Fever plays a role in activating innate immunity while its relevance in activating adaptive immunity is less clear. Even brief exposure to elevated temperatures significantly impacts on the immunostimulatory capacity of dendritic cells (DCs), but the consequences on immune response remain unclear. To address this issue, we analyzed the gene expression profiles of normal human monocyte-derived DCs from nine healthy adults subjected either to fever-like thermal conditions (39 degrees C) or to normal temperature (37 degrees C) for 180 minutes. Exposure of DCs to 39 degrees C caused upregulation of 43 genes and downregulation of 24 genes. Functionally, the up/downregulated genes are involved in post-translational modification, protein folding, cell death and survival, and cellular movement. Notably, when compared to monocytes, DCs differentially upregulated transcription of the secreted protein IGFBP-6, not previously known to be specifically linked to hyperthermia. Exposure of DCs to 39 degrees C induced apoptosis/necrosis and resulted in accumulation of IGFBP-6 in the conditioned medium at 48 h. IGFBP-6 may have a functional role in the hyperthermic response as it induced chemotaxis of monocytes and T lymphocytes, but not of B lymphocytes. Thus, temperature regulates complex biological DC functions that most likely contribute to their ability to induce an efficient adaptive immune response.

Cyber insurance is a rapidly developing area which draws more and more attention of practitioners and researchers. Insurance, an alternative way to deal with residual risks, was only recently applied to the cyber world. The immature cyber insurance market faces a number of unique challenges on the way of its development.In this paper we summarise the basic knowledge about cyber insurance available so far from both market and scientific perspectives. We provide a common background explaining basic terms and formalisation of the area. We discuss the issues which make this type of insurance unique and show how different technologies are affected by these issues. We compare the available scientific approaches to analysis of cyber insurance market and summarise their findings with a common view. Finally, we propose directions for further advances in the research on cyber insurance.

We consider the mathematical modeling of the coupled mechanical-transport problem found in arterial physiopathology. The chapter provides an extensive description of the physiology and the microstructure of the arterial wall and explains how these are coupled to the molecular transport problem. The details of the most recent developments of the mechanistic descriptions of the multi-scale multi-physics are presented.

In this paper we investigate the extent to which variable porosity drug-eluting coatings can provide better control over drug release than coatings where the porosity is constant throughout. In particular, we aim to establish the potential benefits of replacing a single-layer with a two-layer coating of identical total thickness and initial drug mass. In our study, what distinguishes the layers (other than their individual thickness and initial drug loading) is the underlying microstructure, and in particular the effective porosity and the tortuosity of the material. We consider the effect on the drug release profile of varying the initial distribution of drug, the relative thickness of the layers and the relative resistance to diffusion offered by each layer's composition. Our results indicate that the contrast in properties of the two layers can be used as a means of better controlling the release, and that the quantity of drug delivered in the early stages can be modulated by varying the distribution of drug across the layers. We conclude that microstructural and loading differences between multi-layer variable porosity coatings can be used to tune the properties of the coating materials to obtain the desired drug release profile for a given application.

The topic of controlled drug release has received much attention in recent years, for example in the design of tablets and in local drug delivery devices such as stents, transdermal patches, therapeutic contact lenses and orthopaedic implants. In recent years, we have developed a series of models for such devices to describe drug release from a polymeric platform, drug transport in surrounding biological tissues and fully coupled models of them. These works have culminated in the development of the first mathematical model to demonstrate agreement with in-vivo drug release and tissue uptake data, for the case of a drug-eluting stent . If, on the one hand, these fully coupled models are indeed necessary to understand the spatio-temporal drug concentration in the surrounding environment, on the other hand it is clear that device manufacturers cannot intervene on the underlying biology. What they can control, however, are the properties of the polymeric platform to ensure the desired drug release profile is achieved. Indeed, the release profile is known to be a key predictor of device performance. Therefore, in the present work we take a step back from the fully coupled computational models and focus instead solely on the properties of the drug-containing coating. We consider two particular aspects of the drug coating design. Firstly, the delivery of two therapeutic agents, what we refer to as dual drug delivery. Depending on the particular application in question, it may be desirable for the drugs to be released at similar rates, or perhaps one of the drugs released rapidly with the other being eluted over a longer period of time. In the case of drug-eluting stents, for example, devices which release an anti-proliferative and a `pro-healing' drug have been proposed, whilst a combination of two of the early drug-eluting stent drugs - paclitaxel and sirolimus - has also been suggested. Secondly, motivated by today's advances in micro and nanotechnology, we propose variable porosity multi-layer coatings as an additional means of controlling the dual drug delivery.

