In this paper we analyze the stochastic version of a minimalistic multi-strain model,which captures essential differences between primary and secondary infections in denguefever epidemiology, and investigate the interplay between stochasticity, seasonality andimport. The introduction of stochasticity is needed to explain the fluctuations observedin some of the available data sets, revealing a scenario where noise and complexdeterministic skeleton strongly interact. For large enough population size, the stochasticsystem can be well described by the deterministic skeleton gaining insight on the relevantparameter values purely on topological information of the dynamics, rather than classicalparameter estimation of which application is in general restricted to fairly simpledynamical scenarios.

This paper is concerned with the numerical simulation of a thermodynamically compatibleviscoelastic shear-thinning fluid model, particularly well suited to describe therheological response of blood, under physiological conditions. Numerical simulations areperformed in two idealized three-dimensional geometries, a stenosis and a curved vessel,to investigate the combined effects of flow inertia, viscosity and viscoelasticity inthese geometries. The aim of this work is to provide new insights into the modeling andsimulation of homogeneous rheological models for blood and a basis for furtherdevelopments in modeling and prediction.

This work deals with the consequences on structural stability of Gause type predator-preymodels, when are considered three standard functional responses and the prey growth rateis subject to an Allee effect.

An important consequence of this ecological phenomenon is the existence of a separatrixcurve dividing the behavior of trajectories in the phase plane. The origin is an attractorfor any set of parameters and the existence of heteroclinic curves can be also shown.

Conditions on the parameter values are established to ensure the existence of a uniquepositive equilibrium, which can be either an attractor or a repellor surrounded by one ormore limit cycles.

The influence of the Allee effect on the number of limit cycles is analyzed and theresults are compared with analogous models without this phenomenon, and which mainfeatures have been given in various above works. Ecological interpretations of theseresults are also given.

Various particle methods are widely used to model dynamics of complex media. In this workmolecular dynamics and dissipative particles dynamics are applied to model blood flowscomposed of plasma and erythrocytes. The properties of the homogeneous particle fluid arestudied. Capillary flows with erythrocytes are investigated.

The paper proposes a general framework allowing the analysis of wetting problems in thesituation when interfacial tensions depend on external fields. An equation predictingapparent contact angles of sessile droplets deposited on rough surfaces in the presence ofexternal fields is derived. The problem of wetting is discussed in the framework of thevariational approach. Derivation of a general equation generalizing the Cassie and Wenzelapproaches is presented. The effects related to the line tension which are important fornano-structured surfaces are considered.

The paper investigates an age-structured infinite-horizon optimal control model ofharvesting a biological resource, interpreted as fish. Time and age are considered ascontinuum variables. The main result shows that in case of selective fishing, where onlyfish of prescribed sizes is harvested, it may be advantageous in the log run to implementa periodic fishing effort, rather than constant (the latter suggested by single-fishmodels that disregard the age-heterogeneity). Thus taking into account the age-structureof the fish may qualitatively change the theoretically optimal fishing mode. This resultis obtained by developing a technique for reliable numerical verification of second ordernecessary optimality conditions for the considered problem. This technique could be usefulfor other optimal control problems of periodic age-structured systems.

For flows with strong periodic content, time-spectral methods can be used to obtaintime-accurate solutions at substantially reduced cost compared to traditionaltime-implicit methods which operate directly in the time domain. However, these methodsare only applicable in the presence of fully periodic flows, which represents a severerestriction for many aerospace engineering problems. This paper presents an extension ofthe time-spectral approach for problems that include a slow transient in addition tostrong periodic behavior, suitable for applications such as transient turbofan simulationor maneuvering rotorcraft calculations. The formulation is based on a collocation methodwhich makes use of a combination of spectral and polynomial basis functions and results inthe requirement of solving coupled time instances within a period, similar to the timespectral approach, although multiple successive periods must be solved to capture thetransient behavior.

The implementation allows for two levels of parallelism, one in the spatial dimension,and another in the time-spectral dimension, and is implemented in a modular fashion whichminimizes the modifications required to an existing steady-state solver. For dynamicallydeforming mesh cases, a formulation which preserves discrete conservation as determined bythe Geometric Conservation Law is derived and implemented. A fully implicit approach whichtakes into account the coupling between the various time instances is implemented andshown to preserve the baseline steady-state multigrid convergence rate as the number oftime instances is increased. Accuracy and efficiency are demonstrated for periodic andnon-periodic problems by comparing the performance of the method with a traditionaltime-stepping approach using a simple two-dimensional pitching airfoil problem, athree-dimensional pitching wing problem, and a more realistic transitioning rotor problem.

We study origin, parameter optimization, and thermodynamic efficiency of isothermal rocking ratchets based on fractional subdiffusion within a generalized non-Markovian Langevin equation approach. A corresponding multi-dimensional Markovian embedding dynamics is realized using a set of auxiliary Brownian particles elastically coupled to the central Brownian particle (see video on the journal web site). We show that anomalous subdiffusive transport emerges due to an interplay of nonlinear response and viscoelastic effects for fractional Brownian motion in periodic potentials with broken space-inversion symmetry and driven by a time-periodic field. The anomalous transport becomes optimal for a subthreshold driving when the driving period matches a characteristic time scale of interwell transitions. It can also be optimized by varying temperature, amplitude of periodic potential and driving strength. The useful work done against a load shows a parabolic dependence on the load strength. It grows sublinearly with time and the corresponding thermodynamic efficiency decays algebraically in time because the energy supplied by the driving field scales with time linearly. However, it compares well with the efficiency of normal diffusion rocking ratchets on an appreciably long time scale.

