Measurements of Grain Motion in a Dense, Three-Dimensional Granular Fluid

We have used an NMR technique to measure the short-time, three-dimensional displacement of grains in a system of mustard seeds vibrated vertically at 15g. The technique averages over a time interval in which the grains move ballistically, giving a direct measurement of the granular temperature profile. The dense, lower portion of the sample is well described by a recent hydrodynamic theory for inelastic hard spheres. Near the free upper surface the mean free path is longer than the particle diameter and the hydrodynamic description fails.Comment: 4 pages, 4 figure

Gaussian Process priors with uncertain inputs? Application to multiple-step ahead time series forecasting

We consider the problem of multi-step ahead prediction in time series analysis using the non-parametric Gaussian process model. k-step ahead forecasting of a discrete-time non-linear dynamic system can be performed by doing repeated one-step ahead predictions. For a state-space model of the form y t = f(Yt-1 ,..., Yt-L ), the prediction of y at time t + k is based on the point estimates of the previous outputs. In this paper, we show how, using an analytical Gaussian approximation, we can formally incorporate the uncertainty about intermediate regressor values, thus updating the uncertainty on the current prediction

The essential oil of Thymbra capitata and its application as a biocide on stone and derived surfaces

Many chemicals used nowadays for the preservation of cultural heritage pose a risk to both human health and the environment. Thus, it is desirable to find new and eco-friendly biocides that can replace the synthetic ones. In this regard, plant essential oils represent effective alternatives to synthetic substances for the preservation of historical monuments. Thymbra capitata (syn. Thymus capitatus) is a medicinal and aromatic plant growing in the Mediterranean area and endowed with important pharmacological properties related to its essential oil. Among them, the antimicrobial ones make the T. capitata essential oil an ideal candidate for industrial applications; for instance, as biocide for the inhibition and elimination of biological patinas of cyanobacteria and green algae on historical monuments. In the present work, we studied the chemical composition of the essential oil from T. capitata growing in Malta by gas chromatography-mass spectrometry (GC/MS). The major volatile component is the phenolic monoterpene carvacrol (73.2%), which is capable of damaging the cytoplasmic membrane and to interfere both in the growth curve and in the invasive capacity, though the contribution of minor components γ-terpinene and p-cymene cannot be disregarded. For the oil application on the stone surface, Pickering emulsions systems were prepared with an essential oil/water 1:3 mass ratio stabilized with kaolinite at 4 mass% in the presence of Laponite®; this allowed to limit the fast volatility of the oil and guaranteed a better application and an easier removal from the artefacts attacked by biodeteriogens both indoor and outdoor. This formulation caused the elimination of biodeteriogens from treated surfaces without residuals or films on artworks surface, and the effect was retained up to four months

On the completeness of impulsive gravitational wave space-times

We consider a class of impulsive gravitational wave space-times, which generalize impulsive pp-waves. They are of the form $M=N\times\mathbb{R}^2_1$, where $(N,h)$ is a Riemannian manifold of arbitrary dimension and $M$ carries the line element $ds^2=dh^2+ 2dudv+f(x)\delta(u)du^2$ with $dh^2$ the line element of $N$ and $\delta$ the Dirac measure. We prove a completeness result for such space-times $M$ with complete Riemannian part $N$.Comment: 13 pages, minor changes suggested by the referee

Probabilistic movement modeling for intention inference in human-robot interaction.

Intention inference can be an essential step toward efficient humanrobot interaction. For this purpose, we propose the Intention-Driven Dynamics Model (IDDM) to probabilistically model the generative process of movements that are directed by the intention. The IDDM allows to infer the intention from observed movements using Bayes ’ theorem. The IDDM simultaneously finds a latent state representation of noisy and highdimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human-robot interaction scenarios, i.e., target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.

Córdoba taurina : apuntes biográficos de matadores, banderilleros, picadores, puntilleros, maletas, ganaderos, propietarios de plazas, empresarios, aficionados, revisteros y escritores taurinos antig..uos y modernos

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2011Del texto se deduce impreso con posterioridad a 189