5 resultados para MC-LR-Cys
em University of Queensland eSpace - Australia
Resumo:
In Australian freshwaters, Anabaena circinalis, Microcystis spp. and Cylindrospermopsis raciborskii are the dominant toxic cyanobacteria. Many of these Surface waters are used as drinking water resources. Therefore, the National Health and Medical Research Council of Australia set a guideline for MC-LR toxicity equivalents of 1.3 mug/l drinking, water. However, due to lack of adequate data, no guideline values for paralytic shellfish poisons (PSPs) (e.g. saxitoxins) or cylindrospermopsin (CYN) have been set. In this spot check. the concentration of microcystins (MCs), PSPs and CYN were determined by ADDA-ELISA, cPPA, HPLC-DAD and/or HPLC-MS/MS, respectively, in two water treatment plants in Queensland/Australia and compared to phytoplankton data collected by Queensland Health, Brisbane. Depending on the predominant cyanobacterial species in a bloom, concentrations of up to 8.0, 17.0 and 1.3 mug/l were found for MCs, PSPs and CYN, respectively. However, only traces (< 1.0 mug/l) of these toxins were detected in final water (final product of the drinking water treatment plant) and tap water (household sample). Despite the low concentrations of toxins detected in drinking water, a further reduction of cyanobacterial toxins is recommended to guarantee public safety. (C) 2004 Elsevier Ltd. All rights reserved.
Review of L Mc Reynolds and J Neuberger eds: Imitation of Life: Two centuries of melodrama in Russia
Resumo:
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.
Resumo:
This paper describes two algorithms for adaptive power and bit allocations in a multiple input multiple output multiple-carrier code division multiple access (MIMO MC-CDMA) system. The first is the greedy algorithm, which has already been presented in the literature. The other one, which is proposed by the authors, is based on the use of the Lagrange multiplier method. The performances of the two algorithms are compared via Monte Carlo simulations. At present stage, the simulations are restricted to a single user MIMO MC-CDMA system, which is equivalent to a MIMO OFDM system. It is assumed that the system operates in a frequency selective fading environment. The transmitter has a partial knowledge of the channel whose properties are measured at the receiver. The use of the two algorithms results in similar system performances. The advantage of the Lagrange algorithm is that is much faster than the greedy algorithm. ©2005 IEEE