Metal‐chelating properties of poly(2‐hydroxyethyl methacrylate–methacryloylamidohistidine) membranes

Metal‐chelating membranes have advantages as adsorbents in comparison with conventional beads because they are not compressible and they eliminate internal diffusion limitations. The aim of this study was to explore in detail the performance of poly(2‐hydroxyethyl methacrylate–methacryloylamidohistidine) [poly(HEMA–MAH)] membranes for the removal of three toxic heavy‐metal ions—Cd(II), Pb(II), and Hg(II)—from aquatic systems. The poly(HEMA–MAH) membranes were characterized with scanning electron microscopy and ¹H‐NMR spectroscopy. The adsorption capacity of the poly(HEMA–MAH) membranes for the selected heavy‐metal ions from aqueous media containing different amounts of these ions (30–500 mg/L) and at different pH values (3.0–7.0) was investigated. The adsorption capacity of the membranes increased with time during the first 60 min and then leveled off toward the equilibrium adsorption. The maximum amounts of the heavy‐metal ions adsorbed were 8.2, 31.5, and 23.2 mg/g for Cd(II), Pb(II), and Hg(II), respectively. The competitive adsorption of the metal ions was also studied. When the metal ions competed, the adsorbed amounts were 2.9 mg of Cd(II)/g, 14.8 mg of Pb(II)/g, and 9.4 mg of Hg(II)/g. The poly(HEMA–MAH) membranes could be regenerated via washing with a solution of nitric acid (0.01M). The desorption ratio was as high as 97%. These membranes were suitable for repeated use for more than three adsorption/desorption cycles with negligible loss in the adsorption capacity. The stability constants for the metal‐ion/2‐methacryloylamidohistidine complexes were calculated to be 3.47 × 10⁶, 7.75 × 10⁷, and 2.01 × 10⁷ L/mol for Cd(II), Pb(II), and Hg(II) ions, respectively, with the Ruzic method. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1213–1219, 2005     

Neural network applications in business: A review and analysis of the literature (1988–1995)

A survey of journal articles on neural network business applications published between 1988 and 1995 indicates that an increasing amount of neural network research is being conducted for a diverse range of business activities. The classification of literature by (1) year of publication, (2) application area, (3) problem domain, (4) decision process phase, (5) level of management, (6) level of task interdependence, (7) means of development, (8) corporate/academic interaction in development, (9) technology integration, (10) comparative study, (11) major contribution, and (12) journal provides some insights into the trends in neural networks research. The implications for neural networks developers/researchers and suggestions on future research areas are discussed.     

Epipolar Geometry and Linear Subspace Methods: A New Approach to Weak Calibration

This paper addresses the problem of estimating the epipolar geometry from point correspondences between two images taken by uncalibrated perspective cameras. It is shown that Jepson's and Heeger's linear subspace technique for infinitesimal motion estimation can be generalized to the finite motion case by choosing an appropriate basis for projective space. This yields a linear method for weak calibration. The proposed algorithm has been implemented and tested on both real and synthetic images, and it is compared to other linear and non-linear approaches to weak calibration.     

Predicting bank financial failures using neural networks,support vector machines and multivariate statistical methods: A comparative analysis in the sample of savings deposit insurance fund (SDIF) transferred banks in Turkey

Bank failures threaten the economic system as a whole. Therefore, predicting bank financial failures is crucial to prevent and/or lessen the incoming negative effects on the economic system. This is originally a classification problem to categorize banks as healthy or non-healthy ones. This study aims to apply various neural network techniques, support vector machines and multivariate statistical methods to the bank failure prediction problem in a Turkish case, and to present a comprehensive computational comparison of the classification performances of the techniques tested. Twenty financial ratios with six feature groups including capital adequacy, asset quality, management quality, earnings, liquidity and sensitivity to market risk (CAMELS) are selected as predictor variables in the study. Four different data sets with different characteristics are developed using official financial data to improve the prediction performance. Each data set is also divided into training and validation sets. In the category of neural networks, four different architectures namely multi-layer perceptron, competitive learning, self-organizing map and learning vector quantization are employed. The multivariate statistical methods; multivariate discriminant analysis, k-means cluster analysis and logistic regression analysis are tested. Experimental results are evaluated with respect to the correct accuracy performance of techniques. Results show that multi-layer perceptron and learning vector quantization can be considered as the most successful models in predicting the financial failure of banks.     

