Abstract
Oogenesis of the freshwater mussel Anodonta cygnea was investigated through histological examination over a 12-month period. All specimens were hermaphrodites, having gonads made up of numerous separate female and male acini. Female acini included oogonia with oocytes at different stages of development. Immature oocytes were attached to the acinar wall by a stalk, while mature oocytes were free within the acinus lumen. Several male and female acini were connected to a single germinal duct filled with mature germ cells. A maturity gradation scale was developed;which incorporated the characteristics of the acini, germinal epithelium, lumen and connective tissue. Although oogenesis seems to occur throughout the year, this scale has shown that oogenesis peaks during the summer months.

Abstract
Many Unionoida are considered to be extinct, endangered, or of special concern. These bivalves have complex life cycle stages that limit successful culture. In nature, the larvae (glochidia) of these bivalves must successfully parasitize a host (mainly fish) in order to metamorphose into juveniles. The two artificial methods used to obtain juvenile freshwater mussels in laboratory are either by induced attachment to host fish or by in vitro culture of glochidia. This article is focused on the in vitro method that represents a novel and alternative process to fish infestation, offering the ability to obtain larger numbers of juveniles without the need for host fishes and reducing the overall costs of propagation. In vitro culture requires a medium which fulfills the nutritional needs of each glochidia species and avoids microbial contamination. Recently, this methodology has presented excellent results with survival and transformation rates up to 94% using host fish plasma. High efficiencies on growth, and survival rates (84%) of juvenile freshwater bivalve Hyriopsis myersiana (Lea, 1856) up to 120 days were obtained when reared in adequate recirculating aquacultural systems using a very specific diet. More research is still needed to demonstrate successful propagation, mainly concerning the media nutritional composition to increase glochidia transformation and juvenile quality.

Abstract
This paper is concerned with the effect of sediment accumulation on shore platform development. Boulder accumulations are common on the granitic shore platforms of Galicia, northwestern Spain. Boulders are produced by erosion of shore platforms and of cliffs consisting of cold-climate deposits from the last glacial period. Measurements were made of the long axis length of more than 800 boulders, and additionally of the short and intermediate axes of 340 of these boulders, as well as of their orientation and gradient. There were two study areas. The boulders on the Barbanza Peninsula are generally a little smaller than those in southern Galicia with, respectively; mean long axis lengths of 0.98 and 1.14, and masses of 1.06 and 1.59 t. There are also some isolated, very coarse boulders and megaclasts in southern Galicia. The distribution and extent of the deposits and boulder imbrication and orientation testify to the high levels of wave energy produced by northwesterly and westerly storms in this region. Although the boulders, as well as the underlying shore platforms, were inherited, in part, from previous interglacial stages, some boulder detachment and movement is occurring today during storms, when significant deep water wave heights exceed 8 to 10 m. Despite some abrasion of the shore platforms, the primary effect of large boulder accumulations is protective. The role of sediment on shore platforms has been neglected, but this study suggests that because of arrested development under thick accumulations, platform gradient in areas with abundant sediment increases with the grain size of the material. The occurrence and type of sediment on shore platforms may therefore help to explain the distribution of sloping and subhorizontal platforms under different morphogenic and geological conditions.

Abstract
We address the identification of discrete-time linear parameter varying systems in the state-space form with affine parameter dependence. In previous work, some of the authors have addressed this problem and an iterative algorithm that avoids the curse of dimensionality, inherent to this class of problems, was developed for the identification of multiple input multiple output systems. Although convergence of this algorithm has been assured for white noise sequences, it has also converged for other type of scheduling signals. Never less, its application is still not generalized to every class of scheduling parameters. In this paper, the algorithm is modified in order to identify multiple input single output systems with quasi-stationary scheduling signals. In every iteration, the system is modeled as a linear time invariant system driven by an extended input composed by the measured input, the Kronecker product between this signal and the scheduling parameter and the Kronecker product between the scheduling and the state estimated at the previous iteration. The remaining unknown signals are considered as "noise". Furthermore, the system is decomposed into a "deterministic" system driven by the known inputs and a "stochastic" subsystem driven by noise. The system is identified as a high order autoregressive exogeneous model. In order to whiten the noise, the input/output data is filtered by the inverse noise transfer function and a state-space model is estimated for the "deterministic" subsystem. Then, the output simulated by this system is subtracted from the measurements to obtain the output stochastic component. Finally, the state of the system is estimated using a Kalman filter and a deconvolution technique. Then, the state becomes an entry to the system for the next iteration, after being multiplied by the scheduling parameter. The whole process is repeated until convergence. The algorithm is tested using periodic scheduling signals and compared with other approaches developed by the same authors. © 2012 IFAC.

Abstract
This paper addresses the detection and classification of low amplitude signals within the QRS complex of the signal-averaged electrocardiogram. Linear and bilinear Kalman filter models are fitted using the subspace system identification family of algorithms. If the residuals from the models are a white noise process, then anything that cannot be modeled with the state-space models will show up in the residuals as low amplitude signal + noise. Diagnostic tests and analysis on the residuals will then lead to detection and classification of abnormalities in the intra-QRS complex. The end result is a diagnostic tool to aid the physician. © 2012 IFAC.

Abstract
In this paper the Wiener-Hammerstein Benchmark is identified as a bilinear discrete system. The bilinear approximation relies on both facts that the Wiener-Hammerstein system can be described by a Volterra series which can be approximated by bilinear systems. The identification is performed with an iterative bilinear subspace identification algorithm previously proposed by the authors. In order to increase accuracy, polynomial static nonlinearities were added to the bilinear model input. These Hammerstein type bilinear models are then identified using the same iterative subspace identification algorithm.