Steady flow in the Willis circle using a Quemada model

The paper presents new results on the dynamics of blood flow in the Willis circle, by taking into account the non-Newtonian nature of the blood through a Quemada model. In previous papers we performed a steady analysis of the blood flow in the Willis polygon, by considering the blood as a Newtonian fluid. In hemodynamics this is the first step, while taking into account the non-Newtonian behaviour of the fluid is called a second order approach. This is in fact the aim of our paper, to compare the results (blood flow rates and pressures) obtained in a non-Newtonian approach with those furnished by a Newtonian modeling of the blood. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive,Delayed-Acceptance MCMC for Targets With Expensive Likelihoods

When conducting Bayesian inference, delayed-acceptance (DA) Metropolis–Hastings (MH) algorithms and DA pseudo-marginal MH algorithms can be applied when it is computationally expensive to calculate the true posterior or an unbiased estimate thereof, but a computationally cheap approximation is available. A first accept-reject stage is applied, with the cheap approximation substituted for the true posterior in the MH acceptance ratio. Only for those proposals that pass through the first stage is the computationally expensive true posterior (or unbiased estimate thereof) evaluated, with a second accept-reject stage ensuring that detailed balance is satisfied with respect to the intended true posterior. In some scenarios, there is no obvious computationally cheap approximation. A weighted average of previous evaluations of the computationally expensive posterior provides a generic approximation to the posterior. If only the k-nearest neighbors have nonzero weights then evaluation of the approximate posterior can be made computationally cheap provided that the points at which the posterior has been evaluated are stored in a multi-dimensional binary tree, known as a KD-tree. The contents of the KD-tree are potentially updated after every computationally intensive evaluation. The resulting adaptive, delayed-acceptance [pseudo-marginal] Metropolis–Hastings algorithm is justified both theoretically and empirically. Guidance on tuning parameters is provided and the methodology is applied to a discretely observed Markov jump process characterizing predator–prey interactions and an ODE system describing the dynamics of an autoregulatory gene network. Supplementary material for this article is available online.     

Performance modeling and analysis of integrated logistic chains: An analytic framework

This paper is geared toward developing a network of inventory-queue models for the performance modeling and analysis of an integrated logistic network. An inventory-queue is a queueing model that incorporates an inventory replenishment policy for a store, which is a basic modeling element for an integrated logistic network. To achieve this objective, first, this paper presents an analytical modeling framework for integrated logistic chains, in which the interdependencies between model components are captured. Second, a network of inventory-queue models for performance analysis of an integrated logistic network with inventory control at all sites is developed. Then this paper extends the previous work done on the supply network model with base-stock control and service requirements. Instead of one-for-one base stock policy, batch-ordering policy and lot-sizing problems are considered. In practice, the assumption of uncapacitated production is often not true, therefore, GI^x/G/1 queueing analysis is used to replace the M^x/G/∞ queue based method. To include lot-sizing issue in the analysis of stores, a fixed-batch target-level production authorization mechanism is employed to explicitly obtain performance measures of the logistic chain queueing model. The validity of the proposed model is illustrated by comparing the results from the analytical performance evaluation model and those obtained from the simulation study.     

A Performance evaluation of neural network models in traffic volume forecasting

Forecasting traffic volume is an important task in controlling urban highways, guiding drivers' routes, and providing real-time transportation information. Previous research on traffic volume forecasting has concentrated on a single forecasting model and has reported positive results, which has been frequently better than those of other models. In addition, many previous researchers have claimed that neural network models are better than linear statistical models in terms of prediction accuracy. However, the forecasting power of a single model is limited to the typical cases to which the model fits best. In other words, even though many research efforts have claimed the general superiority of a single model over others in predicting future events, we believe it depends on the data characteristics used, the composition of the training data, the model architecture, and the algorithm itself.In this paper, we have studied the relationship in forecasting traffic volume between data characteristics and the forecasting accuracy of different models, particularly neural network models. To compare and test the forecasting accuracy of the models, three different data sets of traffic volume were collected from interstate highways, intercity highways, and urban intersections. The data sets show very different characteristics in terms of volatility, period, and fluctuations as measured by the Hurst exponent, the correlation dimension. The data sets were tested using a back-propagation network model, a FIR model, and a time-delayed recurrent model.The test results show that the time-delayed recurrent model outperforms other models in forecasting very randomly moving data described by a low Hurst exponent. In contrast, the FIR model shows better forecasting accuracy than the time-delayed recurrent network for relatively regular periodic data described by a high Hurst exponent. The interpretation of these results shows that the feedback mechanism of the previous error, through the temporal learning technique in the time-delayed recurrent network, naturally absorbs the dynamic change of any underlying nonlinear movement. The FIR and back-propagation model, which have claimed a nonlinear learning mechanism, may not be very good in handling randomly fluctuating events.     

