The book describes a computational model of the immune system reaction, C-ImmSim, built along the lines of the computer model known as the Celada-Seiden model (CS-model). The computational counterpart of the CS-model is called IMMSIM which stands for IMMune system SIMulator. IMMSIM was written in 1992 by the physicist Phil E. Seiden and the immunologist Franco Celada. This model was built around the idea of developing a computerized system to perform experiments similar in vivo experiments; a tool developed to help biologists testing theories and hypothesis about how the immune system works. C-ImmSim is best viewed as a collection of models in a single program. It incorporates the principal core facts of today's immunological knowledge, such as the diversity of specific elements, MHC restriction, clonal selection, thymic education of T cells, antigen processing and presentation (both the cytosolic and endocytic pathways are implemented), cell-cell cooperation, homeostasis of cells created by the bone marrow, hyper mutation of antibodies, maturation of the cellular and humoral response, and memory. Besides, an antigen can represent a bacterium, a virus, or an allergen or a tumor cell. C-ImmSim has been recently customized to simulate the HIV-1 infection. Moreover, it can simulate the immunotherapy for cancer. These features are all present in the code and people can choose to turn them on and off at compiling time. The book presents the basic model as well as the various customizations to implement the description of different diseases and the way they have been used in practice to produce new knowledge either from hypothesis or from lab-experiment data. In this respect, the book can be used as a practical guide to implement a computational model with which to study a specific disease and to try to address realistic clinical questions.

TRANSLATION OF THE ORIGINAL DOCUMENT "NETWORK LITERACY" AVAILABLE AT https://sites.google.com/a/binghamton.edu/netscied/teaching-learning/network-concepts Mentre il nostro mondo diventa sempre più connesso attraverso l'uso di reti, o network, che rendono le comunicazioni e la diffusione di informazioni pressoché istantanee, il livello di comprensione di come queste reti funzionino avrà un ruolo importante nel determinare quanto la società trarrà beneficio da questa connettività accresciuta. In breve, una società connessa richiede un'alfabetizzazione sul concetto di rete, ossia una conoscenza di base di cosa siano le reti, come possano essere utilizzate come strumento per la scoperta e per i processi decisionali, nonché sulle problematiche e i potenziali vantaggi resi accessibili a tutti coloro che vivono nel mondo interconnesso di oggi.

In this paper we present a general model of drug release from a drug delivery device and the subsequent transport in biological tissue. The model incorporates drug diffusion, dissolution and solubility in the polymer coating, coupled with diffusion, convection and reaction in the biological tissue. Each layer contains bound and free drug phases so that the resulting model is a coupled two-phase two-layer system of partial differential equations. One of the novelties is the generality of the model in each layer. Within the drug coating, our model includes diffusion as well as three different models of dissolution. We show that the model may also be used in cases where dissolution is rapid or not relevant, and additionally when drug release is not limited by its solubility. Within the biological tissue, the model can account for nonlinear saturable reversible binding, with linear reversible binding and linear irreversible binding being recovered as special cases. The generality of our model will allow the simulation of the release from a wide range of drug delivery devices encompassing many different applications. To demonstrate the efficacy of our model we simulate results for the particular application of drug release from arterial stents.

Program summary We present the open-source computer program JETSPIN, specifically designed to simulate the electro-spinning process of nanofibers. Its capabilities are shown with proper reference to the underlying model, as well as a description of the relevant input variables and associated test-case simulations. The various interactions included in the electrospinning model implemented in JETSPIN are discussed in detail. The code is designed to exploit different computational architectures, from single to parallel processor workstations. This paper provides an overview of JETSPIN, focusing primarily on its structure, parallel implementations, functionality, performance, and availability.

We investigate the effects of dissipative air drag on the dynamics of electrified jets in the initial stage of the electrospinning process. The main idea is to use a Brownian noise to model air drag effects on the uniaxial elongation of the jets. The developed numerical model is used to probe the dynamics of electrified polymer jets at different conditions of air drag force, showing that the dynamics of the charged jet is strongly biased by the presence of air drag forces. This study provides prospective beneficial implications for improving forthcoming electrospinning experiments. (C) 2015 Elsevier Ltd. All rights reserved.

We present a nonlinear Langevin model to investigate the early-stage dynamics of electrified polymer jets in electrospinning experiments. In particular, we study the effects of air drag force on the uniaxial elongation of the charged jet, right after ejection from the nozzle. Numerical simulations show that the elongation of the jet filament close to the injection point is significantly affected by the nonlinear drag exerted by the surrounding air. These results provide useful insights for the optimal design of current and future electrospinning experiments.

In this paper we present a model of drug release from a drug eluting-stent and the subsequent drug transport in the arterial wall. In order to study the complete process, a two-phase mathematical model describing the transport of a drug between two coupled media of different properties and dimensions is presented. A system of partial differential equations describes both the solid-liquid transfer (dissolution) and diffusion processes in the polymeric substrate as well as diffusion, convection and reaction in the tissue layer. We adopt a semi-analytical approach in solving the four resulting equations. The model serves as a useful tool for providing insight into the influence of solid-liquid mass transfer in drug-eluting stent systems.

