Abstract
Selenastrum, Chlorella and the Cyanophyta groups, important components of the phytoplankton in the natural habitat of Anodonta cygnea in Mira Lagoon, were used separately as experimental diet for Anodonta cygnea. To assess the effects of the different diets, several organic and inorganic compounds of the haemolymph and extrapallial fluid were measured. Protein content was significantly reduced with experimental Non Feed, and carbohydrate content with Non Feed, Selenastrum, Chlorella, and Cyanophyta diets compared to the control in the lagoon. Lipid contents in body fluids were similar among the different diet groups, with the exception of the Chlorella diet, which showed a higher value. In all diets, the inorganic elements, magnesium and chloride, presented a non-significant variation profile. The concentration of sodium and potassium was significantly affected in Selenastrum and Chlorella diets, observing in the Non Feed diet a minimum value for potassium. The non-significant variation of osmolality suggests the presence of a specific osmotic regulatory mechanism independent of the diet. A particular regulation mechanism seems to exist for both calcium and manganese ion inducing similar profiles for all experimental diets with higher contents in Selenastrum and Cyanophyta diets, respectively. The higher calcium ion concentration appears associated with lower protein-carbohydrate contents, probably due to weak calcium aggregation and deposition mechanism, except for the control and Mixture diets. In general, the concentrations of organic and inorganic compounds in the body fluids of Mixture-fed A. cygnea, were more similar to those found in the control diet group. This suggests that an equal mixture of the three algae, Selenastrum, Chlorella, and Cyanophyta, is more appropriate diet to provide the necessary nutrients for a normal maintenance of A. cygnea in the wild.

Abstract
In this paper we provide a different way to estimate matrices B and D, in subspace identification algorithms. The starting point was the method proposed by Van Overschee and De Moor [10] - the only one applying subspace ideas to the estimation of those matrices. We have derived new (and simpler) expressions and we found that the method proposed by Van Overschee and De Moor [10] can be rewritten as a weighted least squares problem, involving the future outputs and inputs.

Abstract
In this paper, two approaches, for the estimation of matrices A and C in CV A-type subspace identification algorithms are compared and the differences between the two obtained estimates are analysed. One of the methods, "least squares" based, was proposed in the original CVA algorithm. The other method, inspired in the techniques of the classical Realization Theory and proposed by Verhaegen, is far more efficient. Therefore, although the two methods produce two different estimates, a replacement is proposed and an expression for correction of the estimates is obtained, in order to reduce the loss of accuracy.

Abstract
In this paper, a recursive algorithm is presented, based on the CVA subspace identification algorithm. The main idea was to explore the relations between the orthogonal and oblique projections involved and to provide simpler expressions that allowed a recursive version of the algorithm - guaranteeing most of the advantages of this kind of methods, and still improving the numerical efficiency.

Abstract
In this paper, a new approach to estimate matrices B and D, in subspace methods, is provided. The starting point was one method proposed by Van Overschee and De Moor (1996). We have derived new (and simpler) expressions and we found that the original method can be rewritten as a weighted least squares problem, involving the future outputs and inputs and the observability matrix.

Abstract
In this paper we present two subspace identification methods implemented through sequences of modified Householder algorithm. The main idea was to show that subspace identification methods can be represented as sequences of least squares problems and implemented wing QR factorizations. Therefore, it is possible to develop iterative algorithms with most of the advantages of this kind of methods, and still improve the numerical efficiency, in order to deal with real-tme applications and minimize the computational burden.