Substrate interaction with recombinant amidase from Pseudomonas aeruginosa during biocatalysis

The interaction of a variety of substrates with Pseudomonas aeruginosa native amidase (E.C. 3.5.1.4), overproduced in an Escherichia coli strain, was investigated using difference FTIR spectroscopy. The amides used as substrates showed an increase in hydrogen bonding upon association in multimers, which was not seen with esters. Evidence for an overall reduction or weakening of hydrogen bonding while amide and ester substrates are interacting with the enzyme is presented. The results describe a spectroscopic approach for analysis of substrate-amidase interaction and in situ monitoring of the hydrolysis and transferase reaction when amides or esters are used as substrates.

Structural and optical studies of Au doped titanium oxide films

Thin films of TiO2 were doped with Au by ion implantation and in situ during the deposition. The films were grown by reactive magnetron sputtering and deposited in silicon and glass substrates at a temperature around 150 degrees C. The undoped films were implanted with Au fiuences in the range of 5 x 10(15) Au/cm(2)-1 x 10(17) Au/cm(2) with a energy of 150 keV. At a fluence of 5 x 10(16) Au/cm(2) the formation of Au nanoclusters in the films is observed during the implantation at room temperature. The clustering process starts to occur during the implantation where XRD estimates the presence of 3-5 nm precipitates. After annealing in a reducing atmosphere, the small precipitates coalesce into larger ones following an Ostwald ripening mechanism. In situ XRD studies reveal that Au atoms start to coalesce at 350 degrees C, reaching the precipitates dimensions larger than 40 nm at 600 degrees C. Annealing above 700 degrees C promotes drastic changes in the Au profile of in situ doped films with the formation of two Au rich regions at the interface and surface respectively. The optical properties reveal the presence of a broad band centered at 550 nm related to the plasmon resonance of gold particles visible in AFM maps. (C) 2011 Elsevier B.V. All rights reserved.

A formação em mediação de conflitos no desenvolvimento profissional dos assistentes operacionais, em escola pública do 1º ciclo do ensino básico

O objetivo da pesquisa pretende verificar se há um contributo da formação em mediação no desenvolvimento de conhecimentos nessa área e na mudança de atitude nos Assistentes Operacionais (AO), face à resolução de conflitos entre alunos. Os recreios das escolas do 1.º Ciclo do Ensino Básico (1.ºCEB) são os locais onde ocorre a quase totalidade dos conflitos entre alunos (Fernández, 2007; Oliveira, 2007; Rosa, 2007). Esses recreios são supervisionados pelos AO, os quais devem ter formação específica em estratégias de resolução de conflitos. A mediação é apontada como a melhor estratégia na abordagem dos conflitos escolares, perspetivando melhoria na convivência escolar e na construção de um clima escolar positivo, propício à eficácia da educação. A estratégia de pesquisa baseia-se num estudo de intervenção com uma amostra de conveniência, simultaneamente qualitativo e quantitativo. Os dados foram recolhidos por questionário, por levantamento dos conhecimentos anteriores e posteriores à formação e por entrevistas aos participantes. No estudo participaram sete AO. Os resultados revelaram que os AO desenvolveram conhecimentos sobre mediação e percecionaram em si mesmos mudanças de atitude face à resolução de conflitos entre alunos. Os resultados ainda revelaram que os AO se sentem desvalorizados no meio escolar, mas motivados na interação com os alunos. Concluiu-se que a formação em mediação de conflitos oferece um contributo significativo no desenvolvimento de conhecimentos sobre mediação e facilita uma mudança de atitude na resolução de conflitos entre alunos. Concluiu-se também que os AO estão conscientes do seu papel educativo e que têm sugestões pertinentes de melhoria.ABSTRAT This research intends to evaluate whether training in mediation contributes for the development of knowledge in this area, and for changes in attitude, when Operational Assistants (OAs) sort out conflicts between students. The playgrounds of the schools of the 1st Cycle of Basic Education (1stCEB) are the places where almost the conflicts between students happen. These playgrounds are supervised by OAs, which must have specific training in conflict resolution strategies. Mediation is considered the best strategy for addressing students’ conflicts in order to improve school coexistence and positive climate, conducive to the effectiveness of education. The research strategy is based on an intervention study with a convenience sample, both qualitative and quantitative. Data was collected by questionnaire, assessment of knowledge before and after training and final interviews. The participants were 7 OAs. The results revealed the development of knowledge about mediation, who perceives themselves as changing attitudes towards conflicts resolution between students. The results also revealed that the OAs feel devalued, but motivated when interacting to students. Training in conflict mediation offers a significant contribution in the development of knowledge about mediation and facilitates a change of attitude in sorting out conflicts between students. It was also concluded that the OAs are aware of their educational role and have relevant suggestions for improvement.

