Mineralization of Acephate, a Recalcitrant Organophosphate Insecticide Is Initiated by a Pseudomonad in Environmental Samples

An aerobic bacterium capable of breaking down the pesticide acephate (O,S-dimethyl acetyl phosphoramidothioic acid) was isolated from activated sludge collected from a pesticide manufacturing facility. A phylogenetic tree based on the 16 S rRNA gene sequence determined that the isolate lies within the Pseudomonads. The isolate was able to grow in the presence of acephate at concentrations up to 80 mM, with maximum growth at 40 mM. HPLC and LC-MS/MS analysis of spent medium from growth experiments and a resting cell assay detected the accumulation of methamidophos and acetate, suggesting initial hydrolysis of the amide linkage found between these two moieties. As expected, the rapid decline in acephate was coincident with the accumulation of methamidophos. Methamidophos concentrations were maintained over a period of days, without evidence of further metabolism or cell growth by the cultures. Considering this limitation, strains such as described in this work can promote the first step of acephate mineralization in soil microbial communities

Gravitational Waves from Gravitational Collapse

Gravitational wave emission from the gravitational collapse of massive stars has been studied for more than three decades. Current state of the art numerical investigations of collapse include those that use progenitors with realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non--axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with advanced ground--based and future space--based interferometric observatories.Comment: 68 pages including 13 figures; revised version accepted for publication in Living Reviews in Relativity (http://www.livingreviews.org

Bounding the Risk Probability

International audienceFor some safety–critical applications, it is important to calculate the probability that a discrete time autoregressive (AR) process leaves a given interval at least once during a certain period of time. For example, such AR process can be interpreted as a temporally correlated safety indicator and the interval as a target zone of the process. It is assumed that the safety of the system under surveillance is compromised if the above-mentioned probability becomes too important. This problem has been previously studied in the case of known distributions of the innovation process. Let us assume now that the distributions of the innovation and initial state are unknown but some special bounds for the cumulative distribution functions and/or for the probability density functions are available. Numerical methods to calculate the bounds for the above-mentioned probability are considered in the paper