A novel, coarse-grained, single-framework 'Eulerian' model for blood flow in the microvascular circulation is presented and used to estimate the variations in flow properties that accrue from all of the following: (i) wall position variation, associated with the endothelial cells' (ECs) shape, (ii) glycocalyx layer (GL) effects and (iii) the particulate nature of blood. We stress that our new model is fully coupled and uses only a single Eulerian computational framework to recover complex effects, dispensing altogether with the need for, e.g. re-meshing and advected sets of Lagrangian points. Physically, blood is modelled as a two-component, incompressible fluid - the plasma and corpuscular elements dispersed in it. The latter are modelled as deformable liquid droplets of increased viscosity. Interfacial membrane effects are present to mimic key blood properties and to avoid droplets' coalescence. The model is encapsulated within a multi-component lattice Boltzmann method that uses a sub-lattice 'wavy wall' closure to represent the ECs. Between this boundary and the flow domain, the model incorporates a coarse-grained representation of the endothelial GL, which is known to cover microvessel walls. The endothelial glycocalyx is modelled as a medium of variable and adaptive porosity, with approaching droplets being subject to a repulsive elastic force. Numerical simulations are presented to show the combined and simultaneous influence on fundamental flow properties of the EC wall undulation, the glycocalyx compression and repulsion and the particulate nature of blood. Several characteristic hemodynamical features of microvessel flow are successfully reproduced, including the deformability of particulates and the Fahraeus-Lindqvist effect. Moreover, the importance of modelling the GL is manifest in the magnitude of and the temporal variations in the flow rate and wall shear stresses.

In this paper we propose a discrete in continuous mathematical model for the morphogenesis of the posterior lateral line system in zebrafish. Our model follows closely the results obtained in recent biological experiments. We rely on a hybrid description: discrete for the cellular level and continuous for the molecular level. We prove the existence of steady solutions consistent with the formation of particular biological structure, the neuromasts. Dynamical numerical simulations are performed to show the behavior of the model and its qualitative and quantitative accuracy to describe the evolution of the cell aggregate.

We consider two models which were both designed to describe the movement of eukaryotic cells responding to chemical signals. Besides a common standard parabolic equation for the diffusion of a chemoattractant, like chemokines or growth factors, the two models differ for the equations describing the movement of cells. The first model is based on a quasilinear hyperbolic system with damping, the other one on a degenerate parabolic equation. The two models have the same stationary solutions, which may contain some regions with vacuum. We first explain in details how to discretize the quasilinear hyperbolic system through an upwinding technique, which uses an adapted reconstruction, which is able to deal with the transitions to vacuum. Then we concentrate on the analysis of asymptotic preserving properties of the scheme towards a discretization of the parabolic equation, obtained in the large time and large damping limit, in order to present a numerical comparison between the asymptotic behavior of these two models. Finally we perform an accurate numerical comparison of the two models in the time asymptotic regime, which shows that the respective solutions have a quite different behavior for large times.

In this paper we study a semilinear hyperbolic-parabolic system modeling biological phenomena evolving on a network composed of oriented arcs. We prove the existence of global (in time) smooth solutions to this problem. The result is obtained by using energy estimates with suitable transmission conditions at nodes.

Introduction: The brain is a connected network, requiring complex-system measures to describe its organization principles [1,2]. Here, we aim at testing whether the normalized compression distance (NCD) [3] is a suitable quantifier of the functional connectivity between cortical regions. This new measure estimates the information shared by two signals comparing the compression length of one signal given the other, without requiring any representation of the single in harmonics or selecting a specific time window where to compare the two signals. We show that this new measure is a good candidate to estimate the inter-nodes connectivity since it displays features 'expected' for brain connectivity, i.e. it is maximal between homologous cortical areas, it is higher for dominant cortical areas, it depends on age. In order to do it we estimated the NCD between functionally homologous primary somatosensory areas (S1) activities, testing the above-mentioned properties. Methods: Twenty-eight healthy, right-handed volunteers participated in the study. We recorded brain magnetic activity in the left and right Rolandic regions by a 28-channel magnetoencephalographic (MEG) system. We recorded rest activity for 3 min in each hemisphere. MEG activity was also collected during the electrical stimulation of the contralateral median nerve at the wrist delivered via surface disks. Elicited electric pulses were 0.2 ms in duration and 631 ms of inter-stimulus interval. Left and right median nerves were separately stimulated, totaling about 200 artifact-free trials for each. We used the Functional Source Separation (FSS) [4,5] algorithm to identify functionally homologous areas in the two hemispheres devoted to the somatosensory hand representation (FS_S1). Therefore, we calculated NCD between the left and right FS_S1s at rest. NCD is a parameter-free, quasi-universal similarity measure, computed from the lengths of compressed data files, singly and in pairwise concatenation. In other terms, NCD defines that two objects are similar if we can significantly "compress" one given the information of the other. We compared the similarity between the left and right homologous areas in single subjects and across the whole group. In particular, we compared the similarity of the activities in the two hemispheres of the same subject, with that in the same or in the opposite hemisphere of different subjects in the group of people. Results: NCD was minimal (maximal functional connectivity) between the neuronal activities of hemispheric functionally homologous areas in the same subject, i.e the NCD between the left and right FS_S1 of the same person was smaller than across different subjects (p<10 -7 consistently). NCD was smaller within the left dominant hemisphere than within the non dominant right one (p=3o10-7), suggesting that more skilled cortical areas express more tuned neuronal activities. Finally, it became more variable in older than younger people (p=.01), indicating that it is sensitive to proprioceptive and sensorimotor skills degradation typical of aging. Conclusions: NCD displayed an excellent ability in quantifying the similarity among neuronal activities, catching the maximal similarity expected for functionally homologous cortical areas of the two hemispheres. It was also sensitive to dominant- and age-dependent properties of somatosensory representation activities. This ability to catch key features of neuronal activity's dynamics indicates NCD as a good candidate for studies of brain functional connectivity, able to overcome the limitations intrinsic to the classical Fourier or autoregressive estimates in assessing the dynamics of two-nodes functional conections.

