Neural Networks for Synthesis and Optimization of Antenna Arrays

This paper describes a usual application of back-propagation neural networks for synthesis and optimization of antenna array. The neural network is able to model and to optimize the antennas arrays, by acting on radioelectric or geometric parameters and by taking into account predetermined general criteria. The neural network allows not only establishing important analytical equations for the optimization step, but also a great flexibility between the system parameters in input and output. This step of optimization becomes then possible due to the explicit relation given by the neural network. According to different formulations of the synthesis problem such as acting on the feed law (amplitude and/or phase) and/or space position of the radiating sources, results on antennas arrays synthesis and optimization by neural networks are presented and discussed. However ANN is able to generate very fast the results of synthesis comparing to other approaches

Effects due to a scalar coupling on the particle-antiparticle production in the Duffin-Kemmer-Petiau theory

The Duffin-Kemmer-Petiau formalism with vector and scalar potentials is used to point out a few misconceptions diffused in the literature. It is explicitly shown that the scalar coupling makes the DKP formalism not equivalent to the Klein-Gordon formalism or to the Proca formalism, and that the spin-1 sector of the DKP theory looks formally like the spin-0 sector. With proper boundary conditions, scattering of massive bosons in an arbitrary mixed vector-scalar square step potential is explored in a simple way and effects due to the scalar coupling on the particle-antiparticle production and localization of bosons are analyzed in some detail

Input Frequencies Optimization Based on Genetic Algorithm for Maximal Mutual Information

Among encountered problems in digital and analog communications, there is mismatch between canals and sources. As regards theory of information, unfortunately, this mismatch found expression in information loss during transfer to reception side. In order to settle the problem, the solution consists in adjustment of probability law at source so that we maximize the mean mutual information. For a little number of symbols, either at emission or at reception, the work can be done analytically with some difficulties. Unfortunately, the problem have tendency to become more and more difficult and complicated as number of symbols increases. In this case and as alternative, we propose a non-traditional optimization method, namely genetic algorithm, which will express, with regard to our problem, all its efficiency through this paper with some conclusive applications

Microstrip antennas array Design Using Genetic algorithms and Simulated Annealing

This publication presents two new approaches of design microstrip antennas array. First is based on the technique of the genetic algorithms inspired from the processes of the evolution of the species and the natural genetics and the second based on the analogy between the resolution of the combinative problems of optimization and the annealing of the solids. These two approaches permits to seek simultaneous the law of optimal feed and the space distribution of the radiant elements so that the radiation pattern is as close as possible to an optimal desired diagram specified from a function or a pattern shape.Cette publication présente deux nouvelles approches de conception de réseaux d'antennes imprimées. La première est basée sur la technique des algorithmes génétiques inspirée des processus de l'évolution des espèces et de la génétique naturelle et la deuxième sur l'analogie entre la résolution des problèmes d'optimisation combinatoire et le recuit des solides. Ces deux approches permettent de rechercher simultanément la loi d'alimentation optimale et la répartition spatiale des éléments rayonnants pour que le diagramme de directivité du réseau soit aussi proche que possible d'un diagramme désiré optimal spécifié à partir d'une fonction ou d'un gabarit

Lymph-migrating, tissue-derived dendritic cells are minor constituents within steady-state lymph nodes

Observations that dendritic cells (DCs) constitutively enter afferent lymphatic vessels in many organs and that DCs in some tissues, such as the lung, turnover rapidly in the steady state have led to the concept that a major fraction of lymph node DCs are derived from migratory DCs that enter the lymph node through upstream afferent lymphatic vessels. We used the lysozyme M–Cre reporter mouse strain to assess the relationship of lymph node and nonlymphoid organ DCs. Our findings challenge the idea that a substantial proportion of lymph node DCs derive from the upstream tissue during homeostasis. Instead, our analysis suggests that nonlymphoid organ DCs comprise a major population of DCs within lymph nodes only after introduction of an inflammatory stimulus

Klein's Paradox

We solve the one dimensional Feshbach-Villars equation for spin-1/2 particle subjected to a scalar smooth potential. The eight component wave function is given in terms of the hypergeometric functions and via a limiting procedure, the wave functions of the step potential are deduced. These wave functions are used to test the validity of the boundary conditions deduced from the Feshbach-Villars transformation. The creation of pairs is predicted from the boundary condition of the charge density.Comment: 18 pages, Latex, another title has been used in the published versio

Spectrum of the Relativistic Particles in Various Potentials

We extend the notion of Dirac oscillator in two dimensions, to construct a set of potentials. These potentials becomes exactly and quasi-exactly solvable potentials of non-relativistic quantum mechanics when they are transformed into a Schr\"{o}dinger-like equation. For the exactly solvable potentials, eigenvalues are calculated and eigenfunctions are given by confluent hypergeometric functions. It is shown that, our formulation also leads to the study of those potentials in the framework of the supersymmetric quantum mechanics

Mafb lineage tracing to distinguish macrophages from other immune lineages reveals dual identity of Langerhans cells

Current systems for conditional gene deletion within mouse macrophage lineages are limited by ectopic activity or low efficiency. In this study, we generated a Mafb-driven Cre strain to determine whether any dendritic cells (DCs) identified by Zbtb46-GFP expression originate from a Mafb-expressing population. Lineage tracing distinguished macrophages from classical DCs, neutrophils, and B cells in all organs examined. At steady state, Langerhans cells (LCs) were lineage traced but also expressed Zbtb46-GFP, a phenotype not observed in any other population. After exposure to house dust mite antigen, Zbtb46-negative CD64(+) inflammatory cells infiltrating the lung were substantially lineage traced, but Zbtb46-positive CD64(−) cells were not. These results provide new evidence for the unique identity of LCs and challenge the notion that some inflammatory cells are a population of monocyte-derived DCs

Glacial lake outburst flood risk in the Bolivian Andes

Glaciers of the Bolivian Andes have experienced areal shrinkage of _43% in the last three decades, which has been accompanied by the development of proglacial lakes, some of which could generate glacial lake outburst floods (GLOFs). We provide the first attempt to assess GLOF risk in Bolivia, and model potential GLOF inundation. There are _137 proglacial lakes in the Bolivian Andes, 25 of which have population and/or infrastructure downstream.We first developed a GLOF risk assessment strategy using Multi-Criteria Decision Analysis (MCDA) guidelines that could be used remotely and free-of-charge to identify glacial lakes that represent the greatest GLOF risk. This revealed that three lakes posed medium or high risk, and required further analysis. Secondly, we undertook a modelling study of potential GLOF inundation from these three lakes. This involved the generation of a 2m resolution Digital Elevation Model (DEM) from stereo and tri-stereo SPOT 6/7 satellite images; the 2D hydrodynamic model HEC-RAS 5.0.3 was used to model GLOF flow. The model was tested against field observations of a 2009 GLOF from Keara, in the Cordillera Apolobamba, and was shown to reproduce realistic flood depths and inundation. The model was then used to model GLOFs from Pelechuco lake (Cordillera Apolobamba), and Laguna Arkhata and Laguna Glaciar (Cordillera Real). In total, six villages could be affected by GLOFs if all three lakes were to burst. We ran the model for three scenarios (pessimistic, intermediate, optimistic) which give a range of 1589 and 2302 people affected by flooding; between 1107 and 2168 people would be exposed to damaging floods (flow depth _ 2m). We suggest that Laguna Arkhata and Pelechuco lake represent the greatest risk due to the higher numbers of people who live in the potential flood paths, and hence should be a priority for risk managers