In this paper we describe a theoretical mathematical model of dual drug delivery from a durable polymer coated medical device. We demonstrate how the release rate of each drug may in principle be controlled by altering the initial loading configuration of the two drugs. By varying the underlying microstructure of polymer coating, further control may be obtained, providing the opportunity to tailor the release profile of each drug for the given application.

We estimate the error of Gauss-Jacobi quadrature rule applied to a function f, which is supposed locally absolutely continuous in some Besov type spaces, or of bounded variation on [-1,1]. In the first case the error bound concerns the weighted main part phi-modulus of smoothness of f introduced by Z. Ditzian and V. Totik, while in the second case we deal with a Stieltjes integral with respect to f. The stated estimates generalize several error bounds from literature and, in both the cases, they assure the same convergence rate of the error of best polynomial approximation in weighted L-1 space. (C) 2017 IMACS. Published by Elsevier B.V. All rights reserved.

In this paper we describe a combined in-vitro experimental and mathematical modelling approach to predict in-vivo drug-eluting stent kinetics. We coated stents with a mixture of sirolimus and a novel acrylic-based polymer in two different ratios. Our results indicate differential release kinetics between low and high drug dose formulations. Furthermore, mathematical model simulations of target receptor saturation suggest potential differences in efficacy.

Well-balanced schemes, nowadays well-known for 1D hyperbolic equations with source terms and systems of balance laws, are extended to strictly parabolic equations, first in 1D, then in 2D on Cartesian computational grids. The construction heavily relies on a particular type of piecewise-smooth interpolation of discrete data known as -splines. In 1D, several types of widely-used discretizations are recovered as particular cases, like the El-Mistikawy-Werle scheme or Scharfetter- Gummel's. Moreover, a distinctive feature of our 2D scheme is that dimensional-splitting never occurs within its derivation, so that all the multi-dimensional interactions are kept at the discrete level. This leads to improved accuracy, as illustrated on several types of drift-diffusion equations.

The numerical solution of reaction-diffusion systems modelling predator-prey dynamics using implicit-symplectic (IMSP) schemes is relatively new. When applied to problems with chaotic dynamics they perform well, both in terms of computational effort and accuracy. However, until the current paper, a rigorous numerical analysis was lacking. We analyse the semi-discrete in time approximations of a first-order IMSP scheme applied to spatially extended predator-prey systems. We rigorously establish semi-discrete a priori bounds that guarantee positive and stable solutions, and prove an optimal a priori error estimate. This analysis is an improvement on previous theoretical results using standard implicit-explicit (IMEX) schemes. The theoretical results are illustrated via numerical experiments in one and two space dimensions using fully-discrete finite element approximations.

Protected Areas are subject to long-term modifications associated with climate and environmental change, enhancing the risk of ecosystem collapse, tipping points and unexpected responses to droughts, fires, floods and other individual events. One of the goals of the EU H2020 Project ECOPOTENTIAL and of the GEO ECO Initiative of the Group on Earth Observations (GEO) is to quantify ongoing and expected changes in the drivers and the characteristics of Protected Areas in Europe and beyond, using gridded climatic datasets, in situ meteo-climatic and biological data and Remote Sensing observations. Several statistical approaches are used to this goal, with the aim of determining the patterns and properties of the changes currently affecting Protected Areas. Use of suitably downscaled climate scenarios allows for estimating how such changes are projected into the next decades. Here we report the results on the changes in meteo-climatic drivers and in some remotely-sensed variables for the set of Protected Areas participating in the ECOPOTENTIAL project, focusing on a few specific examples encompassing mountain, arid/semi-arid and coastal ecosystems.

