Mechanical and Electrical Properties of Cryo-worked Cu

For manufacturing the magnets of fusion machines pure copper of both high mechanical resistance and electrical conductivity is required. Though high purity copper guarantees high electrical conductivity, its mechanical properties may be not suitable for the applications in tokamaks. In this view, a new procedure developed for obtaining high purity copper with excellent mechanical strength is described in this work. Samples of oxygen free copper (OFC) have been worked by pressing in liquid nitrogen (77 K). It has been verified that the mechanical properties of the worked metal are strongly dependent on the strain rate. Very low strain rates permitted to attain values of tensile yield strength (550 MPa) significantly higher than those obtained by traditional cold-working at room temperature (450 MPa). The electrical conductivity of the cryo-worked Cu decreases with the tensile yield strength even though the hardest samples of tensile yield strength of 550 MPa exhibit still acceptable values of conductivity (about 94 % IACS at room temperature).     

Logarithmic wavelength demultiplexers

A general approach for a full 1 /spl times/ N demultiplexer using a tree of filter stages is proposed. The device architecture is compact, requiring at least N - 1 filter stages, and flexible, as each filter stage can be arbitrarily designed, with the only constraint of the half-band power property. The filters can be realized using any optical filtering techniques as thin-film interference, Bragg gratings, or planar delay-line circuits. The performances of the proposed architecture are illustrated with respect to different lattice-form finite impulse response (FIR) and infinite impulse response (IIR) filter stages, showing that the demultiplexer inherently presents low crosstalk and flat passband. A design example of a 1 /spl times/ 4 demultiplexer consisting of three all-pass (AP) filters is compared with a generalized Mach-Zehnder interferometer (MZI) with four AP filters in its arms, showing that the two approaches achieve similar results.     

Design of optical full encoders/decoders for code-based photonic routers

This paper demonstrates that standard multiplexers as generalized Mach-Zehnder interferometers or waveguide grating routers can be designed to generate/process a set of orthogonal optical codes (OCs) with very high-correlation performances. The same device can be used at the ingress node of a generalized multiprotocol label switching network to generate the photonic labels and at each routing node to perform all the correlations simultaneously. To enhance the code cardinality, without increasing the code length, this paper shows that it is possible to use the proposed encoder/decoder architectures to generate/process multidimensional OCs.     

A ?P-Controlled Sliding Integrating-Type Differentiator for Biomedical Signal Processing: Application to dc Ocular Rheography

This paper describes a measurement technique for precise evaluation of hematic ocular flow. The main characteristics and advantages of the proposed technique over conventional approaches are first pointed out. Next, the design criteria and the performance achievable with the prototype instrument developed to carry out the measurement completely automatically, are examined in detail. The instrument, thanks to its microprocessor-based implementation, allows a certain degree of tailoring of the measurement in accordance with the patient's peculiarities. Moreover, it provides the possibility of monitoring the ocular arterial inflow during the test, thus guaranteeing that safety limits will not be exceeded.     

Recognition by constructive neural algorithms

The usability of the constructive neural algorithms as pattern classifiers is investigated. It is pointed out that the unboundedness of the decision regions formed by most neural recognizers leads to substantial limitations of the generalization capabilities of these nets. We specify a constructive neural recognizer that forms bounded decision regions, and report the results of this algorithm on a series of benchmark problems that resemble the usual pattern recognition problems.     

Pseudopotentials and Loading Surfaces for an Endochronic Plasticity Theory with Isotropic Damage

The endochronic theory, developed in the early 70s, allows the plastic behavior of materials to be represented by introducing the notion of intrinsic time. With different viewpoints, several authors discussed the relationship between this theory and the classical theory of plasticity. Two major differences are the presence of plastic strains during unloading phases and the absence of an elastic domain. Later, the endochronic plasticity theory was modified in order to introduce the effect of damage. In the present paper, a basic endochronic model with isotropic damage is formulated starting from the postulate of strain equivalence. Unlike the previous similar analyses, in this presentation the formal tools chosen to formulate the model are those of convex analysis, often used in classical plasticity: namely pseudopotentials, indicator functions, subdifferentials, etc. As a result, the notion of loading surface for an endochronic model of plasticity with damage is investigated and an insightful comparison with classical models is made possible. A damage pseudopotential definition allowing a very general damage evolution is given.     

In situ observations of catalyst dynamics during surface-bound carbon nanotube nucleation

We present atomic-scale, video-rate environmental transmission electron microscopy and in situ time-resolved X-ray photoelectron spectroscopy of surface-bound catalytic chemical vapor deposition of single-walled carbon nanotubes and nanofibers. We observe that transition metal catalyst nanoparticles on SiOx support show crystalline lattice fringe contrast and high deformability before and during nanotube formation. A single-walled carbon nanotube nucleates by lift-off of a carbon cap. Cap stabilization and nanotube growth involve the dynamic reshaping of the catalyst nanocrystal itself. For a carbon nanofiber, the graphene layer stacking is determined by the successive elongation and contraction of the catalyst nanoparticle at its tip.     

A grid environment for high-throughput proteomics

We connect in a grid-enabled pipeline an ontology-based environment for proteomics spectra management with a machine learning platform for unbiased predictive analysis. We exploit two existing software platforms (MS-Analyzer and BioDCV), the emerging proteomics standards, and the middleware and computing resources of the EGEE Biomed VO grid infrastructure. In the setup, BioDCV is accessed by the MS-Analyzer workflow as a Web service, thus providing a complete grid environment for proteomics data analysis. Predictive classification studies on MALDI-TOF data based on this environment are presented.