Cross-entropy optimization for scaling factors of a fuzzy controller: a see-and-avoid approach for unmanned aerial systems

The Cross-Entropy (CE) is an efficient method for the estimation of rare-event probabilities and combinatorial optimization. This work presents a novel approach of the CE for optimization of a Soft-Computing controller. A Fuzzy controller was designed to command an unmanned aerial system (UAS) for avoiding collision task. The only sensor used to accomplish this task was a forward camera. The CE is used to reach a near-optimal controller by modifying the scaling factors of the controller inputs. The optimization was realized using the ROS-Gazebo simulation system. In order to evaluate the optimization a big amount of tests were carried out with a real quadcopter.

Statistical distributions obtained from the compression of monodisperse, soft and frictionless particles

The cyclic compression of several granular systems has been simulated with a molecular dynamics code. All the samples consisted of bidimensional, soft, frictionless and equal-sized particles that were initially arranged according to a squared lattice and were compressed by randomly generated irregular walls. The compression protocols can be described by some control variables (volume or external force acting on the walls) and by some dimensionless factors, that relate stiffness, density, diameter, damping ratio and water surface tension to the external forces, displacements and periods. Each protocol, that is associated to a dynamic process, results in an arrangement with its own macroscopic features: volume (or packing ratio), coordination number, and stress; and the differences between packings can be highly significant. The statistical distribution of the force-moment state of the particles (i.e. the equivalent average stress multiplied by the volume) is analyzed. In spite of the lack of a theoretical framework based on statistical mechanics specific for these protocols, it is shown how the obtained distributions of mean and relative deviatoric force-moment are. Then it is discussed on the nature of these distributions and on their relation to specific protocols.

Jasmonate-dependent modifications of the pectin matrix during potato development function as a defense mechanism targeted by Dickeya dadantii virulence factors

The plant cell wall constitutes an essential protection barrier against pathogen attack. In addition, cell-wall disruption leads to accumulation of jasmonates (JAs), which are key signaling molecules for activation of plant inducible defense responses. However, whether JAs in return modulate the cell-wall composition to reinforce this defensive barrier remains unknown. The enzyme 13-allene oxide synthase (13-AOS) catalyzes the first committed step towards biosynthesis of JAs. In potato (Solanum tuberosum), there are two putative St13-AOS genes, which we show here to be differentially induced upon wounding. We also determine that both genes complement an Arabidopsis aos null mutant, indicating that they encode functional 13-AOS enzymes. Indeed, transgenic potato plants lacking both St13-AOS genes (CoAOS1/2 lines) exhibited a significant reduction of JAs, a concomitant decrease in wound-responsive gene activation, and an increased severity of soft rot disease symptoms caused by Dickeya dadantii. Intriguingly, a hypovirulent D. dadantii pel strain lacking the five major pectate lyases, which causes limited tissue maceration on wild-type plants, regained infectivity in CoAOS1/2 plants. In line with this, we found differences in pectin methyl esterase activity and cell-wall pectin composition between wild-type and CoAOS1/2 plants. Importantly, wild-type plants had pectins with a lower degree of methyl esterification, which are the substrates of the pectate lyases mutated in the pel strain. These results suggest that, during development of potato plants, JAs mediate modification of the pectin matrix to form a defensive barrier that is counteracted by pectinolytic virulence factors from D. dadantii.