Geophysical imaging of stimulated microbial biomineralization

Understanding how microorganisms influence the physical and chemical properties of the subsurface is hindered by our inability to observe microbial dynamics in real time and with high spatial resolution. Here, we investigate the use of noninvasive geophysical methods to monitor biomineralization at the laboratory scale during stimulated sulfate reduction under dynamic flow conditions. Alterations in sediment characteristics resulting from microbe-mediated sulfide mineral precipitation were concomitant with changes in complex resistivity and acoustic wave propagation signatures. The sequestration of zinc and iron in insoluble sulfides led to alterations in the ability of the pore fluid to conduct electrical charge and of the saturated sediments to dissipate acoustic energy. These changes resulted directly from the nucleation, growth, and development of nanoparticulate precipitates along grain surfaces and within the pore space. Scanning and transmission electron microscopy (SEM and TEM) confirmed the sulfides to be associated with cell surfaces, with precipitates ranging from aggregates of individual 3-5 nm nanocrystals to larger assemblages of up to 10-20 m in diameter. Anomalies in the geophysical data reflected the distribution of mineral precipitates and biomass over space and time, with temporal variations in the signals corresponding to changes in the aggregation state of the nanocrystalline sulfides. These results suggest the potential for using geophysical techniques to image certain subsurface biogeochemical processes, such as those accompanying the bioremediation of metal-contaminated aquifers.

Fragmentation of metastable SF6−* ions with microsecond lifetimes in competition with autodetachment

Fragmentation of metastable SF6-* ions formed in low energy electron attachment to SF₆has been investigated. The dissociation reaction SF6-*?SF5-+F has been observed ~ 1.5–3.4 µs and ~ 17–32 µs after electron attachment in a time-of-flight and a double focusing two sector field mass spectrometer, respectively. Metastable dissociation is observed with maximum intensity at ~ 0.3 eV between the SF6-* peak at zero and theSF5- peak at ~ 0.4 eV. The kinetic energy released in dissociation is low, with a most probable value of 18 meV. The lifetime of SF6-* decreases as the electron energy increases, but it is not possible to fit this decrease with statistical Rice–Ramsperger–Kassel/quasiequilibrium theory. Metastable dissociation of SF6-* appears to compete with autodetachment of the electron at all electron energies.

Gene selection by cooperative competition clustering

Clustering analysis of data from DNA microarray hybridization studies is an essential task for identifying biologically relevant groups of genes. Attribute cluster algorithm (ACA) has provided an attractive way to group and select meaningful genes. However, ACA needs much prior knowledge about the genes to set the number of clusters. In practical applications, if the number of clusters is misspecified, the performance of the ACA will deteriorate rapidly. In fact, it is a very demanding to do that because of our little knowledge. We propose the Cooperative Competition Cluster Algorithm (CCCA) in this paper. In the algorithm, we assume that both cooperation and competition exist simultaneously between clusters in the process of clustering. By using this principle of Cooperative Competition, the number of clusters can be found in the process of clustering. Experimental results on a synthetic and gene expression data are demonstrated. The results show that CCCA can choose the number of clusters automatically and get excellent performance with respect to other competing methods.