Abelian extensions of semisimple graded CR algebras

In this paper we take up the problem of describing the CR vector bundles M over compact standard CR manifolds S, which are themselves standard CR manifolds. They are associated to special graded Abelian extensions of semisimple graded CR algebras.Comment: 25 pages, 5 figure

Mapping the spatial variation of soil moisture at the large scale using GPR for pavement applications

The characterization of shallow soil moisture spatial variability at the large scale is a crucial issue in many research studies and fields of application ranging from agriculture and geology to civil and environmental engineering. In this framework, this work contributes to the research in the area of pavement engineering for preventing damages and planning effective management. High spatial variations of subsurface water content can lead to unexpected damage of the load-bearing layers; accordingly, both safety and operability of roads become lower, thereby affecting an increase in expected accidents. A pulsed ground-penetrating radar system with ground-coupled antennas, i.e., 600-MHz and 1600-MHz center frequencies of investigation, was used to collect data in a 16 m × 16 m study site in the Po Valley area in northern Italy. Two ground-penetrating radar techniques were employed to non-destructively retrieve the subsurface moisture spatial profile. The first technique is based on the evalu¬ation of the dielectric permittivity from the attenuation of signal amplitudes. Therefore, dielectrics were converted into moisture values using soil-specific coefficients from Topp’s relationship. Ground-penetrating-radar-derived values of soil moisture were then compared with measurements from eight capacitance probes. The second technique is based on the Rayleigh scattering of the signal from the Fresnel theory, wherein the shifts of the peaks of frequency spectra are assumed comprehensive indi¬cators for characterizing the spatial variability of moisture. Both ground-penetrating radar methods have shown great promise for mapping the spatial variability of soil moisture at the large scale

The CR structure of minimal orbits in complex flag manifolds

Let \^G be a complex semisimple Lie group, Q a parabolic subgroup and G a real form of \^G. The flag manifold \^G/Q decomposes into finitely many G-orbits; among them there is exactly one orbit of minimal dimension, which is compact. We study these minimal orbits from the point of view of CR geometry. In particular we characterize those minimal orbits that are of finite type and satisfy various nondegeneracy conditions, compute their fundamental group and describe the space of their global CR functions. Our main tool are parabolic CR algebras, which give an infinitesimal description of the CR structure of minimal orbits.Comment: AMS-TeX, 44 pages v2: minor revisio

miMic: The microphone as a pencil

miMic, a sonic analogue of paper and pencil is proposed: An augmented microphone for vocal and gestural sonic sketching. Vocalizations are classified and interpreted as instances of sound models, which the user can play with by vocal and gestural control. The physical device is based on a modified microphone, with embedded inertial sensors and buttons. Sound models can be selected by vocal imitations that are automatically classified, and each model is mapped to vocal and gestural features for real-time control. With miMic, the sound designer can explore a vast sonic space and quickly produce expressive sonic sketches, which may be turned into sound prototypes by further adjustment of model parameters

A Game-Theoretic Framework for Optimum Decision Fusion in the Presence of Byzantines

Optimum decision fusion in the presence of malicious nodes - often referred to as Byzantines - is hindered by the necessity of exactly knowing the statistical behavior of Byzantines. By focusing on a simple, yet widely studied, set-up in which a Fusion Center (FC) is asked to make a binary decision about a sequence of system states by relying on the possibly corrupted decisions provided by local nodes, we propose a game-theoretic framework which permits to exploit the superior performance provided by optimum decision fusion, while limiting the amount of a-priori knowledge required. We first derive the optimum decision strategy by assuming that the statistical behavior of the Byzantines is known. Then we relax such an assumption by casting the problem into a game-theoretic framework in which the FC tries to guess the behavior of the Byzantines, which, in turn, must fix their corruption strategy without knowing the guess made by the FC. We use numerical simulations to derive the equilibrium of the game, thus identifying the optimum behavior for both the FC and the Byzantines, and to evaluate the achievable performance at the equilibrium. We analyze several different setups, showing that in all cases the proposed solution permits to improve the accuracy of data fusion. We also show that, in some instances, it is preferable for the Byzantines to minimize the mutual information between the status of the observed system and the reports submitted to the FC, rather than always flipping the decision made by the local nodes as it is customarily assumed in previous works

Are Business Cycles All Alike? A Bandpass Filter Analysis of Italian and US Cycles

In this paper, we apply the bandpass filter to the main Italian and US macroeconomic variables, we estimate cross-correlations with respect to a benchmark indicator of the business cycle, and we compare results with previous empirical analyses. The aim is to investigate on the existence of specific patterns and more general regularities, in order to provide further insights as to what facts macroeconomic theories are supposed to predict and explain, and new hints at the underlying generating mechanisms. Our results underline the existence of significant specificities of the Italian business cycle with respect to the US. Certain macroeconomic relations - such as those between consumption, investments, exports, stock market variables, and the real GDP - do not robustly hold. This is a clear signal that which variables prompt and which respond to business cycles depends on country- specific characteristics.Business Cycles, Bandpass Filter, Cross Correlations, Italian Economy, Macroeconomics.

Are Output Growth-Rate Distributions Fat-Tailed? Some Evidence from OECD Countries

This work explores some distributional properties of aggregate output growth-rate time series. We show that, in the majority of OECD countries, output growth-rate distributions are well-approximated by symmetric exponential-power densities with tails much fatter than those of a Gaussian. Fat tails robustly emerge in output growth rates independently of: (i) the way we measure aggregate output; (ii) the family of densities employed in the estimation; (iii) the length of time lags used to compute growth rates. We also show that fat tails still characterize output growth-rate distributions even after one washes away outliers, autocorrelation and heteroscedasticity.Output Growth-Rate Distributions, Normality, Fat Tails, Time Series, Exponential-Power Distributions, Laplace Distributions, Output Dynamics.

Fluidisation and plastic activity in a model soft-glassy material flowing in micro-channels with rough walls

By means of mesoscopic numerical simulations of a model soft-glassy material, we investigate the role of boundary roughness on the flow behaviour of the material, probing the bulk/wall and global/local rheologies. We show that the roughness reduces the wall slip induced by wettability properties and acts as a source of fluidisation for the material. A direct inspection of the plastic events suggests that their rate of occurrence grows with the fluidity field, reconciling our simulations with kinetic elasto-plastic descriptions of jammed materials. Notwithstanding, we observe qualitative and quantitative differences in the scaling, depending on the distance from the rough wall and on the imposed shear. The impact of roughness on the orientational statistics is also studied