Polyethylenimine‐grafted and HSA‐immobilized poly(GMA–MMA) affinity adsorbents for bilirubin removal

The epoxy‐group‐containing microspheres from cross‐linked glycidyl methacrylate and methyl methacrylate, poly(GMA–MMA), were prepared by suspension polymerisation. The epoxy groups of the poly(GMA–MMA) microspheres were used for grafting with an anionic polymer polyethylenimine (PEI) to prepare non‐specific affinity adsorbents (poly(GMA–MMA)–PEI) for bilirubin removal. The specificity of the poly(GMA–MMA)–PEI adsorbent to bilirubin was further increased by immobilization of human serum albumin (HSA) via adsorption onto PEI‐grafted poly(GMA–MMA) adsorbent. Various amounts of HSA were immobilized on the poly(GMA–MMA)–PEI adsorbent by changing the medium pH and initial HSA concentration. The maximum HSA content was obtained at 68.3 mg g^?1 microspheres. The effects of pH, ionic strength, temperature and initial bilirubin concentration on the adsorption capacity of both adsorbents were investigated in a batch system. Separation of bilirubin from human serum was also investigated in a continuous‐flow system. The bilirubin adsorption on the poly(GMA–MMA)–PEI and poly(GMA–MMA)–PEI–HSA was not well described by the Langmuir model, but obeyed the Freundlich isotherm model. The poly(GMA–MMA)–PEI affinity microspheres are stable when subjected to sanitization with sodium hydroxide after repeated adsorption–desorption cycles. Copyright © 2004 Society of Chemical Industry     

Biosorption of heavy metal ions on immobilized white-rot fungus Trametes versicolor

Trametes versicolor mycelia were immobilized in carboxymethylcellulose, CMC, beads via entrapment, and the bead containing immobilized fungus spores were incubated at 30 degrees C for 3 days to attain uniform growth on the bead surface. After incubation, the live and heat inactivated immobilized fungus on the CMC beads were used for the biosorption of Cu(2+), Pb(2+) and Zn(2+) ions.Plain CMC beads were used as a control system. The biosorption of Cu(2+), Pb(2+) and Zn(2+) ions by the CMC and both live and inactivated immobilized preparations increased as the initial concentration of Cu(2+), Pb(2+) and Zn(2+) ions in the medium increased. The maximum biosorption capacities for both immobilized live and heat inactivated Trametes versicolor were 1.51 and 1.84mmol Cu(2+), 0.85 and 1.11mmol Pb(2+) and 1.33 and 1.67mmol Zn(2+) per g of dry biosorbents, respectively. Biosorption equilibrium was established in about 1.0h and the equilibrium was well described by Langmuir and Freundlich isotherms. A temperature change in the range of 15-45 degrees C did not affect the biosorption capacity. The affect of pH was also investigated and the maximum adsorption of Cu(2+), Pb(2+) and Zn(2+) ions on the CMC and both live and inactivated immobilized fungal biomass was observed between pH 4.0 and 6.0. The CMC beads with the immobilized fungus can be regenerated using 10mM HCl, with up to 97% recovery of the metal ions; the biosorbents reused up to five biosorption-desorption cycles without any major loss in the biosorption capacity.     

Synthesis of Cr(VI)-imprinted poly(4-vinyl pyridine-co-hydroxyethyl methacrylate) particles: its adsorption propensity to Cr(VI)

The aim of this study is to prepare ion-imprinted polymers, which can be used for the selective removal of Cr(VI) anions from aqueous media. 4-Vinyl pyridine (4-VP) was used as functional monomer. The Cr(VI)-imprinted poly(4-vinyl pyridine-co-2-hydroxyethyl methacrylate), poly(VP-HEMA), particles were prepared by bulk polymerization. The Cr(VI)-imprinted polymer particles were grained from the bulk polymer, and the template ions (i.e., Cr(VI)) were removed using thiourea (0.5%, v/v) in 0.5M HCl. The Cr(VI)-imprinted polymer contained 21.4 μmol 4-VP/g polymers. The specific surface area of the IIP2 particles was found to be 34.5m(2)/g (size range of 75-150 μm), and the swelling ratio was about to 108%. The effect of initial concentration of Cr(VI) anions, the adsorption rate and the pH of the medium on adsorption capacity of Cr(VI)-imprinting polymer were studied. The maximum experimental adsorption capacity was 3.31 mmol Cr(VI)/g polymer. Under competitive condition, the adsorption capacity of Cr(VI)-imprinted particles for Cr(VI) is 13.8 and 11.7 folds greater than that of the Cr(III) and Ni(II) ions, respectively. The first- and second order kinetics models were estimated on the basis of comparative analysis of the corresponding rate parameters, equilibrium capacity and correlation coefficients. The Langmuir adsorption isotherm model was well described the Cr(VI)-imprinted system and the maximum adsorption capacity (Q(max)) was found to be 3.42 mmol/g. Moreover, the reusability of the poly(VP-HEMA) particles was tested for several times and no significant loss in adsorption capacity was observed.