The formation and survival probability of negative carbon ions sputtered from a graphite sample was determined. The energy distribution of Cy ions was measured experimentally and the energy distribution of all sputtered carbon atoms was obtained from a computer simulation with the program TRIM.SP. From the two distributions, we obtained the probability that a carbon atom would capture an electron from the graphite and subsequently survive as it moves away from the surface. Ż. The results show two different situations. At low energy below 25 eV , the sputtered particles are all negatively ionized when the affinity level crosses the graphite Fermi level and afterwards, the population decay follows a semi-classical rate equation. Ż.At higher energy above 25 eV , a velocity-dependent fraction reaches the crossing distance as neutral atoms

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We describe our experimentation with the design and implementation of specific environments, consisting of heterogeneous computational, visualization, and control components. We illustrate the approach with the design of a problem–solving environment supporting the execution of genetic algorithms. We describe a prototype supporting parallel execution, visualization, and steering. A life cycle for the development of applications based on genetic algorithms is proposed.

Presacral vertebrae of a new Diplodocidae from the Late Jurassic Amoreira-Porto Novo Formation of Lourinhã, Portugal are described and figured. Dinheirosaurus lourinhanensis gen. et sp. is diagnosed by well developed accessory articulations derived from the hyposphene, exposed in lateral view; and by the smaller dorsoventral length of the lower section of the neural arch. It is considered that the organization of the dorsal neural arch of Dinheirosaurus is more derived than in Diplodocus, except in the dorsoventral development of the lower portion of it, which is higher (more derived) in the latter. Possibly the isolated geography of Portugal in the Late Jurassic gave rise to the distinct characters of this new genus.

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Fuscoredoxin is a unique iron containing protein of yet unknown function originally discovered in the sulfate reducers of the genus Desulfovibrio. It contains two iron-sulfur clusters: a cubane [4Fe-4S] and a mixed oxo- and sulfide-bridged 4Fe cluster of unprecedented structure. The recent determination of the genomic sequence of Escherichia coli (E. coli) has revealed a homologue of fuscoredoxin in this facultative microbe. The presence of this gene in E. coli raises interesting questions regarding the function of fuscoredoxin and whether this gene represents a structural homologue of the better-characterized Desulfovibrio proteins. In order to explore the latter, an overexpression system for the E. coli fuscoredoxin gene was devised. The gene was cloned from genomic DNA by use of the polymerase chain reaction into the expression vector pT7-7 and overexpressed in E. coli BL21(DE3) cells. After two chromatographic steps a good yield of recombinant protein was obtained (approximately 4 mg of pure protein per liter of culture). The purified protein exhibits an optical spectrum characteristic of the homologue from D. desulfuricans, indicating that cofactor assembly was accomplished. Iron analysis indicated that the protein contains circa 8 iron atoms/molecule which were shown by EPR and Mossbauer spectroscopies to be present as two multinuclear clusters, albeit with slightly altered spectroscopic features. A comparison of the primary sequences of fuscoredoxins is presented and differences on cluster coordination modes are discussed on the light of the spectroscopic data. (C) 1999 Academic Press.

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We describe our experimentation with the design and implementation of specific environments, consisting of heterogeneous computational, visualization, and control components. We illustrate the approach with the design of a problem–solving environment supporting the execution of genetic algorithms. We describe a prototype supporting parallel execution, visualization, and steering. A life cycle for the development of applications based on genetic algorithms is proposed.

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