Cation transporters/channels in plants: Tools for nutrient biofortification

Cation transporters/channels are key players in a wide range of physiological functions in plants, including cell signaling, osmoregulation, plant nutrition and metal tolerance. The recent identification of genes encoding some of these transport systems has allowed new studies toward further understanding of their integrated roles in plant. This review summarizes recent discoveries regarding the function and regulation of the multiple systems involved in cation transport in plant cells. The role of membrane transport in the uptake, distribution and accumulation of cations in plant tissues, cell types and subcellular compartments is described. We also discuss how the knowledge of inter- and intra-species variation in cation uptake, transport and accumulation as well as the molecular mechanisms responsible for these processes can be used to increase nutrient phytoavailability and nutrients accumulation in the edible tissues of plants. The main trends for future research in the field of biofortification are proposed.

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.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.