Linear-Linear Basis Functions for MLFMA Solutions of Magnetic-Field and Combined-Field Integral Equations

We present the linear-linear (LL) basis functions to improve the accuracy of the magnetic-field integral equation (MFIE) and the combined-field integral equation (CFIE) for three-dimensional electromagnetic scattering problems involving closed conductors. We consider the solutions of relatively large scattering problems by employing the multilevel fast multipole algorithm. Accuracy problems of MFIE and CFIE arising from their implementations with the conventional Rao-Wilton-Glisson (RWG) basis functions can be mitigated by using the LL functions for discretization. This is achieved without increasing the computational requirements and with only minor modifications in the existing codes based on the RWG functions     

The Evolving Role of Fetuin-A in Nonalcoholic Fatty Liver Disease: An Overview from Liver to the Heart

Nonalcoholic fatty liver disease (NAFLD) is strongly associated to the features of metabolic syndrome which can progress to cirrhosis, liver failure and hepatocellular carcinoma. However, the most common cause of mortality in people with NAFLD is not liver-related but stems from atherosclerotic cardiovascular disease (CVD). The prevalence of NAFLD is on the rise, mainly as a consequence of its close association with two major worldwide epidemics, obesity and type 2 diabetes (T2D). The exact pathogenesis of NAFLD and especially the mechanisms leading to disease progression and CVD have not been completely elucidated. Human fetuin-A (alpha-2-Heremans Schmid glycoprotein), a glycoprotein produced by the liver and abundantly secreted into the circulation appears to play a role in insulin resistance, metabolic syndrome and inflammation. This review discusses the links between NAFLD and CVD by specifically focusing on fetuin-A’s function in the pathogenesis of NAFLD and atherosclerotic CVD.     

Matrix approach to deadlock-free dispatching in multi-class finite buffer flowlines

For finite-buffer manufacturing systems, the major stability issue is "deadlock," rather than "bounded-buffer-length stability." The paper introduces the concept of "system deadlock," defined rigorously in Petri net terms, and system operation with uninterrupted part-flow is characterized in terms of the absence of this condition. For a large class of finite-buffer multiclass re-entrant flowline systems, an analysis of "circular waits" yields necessary and sufficient conditions for the occurrence of "system deadlock." This allows the formulation of a maximally permissive one-step-look-ahead deadlock-avoidance control policy for dispatching jobs, while maximizing the percent utilization of resources. The result is a generalized kanban dispatching strategy, which is more general than the standard multiclass last buffer first serve (LBFS) dispatching strategies for finite buffer flowlines that typically under-utilize the resources. The problem of computational complexity associated with Petri net (PN) applications is overcome by using certain sub-matrices of the PN incidence matrix. Computationally efficient matrix techniques are given for implementing the deadlock-free dispatching policy.     

Usage of bioactivated PCL nanofiber as a fluoxetine capturing matrix in milk

ABSTRACT

In this study, for the first time, polycaprolactone (PCL) nanofiber matrix was bioactivated for the removal of fluoxetine from milk. Bioactivated nanofiber was prepared by immobilizing fluoxetine antibody on PCL nanofiber matrix. The fluoxetine removal efficiency of bioactivated nanofiber in milk was found to be approximately 93.6%. This removal did not significantly change the biochemical composition of milk. In conclusion, as a novel product, bioactivated nanofibrous PCL matrix can be used for the removal of drugs or unwanted chemicals from breast milk or from other fluids.     

A layered approach to learning coordination knowledge in multiagent environments

Multiagent learning involves acquisition of cooperative behavior among intelligent agents in order to satisfy the joint goals. Reinforcement Learning (RL) is a promising unsupervised machine learning technique inspired from the earlier studies in animal learning. In this paper, we propose a new RL technique called the Two Level Reinforcement Learning with Communication (2LRL) method to provide cooperative action selection in a multiagent environment. In 2LRL, learning takes place in two hierarchical levels; in the first level agents learn to select their target and then they select the action directed to their target in the second level. The agents communicate their perception to their neighbors and use the communication information in their decision-making. We applied 2LRL method in a hunter-prey environment and observed a satisfactory cooperative behavior. Guray Erus received the B.S. degree in computer engineering in 1999, and the M.S. degree in cognitive sciences, in 2002, from Middle East Technical University (METU), Ankara, Turkey. He is currently a teaching and research assistant in Rene“ Descartes University, Paris, France, where he prepares a doctoral dissertation on object detection on satellite images, as a member of the intelligent perception systems group (SIP-CRIP5). His research interests include multi-agent systems and image understanding. Faruk Polat is a professor in the Department of Computer Engineering of Middle East Technical University, Ankara, Turkey. He received his B.Sc. in computer engineering from the Middle East Technical University, Ankara, in 1987 and his M.S. and Ph.D. degrees in computer engineering from Bilkent University, Ankara, in 1989 and 1993, respectively. He conducted research as a visiting NATO science scholar at Computer Science Department of University of Minnesota, Minneapolis in 1992–93. His research interests include artificial intelligence, multi-agent systems and object oriented data models.     

Fast and accurate solutions of extremely large integral-equation problems discretised with tens of millions of unknowns

The solution of extremely large scattering problems that are formulated by integral equations and discretised with tens of millions of unknowns is reported. Accurate and efficient solutions are performed by employing a parallel implementation of the multilevel fast multipole algorithm. The effectiveness of the implementation is demonstrated on a sphere problem containing more than 33 million unknowns, which is the largest integral-equation problem ever solved to our knowledge     

Resonant frequency of an air gap tuned circular disc microstrip antenna

In this study, the formulation and the computation of the resonant frequency of an air gap tuned circular disc microstrip antenna are simplified, with improved accuracy, by using a new and very simple effective permittivity expression which is valid for thin and thick gaps. Very good agreement between the theoretical and the experimental resonant frequency values is obtained for the various structural parameters and operational modes.     

An efficient and accurate technique for the incident-waveexcitations in the FDTD method

An efficient technique to improve the accuracy of the finite-difference time-domain (FDTD) solutions employing incident-wave excitations is developed. In the separate-field formulation of the FDTD method, any incident wave may be efficiently introduced to the three-dimensional (3-D) computational domain by interpolating from a one-dimensional (1-D) incident-field array (IFA), which is a 1-D FDTD grid simulating the propagation of the incident wave. By considering the FDTD computational domain as a sampled system and the interpolation operation as a decimation process, signal-processing techniques are used to identify and ameliorate the errors due to aliasing. The reduction in the error is demonstrated for various cases. This technique can be used for the excitation of the FDTD grid by any incident wave. A fast technique is used to extract the amplitude and the phase of a sampled sinusoidal signal     

Stabilization of Integral-Equation Formulations for the Accurate Solution of Scattering Problems Involving Low-Contrast Dielectric Objects

The solution of scattering problems involving low-contrast dielectric objects with three-dimensional arbitrary shapes is considered. Using the traditional forms of the surface integral equations, scattered fields cannot be calculated accurately if the contrast of the object is low. Therefore, we consider the stabilization of the formulations by extracting the nonradiating parts of the equivalent currents. We also investigate various types of stable formulations and show that accuracy can be improved systematically by eliminating the identity terms from the integral-equation kernels. Traditional and stable formulations are compared, not only for small scatterers but also for relatively large problems solved by employing the multilevel fast multipole algorithm. Stable and accurate solutions of dielectric contrasts as low as 10^-4 are demonstrated on problems involving more than 250000 unknowns.