Efficiency of integrated electrooxidation and anaerobic digestion of waste activated sludge.

BACKGROUND: Most of the organic content of waste activated sludge (WAS) comprises microbial cells hard to degrade, which must be pre-treated for energy recovery by anaerobic digestion (AD). Electrooxidation pre-treatment (EOP) with boron-doped diamond (BDD) electrode have been considered a promising novel technology that increase hydrolysis rate, by the disintegrating cell walls from WAS. Although electrochemical oxidation could efficiently solubilize organic substances of macromolecules, limited reports are available on EOP of WAS for improving AD. In this endeavour, the mathematical optimization study and the energy analysis of the effects of initial total solids concentrations [TS] of WAS and current density (CD) during EOP on the methane production and removal of chemical oxygen demand (COD) and volatile solids (VS) were investigated. Because limited reports are available on EOP of WAS for improving biogas production, it is not well understood; however, it has started to attract interest of scientists and engineers. RESULTS: In the present work, the energy recovery as biogas and WAS conversion were comprehensively affected by CD and [TS], in an integrated EOP and AD system. When working with WAS at 3% of [TS] pre-treated at current density of 24.1 mA/cm2, the highest COD and VS removal were achieved, making it possible to obtain the maximum methane (CH4) production of 305 N-L/kg VS and a positive energy balance of 1.67 kWh/kg VS. Therefore, the current densities used in BDD electrode are adequate to produce the strong oxidant (hydroxyl radical, ·OH) on the electrode surface, allow the oxidation of organic compounds that favours the solubilization of particulate matter and VS from WAS. CONCLUSIONS: The improvement of VS removal and COD solubilization were due to the effects of pre-treatments, which help to break down the microbial cells for faster subsequent degradation; this allows a decomposition reaction that leads to biodegrade more compounds during AD. The balance was positive, suggesting that even without any optimization the energy used as electricity could be recovered from the increased methane production. It is worth noting that this kind of analysis have not been sufficiently studied so far. It is therefore important to understand how operational parameters can influence the pre-treatment and AD performances. The current study highlights that the mathematical optimization and energy analysis can make the whole process more convenient and feasible.

Copper removal from an effluent generated by a plastics chromium-plating industry using a rotating cylinder electrode (RCE) reactor.

This work shows the application of a rotating cylinder electrode (RCE) in the removal of Cu(II) content from an effluent generated by a plastics chromium-plating industry, on the laboratory scale; in particular, it deals with rinse water from the electrolytic copper process. This process was designed to convert cupric ions in solution to metal powder. The generation of metal powders in the RCE was achieved at Reynolds numbers between 52925 and 83183 and limiting current densities (J(L)) in the range of 17 to 25 mA cm(-2). The removal of Cu(II) (initially 922 ppm) reached 43 ppm in 10 minutes of electrolysis for Re = 83183 and J = 25 mA cm(-2), with a space-time yield of 88 mg Cu(II) L(-1) min(-1), 95% current efficiency, and energy consumption of 5.3 KWh m(-3). The electrochemical treatment applied to waste rinse water at the RCE allows this treated water to be recycled back to the same rinsing process, avoiding additional consumption and discharge of this liquid.

Detection, classification and 3D reconstruction of biological macromolecules on hypercube computers.

In this work we present results of the mapping on hypercube computers of some of the key steps involved in the procedure for 3D structural determination from transmission electron microscopy images. The goal is the introduction of parallel processing tools in the field of electron microscopy image processing. We show how the rich topology of the hypercube, combined with an efficient programming strategy, allows for order-of-magnitude increase in computational capacity for such time-consuming tasks as calculation of multidimensional FFT's, cross-correlation coefficients, fuzzy partitioning functionals and the filtered back-projection 3D reconstruction method.

Fuzzy sets-based classification of electron microscopy images of biological macromolecules with an application to ribosomal particles.

Pattern recognition methods based on the theory of fuzzy sets are tested for their ability to classify electron microscopy images of biological specimens. The concept of fuzzy sets was chosen for its ability to represent classes of objects that are vaguely described from the measured data. A number of partitional clustering algorithms and an extensive set of cluster-validity functionals (some already reported and some newly developed) have been applied to a test-data set and to two real-data sets of images. One of the real-data sets corresponded to images of the Escherichia coli 50S ribosomal subunits depleted of proteins L7/L12 and the other set to images of the E. coli 70S monosome in the range of overlap views. These two latter sets had been previously studied by another clustering methodology. The new results obtained by the application of fuzzy clustering techniques will be compared to those previously obtained and some conclusions about the consistency of these classifications will be drawn from this comparison.