Tips and Tricks for the Surface Engineering of Well-Ordered Morphologically Driven Silver-Based Nanomaterials

Particularly-shaped silver nanostructures are successfully applied in many scientific fields, such as nanotechnology, catalysis, (nano)engineering, optoelectronics, and sensing. In recent years, the production of shape-controlled silver-based nanostructures and the knowledge around this topic has grown significantly. Hence, on the basis of the most recent results reported in the literature, a critical analysis around the driving forces behind the synthesis of such nanostructures are proposed herein, pointing out the important role of surface-regulating agents in driving crystalline growth by favoring (or opposing) development along specific directions. Additionally, growth mechanisms of the different morphologies considered here are discussed in depth, and critical points highlighted.     

CuPc molecules adsorbed on Au(1 1 0)-(1 × 2): growth morphology and evolution of valence band states

We present the growth morphology, the long-range ordering, and the evolution of the valence band electronic states of ultrathin films of copper phthalocyanine (CuPc) deposited on the Au(1 1 0)-(1 × 2) reconstructed surface, as a function of the organic molecule coverage. The low energy electron diffraction patterns present a (5 × 3) reconstruction from the early adsorption stages. High-resolution UV photoelectron spectroscopy data show the disappearance of the Au surface states related to the (1 × 2) reconstruction, and the presence of new electronic features related to the molecule-substrate interaction and to the CuPc molecular states. The CuPc highest occupied molecular orbital gradually emerges in the valence band, while the interface electronic states are quenched, upon increasing the coverage.     

Long‐range dependence and performance in telecom networks

Telecommunications systems have recently undergone significant innovations. These call for suitable statistical models that can properly describe the behaviour of the input traffic in a network. Here we use fractional Brownian motion (FBM) to model cumulative traffic network, thus taking into account the possible presence of long‐range dependence in the data. A Bayesian approach is devised in such a way that we are able to: (a) estimate the Hurst parameter H of the FBM; (b) estimate the overflow probability which is a parameter measuring the quality of service of a network: (c) develop a test for comparing the null hypothesis of long‐range dependence in the data versus the alternative of short‐range dependence. In order to achieve these inferential results, we elaborate an MCMC sampling scheme whose output enables us to obtain an approximation of the quantities of interest. An application to three real datasets, corresponding to three different levels of traffic, is finally considered. Copyright © 2004 John Wiley & Sons, Ltd.     

Unified theory of bound and scattering molecular Rydberg states as quantum maps

Using a representation of multichannel quantum defect theory in terms of a quantum Poincaré map for bound Rydberg molecules, we apply Jung's scattering map to derive a generalized quantum map, that includes the continuum. We show that this representation not only simplifies the understanding of the method, but moreover produces considerable numerical advantages. Finally we show under what circumstances the usual semi-classical approximations yield satisfactory results. In particular we see that singularities that cause problems in semi-classics are irrelevant to the quantum map.     

An evolutionary approach to visual sensing for vehicle navigation

This paper presents an evolutionary approach able to process a digital image and detect tracks left by preceding vehicles on ice and snow in Antarctica. Biologically inspired by a colony of ants able to interact and cooperate to determine the shortest path to the food, this approach is based on autonomous agents moving along the image pixels and iteratively improving an initial coarse solution. The unfriendly Antarctic environment makes this image analysis problem extremely challenging, since light reflections, abruptly varying brightness conditions, and different terrain slopes must be considered as well. The ant-based approach is compared to a more traditional Hough-based solution and the results are discussed.     

Stress monitoring in a Guinness 10-day scuba dive

Nowadays, there is high demand for sensitive gas sensors both for human and environmental monitoring. This paper deals with a high-resolution (0.2 ppb) laser-based photoacoustic spectroscopic system realized at ENEA Frascati, Italy, applied for monitoring stress in scuba divers during sustained immersion by analyzing breath samples. Blood tests and psychometric tests for scuba divers were performed at Catholic University in Rome. Results will be reported and discussed.     

A non-isothermal Ginzburg–Landau model in superconductivity: Existence,uniqueness and asymptotic behaviour

In this paper we study a Ginzburg–Landau model which describes the behaviour of a superconducting material including thermal effects. We extend the traditional formulation of the problem, by introducing the temperature as an additional state variable. Accordingly, together with the Gor’kov–Eliashberg system, we introduce an evolution equation for the absolute temperature. We examine in detail the case which allows only variations of the concentration of superconducting electrons and of the temperature, neglecting the electromagnetic field. For this problem existence and uniqueness of the solution are shown. Finally we analyze the asymptotic behaviour of the solutions, proving that the system possesses a global attractor.     

Use of capillary gas chromatography/sensory analysis as an additional tool for sampling technique comparison in peach aroma analysis

Capillary GC/sensory analysis was used to judge if dynamic headspace on sliced pulp and on intact fruit, and solvent extraction could collect the “character impact” and the “contributory” aroma compounds in peaches. Capillary GC/sensory data showed that the headspace techniques selectively recovered the “contributory” volatile compounds, which are strictly related to the characteristic odor of the various peach cultivars, whereas solvent extraction better quantified the “character impact” compounds (lactones).     

Phase-space invariants for aggregates of particles: hyperangular momenta and partitions of the classical kinetic energy

Rigorous definitions are presented for the kinematic angular momentum K of a system of classical particles (a concept dual to the conventional angular momentum J), the angular momentum L(xi) associated with the moments of inertia, and the contributions to the total kinetic energy of the system from various modes of the motion of the particles. Some key properties of these quantities are described-in particular, their invariance under any orthogonal coordinate transformation and the inequalities they are subject to. The main mathematical tool exploited is the singular value decomposition of rectangular matrices and its differentiation with respect to a parameter. The quantities introduced employ as ingredients particle coordinates and momenta, commonly available in classical trajectory studies of chemical reactions and in molecular dynamics simulations, and thus are of prospective use as sensitive and immediately calculated indicators of phase transitions, isomerizations, onsets of chaotic behavior, and other dynamical critical phenomena in classical microaggregates, such as nanoscale clusters.