Coupled wetting meniscus model for the mechanism of spontaneous capillary action

Capillarity plays a significant role in many natural and artificial processes, but the mechanism responsible for its dynamics is not completely understood. In this study, we consider capillary flow characteristics and propose a coupled wetting meniscus model for the mechanism of spontaneous capillary action. In this model, capillary action is considered as the dynamic coupling of two interfacial forces, i.e., the wall wetting force at the contact line and the meniscus restoring force on the free interface. The wetting force promotes the motion of the contact line directed toward an equilibrium contact angle, whereas the meniscus restoring force promotes a reduction in the interface curvature, which is more consistent with a 90° contact angle. The competing interaction between these two forces is coupled together via the evolution of the interface shape. The model is then incorporated into a finite volume method for a two-fluid flow with an interface. Capillary flow experiments were performed, including vertical and horizontal flows. Phenomena analysis and data comparisons were conducted to verify the proposed model. According to the results of our study, the model can explain the capillary flow process well and it can be also used to accurately guide capillary flow calculations.     

A physically-based fractional diffusion model for semi-dilute suspensions of rods in a Newtonian fluid

The rheological behavior of suspensions involving interacting (functionalized) rods remains nowadays incompletely understood, in particular with regard to the evolution of the elastic modulus with the applied frequency in small-amplitude oscillatory flows. In a previous work, we addressed this issue by assuming a fractional diffusion mechanism, however the approach followed was purely phenomenological. The present work revisits the topic from a physical viewpoint, with the aim of justifying the fractional nature of diffusion. After accomplishing this first objective, we explore by means of numerical experiments the consequences of the proposed fractional modeling approach in linear and non-linear rheology.     

Stability of the bicarbonate system in the blood

In this paper, we describe a mathematical model about the reaction-diffusion kinetics of bicarbonate system, which it plays a key role in regulating blood pH. It is very important to know the determinants of blood pH in both experimental and theoretical studies, in order to help to investigate the hidden mechanism of acid-base disorders in the clinical setting. We explore the dynamics of the bicarbonate system under the closed condition. This condition yields that the total amount of carbon dioxide is conserved and the difference in concentrations between anions and cations is conserved. For the stability of the model, we hypothesize that the amount of initial concentrations perturbed around an equilibrium point is less than a certain constant depending on a rate constant. With an application of Liapunov's method, we prove that the model in the form of reaction-diffusion system is globally stable under the hypothesis. We also provide the blood pH profile, which is computed in our model with the experimentally observed rate constants.     

Using Dynamic Geometry Software to Simulate Physical Motion

In this paper we analyse to what extent the computational model of the geometry implemented in a dynamic geometry environment provides models for physical motion, focusing on the continuity issues related to motion. In particular, we go over the utility of dynamic geometry environments to simulate the motion of mechanical linkages, as this activity allows us to compare, by means of dynamic drawings, the computable representation of geometric properties with the real motion of a mechanism. Analysing a simple example, we provide theoretical foundations for particular behaviours observed in the motion of a picture on the screen, which require a subtle interpretation to be understood in a purely physical context. In this way, we reflect on some requirements imposed by the computable representation of knowledge. We consider this work to be a necessary step to determine didactic consequences related to students' perceptions of the moving displays; in particular those concerning the uses of the dragging mode as a tool not only for automatic drawing of many instances of a construction,but also to produce continuous motion. This revised version was published online in July 2006 with corrections to the Cover Date.     

The density based access method: A novel approach to optimizing run-time throughput for IEEE 802.11 DCF access control

According to previous work, the performance of the Distributed Coordination Function (DCF) (i.e., the basic access method of the IEEE 802.11 protocol) is far from optimum due to use of the binary exponential backoff (BEB) scheme as its collision avoidance mechanism. There has been considerable discussion of DCF issues and its performance analysis. However, most schemes assume an ideal channel, which is contrary to realistic wireless environments. In this paper, we present a simple yet pragmatic distributed algorithm, designated the density based access method (DBM), which allows stations to dynamically optimize the network throughput based on run-time measurements of the channel status. Our simulation results demonstrate that the DBM is highly accurate. The performance in terms of throughput and fairness is nearly optimal by use of the proposed scheme.     

A remark on the Kazhikhov–Smagulov type model: The vanishing initial density

This work deals with the global existence of weak solutions for a Kazhikhov–Smagulov type system with a density which may or not vanish. Our model is formally equivalent to the physical compressible model with Fick’s law, in contrast to those in previous works. This model may be used for addressing environmental problems such as propagation of pollutants and avalanche modelling. We also explain why this system may be seen as a physical regularization of the standard nonhomogeneous incompressible Navier–Stokes equations and we give an existence result with an initial density less regular but away from the vacuum.     

Heuristic algorithms for delivered price spatially competitive network facility location problems

We review previous formulations of models for locating a firm's production facilities while simultaneously determining production levels at those facilities so as to maximize the firm's profit. We enhance these formulations by adding explicit variables to represent the firm's shipping activities and discuss the implications of this revised approach. In these formulations, existing firms, as well as new entrants, are assumed to act in accordance with an appropriate model of spatial equilibrium. The firm locating new production facilities is assumed to be a large manufacturer entering an industry composed of a large number of small firms. Our previously reported proof of existence of a solution to the combined location-equilibrium problem is briefly reviewed. A heuristic algorithm based on sensitivity analysis methods which presume the existence of a solution and which locally approximate price changes as linear functions of production perturbations resulting from newly established facilities is presented. We provide several numerical tests to illustrate the contrasting locational solutions which this paper's revised delivered price formulation generates relative to those of previous formulations. An exact, although computationally burdensome, method is also presented and employed to check the reliability of the heuristic algorithm.     

