Pilot Plant Study of Simultaneous Sewage Sludge Digestion and Metal Leaching

This research is related to a preindustrial pilot scale study of the performance of the simultaneous sewage sludge digestion and metal leaching (SSDML) process for decontamination and stabilization of sewage sludge. Ten batch tests were carried out in two 4?m3 bioreactors under various conditions of operation. Results indicated that the addition of 1.0 to 1.5?g?S0/L, which is the equivalent of approximately 30 to 50?kg?S0 per tons dry sludge, is sufficient to obtain conditions of acidity (pH<2.5) and oxido-reduction potential greater than 500 mV necessary for an effective solubilization of toxic metals. The final average of metal solubilization in the output sludge during the SSDML process varied in the following ranges: 25–78% Cd, 9–32% Cr, 48–100% Cu, 77–99% Mn, 15–53% Ni, 12–47% Pb, and 66–100% Zn. The N, P, and K contents were also preserved in the decontaminated sludge. Moreover, the use of low concentrations of elemental sulfur makes it possible to obtain decontaminated sludge with a low total sulfur content (1.4–1.5% S) compatible with agricultural use. The suspended solids removal calculated for the SSDML process was slightly lower, (2.5±0.4)% volatile suspended solids per day, than those reached using standard aerobic digestion. Finally, the SSDML process was found to be effective in removing bad odors and in the destruction (99–100%) of indicator bacteria.     

Sparse field level set method for non-convex Hamiltonians in 3D plasma etching profile simulations

Level set method [S. Osher, J. Sethian, J. Comput. Phys. 79 (1988) 12] is a highly robust and accurate computational technique for tracking moving interfaces in various application domains. It originates from the idea to view the moving front as a particular level set of a higher dimensional function, so the topological merging and breaking, sharp gradients and cusps can form naturally, and the effects of curvature can be easily incorporated. The resulting equations, describing interface surface evolution, are of Hamilton-Jacobi type and they are solved using techniques developed for hyperbolic equations. In this paper we describe an extension of the sparse field method for solving level set equations in the case of non-convex Hamiltonians, which are common in the simulations of the profile surface evolution during plasma etching and deposition processes. Sparse field method itself, developed by Whitaker [R. Whitaker, Internat. J. Comput. Vision 29 (3) (1998) 203] and broadly used in image processing community, is an alternative to the usual combination of narrow band and fast marching procedures for the computationally effective solving of level set equations. The developed procedure is applied to the simulations of 3D feature profile surface evolution during plasma etching process, that include the effects of ion enhanced chemical etching and physical sputtering, which are the primary causes of the Hamiltonian non-convexity.     

On the effect of spatial variances in historical rainfall time series to CSO performance evaluation.

Historical, high-resolution rain series are the backbone of modern combined sewer overflow (CSO) structure design. These rain series are the input to the computational estimation of the performance of the measures with respect to CSO pollution abatement. However, those historical precipitation measurements are available at only a few locations. Frequently rain series have to be used from gauging stations at a significant distance. In order to judge and to compensate for this influence an estimate between rain characteristics and combined sewer outflow (CSO) performance indicators would be useful. In this paper such correlations have been sought for a collection of 37 rain series covering large areas of Europe. It was found that the mean annual rain volume can explain most of the variances for the performance indicators Number of overflows and CSO volume. For explaining the spatial differences in the efficiency of the CSO structure another rain characteristic, i.e. the maximum event with a return period of one year, is to be used.     

A new polymer electrolyte poly(acrylonitrile)-dimethylsulphoxide-salt for electrochemical capacitors

The PAN-DMSO-Et₄NBF₄ and PAN-DMSO-Et₄NTf (Tf is triflate ion) electrolytes were prepared as white, turbid foils with a thickness in the range of 0.1-0.5 mm, using the casting technique. Room temperature conductance of the electrolytes, detected from ac impedance experiments, was at the level of 8 and 14 mS cm⁻¹ for Et₄NBF₄ and Et₄NTf salts, respectively. The electrochemical stability window of approximately 2.6-2.8 V was estimated using a glassy carbon electrode. Temperature dependence of the conductivity is of the Arrhenius-type for both electrolytes, with an activation energy of approximately 34 kJ mol⁻¹. The double-layer capacitors built with these electrolytes, serving both as separators and activated carbon powder (ACP) binders, showed a specific capacity of 50 F g⁻¹ of carbon material. Capacitors were assembled by sandwiching the PAN-DMSO-salt electrolyte between two PAN-salt-DMSO-ACP-AB electrodes and pressing across the system; the resulting devices had a coin-like shape with 8 mm diameter and thickness between 2.0 and 2.5 mm.     

Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

Vehicle detection by means of stereo vision-based obstacles features extraction and monocular pattern analysis.

This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision-based algorithm is used to extract relevant three-dimensional (3-D) features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3-D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3-D information previously extracted, an accurate distance computation is performed.     

Velocity selective filters recursively implemented in the spatiotemporal domain.

Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.     

Josef Maria Bro?ek (1913-2004).

Presents an obituary and information about the life and accomplishments of Josef Maria Bro?ek. Born August 14, 1913, in the ancient town of Melnik, in central Bohemia, today the Czech Republic, Josef spent his childhood in Poland (Warsaw, 1913- 1915) and in Siberia (1915-1920). His education in Czechoslovakia culminated with a thesis on "Memory, Its Measurement and Structure" and a PhD awarded in June 1937. In the history of psychology, his lifetime project bore the title "Historiography of Psychology Around the World," and it covered about 20 geographical areas. Extensive attention was devoted to institutional and organizational developments as journals, academic settings, archives, museums, research groups, conferences, and institutes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hydrogen annealing effect on DC and low-frequency noise characteristics in CMOS FinFETs

The hydrogen annealing process has been used to improve surface roughness of the Si-fin in CMOS FinFETs for the first time. Hydrogen annealing was performed after Si-fin etch and before gate oxidation. As a result, increased saturation current with a lowered threshold voltage and a decreased low-frequency noise level over the entire range of drain current have been attained. The low-frequency noise characteristics indicate that the oxide trap density is reduced by a factor of 3 due to annealing. These results suggest that hydrogen annealing is very effective for improving device performance and for attaining a high-quality surface of the etched Si-fin.