Monitoring biodiversity at the level of habitats and landscape is becoming widespread in Europe and elsewhere as countries establish international and national habitat conservation policies and monitoring systems. Earth Observation (EO) data offers a potential solution to long-term biodiversity monitoring through direct mapping of habitats or by integrating Land Cover/Use (LC/LU) maps with contextual spatial information and in situ data. Therefore, it appears necessary to develop an automatic/ semi-automatic translation framework of LC/ LU classes to habitat classes, but also challenging due to discrepancies in domain definitions. In the context of the FP7 BIO_SOS (www.biosos.eu) project, the authors demonstrated the feasibility of the Food and Agricultural Organization Land Cover Classification System (LCCS) taxonomy to habitat class translation. They also developed a framework to automatically translate LCCS classes into the recently proposed General Habitat Categories classification system, able to provide an exhaustive typology of habitat types, ranging from natural ecosystems to urban areas around the globe. However discrepancies in terminology, plant height criteria and basic principles between the two mapping domains inducing a number of one-to-many and many-to-many relations were identified, revealing the need of additional ecological expert knowledge to resolve the ambiguities. This paper illustrates how class phenology, class topological arrangement in the landscape, class spectral signature from multi-temporal Very High spatial Resolution (VHR) satellite imagery and plant height measurements can be used to resolve such ambiguities. Concerning plant height, this paper also compares the mapping results obtained by using accurate values extracted from LIght Detection And Ranging (LIDAR) data and by exploiting EO data texture features (i.e. entropy) as a proxy of plant height information, when LIDAR data are not available. An application for two Natura 2000 coastal sites in Southern Italy is discussed.

In the present work the numerical simulation of breaking wave processes is discussed. A detailed analysis is performed using Smoothing Particle Hydrodynamics (SPH) models as well as a mesh-based Level-Set Finite Volume Method (LS-FVM). Considerations on the numerical dissipation involved in such models are discussed within the frameworks of weakly compressible and incompressible ssumptions. The breaking wave processes are simulated using both mono- and two-phases models. Due to the extensive test-cases discussed, the present analysis is limited to a bi-dimensional framework. Test-cases with increasing complexities are considered starting from a simple 1D impact of two water-jet up to complex shallow water breaking waves. The analyses presented in this article are not only useful to weakly compressible SPH or LS-FVM users but can be extended to other numerical models for which accurate (convergent) results on benchmark test-cases are provided.

This work investigates the capability of supervised classification methods in detecting both major tissues and subcortical structures using multispectral brain magnetic resonance images. First, by means of a realistic digital brain phantom, we investigated the classification performance of various Discriminant Analysis methods, K-Nearest Neighbor and Support Vector Machine. Then, using phantom and real data, we quantitatively assessed the benefits of integrating anatomical information in the classification, in the form of voxels coordinates as additional features to the intensities or tissue probabilistic atlases as priors. In addition we tested the effect of spatial correlations between neighbouring voxels and image denoising. For each brain tissue we measured the classification performance in terms of global agreement percentage, false positive and false negative rates and kappa coefficient. The effectiveness of integrating spatial information or a tissue probabilistic atlas has been demonstrated for the aim of accurately classifying brain magnetic resonance images.

We present a new numerical procedure to assess the plausibility of a subglacial lake in case of relative small/moderate extension and surging temperate icefield. In addition to the flat signal from Ground Penetrating Radar remote survey of the area, early indication of a likely subglacial lake, required icefield data are: top surface elevation and bathymetry, top surface velocity at some points, in-depth temperature and density profiles of upper layer. The procedure is based on a mathematical model of the evolution of dynamics and thermo-dynamics of the icefield and of a subglacial lake. The Glen's law is adopted for ice rheology and Stokes reduction is applied; Large Eddy Simulation technique is used for the lake. Ice/water phase change is described. Finite volumes for model discretization and a front-tracking technique to follow the moving interface characterize the numerical method. We have applied this procedure to the case of a subglacial lake conjectured in the area of Amundsenisen, Svalbard, and, here, the results of a sensitivity study are discussed. In particular we point out that the effect of firn and snow upper layers on the system, in terms of temperature field, density and water content, has to be included in the modeling, as it contributes to the overcoming of the ice metastable state and the release of subglacial water. Accordingly, ice water content changes have to be carefully described. The depth of the bed depression is confirmed to be critical for the formation of the lake.

