Adsorption Characteristics of Reactive Dyes in Columns of Activated Carbon

Abstract: Adsorption behaviour of reactive dyes in fixed-bed adsorber was evaluated in this work. The characteristics of mass transfer zone (MTZ), where adsorption in column occurs, were affected by carbon bed depth and influent dye concentration. The working lifetime (t(x)) of MTZ, the height of mass transfer zone (HMTZ), the rate of mass transfer zone (RMTZ), and the column capacity at exhaustion (q(column)) were estimated for the removal of remazol reactive yellow and remazol reactive black by carbon adsorber. The results showed that column capacity calculated at 90% of column exhaustion was lower than carbon capacity obtained from equilibrium studies. This indicated that the capacity of activated carbon was not fully utilized in the fixed-bed adsorber. The bed-depth service time model (BDST) was applied for analysis of reactive yellow adsorption in the column. The adsorption capacity of reactive yellow calculated at 50% breakthrough point (No) was found to be 0.1 kg kg(-1) and this value is equivalent to about 14% of the available carbon capacity. The results of this study indicated the applicability of fixed-bed adsorber for removing remazol reactive yellow from solution. (C) 2008 Elsevier B.V. All rights reserved.

Constructing probabilistic ATMS using extended incidence calculus

This paper discusses the relations between extended incidence calculus and assumption-based truth maintenance systems (ATMSs). We first prove that managing labels for statements (nodes) in an ATMS is equivalent to producing incidence sets of these statements in extended incidence calculus. We then demonstrate that the justification set for a node is functionally equivalent to the implication relation set for the same node in extended incidence calculus. As a consequence, extended incidence calculus can provide justifications for an ATMS, because implication relation sets are discovered by the system automatically. We also show that extended incidence calculus provides a theoretical basis for constructing a probabilistic ATMS by associating proper probability distributions on assumptions. In this way, we can not only produce labels for all nodes in the system, but also calculate the probability of any of such nodes in it. The nogood environments can also be obtained automatically. Therefore, extended incidence calculus and the ATMS are equivalent in carrying out inferences at both the symbolic level and the numerical level. This extends a result due to Laskey and Lehner.

Effect of solution pH, ionic strength, and temperature on adsorption behavior of reactive dyes on activated carbon

The adsorption behavior of C.I. Reactive Blue 2, C.I. Reactive Red 4, and C.I. Reactive Yellow 2 from aqueous solution onto activated carbon was investigated under various experimental conditions. The adsorption capacity of activated carbon for reactive dyes was found to be relatively high. At pH 7.0 and 298 K, the maximum adsorption capacity for C.I. Reactive Blue 2, C.I. Reactive Yellow 2 and C.I. Reactive Red 4 dyes was found to be 0.27, 0.24, and 0.11 mmol/g, respectively. The shape of the adsorption isotherms indicated an L2-type isotherm according to the Giles and Smith classification. The experimental adsorption data showed good correlation with the Langmuir and Ferundlich isotherm models. Further analysis indicated that the formation of a complete monolayer was not achieved, with the fraction of surface coverage found to be 0.45, 0.42, and 0.22 for C.I. Reactive Blue 2, C.I. Reactive Yellow 2 and C.I. Reactive Red 4 dyes, respectively. Experimental data indicated that the adsorption capacity of activated carbon for the dyes was higher in acidic rather than in basic solutions, and further indicated that the removal of dye increased with increase in the ionic strength of solution, this was attributed to aggregation of reactive dyes in solution. Thermodynamic studies indicated that the adsorption of reactive dyes onto activated carbon was an endothermic process. The adsorption enthalpy (?H) for C.I. Reactive Blue 2 and C.I. Reactive Yellow 2 dyes were calculated at 42.2 and 36.2 kJ/mol, respectively. The negative values of free energy (?G) determined for these systems indicated that adsorption of reactive dyes was spontaneous at the temperatures under investigation (298-328 K). © 2007 Elsevier Ltd. All rights reserved.

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.

Application of poly(ethylene glycol)-based aqueous biphasic systems as reaction and reactive extraction media

Poly(ethylene glycol)-based aqueous biphasic systems (PEG-ABSs) have been investigated as tunable reaction media, in the example presented here, to control the oxidation of cyclohexene to adipic acid with hydrogen peroxide. The production of adipic acid was found to increase from the monophasic to the biphasic regimes, was greatest at short tie-line lengths (close to the system's critical point), and demonstrates how control of the ABS media, through changes in system composition, PEG, salt, and tie-line length, can be used to readily tune and control reactivity and product isolation in these aqueous biphasic reactive extraction systems. Challenges in using this system, including possible oxidation reactions of the PEG-OH end groups, are also discussed.

Exploratory analysis of spatiotemporal patterns of cellular automata by clustering compressibility

In this paper we study the classification of spatiotemporal pattern of one-dimensional cellular automata (CA) whereas the classification comprises CA rules including their initial conditions. We propose an exploratory analysis method based on the normalized compression distance (NCD) of spatiotemporal patterns which is used as dissimilarity measure for a hierarchical clustering. Our approach is different with respect to the following points. First, the classification of spatiotemporal pattern is comparative because the NCD evaluates explicitly the difference of compressibility among two objects, e.g., strings corresponding to spatiotemporal patterns. This is in contrast to all other measures applied so far in a similar context because they are essentially univariate. Second, Kolmogorov complexity, which underlies the NCD, was used in the classification of CA with respect to their spatiotemporal pattern. Third, our method is semiautomatic allowing us to investigate hundreds or thousands of CA rules or initial conditions simultaneously to gain insights into their organizational structure. Our numerical results are not only plausible confirming previous classification attempts but also shed light on the intricate influence of random initial conditions on the classification results.