ElectroCOrticoGraphy (ECoG) is an invasive neuroimaging technique that measures electrical potentials produced by brain currents via an electrode grid implanted on the cortical surface. A full interpretation of ECoG data is difficult because it requires solving the inverse problem of reconstructing the spatio-temporal distribution of neural currents responsible of the recorded ECoG signals, which is ill-posed. Only in the last few years novel computational methods to solve this inverse problem have been developed. This study describes a beamformer method for ECoG source modeling. First, we extended the OpenMEEG software with a new method to estimate the lead-field matrix which maps the neural currents onto the sensors space. We further conducted an analysis of the numerical stability of the ECoG inverse problem by computing the condition number of the lead-field matrix for different configurations of the electrodes grid. Finally, we localized sources via a Linear Constraint Minimum Variance (LCMV) beamformer method applied to both synthetic and real data.

Source modeling of EEG data is an important tool for both neuroscience and clinical applications, such as epilepsy. Despite their simplicity, multiple dipole models remain highly desirable to explain neural sources. However, estimating dipole models from EEG time-series remains a difficult task, mainly due to the ill-posedness of the inverse problem and to the fact that the number of dipoles is usually not known a priori. Recently, a Bayesian approach has been presented for multiple dipole estimation of MEG/EEG data [1,2]: the method estimates simultaneously the number of dipoles and the dipole parameters, by exploring a multiple dipole state space with a Monte Carlo procedure combined with a tempering schedule [3]. Here, we present the first validation of this method with experimental EEG data.

We give a complete characterization of bipartite graphs having tree-like Galois lattices. We prove that the poset obtained by deleting bottom and top elements from the Galois lattice of a bipartite graph is tree-like if and only if the graph is a bipartite distance hereditary graph. Relations with the class of Ptolemaic graphs are discussed and exploited to give an alternative proof of the result. (C) 2015 Elsevier B.V. All rights reserved.

A {0, 1}-matrix A is balanced if it does not contain a submatrix of odd order having exactly two 1's per row and per column. A graph is balanced if its clique-matrix is balanced. No characterization of minimally unbalanced graphs is known, and even no conjecture on the structure of such graphs has been posed, contrary to what happened for perfect graphs. In this paper, we provide such a characterization for the class of diamond-free graphs and establish a connection between minimally unbalanced diamond-free graphs and Dyck-paths.

Partial integro-differential equation (PIDE) formulations are often preferable for pricing options under models with stochastic volatility and jumps. In this talk, we consider the numerical approximation of such models. On one hand, due to the non-local nature of the integral term, we propose to use Implicit-Explicit (IMEX) Runge-Kutta methods for the time integration to solve the integral term explicitly, giving higher order accuracy schemes under weak stability time-step restrictions. On the other hand, we propose a hybrid tree-finite difference method to approximate the Heston model, possibly in the presence of jumps. Numerical tests are presented to show the computational efficiency of the approximation.

We consider the problem of finding a square low-rank correction (?C - B)F to a given square pencil (?E - A) such that the new pencil ?(E - CF) - (A - BF) has all its generalised eigenvalues at the origin. We give necessary and sufficient conditions for this problem to have a solution and we also provide a constructive algorithm to compute F when such a solution exists. We show that this problem is related to the deadbeat control problem of a discrete-time linear system and that an (almost) equivalent formulation is to find a square embedding that has all its finite generalised eigenvalues at the origin.

Financial and activity report - project T.He.T.A. "Technological tools for the Promotion of Transadriatic Archaeological Heritage"

One of the promising frontiers of bioengineering is the controlled release of a therapeutic drug from a vehicle across the skin (transdermal drug delivery). In order to study the complete process, a two-phase mathematical 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. Drug masses are given and their dependence on the physical parameters is discussed.