Abstract
Long-term continuous in-situ radon field monitoring was carried out in the southern region of Israel, at the Amram Mountain research tunnel in Elat and in shallow boreholes in the Gevanim valley in Makhtesh Ramon. This work shows that long-term radon monitoring based on simultaneous alpha and gamma measurement enables to differentiate between the impact of ambient temperature and pressure on radon transportation within porous media both in sites isolated from outer meteorological influence as in the Amram tunnel and in sites open to the influence of environmental conditions as in the Gevanim boreholes array. It was found that if the monitoring site is a closed measuring space with undisturbed environmental conditions, the radon in the air space will reach equilibrium with the radon in the rock. Then the radon time series as measured by both gamma and alpha detectors exhibit the same temporal variations. The results in this case indicate that the diurnal, intra-seasonal and seasonal variations in the radon concentration are clearly associated with the ambient temperature gradient outside the rock air interface, 100 m above the tunnel. In shallow, open boreholes, no equilibrium between the radon within the porous media and the radon in the open borehole air is necessarily established and the results of radon monitoring are different. Gamma detectors that measure the changes in radon concentrations in the porous rock indicated a clear correlation between radon concentrations and the daily variations of external surface temperature, from about 1 m up to 85 m. Yet the alpha detectors that measure the changes in radon concentrations in very shallow borehole air (about 1 m) reveal a clear anti-correlation with atmospheric pressure waves at semi-daily, daily, and intra-seasonal time scales. At depths of several tens of meters, outer pressure waves induce anti-correlated radon variations lasting the same time, but destroy the ordered radon daily periodicity in the measuring air space, although almost not disturbing the daily radon variation within the surrounding porous media.

Abstract
Echinoderm Mutable Collagenous Tissues (MCTs) undergo nervously mediated, drastic and reversible changes in their passive mechanical properties. MCT mutability is involved in autotomy, posture maintenance and motility, and, as a consequence, it influences all aspects of echinoderm biology (nutrition, reproduction, habitat selection, self-defense and predatory behavior) representing a key-factor for the ecological success of the phylum. Besides this, MCT performance represents a topic of remarkable interest for many different applied fields. A biomimetic research route looks at MCTs as a source of inspiration for the development of smart and innovative biomaterials with great potential for in vitro and in vivo applications when controlled and reversible plasticization and/or stiffening of the extracellular matrix is required. The MIMESIS (Marine Invertebrate Models & Engineered Substrates for Innovative bio-Scaffolds) project has been developed within this scientific context. The selected echinoderm model is the common sea urchin Paracentrotus lividus. This project is based on a multidisciplinary approach combining functional biology with biomaterial engineering. A brief review of recent morphological, biomolecular, biomechanical and biochemical results on P lividus MCTs are here presented in a biotechnological perspective, taking into account also a promising application regarding the use of MCT-derived substrata for cell culture studies.

Abstract
This study was concerned with shoreline change and cliff recession. Galicia (north-west Spain) comprises a very energetic and diversified coast. The study focused on the analysis of the coastal dynamics and the spatio-temporal changes of coastal morphology for the years 1956, 2003, 2006 and 2008, using the digital shoreline analysis system (DSAS) extension. Estimation of the rates of erosion and accretion along the pilot site (Fisterra/Finisterre area) was performed. In addition, a continuous coastline along Galicia was integrated into a geographical information system project which comprises an interactive database with key information. A coastal susceptibility map (erosion/accretion) was created based on the DSAS results for the short-term approach and cross-checked with knowledge of the area in terms of geology, geomorphology and landslide occurrences. Aspects related to the engineering solutions, land-use planning or environmental management were considered in the recommended strategy, as well as the impact and disturbance severity analysis for each action used. This research was developed to provide useful information about the Galicia territory and to give reliable data for the coastal management plan supported by the council. Such plan addresses some changes to the coastal policy and encourages future issues.

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.