Abstract
In this article, an algorithm to identify LPV State Space models is proposed. The LPV State Space system is in the companion reachable canonical form. Both the state matrix and the output vector coefficients are linear combinations of a set of nonlinear basis functions dependent on the scheduling signal. This model structure, although simple, can describe accurately the behaviour of many nonlinear systems by an adequate choice of the scheduling signal. The identification algorithm minimises a quadratic criterion of the output error. Since this error is a linear function of the output vector parameters, a separable nonlinear least squares approach is used to minimise the criterion function by a gradient method. The derivatives required by the algorithm are the states of LPV systems that need to be simulated at every iteration. The effectiveness of the algorithm is assessed by two simulated examples.

Abstract
There is good evidence that naltrexone, an opioid antagonist, has a strong neuroprotective role and may be a potential drug for the treatment of fibromyalgia. In previous work, some of the authors used experimental clinical data to identify input-output linear time invariant models that were used to extract useful information about the effect of this drug on fibromyalgia symptoms. Additional factors such as anxiety, stress, mood, and headache, were considered as additive disturbances. However, it seems reasonable to think that these factors do not affect the drug actuation, but only the way in which a participant perceives how the drug actuates on herself. Under this hypothesis the linear time invariant models can be replaced by State-Space Affine Linear Parameter Varying models where the disturbances are seen as a scheduling signal signal only acting at the parameters of the output equation. In this paper a new algorithm for identifying such a model is proposed. This algorithm minimizes a quadratic criterion of the output error. Since the output error is a linear function of some parameters, the Affine Linear Parameter Varying system identification is formulated as a separable nonlinear least squares problem. Likewise other identification algorithms using gradient optimization methods several parameter derivatives are dynamical systems that must be simulated. In order to increase time efficiency a canonical parametrization that minimizes the number of systems to be simulated is chosen. The effectiveness of the algorithm is assessed in a case study where an Affine Parameter Varying Model is identified from the experimental data used in the previous study and compared with the time-invariant model.

Abstract
An indirect downsampling approach for continuous-time input/output system identification is proposed. This modus operandi was introduced to system identification through a sub-space algorithm, where the input/output data set is partitioned into lower rate m subsets. Then, a state-space discrete-time model is identified by fusing the data subsets into a single one. In the present work the identification of the input/output downsampled model is performed by a least squares and a simplified refined instrumental variables (IV) procedures. In this approach, the inter-sample behaviour is preserved by the addition of fictitious inputs, leading to an increase of excitation requirements of the input signal. This over requirement is removed by directly estimating from the data the parameters of the transfer function numerator. The performance of the method is illustrated using the Rao-Garnier test system.

Abstract
Student knowledge of Nature of Science (NOS) is an important and critical issue to their understanding of science, as well as to the development of scientific literacy. In the same way, the ability to use and generate models is central to scientific literacy and to the learning of science. Having this in mind, and recognizing that teachers' views and practices strongly influence students' learning, we intended to evaluate Portuguese prospective science teachers' (PPST) views of Nature of Science (NOS), models and earth structure models. A questionnaire, focused on those aspects, was applied to 19 prospective science teachers at the University of Porto. In general, the majority of the participants revealed correct perceptions about those issues. However, some inconsistences and alternative conceptions were found.

Abstract
Results of self-potential, seismic reflection and refraction, Infrared spectroscopy, ion chromatography and IR thermography survey performed over a Portuguese artistic tomb made of a porous limestone are presented. The tomb presents nowadays severe decay phenomena. The decay products associated to the decay patterns observed are mainly related with the presence of salts, namely nitrates and secondarily of chlorides. The self-potential and the thermography survey allowed verifying that moisture degrees change in different side walls of the tomb. The seismic methods showed there is no clear interface between undamaged and damaged stone material where the limestone is soft and the strength is slightly lower in the most humid zones.

Abstract
The result obtained from the investigation of Shear Waves Velocity (Vs) using Multichannel Analysis of Surface Waves for the geothecnical purposes in five study area of Aveiro gave an estimated Vs30 to develop the microzonation studies in this area. Copyright