Hybrid Neural Networks for Frequency Estimation of Unevenly Sampled Data

In this paper we present a hybrid system composed by a neural network based estimator system and genetic algorithms. It uses an unsupervised Hebbian nonlinear neural algorithm to extract the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. We generalize this method to avoid an interpolation preprocessing step and to improve the performance by using a new stop criterion to avoid overfitting. Furthermore, genetic algorithms are used to optimize the neural net weight initialization. The experimental results are obtained comparing our methodology with the others known in literature on a Cepheid star light curve.Comment: 5 pages, to appear in the proceedings of IJCNN 99, IEEE Press, 199

"WDM-DPSK Detection by means of Frequency-Periodic Gaussian Filtering"

A single frequency-periodic narrow filter converts DPSK to intensity modulation in a high number of WDM channels. It also strongly enhances their tolerance to chromatic dispersion and is exploited in a 16x10 Gbit/s transmission over 240 km G.652 fibre with no chromatic dispersion compensation

Accurate Performance Estimationof high-speed Digital Optical Signals

A novel technique allows an easy and accurate estimation of the system BER by collecting the statistical distribution of the analog samples, i.e. before decision. The scheme is confirmed by both simulations and experimental measurements

Investigation of the Effects of Chirped RZ Signals in Reducing the Transmission Impairments in R-SOA-Based Bidirectional PONs

Distributed and concentrated reflections represent the two main limitations in reflective-semiconductor optical amplifier (R-SOA)-based passive optical networks (PONs). In this paper, we experimentally discuss how the use of chirped signals in centralized light seeding bidirectional PON can increase the resilience of the system against those two types of reflections. An experimental comparison of the performance of a highly chirped return to zero (RZ) modulation format and the nonreturn to zero is given. Error-free operation is achieved down to 10 dB of signal to crosstalk ratio in presence of distributed reflection, when the upstream signal is highly chirped RZ signal. The same chirped modulation leads to a tolerance of more than dB network return loss due to concentrated reflections. Finally, we assess also the system feasibility of a R-SOA-based full-duplex PON where both the upstream and the downstream are modulated signals

Promotion of Resilience in Migrants: A Systematic Review of Study and Psychosocial Intervention

This systematic review aimed to contribute to a better and more focused understanding of the link between the concept of resilience and psychosocial interventions in the migrant population. The research questions concerned the type of population involved, definition of resilience, methodological choices and which intervention programmes were targeted at migrants. In the 90 articles included, an heterogeneity in defining resilience or not well specified definition resulted. Different migratory experiences were not adequately considered in the selection of participants. Few resilience interventions on migrants were resulted. A lack of procedure’s descriptions that keep in account specific migrants’ life-experiences and efficacy’s measures were highlighted

System feasibility of using stimulated Brillouin scattering in self coherent detection schemes

We demonstrate the first self-coherent detection of 10 Gbit/s BPSK signals based on narrow-band amplification of the optical carrier by means of Stimulated Brillouin effect in a common fiber. We found that this technique is very effective only if it is combined with proper line coding and high-pass electrical filtering at the receiver. In this case we obtain OSNR-performance close to the ideal coherent receiver. (C) 2010 Optical Society of Americ

Early suppression of lymphoproliferative response in dogs with natural infection by Leishmania infantum.

Dogs are the domestic reservoirs of zoonotic visceral leishmaniasis caused by Leishmania infantum. Early detection of canine infections evolving to clinically patent disease may be important to leishmaniasis control. In this study we firstly investigated the peripheral blood mononuclear cell (PBMC) response to leishmanial antigens and to polyclonal activators concanavalin A, phytohemagglutinin and pokeweed mitogen, of mixed-breed dogs with natural L. infantum infection, either in presymptomatic or in patent disease condition, compared to healthy animals. Leishmania antigens did not induce a clear proliferative response in any of the animals examined. Furthermore, mitogen-induced lymphocyte proliferation was found strongly reduced not only in symptomatic, but also in presymptomatic dogs suggesting that the cell-mediated immunity is suppressed in progressive canine leishmaniasis. To test this finding, naive Beagle dogs were exposed to natural L. infantum infection in a highly endemic area of southern Italy. Two to 10 months after exposure all dogs were found to be infected by Leishmania, and on month 2 of exposure they all showed a significant reduction in PBMC activation by mitogens. Our results indicate that suppression of the lymphoproliferative response is a common occurrence in dogs already at the beginning of an established leishmanial infection. # 1999 Elsevier Science B.V. All rights reserved

Spectral Analysis of Stellar Light Curves by Means of Neural Networks

Periodicity analysis of unevenly collected data is a relevant issue in several scientific fields. In astrophysics, for example, we have to find the fundamental period of light or radial velocity curves which are unevenly sampled observations of stars. Classical spectral analysis methods are unsatisfactory to solve the problem. In this paper we present a neural network based estimator system which performs well the frequency extraction in unevenly sampled signals. It uses an unsupervised Hebbian nonlinear neural algorithm to extract, from the interpolated signal, the principal components which, in turn, are used by the MUSIC frequency estimator algorithm to extract the frequencies. The neural network is tolerant to noise and works well also with few points in the sequence. We benchmark the system on synthetic and real signals with the Periodogram and with the Cramer-Rao lower bound

Structure and Properties of DNA Molecules Over The Full Range of Biologically Relevant Supercoiling States

Topology affects physical and biological properties of DNA and impacts fundamental cellular processes, such as gene expression, genome replication, chromosome structure and segregation. In all organisms DNA topology is carefully modulated and the supercoiling degree of defined genome regions may change according to physiological and environmental conditions. Elucidation of structural properties of DNA molecules with different topology may thus help to better understand genome functions. Whereas a number of structural studies have been published on highly negatively supercoiled DNA molecules, only preliminary observations of highly positively supercoiled are available, and a description of DNA structural properties over the full range of supercoiling degree is lacking. Atomic Force Microscopy (AFM) is a powerful tool to study DNA structure at single molecule level. We here report a comprehensive analysis by AFM of DNA plasmid molecules with defined supercoiling degree, covering the full spectrum of biologically relevant topologies, under different observation conditions. Our data, supported by statistical and biochemical analyses, revealed striking differences in the behavior of positive and negative plasmid molecules