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In this paper a macroscopic model of tumor cord growth is developed, relying on the mathematical theory of deformable porous media. Tumor is modeled as a saturated mixture of proliferating cells, extracellular fluid and extracellular matrix, that occupies a spatial region close to a blood vessel whence cells get the nutrient needed for their vital functions. Growth of tumor cells takes place within a healthy host tissue, which is in turn modeled as a saturated mixture of non-proliferating cells. Interactions between these two regions are accounted for as an essential mechanism for the growth of the tumor mass. By weakening the role of the extracellular matrix, which is regarded as a rigid non-remodeling scaffold, a system of two partial differential equations is derived, describing the evolution of the cell volume ratio coupled to the dynamics of the nutrient, whose higher and lower concentration levels determine proliferation or death of tumor cells, respectively. Numerical simulations of a reference two-dimensional problem are shown and commented, and a qualitative mathematical analysis of some of its key issues is proposed. © American Institute of Mathematical Sciences.

Viene qui presentata una metodologia d'approccio basata sull'uso di dati di tipo Shuttle Radar Topography Mission (SRTM) nella risoluzione di problemi legati all'evoluzione geomorfologica di aree di catena ad elevata mobilità tettonica quaternaria. L'ampia area campione prescelta per tale scopo è rappresentata dal bacino intermontano di Auletta, una depressione tettonica bordata da scarpate di linea di faglia a sviluppo decakilometrico e andamento N120-130°, colmata da sedimenti marino-transizionali e continentali di età compresa tra il Pliocene medio ed il Pleistocene medio. Le informazioni estratte dai dati topografici SRTM (elevazione, slope e aspect) sono state utilizzate, unitamente ai dati dell'analisi morfostrutturale tradizionale, per la comprensione dell'evoluzione del rilievo e per definire in tal senso il ruolo delle grandi strutture perimetrali. L'elaborazione dei dati ha inoltre facilitato il calcolo del tasso di erosione sul medio-lungo termine, grazie alla diffusa presenza di marker del sollevamento quaternario come le superfici erosionali sospese.

Recent results from the WAGRIT project (Web for AGRIculture and environmenT), funded by the Italian Space Agency, have seen the development of algorithms for the classification and segmentation of remotely sensed images. The goal is to provide a client-server Internet application for agricultural monitoring of cultivated areas, exploiting remotely sensed high spectral resolution images.

In this paper we will focus on knowledge dissemination and training on Numerical Grid Generation (NGG) and Computational Field Simulation (CFS) carried out by classroom and online combined strategies. We update presentation of activities and events of the European Atelier for Engineering and Computational Sciences, EUA4X, a three year project (2005-2007) financed by the European Union Marie Curie Conferences and Training Courses (Contract\# MSCF-CT-2004-013336). We illustrate the integrated training approach and its scientific contents, we describe the organizational steps of courses and conference type events and we present advances of the web environments designed at IAC to allow permanent online Atelier activities.

Design/methodology/approach - The method relies on alternation of identification of the active genes using a mixture model and clustering of the samples based on Ward hierarchical clustering. The initial-point of the procedure is obtained by means of a ?2 test. The method attempts to locally minimize the sum of the within cluster sample variances under a suitable Gaussian assumption on the distribution of data. Findings - This paper illustrates the proposed methodology and its success by means of results from both simulated and real cDNA microarray data. The comparison of the results with those from a related known method demonstrates the superiority of the proposed approach. Research limitations/implications - Only empirical evidence of algorithm convergence is provided. Theoretical proof of algorithm convergence is an open issue. Practical implications - The proposed methodology can be applied to perform cDNA microarray data analysis. Originality/value - This paper provides a contribution to the development of successful statistical methods for cDNA microarray data analysis.

The paper addresses the calculation of the value at risk (VaR) of the mathematical provision applied in a fair valuation context. Following a balance-sheet approach, the classical definition of VaR needs some clarifications. For identifying worst cases it is opportune to observe that an increase in the value of the liability corresponds to expenses or, better, additional costs, which may result in either a profit shrinkage or a proper loss. Therefore, the classical portfolio return distribution can be redesigned as a liability cost distribution, where critical values lie in the right-hand tail. In the case of the mathematical provision, the expected cost can be easily linked to the expected value of the reserve at the end of the risk horizon. After an overall view on the VaR problems from a managerial perspective, the paper presents, the choice of the VaR model and the number of risk factors to take into account, in addition to describing the calculation technique. The calculation, performed using a simulation approach, is developed as an application case of a life annuity portfolio and provides an estimate of the worst-case loss at a fixed confidence level after a fixed period of time.