About 50 % of the glaciated area outside the large ice sheets is located in the Arctic, and they contribute about 30 % to the runoff. IPCC predicts that the largest contribution to global sea level rise will stem from glaciers and ice caps. However, the uncertainties are large, up to 50%. Present estimates of mass balance of Svalbard glaciers are scarce and vary from close to balance to significantly negative. The dynamic response of the glaciers varies on the different glacier types: 1) Ice caps 2) tidewater glaciers and 3) glaciers ending on land. We are interested in estimating how changes in climate can affect the future mass balance of Svalbard glaciers and, consequently, the contribution to sea-level rise. This will be accomplished through modelling of ice flow, including calving fluxes, supported by field data. The proposed modelling work also includes Regional Climate modelling providing surface mass balance estimates for the whole of Svalbard, surface mass balance modelling for targeted glaciers and sensitivity analysis by different approaches using degree-day and energy balance models as well as couplings to atmosphere, hydrology and dynamics. A warmer climate may change both surface processes (snow accumulation, internal refreezing, superimposed ice and ablation) and dynamics. Predictions of future mass balance and dynamic response require boundary information about the thermal structure of the ice, the present and past surface mass balance, meteorological data/atmospheric field studies (AWS), surface and bed topography and current flow. These points will be the main focus for the field and remote sensing investigations. Remote sensing data is the only way to get enough spatial data, but must be validated by field data. We propose to address the above questions in a set of complementary field, remote sensing and modelling programs.

We present a comparison of three methods for the solution of the magnetoencephalography inverse problem. The methods are: a linearly constrained minimum variance beamformer, an algorithm implementing multiple signal classification with recursively applied projection and a particle filter for Bayesian tracking. Synthetic data with neurophysiological significance are analyzed by the three methods to recover position, orientation and amplitude of the active sources. Finally, a real data set evoked by a simple auditory stimulus is considered.

IL TALENTO MATEMATICO DI MAURO PICONE Nella puntata n. 33 in onda mercoledì 28 aprile 2010 Per "STORIA DELL'INFORMATICA ITALIANA" "L'artigliere e l'istituto di calcolo" L' Istituto per le Applicazioni del Calcolo, nato a Napoli nel 1927 e in seguito, per volontà di Marconi, trasferito a Roma, si prefiggeva l'obbiettivo di riunire un insieme di macchine di calcolo e di persone, capaci di utilizzarle al meglio, anche per svilupparne di nuove, al servizio della ricerca scientifica. Un'idea apparentemente semplice, ma in realtà assolutamente innovativa. Alla sua nascita infatti, l'Istituto di Calcolo italiano è il primo istituto di calcolo al mondo! Dietro quest'idea, una delle figure più significative della storia del calcolo e dell'informatica italiana: Mauro Picone.

We present a multiphase mathematical model for tumor growth which incorporates the remodeling of the extracellular matrix and describes the formation of fibrotic tissue by tumor cells. We also detail a full qualitative analysis of the spatially homogeneous problem, and study the equilibria of the system in order to characterize the conditions under which fibrosis may occur. © 2010 Elsevier Ltd.

Here we discuss the biological high-throughput data dilemma: how to integrate replicated experiments and nearby species data? Should we consider each species as a monadic source of data when replicated experiments are available or, viceversa, should we try to collect information from the large number of nearby species analyzed in the different laboratories? In this paper we make and justify the observation that experimental replicates and phylogenetic data may be combined to strength the evidences on identifying transcriptional motifs and identify networks, which seems to be quite difficult using other currently used methods. In particular we discuss the use of phylogenetic inference and the potentiality of the Bayesian variable selection procedure in data integration. In order to illustrate the proposed approach we present a case study considering sequences and microarray data from fungi species. We also focus on the interpretation of the results with respect to the problem of experimental and biological noise.

Clustering is one of the most important unsupervised learning problems and it deals with finding a structure in a collection of unlabeled data; however, different clustering algorithms applied to the same data-set produce different solutions. In many applications the problem of multiple solutions becomes crucial and providing a limited group of good clusterings is often more desirable than a single solution. In this work we propose the Least Square Consensus clustering that allows a user to extrapolate a small number of different clustering solutions from an initial (large) set of solutions obtained by applying any clustering algorithm to a given data-set. Two different implementations are presented. In both cases, each consensus is accomplished with a measure of quality defined in terms of Least Square error and a graphical visualization is provided in order to make immediately interpretable the result. Numerical experiments are carried out on both synthetic and real data-sets.

Analisi storica degli strumenti di calcolo utilizzati presso l'allora Istituto Nazionale per le Applicazioni del Calcolo prima dell'acquisto del calcolatore elettronico FINAC

Riassunto delle scarsissime informazioni disponibili sulla produzione italiana in questo settore, affine a quello delle macchine calcolatrici, e soprattutto sui brevetti depositati in Italia ed all'estero da inventori italiani.

A mathematical model of the galvanic iron corrosion is, here, presented. The iron(III)-hydroxide formation is considered together with the redox reaction. The PDE system, assembled on the basis of the fundamental holding electro-chemistry laws, is numerically solved by a locally refined FD method. For verification purpose we have assembled an experimental galvanic cell; in the present work, we report two tests cases, with acidic and neutral electrolitical solution, where the computed electric potential compares well with the measured experimental one

Marine phytoplankton is known to produce surface-activity materials as part of its metabolism.