We review mathematical results about the qualitative structure of chemotherapy protocols that were obtained with the methods of optimal control. As increasingly more complex features are incorporated into the mathematical model—progressing from models for homogeneous, chemotherapeutically sensitive tumor cell populations to models for heterogeneous agglomerations of subpopulations of various sensitivities to models that include tumor immune-system interactions—the structures of optimal controls change from bang-bang solutions (which correspond to maximum dose rate chemotherapy with restperiods) to solutions that favor singular controls (representing reduced dose rates). Medically, this corresponds to a transition from standard MTD (maximum tolerated dose) type protocols to chemo-switch strategies towards metronomic dosing.

Mechanisms contributing to the spread of avian influenza seem to be well identified, buthow their interplay led to the current worldwide spread pattern of H5N1 influenza is still unknowndue to the lack of effective global surveillance and relevant data. Here we develop some deterministicmodels based on the transmission cycle and modes of H5N1 and focusing on the interactionamong poultry, wild birds and environment. Some of the model parameters are obtained fromexisting literatures, and others are allowed to vary in order to assess the effectiveness of variouscontrol strategies involving bird migration, agro-ecological environments, live and dead poultrytrading, smuggling of wild birds, mechanical movement of infected materials and specific farmingpractices. Our simulations are carried out for a set of parameters that leads to the basic reproductionnumber 3.3. We show that by reducing 95% of the initial susceptible poultry population or bykilling all infected poultry birds within one day, one may control the disease outbreak in a localsetting. Our simulation shows that cleaning the environment is also a feasible and useful controlmeasure, but culling wild birds and destroying their habitat are ineffective control measures. Weuse a one dimensional PDE model to examine the contribution to the spatial spread rate by thesize of the susceptible poultry birds, the diffusion rates of the wild birds and the virus. We noticethe diffusion rate of the wild birds with high mortality has very little impact on the spread speed.But for the wild birds who can survive the infection, depending on the direction of convection,their diffusion rate can substantially increase the spread rate, indicating a significant role of themigration of these type of wild birds in the spread of the disease.

Spatial dynamics of fibrin clot formation in non-stirred system activated by glasssurface was studied as a function of FIX activity. Haemophilia B plasma was obtained fromuntreated patients with different levels of FIX deficiency and from severe haemophilia B patienttreated with FIX concentrate (Ahemphil B) during its clearance with half-life t1/2=12 hours. Asreported previously (Ataullakhanov et al. Biochim Biophys Acta 1998; 1425: 453-468), clotgrowth in space showed two distinct phases: activation and propagation. The activation phase ischaracterized by the time required to start clot growth from the activator, while the characteristicparameter of the propagation phase is the clot elongation rate. This rate reaches steady state inapproximately ten minutes after the beginning of growth. In haemophilia B plasma, clotformation is substantially impaired: clot starts to grow from the activating surface later than inhealthy donor plasma, and its propagation rate is considerably lower. The most significantabnormalities in clot growth kinetics are observed at FIX activity below 10% of normal.Simulation of these experiments was performed theoretically using a detailed biochemical model(Panteleev et al. Biophys J 2006; 90: 1489-1500) adapted for experimental conditions used.Suitability of the assumptions used to describe triggering contact activation was verified.

We consider the problem of state and parameter estimation for a class of nonlinearoscillators defined as a system of coupled nonlinear ordinary differential equations.Observable variables are limited to a few components of state vector and an input signal.This class of systems describes a set of canonic models governing the dynamics of evokedpotential in neural membranes, including Hodgkin-Huxley, Hindmarsh-Rose, FitzHugh-Nagumo,and Morris-Lecar models. We consider the problem of state and parameter reconstruction forthese models within the classical framework of observer design. This framework offerscomputationally-efficient solutions to the problem of state and parameter reconstructionof a system of nonlinear differential equations, provided that these equations are in theso-called adaptive observer canonic form. We show that despite typical neural oscillatorsbeing locally observable they are not in the adaptive canonic observer form. Furthermore,we show that no parameter-independent diffeomorphism exists such that the originalequations of these models can be transformed into the adaptive canonic observer form. Wedemonstrate, however, that for the class of Hindmarsh-Rose and FitzHugh-Nagumo models,parameter-dependent coordinate transformations can be used to render these systems intothe adaptive observer canonical form. This allows reconstruction, at least partially andup to a (bi)linear transformation, of unknown state and parameter values with exponentialrate of convergence. In order to avoid the problem of only partial reconstruction and atthe same time to be able to deal with more general nonlinear models in which the unknownparameters enter the system nonlinearly, we present a new method for state and parameterreconstruction for these systems. The method combines advantages of standardLyapunov-based design with more flexible design and analysis techniques based on thenotions of positive invariance and small-gain theorems. We show that this flexibilityallows to overcome ill-conditioning and non-uniqueness issues arising in this problem.Effectiveness of our method is illustrated with simple numerical examples.

