Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

ß-lactamases in the biochemistry and molecular biology laboratory

β-lactamases are hydrolytic enzymes that inactivate the β-lactam ring of antibiotics such as penicillins and cephalosporins. The major diversity of studies carried out until now have mainly focused on the characterization of β-lactamases recovered among clinical isolates of Gram-positive staphylococci and Gram-negative enterobacteria, amongst others. However, only some studies refer to the detection and development of β-lactamases carriers in healthy humans, sick animals, or even in strains isolated from environmental stocks such as food, water, or soils. Considering this, we proposed a 10-week laboratory programme for the Biochemistry and Molecular Biology laboratory for majors in the health, environmental, and agronomical sciences. During those weeks, students would be dealing with some basic techniques such as DNA extraction, bacterial transformation, polymerase chain reaction (PCR), gel electrophoresis, and the use of several bioinformatics tools. These laboratory exercises would be conducted as a mini research project in which all the classes would be connected with the previous ones. This curriculum was compared in an experiment involving two groups of students from two different majors. The new curriculum, with classes linked together as a mini research project, was taught to a major in Pharmacy and an old curriculum was taught to students from environmental health. The results showed that students who were enrolled in the new curriculum obtained better results in the final exam than the students who were enrolled in the former curriculum. Likewise, these students were found to be more enthusiastic during the laboratory classes than those from the former curriculum.

Computational analysis of quinoxalines N,N-Dioxide and ITS Derivates

A quinoxalina e seus derivativos são uma importante classe de compostos heterocíclicos, onde os elementos N, S e O substituem átomos de carbono no anel. A fórmula molecular da quinoxalina é C8H6N2, formada por dois anéis aromáticos, benzeno e pirazina. É rara em estado natural, mas a sua síntese é de fácil execução. Modificações na estrutura da quinoxalina proporcionam uma grande variedade de compostos e actividades, tais como actividades antimicrobiana, antiparasitária, antidiabética, antiproliferativa, anti-inflamatória, anticancerígena, antiglaucoma, antidepressiva apresentando antagonismo do receptor AMPA. Estes compostos também são importantes no campo industrial devido, por exemplo, ao seu poder na inibição da corrosão do metal. A química computacional, ramo natural da química teórica é um método bem desenvolvido, utilizado para representar estruturas moleculares, simulando o seu comportamento com as equações da física quântica e clássica. Existe no mercado uma grande variedade de ferramentas informaticas utilizadas na química computacional, que permitem o cálculo de energias, geometrias, frequências vibracionais, estados de transição, vias de reação, estados excitados e uma variedade de propriedades baseadas em várias funções de onda não correlacionadas e correlacionadas. Nesta medida, a sua aplicação ao estudo das quinoxalinas é importante para a determinação das suas características químicas, permitindo uma análise mais completa, em menos tempo, e com menos custos.

Application of computational intelligence to engineering

Computational Intelligence (CI) includes four main areas: Evolutionary Computation (genetic algorithms and genetic programming), Swarm Intelligence, Fuzzy Systems and Neural Networks. This article shows how CI techniques overpass the strict limits of Artificial Intelligence field and can help solving real problems from distinct engineering areas: Mechanical, Computer Science and Electrical Engineering.

S100A6 Amyloid Fibril Formation Is Calcium-modulated and Enhances Superoxide Dismutase-1 (SOD1) Aggregation

S100A6 is a small EF-hand calcium- and zinc-binding protein involved in the regulation of cell proliferation and cytoskeletal dynamics. It is overexpressed in neurodegenerative disorders and a proposed marker for Amyotrophic Lateral Sclerosis (ALS). Following recent reports of amyloid formation by S100 proteins, we investigated the aggregation properties of S100A6. Computational analysis using aggregation predictors Waltz and Zyggregator revealed increased propensity within S100A6 helices HI and HIV. Subsequent analysis of Thioflavin-T binding kinetics under acidic conditions elicited a very fast process with no lag phase and extensive formation of aggregates and stacked fibrils as observed by electron microscopy. Ca2+ exerted an inhibitory effect on the aggregation kinetics, which could be reverted upon chelation. An FT-IR investigation of the early conformational changes occurring under these conditions showed that Ca2+ promotes anti-parallel β-sheet conformations that repress fibrillation. At pH 7, Ca2+ rendered the fibril formation kinetics slower: time-resolved imaging showed that fibril formation is highly suppressed, with aggregates forming instead. In the absence of metals an extensive network of fibrils is formed. S100A6 oligomers, but not fibrils, were found to be cytotoxic, decreasing cell viability by up to 40%. This effect was not observed when the aggregates were formed in the presence of Ca2+. Interestingly, native S1006 seeds SOD1 aggregation, shortening its nucleation process. This suggests a cross-talk between these two proteins involved in ALS. Overall, these results put forward novel roles for S100 proteins, whose metal-modulated aggregation propensity may be a key aspect in their physiology and function.