Variability and Correlations of Some Investigated Traits of Perennial Ryegrass Populations

Perennial ryegrass (Lolium perenne) is one of the most important perennial forage grasses for temperate climates. It is a highly productive grass with the highest nutritive value (Sokolovi et al., 2002). In Serbia, breeders have developed perennial ryegrass cultivars with high stabile yield and quality with different times of maturity and resistance to drought and frost. The initial breeding material were usually wild populations (Charmet et. al., 1996) with high variability and adaptability. These characteristics lend themselves for selection of superior genotypes. But breeding for some important agronomic traits may influence others. This relationship between traits and breeding population variability is the objective of this article

Linearization of multichannel amplifiers with the injection of second harmonics into the amplifier and predistortion circuit

A linearization technique that uses the injection of the fundamental signal second harmonics together with the fundamental signals at the amplifier input has been extended in this paper by introducing the injection the second harmonics into nonlinear microwave amplifier and so-called predistortion circuit. Predistortion circuit produces the third-order intermodulation signals that are injected at the amplifier input together with the second harmonics making the linearization procedure more independent on the phase variation of the second harmonics. In addition, a considerably better improvement is attained for the power of fundamental signals close to 1-dB compression point by applying the linearization technique proposed in this paper in comparison to the linearization with the injection of the second harmonics merely in the nonlinear amplifier

Coexistence of Superconductivity and Spin Density Wave orderings in the organic superconductor (TMTSF)_2PF_6

The phase diagram of the organic superconductor (TMTSF)_2PF_6 has been revisited using transport measurements with an improved control of the applied pressure. We have found a 0.8 kbar wide pressure domain below the critical point (9.43 kbar, 1.2 K) for the stabilisation of the superconducting ground state featuring a coexistence regime between spin density wave (SDW) and superconductivity (SC). The inhomogeneous character of the said pressure domain is supported by the analysis of the resistivity between T_SDW and T_SC and the superconducting critical current. The onset temperature T_SC is practically constant (1.20+-0.01 K) in this region where only the SC/SDW domain proportion below T_SC is increasing under pressure. An homogeneous superconducting state is recovered above the critical pressure with T_SC falling at increasing pressure. We propose a model comparing the free energy of a phase exhibiting a segregation between SDW and SC domains and the free energy of homogeneous phases which explains fairly well our experimental findings.Comment: 13 pages, 10 figures, revised v: fig.9 added, section 4.2 rewritten, accepted v: sections 4&5 improve

Influence of Quantum Hall Effect on Linear and Nonlinear Conductivity in the FISDW States of the Organic Conductor (TMTSF)_2PF_6

We report a detailed characterization of quantum Hall effect (QHE) influence on the linear and non-linear resistivity tensor in FISDW phases of the organic conductor (TMTSF)2PF6. We show that the behavior at low electric fields, observed for nominally pure single crystals with different values of the resistivity ratio, is fully consistent with a theoretical model, which takes QHE nature of FISDW and residual quasi-particle density associated with different crystal imperfection levels into account. The non-linearity in longitudinal and diagonal resistivity tensor components observed at large electric fields reconciles preceding contradictory results. Our theoretical model offers a qualitatively good explanation of the observed features if a sliding of the density wave with the concomitant destruction of QHE, switched on above a finite electric field, is taken into account.Comment: 8 pages, 6 figures, submitted to EPJ

A Feed-Forward Neural Network Approach for Energy-Based Acoustic Source Localization

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Efficient steplike carrier multiplication in percolative networks of epitaxially connected PbSe nanocrystals

Carrier multiplication (CM) is a process in which a single photon excites two or more electrons. CM is of interest to enhance the efficiency of a solar cell. Until now, CM in thin films and solar cells of semiconductor nanocrystals (NCs) has been found at photon energies well above the minimum required energy of twice the band gap. The high threshold of CM strongly limits the benefits for solar cell applications. We show that CM is more efficient in a percolative network of directly connected PbSe NCs. The CM threshold is at twice the band gap and increases in a steplike fashion with photon energy. A lower CM efficiency is found for a solid of weaker coupled NCs. This demonstrates that the coupling between NCs strongly affects the CM efficiency. According to device simulations, the measured CM efficiency would significantly enhance the power conversion efficiency of a solar cell

Energy-Based Acoustic Localization by Improved Elephant Herding Optimization

UIDB/EEA/50008/2020The present work proposes a new approach to address the energy-based acoustic localization problem. The proposed approach represents an improved version of evolutionary optimization based on Elephant Herding Optimization (EHO), where two major contributions are introduced. Firstly, instead of random initialization of elephant population, we exploit particularities of the problem at hand to develop an intelligent initialization scheme. More precisely, distance estimates obtained at each reference point are used to determine the regions in which a source is most likely to be located. Secondly, rather than letting elephants to simply wander around in their search for an update of the source location, we base their motion on a local search scheme which is found on a discrete gradient method. Such a methodology significantly accelerates the convergence of the proposed algorithm, and comes at a very low computational cost, since discretization allows us to avoid the actual gradient computations. Our simulation results show that, in terms of localization accuracy, the proposed approach significantly outperforms the standard EHO one for low noise settings and matches the performance of an existing enhanced version of EHO (EEHO). Nonetheless, the proposed scheme achieves this accuracy with significantly less number of function evaluations, which translates to greatly accelerated convergence in comparison with EHO and EEHO. Finally, it is also worth mentioning that the proposed methodology can be extended to any population-based metaheuristic method (it is not only restricted to EHO), which tackles the localization problem indirectly through distance measurements.publishersversionpublishe

Performance analysis of distributed control configurations in LQR multi-agent system design

The paper considers a distributed Linear Quadratic Regulator (LQR) design framework for a network of identical dynamically decoupled multi-agent systems. It is known that in this case a stabilizing distributed controller for the network can be obtained by solving a centralized LQR problem whose size depends on the maximum vertex degree of the graph. A systematic method is presented for computing the performance loss of various distributed control configurations relative to the performance of the centralized controller. A procedure is developed for analyzing the performance loss for general distributed control configurations and state-space directions. It is also shown that by removing a single link we can always define a control configuration for which there is no performance loss, provided the initial state of the aggregate system lies in a particular direction of state-space which is identified. The results are illustrated by an exhaustive analysis of the network consisting of six identical agents