This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

In the past decades, flow-like catastrophic landslides caused many victims and important economic damage around the world. It is therefore important to predict their path, velocity and depth in order to provide adequate mitigation and protection measures. This paper presents a model that incorporates coupling between pore pressures and the solid skeleton inside the avalanching mass. A depth-integrated, coupled, mathematical model is derived from the velocity–pressure version of the Biot–Zienkiewicz model, which\ud is used in soil dynamics. The equations are complemented with simple rheological equations describing soil behaviour and are discretized using the SPH method. The accuracy of the model is assessed using a series of benchmarks, and then it is applied to back-analyse the propagation stage of some catastrophic flow-like slope movements for which field data are available

The growth of a cultivated typical brain tumor is studied in this work. The tumor is analyzed both dynamically and morphologically. We have measured its fractal dimension to be d f 1.21 6 0.05. From its dynamical behavior we determine the scaling critical exponents of this circular symmetry system which are compatible with the linear molecular beam epitaxy universality class. A very important feature of tumor profiles is that they are super-rough, which constitutes the first (1 1 1)-dimensional experiment in literature with super-roughness. The results obtained from the dynamics study make manifest two very surprising features of tumor growth: Its dynamics is mainly due to contour cells and the tendency of an interface cell to duplicate is a function of the local curvature.[ S0031-9007(98)

A common working procedure in Ecology is to identify patterns and elaborate hypotheses about the processes that may be responsible for their occurrence (Levin, 1992). One approach to identifying and characterizing patterns in community and network ecology is through the calculation of nestedness (Bascompte et al., 2003). Nestedness is a measure of a particular type of pattern in an ecological system, referring to the order that emanates from the way elements of a particular set are linked to elements of a second set. These links may relate, for instance, to the interactions that are established between two sets of species in an ecosystem (e.g., plant-pollinator interactions, Bascompte et al., 2003), or to the occurrence of a set of species in a given set of habitat fragments of different sizes (Atmar and Patterson, 1993). Thus, in the latter case, species assemblages are nested if the species present in species-poor sites are proper subsets of the assemblages found in species-rich sites (Patterson and Atmar, 1986), and perfect nestedness occurs when all species-poor sites are proper subsets of the assemblages found in richerspecies sites (Almeida-Neto et al., 2007). It should be noted, though, that absence of nestedness does not always mean absence of pattern. Several other types of patterns, such as gradients and compartments, may also be found in ecological systems (Leibold and Mikkelson, 2002;Lewinsohn et al., 2006;Almeida-Neto et al., 2007). Nestedness can be assessed through an ordered binary presence-absence

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