Conception of a 90-GHz metamaterial-based coupler for astrophysical applications

Designed for astrophysical applications, this coupler must be as small as possible to be integrated in a low temperature superconducting detection chain. By using metamaterials, dimensions can be reduced and performances enhanced compared with a conventional coupler. The novelty of the work presented in this paper is a coupler that operates at millimeter waves (W band) and cryogenic temperatures (4 K) for astrophysics applications and more precisely for the detection of the cosmological microwave background radiation.     

FT-EPR study of photoionization in micellar solutions

Fourier Transform EPR (FT-EPR) was used to study the formation and decay of free radicals produced by photoionization of phenothiazine (PTH) solubilized in aqueous SDS and Triton X-100 micellar solutions in the absence and presence of electron acceptors. CIDEP spectra produced by PTH photoionization in micellar solution differ from those found in homogeneous solution. The effect is attributed to changes in relative importance of single-photon, singlet excited state, and biphotonic, triplet excited state, photoionization. With quinone acceptors present in the bulk aqueous phase, photoionization of PTH in SDS, results in instantaneous formation of quinone anion radicals that carry the spin polarization of the precursor hydrated electrons. If the acceptor is anchored in the micelle, electron capture cannot compete with electron escape into the aqueous phase. Instead, anion radicals are formed primarily by reductive quenching of³PTH*. This process gives rise to a spectrum that is attributed to long-lived spin-correlated radical pairs, [PTH⁺…Q^?].     

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.     

A multi-objective design optimization strategy as applied to pre-mixed pre-vaporized injection systems for low emission combustors

This paper presents a multi-objective optimization procedure as applied to the design of the injection system of a Lean Pre-mixed Pre-vaporized combustion chamber. The optimizer drives an Artificial Neural Network in a repeated analysis scheme in order to simultaneously reduce NO_X and CO pollutant emissions. The ANN is trained with a few three-dimensional high resolution reactive viscous flow simulations, carried out with a reliable and robust CFD code. Results, obtained in a four-dimensional state space, demonstrate the validity of the overall procedure with truly moderate computational costs.     

A New Validity Index Based on Fuzzy Energy and Fuzzy Entropy Measures in Fuzzy Clustering Problems

Two well-known drawbacks in fuzzy clustering are the requirement of assigning in advance the number of clusters and random initialization of cluster centers. The quality of the final fuzzy clusters depends heavily on the initial choice of the number of clusters and the initialization of the clusters, then, it is necessary to apply a validity index to measure the compactness and the separability of the final clusters and run the clustering algorithm several times. We propose a new fuzzy C-means algorithm in which a validity index based on the concepts of maximum fuzzy energy and minimum fuzzy entropy is applied to initialize the cluster centers and to find the optimal number of clusters and initial cluster centers in order to obtain a good clustering quality, without increasing time consumption. We test our algorithm on UCI (University of California at Irvine) machine learning classification datasets comparing the results with the ones obtained by using well-known validity indices and variations of fuzzy C-means by using optimization algorithms in the initialization phase. The comparison results show that our algorithm represents an optimal trade-off between the quality of clustering and the time consumption.     

Model-theoretic aspects of the Gurarij operator system

We establish some of the basic model theoretic facts about the Gurarij operator system GS recently constructed by the second-named author. In particular, we show: (1) GS is the unique separable 1-exact existentially closed operator system; (2) GS is the unique separable nuclear model of its theory; (3) every embedding of GS into its ultrapower is elementary; (4) GS is the prime model of its theory; and (5) GS does not have quantifier-elimination, whence the theory of operator systems does not have a model companion. We also show that, for any q ∈ ?, the theories of M_q-spaces and M_q-systems do have a model companion, namely the Fra¨?ssé limit of the class of finite-dimensional M_q-spaces and M_q-systems respectively; moreover, we show that the model companion is separably categorical. We conclude the paper by showing that no C* algebra can be existentially closed as an operator system.     

Control and characterization of the nucleation process during co-expansion of ternary mixtures

In this paper, we show how the use of a third non-condensable species gives both new insight and control on the binary nucleation process during supersonic expansion of gas mixtures. We present the case of an oxygen-nitrogen mixture diluted in various proportions of helium. Using beam diagnostics, we determine the mean cluster composition and size as well as the percentage of uncondensed matter present in the beam. The presence of helium permits us to understand the cooling and clustering role played by each species during the expansion process. We discuss, in particular, its influence on the dramatic composition change observed at the nucleation onset. Received 18 April 2001     

Hydrolytic Pathway of Glufosfamide,a New Phosphorylated Anticancer Agent

31 P NMR was used to demonstrate that glufosfamide is hydrolyzed into isophosphoramide mustard (IPM) with a half-life of about 25 h at 37;C and pH 7.4 in buffer as well as in human plasma. Through a cascade of reactions, IPM gives rise to three final products, dihydroxyIPM, phosphate ion, and phosphorylethanolamine, which is by far the major compound.     

Preformulation study of nicergoline solid dispersions

Nicergoline, a semisynthetic ergot derivative, which, in its crystalline state, is insoluble in water, was dispersed in polyvinylpyrrolidone K30 (PVP K30) to improve drug particle dissolution. Preformulation studies were carried out initially by differential scanning calorimetry and X-ray powder diffraction in order to predict the conditions and the possibility to actually obtain solid dispersions by mixing the two components at different proportions. Solid dispersions were finally prepared by dissolving nicergoline and PVP K30 in chloroform that was next evaporated under reduced pressure. Under these conditions, an amorphous powder was recovered in every proportion of the two components. Nicergoline demonstrated to be physically and chemically stable for 1 year. The dissolution studies revealed a very high dissolution rate of nicergoline from solid dispersions only lower than the pure amorphous form. This is the consequence of the molecular dispersion of nicergoline in the polymer that enhances the rate of drug release from the polymer.