POTASSIUM ABSORPTION AND PARTITIONING IN COTTON AS AFFECTED BY PERIODS OF POTASSIUM-DEFICIENCY

Cotton (Gossypium hirsutum var. Latifolium) was grown in nutrient media, at two K levels: 58.5 mg/K and 11.7 mg/K. Potassium deficiency (11.7 mg K/g of K) was imposed upon cotton plants at different stages of plant development. A sequence of increasing sensitivity to K deficiency among cotton plant parts was observed: leaves < bolls < roots < stems. When K deficiency symptoms are clearly visible in the leaves, all the other plant parts are already affected. Bolls are a very important component in K partitioning within the cotton plant, but K is required most by the bur itself and is not translocated to seeds or fibers. Cotton could overcome a 30 day deficiency late in the season without significant losses in lint and seed cotton yields.

Constructive heuristic algorithm in branch-and-bound structure applied to transmission network expansion planning

A constructive heuristic algorithm to solve the transmission system expansion planning problem is proposed with the aim of circumventing some critical problems of classical heuristic algorithms that employ relaxed mathematical models to calculate a sensitivity index that guides the circuit additions. The proposed heuristic algorithm is in a branch-and-bound algorithm structure, which can be used with any planning model, such as Transportation model, DC model, AC model or Hybrid models. Tests of the proposed algorithm are presented on real Brazilian systems.

Modified Chebyshev algorithm: some applications

Two applications of the modified Chebyshev algorithm are considered. The first application deals with the generation of orthogonal polynomials associated with a weight function having singularities on or near the end points of the interval of orthogonality. The other application involves the generation of real Szego polynomials.

Branch and bound algorithm for transmission system expansion planning using a transportation model

A method for optimal transmission network expansion planning is presented. The transmission network is modelled as a transportation network. The problem is solved using hierarchical Benders decomposition in which the problem is decomposed into master and slave subproblems. The master subproblem models the investment decisions and is solved using a branch-and-bound algorithm. The slave subproblem models the network operation and is solved using a specialised linear program. Several alternative implementations of the branch-and-bound algorithm have been rested. Special characteristics of the transmission expansion problem have been taken into consideration in these implementations. The methods have been tested on various test systems available in the literature.

Specialised branch-and-bound algorithm for transmission network expansion planning

An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

Partitioning of the glucoamylase activity at the cell surfaces in cultures of Saccharomyces

Glucoamylases have been used with alpha-amylases for the industrial conversion of starch into glucose. However, little is known about the properties of this glycosylated protein retained in the cell wall of Saccharomyces as well as its role in the saccharification and fermentation of amylaceous substrates, notably in high cell density processes. In most of the strains assayed, decreases in biomass formation were followed by increases in glucoamylase secretion (expressed as U/mg(biomass) in 1 ml of culture) when glucose was exchanged for starch as carbon source or the growth temperature was raised from 30 to 35 degrees C. Despite the losses in viability, significant increases in the activity of the wall fraction occurred when cultures of thermotolerant yeasts propagated at 30 degrees C or washed cells resuspended in buffer solution were heated to 60 degrees C for 60-80 min prior to amylolytic assays. Thus, intact cells of thermotolerant yeasts can be used as colloidal biocatalysts in starch degradation processes. (C) 2005 Published by Elsevier Ltd.

Efficient linear programming algorithm for the transmission network expansion planning problem

The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.

Food resources partitioning among sciaenid fishes (Perciformes, Sciaenidae) of the Flamengo bay, Ubatuba, southeastern Brazil

The determination of the diet and feeding habits is one of the principal aspects of the study on fish biology, as feeding is a basic process and its study is necessary for the understanding of the populations' dynamic and ecology. The Sciaenidae family has a significant occurrence in the bay's demersal ichthyofauna, constituting an important fishing resource. The goal of this work was to analyze how the partitioning of available food resources takes place among the ten sciaenid species which live in the Flamengo Bay. One single survey, consisting of three trawls, was carried out with a fishing boat equipped with two otter-trawl. Diet analysis showed that all species are exclusively carnivore, using several items as food, but crustaceans are the main food ingested. The use of the ''Proportional Overlap Index'' showed possible overlapping between six couples of species but in the majority of cases, morphologic differences between these species, such as the mouth position, probably determine different foraging strategies.

An alternative approach to solve convergence problems in the backpropagation algorithm

The multilayer perceptron network has become one of the most used in the solution of a wide variety of problems. The training process is based on the supervised method where the inputs are presented to the neural network and the output is compared with a desired value. However, the algorithm presents convergence problems when the desired output of the network has small slope in the discrete time samples or the output is a quasi-constant value. The proposal of this paper is presenting an alternative approach to solve this convergence problem with a pre-conditioning method of the desired output data set before the training process and a post-conditioning when the generalization results are obtained. Simulations results are presented in order to validate the proposed approach.

Magnesium levels in nutrient solution and common bean (Phaseolus vulgaris L cv Carioca) development. Evaluation of the growth relations and assimilate partitioning

The effect of magnesium levels in nutrient solution upon relation between shoot and root, leaf weight ratio and assimilate partitioning of common bean (Phaseolus vulgaris L. cv Carioca) was studied. Bean plants (3 per pot) were grown in 6 l pots containing Hoagland & Arnon n. 2 solution modified to obtain 2.4, 24.3, 48.6, 72.9 and 97.2 ppm of magnesium. The experimental design was a completely randomized factorial replicated 3 times with 5 levels of magnesium and 5 samplings wich were done forthnightly. Therefore, it may be suggested that the 48.6 ppm of magnesium level proposed by Hoagland & Amen (1950) is the best choice for the common bean, according to the conditions of this experiment. Magnesium concentrations over 48.6 ppm didn't show significant alterations of the evaluated parameters. Nutrient solution with 2.4 ppm of magnesium content provides higher efficiency to the common bean plants during almost all its cycle, except the final of the reproductive phase. These results suggest that magnesium concentration increased to 48.6 ppm, in the cycle final perhaps could increase the productivity.

Tabu search algorithm for network synthesis

Large scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically the same investment, but with substantially different structures (configurations obtained with different sets of circuit/transformer additions). The proposed parallel tabu search algorithm has shown to be effective in exploring this type of optimization landscape. The algorithm is a third generation tabu search procedure with several advanced features. This is the most comprehensive combinatorial optimization technique available for treating difficult problems such as the transmission expansion planning. The method includes features of a variety of other approaches such as heuristic search, simulated annealing and genetic algorithms. In all test cases studied there are new generation, load sites which can be connected to an existing main network: such connections may require more than one line, transformer addition, which makes the problem harder in the sense that more combinations have to be considered.

A modified ant colony optimization algorithm modeled on tabu-search methods

An earlier model underlying the foraging strategy of a pachycodyla apicalis ant is modified. The proposed algorithm incorporates key features of the tabu-search method in the development of a relatively simple but robust global ant colony optimization algorithm. Numerical results are reported to validate and demonstrate the feasibility and effectiveness of the proposed algorithm in solving electromagnetic (EM) design problems.