Biodegradation of the cyanobacterial toxin microcystin LR in natural water and biologically active slow sand filters

A bacterium (MJ-PV) previously demonstrated to degrade the cyanobacterial toxin microcystin LR, was investigated for bioremediation applications in natural water microcosms and biologically active slow sand filters. Enhanced degradation of microcystin LR was observed with inoculated (1 x 10(6) cell/mL) treatments of river water dosed with microcystin LR (> 80% degradation within 2 days) compared to uninoculated controls. Inoculation of MJ-PV at lower concentrations (1 x 10(2)-1 x 10(5)cells/mL) also demonstrated enhanced microcystin LR degradation over control treatments. Polymerase chain reactions (PCR) specifically targeting amplification of 16S rDNA of MJ-PV and the gene responsible for initial degradation of microcystin LR (mlrA) were successfully applied to monitor the presence of the bacterium in experimental trials. No amplified products indicative of an endemic MJ-PV population were observed in uninoculated treatments indicating other bacterial strains were active in degradation of microcystin LR, Pilot scale biologically active slow sand filters demonstrated degradation of microcystin LR irrespective of MJ-PV bacterial inoculation. PCR analysis detected the MJ-PV population at all locations within the sand filters where microcystin degradation was measured. Despite not observing enhanced degradation of microcystin LR in inoculated columns compared to uninoculated column, these studies demonstrate the effectiveness of a low-technology water treatment system like biologically active slow sand filters for removal of microcystins from reticulated water supplies. Crown Copyright (c) 2006 Published by Elsevier Ltd. All rights reserved.

The role of advanced DEM based modelling tools in increasing comminution energy efficiency

Particle breakage is an essential part of mineral processing. The aim is to reduce run of mine mineral ore to an optimal size for liberating target minerals and for subsequent recovery by separation processes such as flotation. This size reduction is typically accomplished in a series of stages in a grinding circuit tailored to the properties of the particular mine ore. Commonly this involves two or more classes of equipment starting with crushers, followed by SAG mills and then sometimes ball mills. Occasionally, high pressure grinding rolls or other novel devices are substituted. Broadly, energy consumption increases and energy efficiency decreases with the fineness of the material produced by each piece of equipment.

Undular tidal bore dynamics in the Daly Estuary, Northern Australia

Measurements in the macro-tidal Daly Estuary show that the presence of an undular tidal bore contributed negligibly to the dissipation of tidal energy. No recirculation bubble was observed between a trough and the following wave crest in the lee waves following the undular bore. This differs to stationary undular bores in laboratory experiments at larger Froude numbers where a recirculation bubble exists. Secondary motions and the turbulence generated by the undular bore had no measurable influence on the sediment transport. This situation contrasts with the intense sediment resuspension observed in breaking tidal bores. The tidally averaged sediment budget in the Daly Estuary was controlled by the asymmetry of tidal currents. The undular bore may widen the river by breaking along the banks that it undercuts, leading to bank slippage. A patch of river-wide macro-turbulence of 3-min duration occurred about 20 min after the passage of the bore during accelerating tidal currents. (C) 2004 Elsevier Ltd. All rights reserved.

Searching for convergence in phylogenetic Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism, and, if Metropolis-coupled MCMC is being used, the number of heated chains and their temperatures. Although some parameter settings have been examined in detail in the literature, others are frequently chosen with more regard to computational time or personal experience with other data sets. Such choices may lead to inadequate sampling of tree space or an inefficient use of computational resources. We performed a detailed study of convergence and mixing for 70 randomly selected, putatively orthologous protein sets with different sizes and taxonomic compositions. Replicated runs from multiple random starting points permit a more rigorous assessment of convergence, and we developed two novel statistics, delta and epsilon, for this purpose. Although likelihood values invariably stabilized quickly, adequate sampling of the posterior distribution of tree topologies took considerably longer. Our results suggest that multimodality is common for data sets with 30 or more taxa and that this results in slow convergence and mixing. However, we also found that the pragmatic approach of combining data from several short, replicated runs into a metachain to estimate bipartition posterior probabilities provided good approximations, and that such estimates were no worse in approximating a reference posterior distribution than those obtained using a single long run of the same length as the metachain. Precision appears to be best when heated Markov chains have low temperatures, whereas chains with high temperatures appear to sample trees with high posterior probabilities only rarely. [Bayesian phylogenetic inference; heating parameter; Markov chain Monte Carlo; replicated chains.]