A new cytotoxic polychlorinated sulfolipid from contaminated Adriatic mussels

A detailed analysis of toxic shellfish collected in the Adriatic sea in October 2000 allowed us to isolate a new cytotoxic chlorosulfolipid (3). Its gross structure has been elucidated through an extensive NMR analysis including various 2D techniques; the relative stereochemistry has been solved by applying the Murata's method. Compound 3 showed to posses cytotoxic activity against WEHI 164 and J774 cells. The presence of chlorosulfolipids in toxic mussels from the northern Adriatic sea has not to be considered incidental as we have been detecting these cytotoxic compounds since 1998. Their simultaneous and constant presence together with typical marine biotoxins represents a further risk both to consumers' health and aquacultures economic proceeds.     

Thermal and kinetic study of tyre waste pyrolysis via TG-FTIR-MS analysis

The world production of tyre waste amounts to 5·10⁶ ton year^–1, 2·10⁶ tons of which are produced in Europe, but the final destination of nearly 65–70% of them is the landfill, despite the high added value materials lost and the consequent environmental impact. Treatments alternative to landfilling take into account reconstruction and reuse of the tyres or the matter and/or energy recovery by means of thermal treatment processes (incineration, gasification and pyrolysis). Among these, pyrolysis seems to be a promising and realistic alternative to attain the conversion of tyre waste into valuable and reusable products. Present work relates to experimental tests and results obtained for the study of tyre waste pyrolysis, conducted by means of thermo-gravimetric analysis (TG) of the material and the simultaneous determination, through Fourier transform infrared (FTIR) and mass spectrometry (MS), of the decomposition products. The analysis of the volatile fraction allows to isolate, within the thermograms, the evolution of products referable to specific tyre components and therefore it suggests the application of a multi-component decomposition model. The kinetic model consequently developed agrees fairly well with the experimental data.     

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     

Poly(1,4‐cyclohexylenedimethylene 1,4‐cyclohexanedicarboxylate): Influence of stereochemistry of 1,4‐cyclohexylene units on the thermal properties

A series of poly(1,4‐cyclohexylenedimethylene 1,4‐cyclohexanedicarboxylate) (PCCD) samples, characterized by different cis/trans ratio of the 1,4‐cyclohexanedicarbonyl unit, have been synthesized and analyzed by thermogravimetry (TGA), calorimetry (DSC), and X‐ray diffraction (WAXD). The thermal stability results are good and are not affected by the stereochemistry of the 1,4‐cyclohexylene units. On the other hand, the thermal transitions are notably influenced by the cis/trans content. With the increment of the trans content the polymer changes from completely amorphous to semicrystalline material. T_g, T_m, and crystallinity increase. These results suggest that the trans configuration induces a better chain packing and higher symmetry, improving the crystallizability of the samples. The effect of the molecular structure on the thermal properties is analyzed by using a statistical approach. From the effective correlations found between stereochemistry of the C₆ rings and transition temperatures it is possible to extrapolate that the configuration of 1,4‐cyclohexylene ring deriving from 1,4‐cyclohexanedicarboxylic acid or dimethyl 1,4‐cyclohexanedicarboxylate results to be the main element responsible for the thermal properties. This is due to the high rigidity of the 1,4‐cyclohexanedicarbonyl unit with respect to 1,4‐cyclohexanedimethyleneoxy unit, deriving from the diol. © 2008 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 46: 619–630, 2008     

A numerical method for a blood-artery interaction problem

We present a numerical method for the resolution of a bidimensional blood flow problem and more generally for a fluid flow surrounded by a time dependent domain. Our approach is based on an ALE formulation which is solved using a Galerkin method with an eigenvectors basis set on the initial fixed domain.     

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.     

Zinc oxide nanostructures grown by pulsed laser deposition

We report the use of PLD to grow different ZnO nanostructures. Very different film morphologies have been observed using different laser wavelengths to ablate the target. The influence of substrate temperature and oxygen background pressure on the film morphology has been investigated too. Smooth and rough films, hexagonal pyramids and columns have been obtained by using a KrF excimer laser (248 nm) for the target ablation, while hexagonal hierarchical structures and pencils have been obtained by using ArF (193 nm). Photoluminescence and X-ray diffraction measurements revealed the good quality of the samples, in particular of those deposited using the ArF laser beam.     

Product decompositions of depolarizing Mueller matrices with negative determinants

We show that the product decomposition of a depolarizing Mueller matrix (S.-Y. Lu, R.A. Chipman, J. Opt. Soc. Am. A 13 (1996) 1106) as well as the recently proposed reverse decomposition (R. Ossikovski, A. De Martino, Opt. Lett. 32 (2007) 689) need to be extended in order to account for Mueller matrices with negative determinants. The necessity of such an extension of the formalism is illustrated on experimentally determined Mueller matrices. The procedure of the modified decomposition formalism is explicitly described.     

Enhanced imaging of magnetic structures in micropatterned arrays of Co dots and antidots

A specific technique of numerical treatment of atomic force microscopy (AFM) and magnetic force microscopy (MFM) signal has been developed to enhance the quality of raw images, in order both to improve their contrast and to gain better insight on the sample topography and on the local arrangement of the magnetisation vector. Basically, the technique consists in computing the optimum conformal transformation that allows one to superimpose two AFM images of the same area, acquired performing subsequent scans whose fast scan axis were mutually perpendicular, and applying the inverse transform to the second image. After MFM image superposition, the two datasets were either summed or subtracted, in order to improve the magnetic contrast. Computations have been done in a Matlab^® workspace with the help of Image Processing Toolbox 4.2. Improved MFM images obtained on both dots and antidots thin evaporated Co arrays in the demagnetised state (after performing alternate field demagnetisation parallel and perpendicular to the array plane) have been interpreted. Samples consisting of large-size patterns (1×1 mm) of circular dots/antidots with square/hexagonal lattices and minimum diameters of 1 μm were prepared by optical lithography. The magnetic film thickness was chosen depending on resist thickness, and varied between 25 and 150 nm, with a fixed ratio 1:4 between metal/resist film thickness. MFM was exploited to obtain images of either intra-dot or inter-antidot magnetic structures.