Investigation of structural properties of ITO thin films deposited on different substrates

The influence of the substrate nature on the structure and morphology of ITO thin films grown by thermal evaporation in vacuum is investigated. The as-prepared metal films with Sn/In molar ratio of 0.1 were subsequently annealed for 2 h at 723 K in air (to obtain tin doped indium oxide), then annealed in vacuum at 523 K, followed by UV irradiation (to reduce the electrical resistivity). Irrespective of substrate nature, XRD data evidence a (222) preferential orientation in films. Substrate nature, annealing in vacuum and UV irradiation influence the structure, morphology, optical, electrical and surface wetting properties of the films' surface.     

Primary lymphoma of the breast. Three cases of non-Hodgkin lymphoma

Primary and sole breast lymphoma is a very rare disease. With the review of our series of 616 cases operated on for breast cancer, only 3 cases (0.48%) of primary breast non-Hodgkin lymphoma (LNH) have been observed. The authors outline the problems concerning diagnosis and therapy of this rare disease: pathological and immunohistochemical aspects are discussed. They stress the importance of staging in order to plan a correct multidisciplinary approach.     

Random Vibration of Systems with Viscoelastic Memory

The equation of motion of linear dynamic systems with viscoelastic memory is usually expressed in a integrodifferential form, and its numerical solution is computationally heavy. In two recent papers, the writers suggested that the system memory be accounted for through the introduction of a number of additional internal variables. Following this approach, the motion of the system is governed by a set of first-order, linear differential equations, whose solution is quite easy. In this paper, the approach is extended to single-degree-of-freedom systems subjected to random, nonstationary excitation. The equations governing the time variation of the second-order statistics are derived, and an effective step-by-step solution procedure is proposed. Numerical example shows the accuracy of the procedure for white and nonwhite excitations.     

TGF-beta-induced apoptosis of cerebellar granule neurons is prevented by depolarization

The regulation of programmed cell death in the developing nervous system involves target-derived survival factors, afferent synaptic activity, and hormone- and cytokine-dependent signaling. Cultured immature cerebellar granule neurons die by apoptosis within several days in vitro unless maintained in depolarizing (high) concentrations of potassium (25 mM K+). Here we report that transforming growth factors (TGF)-beta1, -beta2, and -beta3 accelerate apoptosis of these neurons when maintained in physiological (low) K+ medium (5mM K+) as assessed by measures of viability, quantitative DNA fragmentation, and nuclear morphology. TGF-beta-induced apoptosis of these neurons is not blocked by CNTF and LIF, cytokines that enhance neuronal survival when applied alone, or by IGF-I, which prevents apoptosis upon potassium withdrawal. In contrast, neurons that differentiate in high K+ medium for several days in vitro acquire resistance to TGF-beta-mediated cell death. Granule neurons maintained in either low or high K+ medium produce latent, but not bioactive, TGF-beta1 and -beta2. Because neutralizing TGF-beta antibodies fail to augment survival of low K+ neurons, the cerebellar neurons are apparently unable to activate latent TGF-beta. Thus, apoptosis of low K+ neurons is not attributable to endogenous production of TGF-beta. Taken together, our data suggest that TGF-beta may limit the expansion of postmitotic neuronal precursor populations by promoting their apoptosis but may support survival of those neurons that have maturated, differentiated, and established supportive synaptic connectivity.     

Active state estimation for nonlinear systems: a neural approximation approach.

In this paper, we consider the problem of actively providing an estimate of the state of a stochastic dynamic system over a (possibly long) finite time horizon. The active estimation problem (AEP) is formulated as a stochastic optimal control one, in which the minimization of a suitable uncertainty measure is carried out. Toward this end, the use of the Renyi entropy as an information measure is proposed and motivated. A neural control scheme, based on the application of the extended Ritz method (ERIM) and on the use of a Gaussian sum filter (GSF), is then presented. Simulation results show the effectiveness of the proposed approach.     

Good teaching inputs do not correspond to desired responses in ecological neural networks

In this paper we analyze how supervised learning occurs in ecological neural networks, i.e. networks that interact with an autonomous external environment and, therefore, at least partially determine with their behavior their own input. Using an evolutionary method for selecting good teaching inputs we surprisingly find that to obtain a desired outputX it is better to use a teaching input different fromX. To explain this fact we claim that teaching inputs in ecological networks have two different effects: (a) to reduce the discrepancy between the actual output of the network and the teaching input, (b) to modify the network's behavior and, as a consequence, the network's learning experiences. Evolved teaching inputs appear to represent a compromise between these two needs. We finally show that evolved teaching inputs that are allowed to change during the learning process function differently at different stages of learning, first giving more weight to (b) and, later on, to (a).     

Large band simulation of the wind speed for real time wind turbine simulators

In this paper, the authors propose two modeling procedures for wind speed simulation. These procedures could be implemented on the structure of a wind turbine simulator during studies concerning stand-alone or hybrid wind systems. The evolution of a horizontal wind speed has been synthesized taking into account two components. The medium- and long-term component is described by a power spectrum associated to a specific site. The turbulence component is assumed to be dependent on the medium- and long-term wind speed evolution. It is considered as a nonstationary process. Two simulation methods for this component, using rational and nonrational filters are proposed. In both procedures, the turbulence model is defined by two parameters, which are either obtained experimentally, or adopted a priori, according to information from the considered site. Numerical results and implementation aspects are also discussed.