The large H2020 project ECOPOTENTIAL (2015-2019, 47 partners, contributing to GEO and GEOSS http://www.ecopotential-project.eu/) is devoted to making best use of remote sensing and in situ data to improve future ecosystem benefits, adopting the view of ecosystems as one physical system with their environment, focusing on geosphere-biosphere interactions, Earth Critical Zone dynamics, Macrosystem Ecology and cross-scale interactions, the effect of extreme events and using Essential (Climate, Biodiversity and Ocean) Variables as descriptors of change. In ECOPOTENTIAL, remote sensing and in situ data are collected, processed and used for a betterunderstandingoftheecosystemdynamics,analysingandmodellingtheeffectsofglobalchangesonecosystem functions and services, over an array of different ecosystem types, including mountain, marine, coastal, arid and semi-arid ecosystems. The project focuses on a network of Protected Areas of international relevance, that is representative of the range of environmental and biogeographical conditions characterizing Europe. Some of the activitiesoftheprojectaredevotedtodetectandquantifythechangestakingplaceintheProtectedAreas,through the analysis of remote sensing observations, in-situ data and gridded climatic datasets. Likewise, the project aims atprovidingestimatesofthefutureecosystemconditionsindifferentclimateandenvironmentalchangescenarios. In all such endeavours, one is faced with cross-scale issues: downscaling of climate information to drive ecosystem response, and upscaling of local ecosystem changes to larger scales. So far, the analysis has been conducted mainly by using traditional methods, but there is wide room for improvement by using more refined approaches. In particular, a crucial question is how to upscale the information gained at single-site scale to larger, regional or continental scale, an issue that could benefit from using, for example, complex network analysis.

A model consisting of a kinetic equation for \run-and-tumble" biased bacteria motion, coupled with two reaction-diusion equations for chemical signals, is studied. It displays time- asymptotic propagation at constant velocity, i.e., aggregated travelling (exponential) layers. To capture them for various parameters, a well-balanced setup is based on both \Case's elementary solutions" and L-spline reconstruction. Far from the diusive regime, waves travelling at dierent velocities (bistability) are proved to coexist. Numerics suggest that they are locally asymptotically stable, so that the resulting bifurcation diagram shows counterintuitive features.

The emergencies management in industrial plants is an issue widely discussed in the literature and in the European legislative framework. Despite the large interest shown by the different actors involved in emergencies management, neither scientific nor in industrial field, have developed intelligent tools to support the decisions in these particular contexts. This work, realized inside an Italian financed project (DIEM-SSP), faces the problem to evacuate the greater number of persons from a risky area and transfer them in a unique destination outside from this area using the available and limited resources. Supposing that these persons have problem of mobility, the problem to solve becomes this: collect the highest number of persons from several origins and bring them into a unique destination, using a limited number of capacitated vehicles respecting a time limit. This problem has been modelled as a Multi origins Capacitated Team Orienteering Problem (Mo-CTOP) and solved implementing Ants Colony Optimization algorithm (ACOa). Results and tests are given in order to validate the proposed model and to offer a solution for a real case treaty into the abovementioned project.

We investigate the effects of nanoparticles on the onset of varicose and whipping instabilities in the dynamics of electrified jets. In particular, we show that the non-linear interplay between the mass of the nanoparticles and electrostatic instabilities, gives rise to qualitative changes of the dynamic morphology of the jet, which in turn, drastically affect the final deposition pattern in electrospinning experiments. It is also shown that even a tiny amount of excess mass, of the order of a few percent, may more than double the radius of the electrospun fiber, with substantial implications for the design of experiments involving electrified jets as well as spun organic fibers. Copyright (C) EPLA, 2017

