Ancient DNA from Hunter-Gatherer and Farmer Groups from Northern Spain Supports a Random Dispersion Model for the Neolithic Expansion into Europe

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A Data Dropout Compensation Algorithm Based on the Iterative Learning Control Methodology for Discrete-Time Systems

This paper deals with the convergence of a remote iterative learning control system subject to data dropouts. The system is composed by a set of discrete-time multiple input-multiple output linear models, each one with its corresponding actuator device and its sensor. Each actuator applies the input signals vector to its corresponding model at the sampling instants and the sensor measures the output signals vector. The iterative learning law is processed in a controller located far away of the models so the control signals vector has to be transmitted from the controller to the actuators through transmission channels. Such a law uses the measurements of each model to generate the input vector to be applied to its subsequent model so the measurements of the models have to be transmitted from the sensors to the controller. All transmissions are subject to failures which are described as a binary sequence taking value 1 or 0. A compensation dropout technique is used to replace the lost data in the transmission processes. The convergence to zero of the errors between the output signals vector and a reference one is achieved as the number of models tends to infinity.

Dispersion of gamma-Alumina Nano-Sized Spherical Particles in a Calamitic Liquid Crystal. Study and Optimization of the Confinement Effects

We report an experimental study on confined systems formed by butyloxybenzylidene octylaniline liquid crystal (4O.8) + gamma-alumina nanoparticles. The effects of the confinement in the thermal and dielectric properties of the liquid crystal under different densities of nanoparticles is analyzed by means of high resolution Modulated Differential Scanning Calorimetry (MDSC) and broadband dielectric spectroscopy. First, a drastic depression of the N-I and SmA-N transition temperatures is observed with confinement, the more concentration of nanoparticles the deeper this depression is, driving the nematic range closer to the room temperature. An interesting experimental law is found for both transition temperatures. Second, the change in shape of the heat capacity peaks is quantified by means of the full width half maximum (FWHM). Third, the confinement does not noticeably affect the molecular dynamics. Finally, the combination of nanoparticles and the external applied electric field tends to favor the alignment of the molecules in metallic cells. All these results indicate that the confinement of liquid crystals by means of gamma-alumina nanoparticles could be optimum for liquid crystal-based electrooptic devices.