Diffusion bonding of an aluminium-lithium alloy (AA8090) using aluminium-copper alloy interlayers

Diffusion bonds have been produced between sheets of an Al-Li-Cu-Mg-Zr alloy using aluminium-4% copper vapour deposited metallic interlayers. Microstructural changes occurred both in the parent alloy and in the bond interface after diffusion bonding cycles and post-bonding heat treatments were analysed. Different metallographic techniques (light microscopy, scanning and transmission electron microscopy) have been used. Diffusion bonding trials were carried out using the same alloy (AA8090), both in non-superplastic (T6) and superplastic conditions. Differences in their behaviours in relation to diffusion bonding were observed.     

Hydrodechlorination of 3-chloropyridine and chlorobenzene in methanol solution over alkali-modified zirconia-supported palladium catalysts

The liquid-phase hydrodechlorination of 3-chloropyridine and chlorobenzene has been studied over alkali-modified zirconia-supported palladium catalysts. The modification of the ZrO₂ with alkali metal carbonates improves the catalytic activity of the final palladium catalyst. Therefore, the larger the ionic radii (Li⁺ < Na⁺ < K⁺), the greater the catalytic activity (TOF) of the palladium catalyst. For 3-chloropyridine, hydrodechlorination proceeds without catalyst deactivation. This is explained as the result of the interaction of reaction products (pyridine and HCl) forming pyridinium chloride, thus avoiding the detrimental effect of HCl on the palladium particles. Catalytic hydrodechlorination of chlorobenzene over Pd catalysts exhibits an initial catalytic activity (TOF) much lower than that of 3-chloropyridine and the Pd catalysts deactivate as the reaction proceeds. Finally, chlorobenzene hydrodehalogenation has also been carried out in the presence of an equimolecular amount of pyridine resulting in a decrease in the initial reaction rate on the one hand, but also in an increase in final conversion on the other.     

Transmission Fiber Chromatic Dispersion Dependence on Temperature: Implications on 40 Gb/s Performance

In this letter, we will evaluate the performance degradation of a 40 km high‐speed (40 Gb/s) optical system, induced by optical fiber variations of the chromatic dispersion induced by temperature changes. The chromatic dispersion temperature sensitivity will be estimated based on the signal quality parameters.     

Anodising potential influence on well-ordered nanostructures formed by anodisation of aluminium in sulphuric acid

High-density structures with relatively well-ordered nanopore arrays have been obtained by the self-ordering growth of nanopores occurring during anodisation of aluminium in sulphuric acid. The resulting array of well-ordered nanopores strongly depends on an applied voltage of anodising, temperature and a procedure of synthesis. Regular arranged hexagonal arrays on aluminium with a relatively uniform pore diameter, interpore distance, and depth of pores exceeding 90 μm, can be formed by the self-ordering two-step anodising at 1 °C. The interpore distance and the pore diameter were evaluated on anodised aluminium layers obtained at different cell potentials ranging from 15 to 25 V. The detailed analyses of their uniformity were performed from SEM images. The analysis of a pore arrangement defects was made from SEM top view images taken on samples anodised at various cell potentials. The defect maps, known as Delaunay triangulations, of the arrangement of about 1000 pores were constructed for different applied anodising potentials. The percentage of pores that are not six-fold coordinated by the neighbouring pores indicates the percentage of defected surface.     

Antimutagenic activity of natural phenolic compounds present in the common bean ( Phaseolus vulgaris ) against aflatoxin B 1

Polyphenols with antimutagenic and anticarcinogenic properties are present in fruits, vegetables and legumes. In this study, the Salmonella typhimurium tester strains TA98 and TA100 were used in the microsuspension assay to examine the antimutagenic effect of phenolic compounds extracted from the common bean (Phaseolus vulgaris) against mutagenicity induced by aflatoxin B 1 (AFB 1 ). A dose-response curve was constructed for AFB 1 ; from which a level of 40ng AFB 1 /tube was selected for all antimutagenicity assays. The AFB 1 and phenolic extract (PE) were not toxic to the bacteria at concentrations tested. In the case of PE, results were similar to the number of spontaneous revertants for TA98 and TA100. The inhibitory effect of PE against AFB 1 mutagenicity was dose-dependent at the lower concentrations tested (2.5, 5, 10, 12.5, 15 and 25 μg-equivalent ( + )-catechin/tube for TA98; 0.5, 1, 1.5, 2.5, 5, 10 and 25 μg-equivalent ( + )-catechin/ tube for TA100). Further, a two-stage incubation procedure was used to investigate the potential interaction between PE and AFB 1 . The greatest inhibitory effect of the PE on AFB 1 mutagenicity occurred when PE and AFB 1 were incubated together. When the bacteria were first incubated with PE followed by a second incubation with AFB 1 , lower inhibition was observed. Lower inhibition was also observed when the bacteria were first incubated with AFB 1 followed by a second incubation with PE. The results suggest that the mechanism of inhibition could involve the formation of a chemical complex between of PE and AFB 1 .     

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.     

Multiple Testing Correction in Medical Image Analysis

We present a novel method for correcting the significance level of hypothesis testing that requires multiple comparisons. It is based on the spectral graph theory, in which the variables are seen as the vertices of a complete undirected graph and the correlation matrix as the adjacency matrix that weights its edges. The method increases the statistical power of the analysis by refuting the assumption of independence among variables, while keeping the probability of false positives low. By computing the eigenvalues of the correlation matrix, it is possible to obtain valuable information about the dependence levels among the variables of the problem, so that the effective number of independent variables can be estimated. The method is compared to other available models and its effectiveness illustrated in case studies involving high-dimensional sets of variables.