Phase transitions and nonlinear phenomena in neuronal network models

Communication and cooperation between billions of neurons underlie the power of the brain. How do complex functions of the brain arise from its cellular constituents? How do groups of neurons self-organize into patterns of activity? These are crucial questions in neuroscience. In order to answer them, it is necessary to have solid theoretical understanding of how single neurons communicate at the microscopic level, and how cooperative activity emerges. In this thesis we aim to understand how complex collective phenomena can arise in a simple model of neuronal networks. We use a model with balanced excitation and inhibition and complex network architecture, and we develop analytical and numerical methods for describing its neuronal dynamics. We study how interaction between neurons generates various collective phenomena, such as spontaneous appearance of network oscillations and seizures, and early warnings of these transitions in neuronal networks. Within our model, we show that phase transitions separate various dynamical regimes, and we investigate the corresponding bifurcations and critical phenomena. It permits us to suggest a qualitative explanation of the Berger effect, and to investigate phenomena such as avalanches, band-pass filter, and stochastic resonance. The role of modular structure in the detection of weak signals is also discussed. Moreover, we find nonlinear excitations that can describe paroxysmal spikes observed in electroencephalograms from epileptic brains. It allows us to propose a method to predict epileptic seizures. Memory and learning are key functions of the brain. There are evidences that these processes result from dynamical changes in the structure of the brain. At the microscopic level, synaptic connections are plastic and are modified according to the dynamics of neurons. Thus, we generalize our cortical model to take into account synaptic plasticity and we show that the repertoire of dynamical regimes becomes richer. In particular, we find mixed-mode oscillations and a chaotic regime in neuronal network dynamics.

Optimal control and numerical optimization applied to epidemiological models

A relação entre a epidemiologia, a modelação matemática e as ferramentas computacionais permite construir e testar teorias sobre o desenvolvimento e combate de uma doença. Esta tese tem como motivação o estudo de modelos epidemiológicos aplicados a doenças infeciosas numa perspetiva de Controlo Ótimo, dando particular relevância ao Dengue. Sendo uma doença tropical e subtropical transmitida por mosquitos, afecta cerca de 100 milhões de pessoas por ano, e é considerada pela Organização Mundial de Saúde como uma grande preocupação para a saúde pública. Os modelos matemáticos desenvolvidos e testados neste trabalho, baseiam-se em equações diferenciais ordinárias que descrevem a dinâmica subjacente à doença nomeadamente a interação entre humanos e mosquitos. É feito um estudo analítico dos mesmos relativamente aos pontos de equilíbrio, sua estabilidade e número básico de reprodução. A propagação do Dengue pode ser atenuada através de medidas de controlo do vetor transmissor, tais como o uso de inseticidas específicos e campanhas educacionais. Como o desenvolvimento de uma potencial vacina tem sido uma aposta mundial recente, são propostos modelos baseados na simulação de um hipotético processo de vacinação numa população. Tendo por base a teoria de Controlo Ótimo, são analisadas as estratégias ótimas para o uso destes controlos e respetivas repercussões na redução/erradicação da doença aquando de um surto na população, considerando uma abordagem bioeconómica. Os problemas formulados são resolvidos numericamente usando métodos diretos e indiretos. Os primeiros discretizam o problema reformulando-o num problema de optimização não linear. Os métodos indiretos usam o Princípio do Máximo de Pontryagin como condição necessária para encontrar a curva ótima para o respetivo controlo. Nestas duas estratégias utilizam-se vários pacotes de software numérico. Ao longo deste trabalho, houve sempre um compromisso entre o realismo dos modelos epidemiológicos e a sua tratabilidade em termos matemáticos.

Development of open models and tools for seismic risk assessment: application to Portugal

The exponential growth of the world population has led to an increase of settlements often located in areas prone to natural disasters, including earthquakes. Consequently, despite the important advances in the field of natural catastrophes modelling and risk mitigation actions, the overall human losses have continued to increase and unprecedented economic losses have been registered. In the research work presented herein, various areas of earthquake engineering and seismology are thoroughly investigated, and a case study application for mainland Portugal is performed. Seismic risk assessment is a critical link in the reduction of casualties and damages due to earthquakes. Recognition of this relation has led to a rapid rise in demand for accurate, reliable and flexible numerical tools and software. In the present work, an open-source platform for seismic hazard and risk assessment is developed. This software is capable of computing the distribution of losses or damage for an earthquake scenario (deterministic event-based) or earthquake losses due to all the possible seismic events that might occur within a region for a given interval of time (probabilistic event-based). This effort has been developed following an open and transparent philosophy and therefore, it is available to any individual or institution. The estimation of the seismic risk depends mainly on three components: seismic hazard, exposure and vulnerability. The latter component assumes special importance, as by intervening with appropriate retrofitting solutions, it may be possible to decrease directly the seismic risk. The employment of analytical methodologies is fundamental in the assessment of structural vulnerability, particularly in regions where post-earthquake building damage might not be available. Several common methodologies are investigated, and conclusions are yielded regarding the method that can provide an optimal balance between accuracy and computational effort. In addition, a simplified approach based on the displacement-based earthquake loss assessment (DBELA) is proposed, which allows for the rapid estimation of fragility curves, considering a wide spectrum of uncertainties. A novel vulnerability model for the reinforced concrete building stock in Portugal is proposed in this work, using statistical information collected from hundreds of real buildings. An analytical approach based on nonlinear time history analysis is adopted and the impact of a set of key parameters investigated, including the damage state criteria and the chosen intensity measure type. A comprehensive review of previous studies that contributed to the understanding of the seismic hazard and risk for Portugal is presented. An existing seismic source model was employed with recently proposed attenuation models to calculate probabilistic seismic hazard throughout the territory. The latter results are combined with information from the 2011 Building Census and the aforementioned vulnerability model to estimate economic loss maps for a return period of 475 years. These losses are disaggregated across the different building typologies and conclusions are yielded regarding the type of construction more vulnerable to seismic activity.