Cancer has recently overtaken heart disease as the world’s biggest killer. Cancer isinitiated by gene mutations that result in local proliferation of abnormal cells and theirmigration to other parts of the human body, a process called metastasis. The metastasizedcancer cells then interfere with the normal functions of the body, eventually leading todeath. There are two hundred types of cancer, classified by their point of origin. Most ofthem share some common features, but they also have their specific character. In thisarticle we review mathematical models of such common features and then proceed to describemodels of specific cancer diseases.

Whether the size of an animal population is environmentally limited or regulatedby density dependent negative feedback mechanisms is of ecological interest. Proponents oflimitation theory have issued a set of specific challenges which are addressed in this paperusing field data for the insect Tipula paludosa. This species is known to be subject to population crashes caused by adverse environmental conditions and assumed to be limited.We re-examine published data in support of this hypothesis and show that there is alsoevidence of negative feedback between generations. Meta-analyses of annual count data fromindividual fields, and regional surveys provide further evidence of negative feedback and itis concluded that population regulation occurs at both local and regional scales. Evidencefrom other studies is used to propose that cannibalism is the causative mechanism. Sincesimilar negative feedback responses were apparent under both normal and environmentallylimiting conditions when populations crash, a single population model that could simulatethe differing regional dynamics observed from the annual surveys was produced. We concludethat the range of annual fluctuations observed in T. paludosa populations is the outcome ofboth limiting and regulating processes, confirming from field observations that these are notexclusive mechanisms.

This paper proposes a quantitative model of the reaction-diffusion type to examine thedistribution of interferon-α (IFNα) in a lymph node(LN). The numerical treatment of the model is based on using an original unstructured meshgeneration software Ani3D and nonlinear finite volume method for diffusion equations. Thestudy results in suggestion that due to the variations in hydraulic conductivity ofvarious zones of the secondary lymphoid organs the spatial stationary distribution ofIFNα is essentially heterogeneous across the organs. Highly protecteddomains such as sinuses, conduits, co-exist with the regions in which where the stationaryconcentration of IFNα is lower by about 100-fold. This is the first studywhere the spatial distribution of soluble immune factors in secondary lymphoid organs ismodelled for a realistic three-dimensional geometry.

Computational models for human decision making are typically based on the properties of bistable dynamical systems where each attractor represents a different decision. A limitation of these models is that they do not readily account for the fragilities of human decision making, such as “choking under pressure”, indecisiveness and the role of past experiences on current decision making. Here we examine the dynamics of a model of two interacting neural populations with mutual time–delayed inhibition. When the input to each population is sufficiently high, there is bistability and the dynamics is determined by the relationship of the initial function to the separatrix (the stable manifold of a saddle point) that separates the basins of attraction of two co–existing attractors. The consequences for decision making include long periods of indecisiveness in which trajectories are confined in the neighborhood of the separatrix and wrong decision making, particularly when the effects of past history and irrelevant information (“noise”) are included. Since the effects of delay, past history and noise on bistable dynamical systems are generic, we anticipate that similar phenomena will arise in the setting of other physical, chemical and neural time–delayed systems which exhibit bistability.

An exploratory study is performed to investigate the use of a time-dependent discreteadjoint methodology for design optimization of a high-lift wing configuration augmentedwith an active flow control system. The location and blowing parameters associated with aseries of jet actuation orifices are used as design variables. In addition, a geometricparameterization scheme is developed to provide a compact set of design variablesdescribing the wing shape. The scaling of the implementation is studied using severalthousand processors and it is found that asynchronous file operations can greatly improvethe overall performance of the approach in such massively parallel environments. Threedesign examples are presented which seek to maximize the mean value of the liftcoefficient for the coupled system, and results demonstrate improvements as high as 27%relative to the lift obtained with non-optimized actuation. This lift gain is more thanthree times the incremental lift provided by the non-optimized actuation.

The Asymptotic Numerical Method (ANM) is a family of algorithms, based on computation oftruncated vectorial series, for path following problems [2]. In this paper, we present anddiscuss some techniques to define local parameterization [4, 6, 7] in the ANM. We givesome numerical comparisons of pseudo arc-length parameterization and localparameterization on non-linear elastic shells problems

We prove the instability of threshold resonances and eigenvalues of the linearized NLSoperator. We compute the asymptotic approximations of the eigenvalues appearing from theendpoint singularities in terms of the perturbations applied to the original NLS equation.Our method involves such techniques as the Birman-Schwinger principle and the Feshbachmap.

In this paper several models in virus dynamics with and without immune response arediscussed concerning asymptotic behaviour. The case of immobile cells but diffusing viruses andT-cells is included. It is shown that, depending on the value of the basic reproductive number R0of the virus, the corresponding equilibrium is globally asymptotically stable. If R0 < 1 then thevirus-free equilibrium has this property, and in case R0 > 1 there is a unique disease equilibriumwhich takes over this property.