We investigate the effects of high solvated-methane concentration on methane-hydrate nucleation at 250 K and 500 atm. We consider solutions at four levels of methane molar fraction in the initial H2O-CH4 solution, ?CH4 = 0.038, 0.044, 0.052, and 0.058, which are higher than (metastable) bulk supersaturation. ?CH4 is controlled independently of the temperature and pressure thanks to the use of special simulation techniques [Phys. Chem. Chem. Phys. 2011, 13, 13177]. These conditions mimic a possible increase of local methane concentration beyond supersaturation induced, for example, by freeze concentration or thermal fluctuations. The nucleation mechanism and kinetics are investigated using the dynamical approach to nonequilibrium molecular dynamics. We demonstrate a hydrate-forming/-ordering process of solvated methane and water molecules in a manner consistent with both the "blob" hypothesis and "cage adsorption hypothesis": the system initially forms an amorphous nucleus at high methane concentration, which then gets ordered, forming the clathrate crystallite. We evaluate nucleation rates using both the methods of the mean first-passage time, i.e., the curve of the average time the system takes to reach a crystalline nucleus of given size, and survival probability, i.e., probability that up to a given time the system has not nucleated yet. We found a dependence of the nucleation rate on initial methane concentration of a form consistent with the dependence of classical nucleation theory rate on supersaturation and determined the relevant parameters of this relation. We found a very rapid increase of nucleation rate with solvated-methane concentration, proving that methane molar fraction, even beyond bulk supersaturation, is key at triggering the homogeneous nucleation of clathrate. We derive a kinetic equation that allows for estimation of the nucleation rate over a wide range of concentration conditions.

We present a multi-layer mathematical model to describe the transdermal drug release from an iontophoretic system. The Nernst-Planck equation describes the basic convection-diffusion process, with the electric potential obtained by solving the Laplace's equation. These equations are complemented with suitable interface and boundary conditions in a multi-domain. The stability of the mathematical problem is discussed in different scenarios and a finite-difference method is used to solve the coupled system. Numerical experiments are included to illustrate the drug dynamics under different conditions.

The expansion of biological species in natural environments is usually described as the combined effect individual spatial dispersal and growth. In the case of aquatic ecosystems flow transport can also be extremely relevant as an extra, advection induced, dispersal factor. We designed and assembled a dedicated microfluidic device to control and quantify the expansion of populations of E. coli bacteria under both co-flowing and counter-flowing conditions, measuring the front speed at varying intensity of the imposed flow. At variance with respect to the case of classic advective-reactive-diffusive chemical fronts, we measure that almost irrespective of the counter-flow velocity, the front speed remains finite at a constant positive value. A simple model incorporating growth, dispersion and drift on finite-size hard beads allows to explain this finding as due to a finite volume effect of the bacteria. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) that ignore the finite size of organisms may be inaccurate to describe the physics of spatial growth dynamics of bacteria.

Understanding and modeling the dynamics of pedestrian crowds can help with designing and increasing the safety of civil facilities. A key feature of a crowd is its intrinsic stochasticity, appearing even under very diluted conditions, due to the variability in individual behaviors. Individual stochasticity becomes even more important under densely crowded conditions, since it can be nonlinearly magnified and may lead to potentially dangerous collective behaviors. To understand quantitatively crowd stochasticity, we study the real-life dynamics of a large ensemble of pedestrians walking undisturbed, and we perform a statistical analysis of the fully resolved pedestrian trajectories obtained by a yearlong high-resolution measurement campaign. Our measurements have been carried out in a corridor of the Eindhoven University of Technology via a combination of Microsoft Kinect 3D range sensor and automatic head-tracking algorithms. The temporal homogeneity of our large database of trajectories allows us to robustly define and separate average walking behaviors from fluctuations parallel and orthogonal with respect to the average walking path. Fluctuations include rare events when individuals suddenly change their minds and invert their walking directions. Such tendency to invert direction has been poorly studied so far, even if it may have important implications on the functioning and safety of facilities. We propose a model for the dynamics of undisturbed pedestrians, based on stochastic differential equations, that provides a good agreement with our field observations, including the occurrence of rare events.

integral(R) A(vertical bar f' (x)vertical bar h(f(x))) dx <= C-1 integral(R) A(C-2 (p) root vertical bar Mf"(x)T-h,T-p (f,x)vertical bar. h(f(x))dx, Given a N-function A and a continuous function h satisfying certain assumptions, we derive the inequality [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], with constants [C.sub.1], [C.sub.2] independent of f, where f [greater than or equal to] 0 belongs locally to the Sobolev space [W.sup.2,1] (R), f' has compact support, p 1 is smaller than the lower Boyd index of A, [T.sub.h,p] (*) is certain nonlinear transform depending of h but not of A and M denotes the Hardy-Littlewood maximal function. Moreover, we show that when h [equivalent to] 1, then Mf" can be improved by f". This inequality generalizes a previous result by the third author and Peszek, which was dealing with p = 2.