Responsabilidade ambiental: análise das divulgações ambientais das empresas do PSI-20 comparativamente com empresas não cotadas

Orientador: Mestre, António Pinto Marques

Intelligent decision making in electricity markets: simulated annealing Q-Learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

Mass spectrometry improvement on an high current ion implanter

The development of accurate mass spectrometry, enabling the identification of all the ions extracted from the ion source in a high current implanter is described. The spectrometry system uses two signals (x-y graphic), one proportional to the magnetic field (x-axes), taken from the high-voltage potential with an optic fiber system, and the other proportional to the beam current intensity (y-axes), taken from a beam-stop. The ion beam mass register in a mass spectrum of all the elements magnetically analyzed with the same radius and defined by a pair of analyzing slits as a function of their beam intensity is presented. The developed system uses a PC to control the displaying of the extracted beam mass spectrum, and also recording of all data acquired for posterior analysis. The operator uses a LabView code that enables the interfacing between an I/O board and the ion implanter. The experimental results from an ion implantation experiment are shown. (C) 2011 Elsevier B.V. All rights reserved.

Cooperative scheduling system with emergent swarm based behavior

This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.

Supercritical carbon dioxide extraction of bioactive compounds from microalgae and volatile oils from aromatic plants

A discussion of the most interesting results obtained in our laboratories, during the supercritical CO(2) extraction of bioactive compounds from microalgae and volatile oils from aromatic plants, was carried out. Concerning the microalgae, the studies on Botryococcus braunii and Chlorella vulgaris were selected. Hydrocarbons from the first microalgae, which are mainly linear alkadienes (C(23)-C(31)) with an odd number of carbon atoms, were selectively extracted at 313 K increasing the pressure up to 30.0 MPa. These hydrocarbons are easily extracted at this pressure, since they are located outside the cellular walls. The extraction of carotenoids, mainly canthaxanthin and astaxanthin, from C. vulgaris is more difficult. The extraction yield of these components at 313 K and 35.0 MPa increased with the degree of crushing of the microalga, since they are not extracellular. On the other hand, for the extraction of volatile oils from aromatic plants, studies on Mentha pulegium and Satureja montana L were chosen. For the first aromatic plant, the composition of the volatile and essential oils was similar, the main components being the pulegone and menthone. However, this volatile oil contained small amounts of waxes, which content decreased with decreasing particle size of the plant matrix. For S. montana L it was also observed that both oils have a similar composition, the main components being carvacrol and thymol. The main difference is the relative amount of thymoquinone, which content can be 15 times higher in volatile oil. This oxygenated monoterpene has important biological activities. Moreover, experimental studies on anticholinesterase activity of supercritical extracts of S. montana were also carried out. The supercritical nonvolatile fraction, which presented the highest content of the protocatechuic, vanilic, chlorogenic and (+)-catechin acids, is the most promising inhibitor of the enzyme butyrylcholinesterase. In contrast, the Soxhlet acetone extract did not affect the activity of this enzyme at the concentrations tested. (C) 2011 Elsevier B.V. All rights reserved.

Synthesis and structural characterization of iron complexes with 2,2,2-tris(1-pyrazolyl)ethanol ligands: Application in the peroxidative oxidation of cyclohexane under mild conditions

The reactions of FeCl2 center dot 2H(2)O and 2,2,2-tris(1-pyrazolyl) ethanol HOCH2C(pz)(3) (1) (pz = pyrazolyl) afford [Fe{HOCH2C(pz)(3)}(2)][FeCl4]Cl (2), [Fe{HOCH2C(pz)(3)}(2)](2)[Fe2OCl6](Cl)(2)center dot 4H(2)O (3 center dot 4H(2)O), [Fe{HOCH2C(pz)(3)}(2)] [FeCl{HOCH2C(pz)(3)}(H2O)(2)](2)(Cl)(4) (4) or [Fe{HOCH2C(pz)(3)}(2)]Cl-2 (5), depending on the experimental conditions. Compounds 1-5 were isolated as air-stable crystalline solids and fully characterized, including (1-4) by single-crystal X-ray diffraction analyses. The latter technique revealed strong intermolecular H-bonds involving the OH group of the scorpionate 2 and 3 giving rise to 1D chains which, in 3, are further expanded to a 2D network with intercalated infinite and almost plane chains of H-interacting water molecules. In 4, intermolecular pi center dot center dot center dot pi interactions involving the pyrazolyl rings are relevant. Complexes 2-5 display a high solubility in water (S-25 degrees C ca. 10-12 mg mL(-1)), a favourable feature towards their application as catalysts (or catalyst precursors) for the peroxidative oxidation of cyclo-hexane to cyclohexanol and cyclohexanone, with aqueous H2O2/MeCN, at room temperature (TON values up to ca. 385). (C) 2011 Elsevier B. V. All rights reserved.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

ISEM: a multi-agent system that simulates competitive electronic marketplaces

With the increasing importance of large commerce across the Internet it is becoming increasingly evident that in a few years the Iternet will host a large number of interacting software agents. a vast number of them will be economically motivated, and will negociate a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use all available means to anticipate their collective interactions. This papers addresses this concern by presenting a multi-agent market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, consideting risk preferences. The system includes agents that are capable of increasing their performance with their own experience, by adapting to the market conditions. The results of the negotiations between agents are analysed by data minig algorithms in order to extract rules that give agents feedback to imprive their strategies.

Estudo do meio: os animais no âmbito da Educação Pré-Escolar e do Ensino do 1º Ciclo do Ensino Básico

Mestrado, Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico, 26 de Junho de 2013, Universidade dos Açores (Relatório de Estágio).