Nonlinear behavioral modeling of mixed signal RF-digital I/O devices

Esta tese investiga a caracterização (e modelação) de dispositivos que realizam o interface entre os domínios digital e analógico, tal como os buffers de saída dos circuitos integrados (CI). Os terminais sem fios da atualidade estão a ser desenvolvidos tendo em vista o conceito de rádio-definido-por-software introduzido por Mitola. Idealmente esta arquitetura tira partido de poderosos processadores e estende a operação dos blocos digitais o mais próximo possível da antena. Neste sentido, não é de estranhar que haja uma crescente preocupação, no seio da comunidade científica, relativamente à caracterização dos blocos que fazem o interface entre os domínios analógico e digital, sendo os conversores digital-analógico e analógico-digital dois bons exemplos destes circuitos. Dentro dos circuitos digitais de alta velocidade, tais como as memórias Flash, um papel semelhante é desempenhado pelos buffers de saída. Estes realizam o interface entre o domínio digital (núcleo lógico) e o domínio analógico (encapsulamento dos CI e parasitas associados às linhas de transmissão), determinando a integridade do sinal transmitido. Por forma a acelerar a análise de integridade do sinal, aquando do projeto de um CI, é fundamental ter modelos que são simultaneamente eficientes (em termos computacionais) e precisos. Tipicamente a extração/validação dos modelos para buffers de saída é feita usando dados obtidos da simulação de um modelo detalhado (ao nível do transístor) ou a partir de resultados experimentais. A última abordagem não envolve problemas de propriedade intelectual; contudo é raramente mencionada na literatura referente à caracterização de buffers de saída. Neste sentido, esta tese de Doutoramento foca-se no desenvolvimento de uma nova configuração de medição para a caracterização e modelação de buffers de saída de alta velocidade, com a natural extensão aos dispositivos amplificadores comutados RF-CMOS. Tendo por base um procedimento experimental bem definido, um modelo estado-da-arte é extraído e validado. A configuração de medição desenvolvida aborda não apenas a integridade dos sinais de saída mas também do barramento de alimentação. Por forma a determinar a sensibilidade das quantias estimadas (tensão e corrente) aos erros presentes nas diversas variáveis associadas ao procedimento experimental, uma análise de incerteza é também apresentada.

Nonlinear distortion generation mechanisms in Doherty amplifiers

Nowadays, wireless communications systems demand for greater mobility and higher data rates. Moreover, the need for spectral efficiency requires the use of non-constant envelope modulation schemes. Hence, power amplifier designers have to build highly efficient, broadband and linear amplifiers. In order to fulfil these strict requirements, the practical Doherty amplifier seems to be the most promising technique. However, due to its complex operation, its nonlinear distortion generation mechanisms are not yet fully understood. Currently, only heuristic interpretations are being used to justify the observed phenomena. Therefore, the main objective of this work is to provide a model capable of describing the Doherty power amplifier nonlinear distortion generation mechanisms, allowing the optimization of its design according to linearity and efficiency criteria. Besides that, this approach will allow a bridge between two different worlds: power amplifier design and digital pre-distortion since the knowledge gathered from the Doherty operation will serve to select the most suitable pre-distortion models.

Digital nonlinear equalization for optical transmission systems

This thesis focuses on digital equalization of nonlinear fiber impairments for coherent optical transmission systems. Building from well-known physical models of signal propagation in single-mode optical fibers, novel nonlinear equalization techniques are proposed, numerically assessed and experimentally demonstrated. The structure of the proposed algorithms is strongly driven by the optimization of the performance versus complexity tradeoff, envisioning the near-future practical application in commercial real-time transceivers. The work is initially focused on the mitigation of intra-channel nonlinear impairments relying on the concept of digital backpropagation (DBP) associated with Volterra-based filtering. After a comprehensive analysis of the third-order Volterra kernel, a set of critical simplifications are identified, culminating in the development of reduced complexity nonlinear equalization algorithms formulated both in time and frequency domains. The implementation complexity of the proposed techniques is analytically described in terms of computational effort and processing latency, by determining the number of real multiplications per processed sample and the number of serial multiplications, respectively. The equalization performance is numerically and experimentally assessed through bit error rate (BER) measurements. Finally, the problem of inter-channel nonlinear compensation is addressed within the context of 400 Gb/s (400G) superchannels for long-haul and ultra-long-haul transmission. Different superchannel configurations and nonlinear equalization strategies are experimentally assessed, demonstrating that inter-subcarrier nonlinear equalization can provide an enhanced signal reach while requiring only marginal added complexity.