Search and identification of Scalar and Vector Leptoquarks at HERA with polarization

We analyze the effects of Scalar and Vector Leptoquarks on various observables in electron (positron) - proton deep inelastic scattering. In view of the future program of the HERA collider, with a high luminosity and also with polarization, we present the constraints that can be reached using this facility for several Leptoquark scenarios. We address the question of the identification of the nature of a discovered Leptoquark. We emphasize the relevance of having polarized lepton and proton beams in order to disentangle completely the various Leptoquark models. This study is also relevant in the context of the TESLA$\times$HERA project.Comment: Version to appear in Eur.Phys.J.C. 3 typos have been correcte

A General Analytical Approximation to Impulse Response of 3-D Microfluidic Channels in Molecular Communication

In this paper, the impulse response for a 3-D microfluidic channel in the presence of Poiseuille flow is obtained by solving the diffusion equation in radial coordinates. Using the radial distribution, the axial distribution is then approximated accordingly. Since Poiseuille flow velocity changes with radial position, molecules have different axial properties for different radial distributions. We, therefore, present a piecewise function for the axial distribution of the molecules in the channel considering this radial distribution. Finally, we lay evidence for our theoretical derivations for impulse response of the microfluidic channel and radial distribution of molecules through comparing them using various Monte Carlo simulations.Comment: The manuscript is submitted to IEEE: Transactions on Nanobioscienc

Emitter Location Finding using Particle Swarm Optimization

Using several spatially separated receivers, nowadays positioning techniques, which are implemented to determine the location of the transmitter, are often required for several important disciplines such as military, security, medical, and commercial applications. In this study, localization is carried out by particle swarm optimization using time difference of arrival. In order to increase the positioning accuracy, time difference of arrival averaging based two new methods are proposed. Results are compared with classical algorithms and Cramer-Rao lower bound which is the theoretical limit of the estimation error

CMF-DFE Based Adaptive Blind Equalization Using Particle Swarm Optimization

The channel matched filter (CMF) is the optimum receiver providing the maximum signal to noise ratio (SNR) for the frequency selective channels. The output intersymbol interference (ISI) profile of the CMF convolved by the channel can be blindly obtained by using the autocorrelation of the received signal. Therefore, the inverse of the autocorrelation function can be used to equalize the channel passed through its own CMF. The only missing part to complete the proposed blind operation is the CMF coefficients. Therefore, in this work, the best training algorithm investigation is subjected for blind estimation of the CMF coefficients. The proposed method allows using more effective training algorithms for blind equalizations. However, the expected high performance training is obtained when the swarm intelligence is used. Unlike the stochastic gradient algorithms, the particle swarm optimization (PSO) is known to have fast convergence because its performance is independent of the characteristics of the systems used. The obtained mean square error (MSE) and bit error rate (BER) performances are promising for high performance real-time systems as an alternative to non-blind equalization techniques