Advanced Compact MOSFET (ACM) model. The design, implementations and testing of a linearized transconductor, and the simulations results of the neural models designed, demonstrate the validity of the expressions developed.

O Ruído de Baixa Frequência (LFN), tais como o ruído flicker e o Random Telegraph Noise (RTN), são limitadores de performance em muitos circuitos analógicos e digitais. Para transistores diminutos, a densidade espectral de potência do ruído pode variar muitas ordens de grandeza, impondo uma séria limitação na performance do circuito e também em sua confiabilidade. Nesta tese, nós propomos um novo modelo de RTN estatístico para descrever o ruído de baixa frequência em MOSFETs. Utilizando o modelo proposto, pode-se explicar e calcular o valor esperado e a variabilidade do ruído em função das polarizações, geometrias e dos parâmetros físicos do transistor. O modelo é validado através de inúmeros resultados experimentais para dispositivos com canais tipo n e p, e para diferentes tecnologias CMOS. É demonstrado que a estatística do ruído LFN dos dispositivos de canal tipo n e p podem ser descritos através do mesmo mecanismo. Através dos nossos resultados e do nosso modelo, nós mostramos que a densidade de armadilhas dos transistores de canal tipo p é fortemente dependente do nível de Fermi, enquanto para o transistor de tipo n a densidade de armadilhas pode ser considerada constante na energia. Também é mostrado e explicado, através do nosso modelo, o impacto do implante de halo nas estatísticas do ruído. Utilizando o modelo demonstra-se porque a variabilidade, denotado por σ[log(SId)], do RTN/LFN não segue uma dependência 1/√área; e fica demonstrado que o ruído, e sua variabilidade, encontrado em nossas medidas pode ser modelado utilizando parâmetros físicos. Além disso, o modelo proposto pode ser utilizado para calcular o percentil do ruído, o qual pode ser utilizado para prever ou alcançar certo rendimento do circuito. / Low Frequency Noise (LFN) and Random Telegraph Noise (RTN) are performance limiters in many analog and digital circuits. For small area devices, the noise power spectral density can easily vary by many orders of magnitude, imposing serious threat on circuit performance and possibly reliability. In this thesis, we propose a new RTN model to describe the statistics of the low frequency noise in MOSFETs. Using the proposed model, we can explain and calculate the Expected value and Variability of the noise as function of devices’ biases, geometry and physical parameters. The model is validated through numerous experimental results for n-channel and p-channel devices from different CMOS technology nodes. We show that the LFN statistics of n-channel and p-channel MOSFETs can be described by the same mechanism. From our results and model, we show that the trap density of the p-channel device is a strongly varying function of the Fermi level, whereas for the n-channel the trap density can be considered constant. We also show and explain, using the proposed model, the impact of the halo-implanted regions on the statistics of the noise. Using this model, we clarify why the variability, denoted by σ[log(SId)], of RTN/LFN doesn't follow a 1/√area dependence; and we demonstrate that the noise, and its variability, found in our measurements can be modeled using reasonable physical quantities. Moreover, the proposed model can be used to calculate the percentile quantity of the noise, which can be used to predict or to achieve certain circuit yield.