Axiomatizations of the Shapley value for games on augmenting systems

This paper deals with cooperative games in which only certain coalitions are allowed to form. There have been previous models developed to confront the problem of unallowable coalitions. Games restricted by a communication graph were introduced by Myerson and Owen. In their model, the feasible coalitions are those that induce connected subgraphs. Another type of model is introduced in Gilles, Owen and van den Brink. In their model, the possibilities of coalition formation are determined by the positions of the players in a so-called permission structure. Faigle proposed another model for cooperative games defined on lattice structures. We introduce a combinatorial structure called augmenting system which is a generalization of the antimatroid structure and the system of connected subgraphs of a graph. In this framework, the Shapley value of games on augmenting systems is introduced and two axiomatizations of this value are showed.     

Tuning distributed control algorithms for optimal functioning

In this paper, we present a model which characterizes distributed computing algorithms. The goals of this model are to offer an abstract representation of asynchronous and heterogeneous distributed systems, to present a mechanism for specifying externally observable behaviours of distributed processes and to provide rules for combining these processes into networks with desired properties (good functioning, fairness...). Once these good properties are found, the determination of the optimal rules are studied.Subsequently, the model is applied to three classical distributed computing problems: namely the dining philosophers problem, the mutual exclusion problem and the deadlock problem, (generalizing results of our previous publications [1], [2]). The property of fairness has a special position that we discuss.     

Zero-sum stochastic games with average payoffs: New optimality conditions

In this paper we study zero-sum stochastic games. The optimality criterion is the long-run expected average criterion, and the payoff function may have neither upper nor lower bounds. We give a new set of conditions for the existence of a value and a pair of optimal stationary strategies. Our conditions are slightly weaker than those in the previous literature, and some new sufficient conditions for the existence of a pair of optimal stationary strategies are imposed on the primitive data of the model. Our results are illustrated with a queueing system, for which our conditions are satisfied but some of the conditions in some previous literatures fail to hold.     

Motion measurement of a two-wheeled skateboard and its dynamical simulation

This study investigates the dynamics of the propulsion mechanism of a two-wheeled skateboard by measurements of human skateboard motion and computer simulations using a simplified model. This model expresses the board motion within the horizontal plane. The inputs of the model are the yaw moment about a vertical axis, horizontal force normal to the skateboard axis, and two-wheel orientations, while the outputs are the center of mass position in the horizontal plane and the board orientation. By selecting parameters of sinusoidal inputs to fit the measurement data, similar output data is obtained from the motion measurements and computer simulations. This result allows us to conclude that some sinusoidal motions and forces can robustly propel this type of skateboard.     

Like family: Network coevolution and the emergence of altruism

Altruism is difficult to explain in an evolutionary context—the mechanisms of selection appear to favor selfishness. Existing scholarly work addressing this puzzle relies on structural and behavioral assumptions that severely limit generalizability. The model presented in this article circumvents the need for such assumptions by incorporating an evolving network component to natural selection. Through a process of coevolution of individual and relational traits, many of the exogenous assumptions of previous models of the evolution of cooperation are realized endogenously within a simulated population. Such endogeneity allows a more precise examination of conditions under which cooperation arises, but also a clearer understanding of how those conditions themselves arise. The model is specified analytically, and interpretation is carried out on simulated outcomes.     

Energy harvesting through arterial wall deformation: A FEM approach to fluid–structure interactions and magneto-hydrodynamics

Engineers are confronted with the energy demand of active medical implants in patients with increasing life expectancy. Scavenging energy from the patient’s body is envisioned as an alternative to conventional power sources. Joining in this effort towards human-powered implants, we propose an innovative concept that combines the deformation of an artery resulting from the arterial pressure pulse with a transduction mechanism based on magneto-hydrodynamics. To overcome certain limitations of a preliminary analytical study on this topic, we demonstrate here a more accurate model of our generator by implementing a three-dimensional multiphysics finite element method (FEM) simulation combining solid mechanics, fluid mechanics, electric and magnetic fields as well as the corresponding couplings. This simulation is used to optimize the generator with respect to several design parameters. A first validation is obtained by comparing the results of the FEM simulation with those of the analytical approach adopted in our previous study. With an expected overall conversion efficiency of 20% and an average output power of 30 μW, our generator outperforms previous devices based on arterial wall deformation by more than two orders of magnitude. Most importantly, our generator provides sufficient power to supply a cardiac pacemaker.     

A multi-agent model describing self-renewal of differentiation effects on the blood cell population

In this work, a new multi-agent model is used to describe blood cell population dynamics. More particularly, we focus our simulations here on differentiation and self-renewal process based on cell communication. We consider the different cases where progenitor cells are able to self-renew or not in the bone marrow. As a consequence of this study, we give some possible explanations of the mechanism for recovery of the system under important blood loss or blood diseases such as anemia.