A two-phasemathematical model describing the dynamics of a substance between two coupled media of different properties and dimensions is presented. A system of partial differential equations describes the diffusion and the binding/unbinding processes in both layers. Additional flux continuity at the interface and clearance conditions into systemic circulation are imposed. An eigenvalue problem with discontinuous coefficients is solved and an analytical solution is given in the form of an infinite series expansion. The model points out the role of the diffusion and reaction parameters, which control the complex transfer mechanism and the drug kinetics across the two layers.

Transcriptome studies have shown the pervasive nature of transcription, demonstrating almost all the genes undergo alternative splicing. Accurately annotating all transcripts of a gene is crucial. It is needed to understand the impact of mutations on phenotypes, to shed light on genetic and epigenetic regulation of mRNAs and more generally to widen our knowledge about cell functionality and tissue diversity. RNA-sequencing (RNA-Seq), and the other applications of the next-generation sequencing, provides precious data to improve annotations' accuracy, simultaneously creating issues related to the variety, complexity and the size of produced data. In this 'scenario', the lack of user-friendly resources, easily accessible to researchers with low skills in bioinformatics, makes difficult to retrieve complete information about one or few genes without browsing a jungle of databases. Concordantly, the increasing amount of data from 'omics' technologies imposes to develop integrated databases merging different data formats coming from distinct but complementary sources. In light of these considerations, and given the wide interest in studying Down syndrome-a genetic condition due to the trisomy of human chromosome 21 (HSA21)-we developed an integrated relational database and a web interface, named ALE-HSA21 (AnaLysis of Expression on HSA21), accessible at http://bioinfo.na.iac.cnr.it/ALE-HSA21. This comprehensive and user-friendly web resource integrates-for all coding and noncoding transcripts of chromosome 21-existing gene annotations and transcripts identified de novo through RNA-Seq analysis with predictive computational analysis of regulatory sequences. Given the role of noncoding RNAs and untranslated regions of coding genes in key regulatory mechanisms, ALE-HSA21 is also an interesting web-based platform to investigate such processes. The 'transcript-centric' and easily-accessible nature of ALE-HSA21 makes this resource a valuable tool to rapidly retrieve data at the isoform level, rather than at gene level, useful to investigate any disease, molecular pathway or cell process involving chromosome 21 genes.

We review recent advances on the mesoscopic modeling of water-like fluids, based on the lattice Boltzmann (LB) methodology. The main idea is to enrich the basic LB (hydro)-dynamics with angular degrees of freedom responding to suitable directional potentials between water-like molecules. The model is shown to reproduce some microscopic features of liquid water, such as an average number of hydrogen bonds per molecules (HBs) between 3 and 4, as well as a qualitatively correct statistics of the hydrogen bond angle as a function of the temperature. Future developments, based on the coupling the present water-like LB model with the dynamics of suspended bodies, such as biopolymers, may open new angles of attack to the simulation of complex biofluidic problems, such as protein folding and aggregation, and the motion of large biomolecules in complex cellular environments.

We present the results of a computational study of coronary trees obtained from CT acquisition at resolution of 0.35mm x 0.35mm x 0.4mm and presenting significant stenotic plaques. We analyze the cardiovascular implications of stenotic plaques for a sizeable number of patients and show that the standard clinical criterion for surgical or percutaneous intervention, based on the Fractional Flow Reserve (FFR), is well reproduced by simulations in a range of inflow conditions that can be finely controlled. The relevance of the present study is related to the reproducibility of FFR data by simulating the coronary trees at global level via high performance simulation methods together with an independent assessment based on in vitro hemodynamics. The data show that controlling the flow Reynolds number is a viable procedure to account for FFR as heart-cycle time averages and maximal hyperemia, as measured in vivo. The reproducibility of the clinical data with simulation offers a systematic approach to measuring the functional implications of stenotic plaques. © 2014 SPIE.

We consider stochastic differential games with N nearly identical players, linear-Gaussian dynamics, and infinite horizon discounted quadratic cost. Admissible controls are feedbacks for which the system is ergodic. We first study the existence of affine Nash equilibria by means of an associated system of N Hamilton-Jacobi-Bellman and N Kolmogorov-Fokker-Planck partial differential equations, proving that for small discount factors quadratic-Gaussian solutions exist and are unique. Then, we prove the convergence of such solutions to the unique quadratic-Gaussian solution of the pair of Mean Field equations. We also discuss some singular limits, such as vanishing discount, vanishing noise, and cheap control.