O presente trabalho descreve o projeto de modelos neurais pulsados em tecnologia CMOS. Foram projetados dois modelos: um neurônio baseado em condutâncias e um neurônio do tipo integra e dispara. O primeiro gera impulsos elétricos similares aos potenciais de ação gerados pelo neurônio biológico. Mediante simulação, foram observadas as seguintes características: disparo do impulso quando se atinge a tensão de limiar, hiperpolarização após o potencial de ação, retorno passivo à tensão de repouso, presença de período refratário e relação sigmoide entre a frequência de disparo e a intensidade do estímulo. Da mesma maneira, foi reproduzida a curva mínima duração x amplitude de estímulo típico dos neurônios biológicos. O segundo realiza a codificação de uma grandeza analógica na fase relativa dos impulsos elétricos gerados. Os impulsos gerados pelo circuito estão afastados em relação a um sinal periódico, em um intervalo que apresenta uma dependência logarítmica de uma corrente de entrada. John Hopfield propus esse tipo de codificação para explicar o reconhecimento de padrões com independência de escala, realizado pelo cérebro humano. No decorrer da pesquisa, foi necessário desenvolver algumas expressões analíticas para o projeto de circuitos de baixa frequência em CMOS, não encontradas na literatura estudada. As expressões estão baseadas na equação da corrente do transistor MOS proposta no modelo conhecido como Advanced Compact Mosfet (ACM). O projeto, implementação e testes de um transcondutor linearizado, e os resultados das simulações dos modelos neurais projetados, demonstram a validade das expressões desenvolvidas. / This work describes the design of pulsed neural models in CMOS technology. Two models were designed: a conductance based neuron and an integrate and fire neuron. The first generates electrical impulses similar to action potentials generated by the biological neuron. Through simulation, the following characteristics were observed: pulse trigger after reaching threshold voltage, hyperpolarization after the action potential, passive return to resting potential, presence of refractory period and sigmoid relationship between the firing rate and the stimulus intensity. Likewise, the curve minimal duration vs stimulus amplitude typical of biological neurons was reproduced. The second one performs the encoding of an analog input in the relative phase of electrical impulses. The impulses generated by the circuit are delayed with respect to a reference periodic signal, in a range that has a logarithmic dependence on an input current. John Hopfield proposed this type of encoding to explain the scale independent pattern recognition performed by the human brain. During the research, it was necessary to develop some analytical expressions for the design of low-frequency circuits in CMOS, not found in the literature studied. The expressions are based on the Advanced Compact MOSFET (ACM) model. The design, implementations and testing of a linearized transconductor, and the simulations results of the neural models designed, demonstrate the validity of the expressions developed.

Uncertainty Quantification (UQ) has been an active area of research in recent years with a wide range of applications in data and imaging sciences. In many problems, the source of uncertainty stems from an unknown parameter in the model. In physical and engineering systems for example, the parameters of the partial differential equation (PDE) that model the observed data may be unknown or incompletely specified. In such cases, one may use a probabilistic description based on prior information and formulate a forward UQ problem of characterising the uncertainty in the PDE solution and observations in response to that in the parameters. Conversely, inverse UQ encompasses the statistical estimation of the unknown parameters from the available observations, which can be cast as a Bayesian inverse problem. The contributions of the thesis focus on examining the aforementioned forward and inverse UQ problems for the low-frequency, time-harmonic Maxwell equations, where the model uncertainty emanates from the lack of knowledge of the material conductivity parameter. The motivation comes from the Controlled-Source Electromagnetic Method (CSEM) that aims to detect and image hydrocarbon reservoirs by using electromagnetic field (EM) measurements to obtain information about the conductivity profile of the sub-seabed. Traditionally, algorithms for deterministic models have been employed to solve the inverse problem in CSEM by optimisation and regularisation methods, which aside from the image reconstruction provide no quantitative information on the credibility of its features. This work employs instead stochastic models where the conductivity is represented as a lognormal random field, with the objective of providing a more informative characterisation of the model observables and the unknown parameters. The variational formulation of these stochastic models is analysed and proved to be well-posed under suitable assumptions. For computational purposes the stochastic formulation is recast as a deterministic, parametric problem with distributed uncertainty, which leads to an infinite-dimensional integration problem with respect to the prior and posterior measure. One of the main challenges is thus the approximation of these integrals, with the standard choice being some variant of the Monte-Carlo (MC) method. However, such methods typically fail to take advantage of the intrinsic properties of the model and suffer from unsatisfactory convergence rates. Based on recently developed theory on high-dimensional approximation, this thesis advocates the use of Sparse Quadrature (SQ) to tackle the integration problem. For the models considered here and under certain assumptions, we prove that for forward UQ, Sparse Quadrature can attain dimension-independent convergence rates that out-perform MC. Typical CSEM models are large-scale and thus additional effort is made in this work to reduce the cost of obtaining forward solutions for each sampling parameter by utilising the weighted Reduced Basis method (RB) and the Empirical Interpolation Method (EIM). The proposed variant of a combined SQ-EIM-RB algorithm is based on an adaptive selection of training sets and a primal-dual, goal-oriented formulation for the EIM-RB approximation. Numerical examples show that the suggested computational framework can alleviate the computational costs associated with forward UQ for the pertinent large-scale models, thus providing a viable methodology for practical applications.

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