Hybrid Monte Carlo for photon transport through optically thick scattering media

A Monte Carlo simulation code developed to model time-domain transillumination measurements with small-area detectors through an optically thick scattering slab is presented. A hybrid approach has been implemented to reduce calculation times. Most of the scattering slab is treated stochastically, albeit with variance reduction techniques and the isotropic diffusion similarity rule. The contribution to the output signal per unit area and time of photon packets propagating in a thin slice near the output face of the slab is calculated analytically after each propagation step. This approach drastically reduces the calculation time but produces spikes in the temporal signals.     

A study of volatile organic compounds decomposition with the use of non-thermal plasma

Non-thermal plasma processing is an effective method to decompose diluted VOC contaminants in manufacturing rooms for the electronic industry. In this paper, two different discharge-type laboratory scale reactors (Double Dielectric Barrier Discharge and Packed-Bed Discharge) that generate non-thermal plasma have been developed and the decomposition tests were conducted. The tested VOC was Benzene, Toluene, Xylene, P-cumene, Diethylether and Dichlormethane. It was found from the experimental results for the present reactors that Benzene oxidization required higher energy than the other aromatic hydrocarbons with side branches. The decomposition efficiency was high for Cumene and Xylene (two methyl-side groups) and low for Toluene (one methyl group) and Diethylether. One of the frequently used solvents in semiconductor industry, Dichlormethane which can destroy atmospheric ozone layer, could be decomposed in the Double Dielectric Barrier Discharge with minimum power consumption and the DDBD reactor had a little higher decomposition efficiency than the Packed-Bed reactor.     

A new approach for the purification and characterisation of PA49.5, the main prebiotic of Lactococcus lactis subsp. cremoris

The main autolysin PA49.5, an enzyme that hydrolyzes or destroys the components of a biological endogenous cell or a tissue, was purified 3045 times from the homogenate of a whole cell extract of Lactococcus lactis subsp. cremoris ATCC 9596 (Mc5), with a recovery yield of 52%. The purification of the protein was carried out through a micro-purification technique using SDS-BigCHAP polyacrylamide gel electrophoresis and concentrated with a Microcon-10 filtration system. SDS-polyacrylamide gel electrophoresis of the purified enzyme confirmed the presence of only one band having a molecular weight of 49.5 kDa. In view of its insolubility, PA49.5 contained in the cell extract precipitate was solubilized in the presence of 0.1% (w/v) of BigCHAP, a non-ionic detergent. Higher concentrations of this detergent completely inhibited the activity of solubilized PA49.5 or prevented its solubilization. The optimal pH and temperature for PA49.5 enzymatic activity are 7.5 and 45 degrees C respectively. In addition 0.1% or less of PA49.5 significantly increased Mc5 lysis. We observed 55% more lysis with 0.25 mug of purified PA49.5 compared to the control. Gas chromatography analysis of the components of the crude cell extract, of the precipitate and of the supernatant indicates the presence of at least 6 fatty acids. The long-chained fatty acids (e.g. C18:0 and C18:3) detected represent 81.65% of the precipitate from which PA49.5 was purified. Of these two acids, the C18:0 (stearic acid) alone represents 47.40% of the precipitate. Mc5 releases proteins at the beginning (major peak) and at the end (moderate peak) of the exponential stage of growth. Analysis by denaturing polyacrylamide gel electrophoresis with Mc5 cell walls incorporated as the autolysin's substrate identified a band corresponding to PA49.5 in the second peak of protein secretion.     

Technical and business considerations of cobalt hydrometallurgy

Approximately 55,000 tonnes of cobalt are produced annually worldwide, which represents an estimated $1–3 billion in annual sales depending on cobalt price changes. Cobalt is a common impurity in both non-ferrous mineral sulfide and oxide processing. In this paper some business and technical considerations are presented to facilitate the decision-making process required to produce either an intermediate or a finished cobalt product via a hydrometallurgical route. Methods currently available and practiced for the recovery of cobalt are considered, and process requirements up- and down-stream associated with each chosen method are discussed. In particular, some environmental, energy, or other sustainable development implications of each process are mentioned. An outlook on the future of the cobalt industry and anticipated future trends is included.     

Segmentation of rodent whole-body dynamic PET images: an unsupervised method based on voxel dynamics

Positron emission tomography (PET) is a useful tool for pharmacokinetics studies in rodents during the preclinical phase of drug and tracer development. However, rodent organs are small as compared to the scanner's intrinsic resolution and are affected by physiological movements. We present a new method for the segmentation of rodent whole-body PET images that takes these two difficulties into account by estimating the pharmacokinetics far from organ borders. The segmentation method proved efficient on whole-body numerical rat phantom simulations, including 3-14 organs, together with physiological movements (heart beating, breathing, and bladder filling). The method was resistant to spillover and physiological movements, while other methods failed to obtain a correct segmentation. The radioactivity concentrations calculated with this method also showed an excellent correlation with the manual delineation of organs in a large set of preclinical images. In addition, it was faster, detected more organs, and extracted organs' mean time activity curves with a better confidence on the measure than manual delineation.     

Impact of treated wastewater irrigation on antibiotic resistance in agricultural soils

Antibiotic resistance (AR) is a global phenomenon with severe epidemiological ramifications. Anthropogenically impacted natural aquatic and terrestrial environments can serve as reservoirs of antibiotic resistance genes (ARG), which can be horizontally transferred to human-associated bacteria through water and food webs, and thus contribute to AR proliferation. Treated-wastewater (TWW) irrigation is becoming increasingly prevalent in arid regions of the world, due to growing demand and decline in freshwater supplies. The release of residual antibiotic compounds, AR bacteria, and ARGs from wastewater effluent may result in proliferation of AR in irrigated soil microcosms. The aim of this study was to assess the impact of TWW-irrigation on soil AR bacterial and ARG reservoirs. Tetracycline, erythromycin, sulfonamide, and ciprofloxacin resistance in soil was assessed using standard culture-based isolation methods and culture-independent molecular analysis using quantitative real-time PCR (qPCR). High levels of bacterial antibiotic resistance were detected in both freshwater- and TWW-irrigated soils. Nonetheless, in most of the soils analyzed, AR bacteria and ARG levels in TWW-irrigated soils were on the whole identical (or sometimes even lower) than in the freshwater-irrigated soils, indicating that the high number of resistant bacteria that enter the soils from the TWW are not able to compete or survive in the soil environment and that they do not significantly contribute ARG to soil bacteria. This strongly suggests that the impact of the TWW-associated bacteria on the soil microbiome is on the whole negligible, and that the high levels of AR bacteria and ARGs in both the freshwater- and the TWW-irrigated soils are indicative of native AR associated with the natural soil microbiome.     

Faults prognosis using partially observed stochastic Petri-nets: an incremental approach

This article deals with the problem of fault prognosis in stochastic discrete event systems. For that purpose, partially observed stochastic Petri nets are considered to model the system with its sensors. The model represents both healthy and faulty behaviors of the system. Our goal is, based on a timed measurement trajectory issued from the sensors, to compute the probability that a fault will occur in a future time interval. To this end, a procedure based on an incremental algorithm is proposed to compute the set of consistent behaviors of the system. Based on the measurement dates, the probabilities of the consistent trajectories are evaluated and a state estimation is obtained as a consequence. From the set of possible current states and their probabilities, a method to evaluate the probability of future faults is developed using a probabilistic model. An example is presented to illustrate the results.