L-glutamate plays a vital role in central nervous system. It is a neurotransmitterassociated with several neurological disorders like Parkinson's disease, epilepsyand stroke. Continuous and fast monitoring of this neurotransmitter has become amajor concern for neuroscientists throughout the world. A simple, sensitive, and reliable L-glutamate microsensor with short responsetime has been developed using ceramic-based microelectrode arrays with platinum recording sites. The electrodes were modified by electrodeposition of Platinum black (Pt-black) to detect hydrogen peroxide (H2O2) which was produced by enzymatic reactions of glutamate oxidase immobilized on the electrode surface. Modification of Pt electrodes with Pt-black has been adoptedbecause the microscale roughness of Pt-black increases the effective surface area of the electrode and promotes efficiency of H2O2 electro-oxidation. The modified Pt recording sites were coated with m-phenylenediamine (mPD) and L-glutamate oxidase (L-GluOx). mPD acts as an barrier for extracellular interferents such as ascorbic acid and dopamine, thus increasing the selectivity of electrode for Glutamate (Glu). This modified microsensor was highly sensitive to H2O2(686.3??156.48 ??AmM-1cm-2), and Glutamate (492.2??112.67 ??AmM-1cm-2) at 700mV versus Ag/AgCl reference. Deposition of Pt nano-particles on recording sites enhanced the sensitivity to H2O2 by 2 times and the sensitivity to glutamate by 1.5 times.

Electroanalysis offers cheap and selective analysis of interesting solutions. However, one of the most common drawbacks is the accessibility for electrochemical sensing. By using high-pressure microfluidics with an integrated three-electrode system, new possibilities open for increased accessibility. Therefore, there is a need to fabricate sustainable reference surfaces into highly pressure tolerant microchannels. In this thesis, Ag/AgCl reference surfaces were in-situ fabricated in high-pressure microfluidic chips. This was performed by electroplating Ag on thin film Pt in microchannels and then chlorinating the silver into Ag/AgCl. Electroanalysis of ferrocyanide was carried out in a microfluidic chip using one of the in-situ fabricated Ag/AgCl references. The half-wave potential showed to be around +251 mV and the electrochemical water window was measured to 1400 mV with a range between -300 mV and +1100 mV. The obtained values show to be comparable to reference data of similar experiments performed elsewhere. For some applications of electrochemistry, a catalysis surface is beneficial. Nanoporous Pt black has proved to generate high catalytic performance in electrochemistry. Therefore, attempts have been carried out to fabricate Pt black onto Pt thin films, with the vision to succeed with such fabrication within microfluidic channels. To summarize, this project work has showed a possibility to in-situ fabricate Ag/AgCl reference surfaces. The project has also showed how to use such surfaces as reference electrodes for electroanalysis in high-pressure microfluidic chips. Lastly, new challenges and ideas to fabricate catalysis surfaces on thin film electrodes in flow channels have been presented. By this thesis, one more step has been taken to increase the accessibility for electroanalysis.

[pt] A alocação de ativos é uma das mais importantes decisões financeiras para investidores. No entanto, as decisões humanas não são totalmente racionais. Sabemos que as pessoas cometem muitos erros sistemáticos como, excesso de confiança, aversão à perda irracional e mau uso da informação entre outros. Nesta tese desenvolvemos duas metodologias distintas para enfrentar esse problema. A primeira abordagem é qualitativa, utiliza o modelo de Black-Litterman e tenta mapear a visão que o investidor tem do mercado. Esse método tenta mitigar a irracionalidade na tomada de decisão tornando mais fácil para um investidor demonstrar suas preferências em relação aos ativos. Black e Litterman desenvolveram um método para otimização de carteiras com a proposta de melhorar o modelo Markowitz, utilizando a construção de visões para representar a opinião do investidor sobre o futuro. No entanto, a forma de construir essas visões é bastante confusa e exige que o investidor estime vários parâmetros que são subjetivos. Assim, propomos uma nova forma de criar essas visões, utilizando Análise Verbal de Decisão. A segunda pesquisa envolve métodos quantitativos para resolver o problema de alocação de ativos com múltiplos estágios com premissas mais realistas. Embora a Programação Dinâmica Dual Estocástica (PDDE) seja uma técnica promissora para a solução de problemas de grande porte, não é adequada para o problema de alocação de ativos devido à dependência temporal associada aos retornos dos ativos. PDDE assume que o processo estocástico tem independência por estágio assegurando uma função única de custo futuro para cada estágio. No problema de alocação de ativos, a dependência do tempo é tipicamente não-linear e no lado esquerdo, o que torna PDDE tradicional não aplicável. Propomos uma variação do PDDE usando modelo oculto de Markov com estados discretos para resolver problemas reais de alocação de ativos com múltiplos períodos e dependência no tempo. Ambas as abordagens foram testadas em dados reais e empiricamente analisadas. As principais contribuições são as metodologia desenvolvidas para simplificar a construção de portfólios e para resolver o problema de alocação de ativos com múltiplos estágios. / [en] Asset allocation is one of the most important financial decisions made by investors. However, human decisions are not fully rational, and people make several systematic mistakes due to overconfidence, irrational loss aversion and misuse of information, among others. In this thesis, we developed two distinct methodologies to tackle this problem. The first approach has a more qualitative view, trying to map the investor s vision of the market. It tries to mitigate irrationality in decision-making by making it easier for an investor to demonstrate his/her preferences for specirfic assets. This first research uses the Black-Litterman model to construct portfolios. Black and Litterman developed a method for portfolio optimization as an improvement over the Markowitz model. They suggested the construction of views to represent an investor s opinion about future stocks returns. However, constructing these views has proven difficult, as it requires the investor to quantify several subjective parameters. This work investigates a new way of creating these views by using Verbal Decision Analysis. The second research focuses on quantitative methods to solve the multistage asset allocation problem. More specifically, it modifies the Stochastic Dynamic Dual Programming (SDDP) method to consider real asset allocation models. Although SDDP is a consolidated solution technique for large-scale problems, it is not suitable for asset allocation problems due to the temporal dependence of returns. Indeed, SDDP assumes a stagewise independence of the random process assuring a unique cost-to-go function for each time stage. For the asset allocation problem, time dependency is typically nonlinear and on the left-hand side, which makes traditional SDDP inapplicable. This thesis proposes an SDDP variation to solve real asset allocation problems for multiple periods, by modeling time dependence as a Hidden Markov Model with concealed discrete states. Both approaches were tested in real data and empirically analyzed. The contributions of this thesis are the methodology to simplify portfolio construction and the methods to solve real multistage stochastic asset allocation problems.