Removal of heavy metal ions from water by using poly(ethyleneglycol dimethacrylate-co-acrylamide) beads

Poly(ethyleneglycol dimethacrylate-co-acrylamide) (poly(EDGMA-co-AAm)) copolymer beads have been prepared for use in the separation Pb(II), Hg(II), and Cd(II), metal ions in aqueous solution by a batch equilibration technique. Adsorption capacity were increased with pH for Pb(II), Cd(II) and Hg(II) and then reached almost plateau value around 6.0. The high initial rate of metal ions uptake (<10 min) suggests that the adsorption occurs mainly at the bead surface. The metal uptake results show that poly(EGDMA-co-AAm) can be used for the adsorption of the following metals in the indicated order: Pb(II) > Cd(II) > Hg(II) expressed on a molar basis. However, when the uptake was expressed in terms of the amount of metal removed from solution was as follows: Pb(II) > Hg(II) > Cd(II). The beads still showed preference toward Pb(II) when this metal was in a mixture with Hg(II) and Cd(II). A linearized form of the Freundlich and the Langmuir isotherm model fits the experimental equilibrium concentration data of Hg(II) and Cd(II) better than isotherm type model of Pb(II). The recovery of the metal ions after adsorption and the regeneration of the adsorbent can be carried out by treatment of the loaded beads with either 0.5 M NaCl, or 1 M HNO₃.     

A novel approach to estimation of E. coli promoter gene sequences: Combining feature selection and least square support vector machine (FS_LSSVM)

In this paper, we have investigated the real-world task of recognizing biological concepts in DNA sequences. Recognizing promoters in strings that represent nucleotides (one of A, G, T, or C) has been performed using a novel approach based on combining feature selection (FS) and least square support vector machine (LSSVM). Dimensionality of Escherichia coli promoter gene sequences dataset has 57 attributes and 106 samples including 53 promoters and 53 non-promoters. The proposed system consists of two parts. Firstly, we have used the FS process to reduce the dimensionality of E. coli promoter gene sequences dataset that has 57 attributes. So the dimensionality of this dataset has been reduced to 4 attributes by means of FS process.Secondly, LSSVM classifier algorithm has been run to estimation the E. coli promoter gene sequences. In order to show the performance of the proposed system, we have used the success rate, sensitivity and specificity analysis, 10-fold cross validation, and confusion matrix. Whilst only LSSVM classifier has been obtained 80% success rate using 10-fold cross validation, the proposed system has been obtained 100% success rate for same condition. These obtained results indicate that the proposed approach improve the success rate in recognizing promoters in strings that represent nucleotides.     

Bridging radial and non-radial measures of efficiency in DEA

Data envelopment analysis (DEA) has been utilized worldwide for measuring efficiencies of banks, telecommunications, electric utilities and so forth. Yet, the existing models have some well-known shortcomings that limit their usefulness. In DEA we have two fundamental approaches to measuring efficiency with very different characteristics; radial and non-radial. We demonstrate a method for linking these two approaches in a unified framework called Connected-SBM (slacks-based measure). It includes two scalar parameters, and by changing the parameter values we can relocate the analysis anywhere between the radial and the non-radial models. An appropriate choice of these parameters can overcome the key shortcomings inherent in the two approaches, namely, proportionality and mixed patterns of slacks.     

Estimation of stochastic nonlinear dynamic response of rock-fill dams with uncertain material parameters for non-stationary random seismic excitation

This research investigates the effect of uncertain material parameters on the stochastic, dynamic response of a rock-fill dam-foundation system subjected to non-stationary random excitation. The uncertain material parameter of particular interest is the shear modulus, developed from a lognormal distribution model. The stochastic seismic response model of the dam-foundation system, with uncertain material parameters and subjected to random loads is the result of a Monte Carlo simulation method. The nonlinear behavior model arises from an equivalent linear method, which considers the nonlinear variation of soil shear modulus and soil damping as a function of shear strain. Specification of the non-stationary stochastic process arises from a simulation method, which generates artificial earthquake accelerograms obtained from the product of a deterministic function of time and a stationary process. The artificial earthquake ground acceleration records reflect the characteristics of soft, medium and firm soil types. Comparison of the numerical results from these approaches provides stochasticity in earthquake seismic excitation and randomness in material parameter (shear modulus) cases. Further, the results indicate that both these cases generally influence the nonlinear dynamic response of rock-fill dams to a non-stationary seismic excitation.     

A first-principles studies on TlX (X=P, As)

We present an ab initio study of the structural, electronic and thermodynamic properties of TlX(X=P,As). The plane-wave pseudopotential approach to the density-functional theory within the LDA and GGA approximations implemented in VASP (Viena Ab-initio Simulation Package) is used. The calculated lattice parameter, elastic constants, and band structures are compared with other available theoretical results, and good agreement is obtained. In addition, we have calculated the transition pressure (P _t ) from zinc-blende (ZB) to (rock-salt) NaCl structures, and have examined some thermodynamic properties.      

Diffusion-weighted imaging evaluation of subtle cerebral microstructural changes in intrauterine fetal hydrocephalus

OBJECTIVE: Hydrocephalus is an important etiological factor in neurological decline. With the advent of fetal ultrasound, fetal hydrocephalus is now more frequently detected than in the past. Ultrasonography (USG) provides information on general morphology, but microstructural changes that may play a prognostic role are beyond the resolution of that technique. These changes may theoretically be revealed by diffusion-weighted magnetic resonance imaging (DW-MRI). In this study, our preliminary findings of DW-MRI on the hydrocephalic fetuses are presented. MATERIALS AND METHODS: Twelve fetuses with fetal USG diagnosis of hydrocephalus were investigated using a 1.5-T MR scanner. In addition to conventional techniques, DWI was performed. It was obtained using a single-shot echo-planar imaging sequence (TR/TE: 4393/81 ms; slice thickness: 5 mm; interslice gap: 1 mm; FOV: 230 mm; matrix size: 128x256; b values: 0 and 1000 s/mm2). Apparent diffusion coefficient (ADC) values were measured in the white matter of the periventricular frontal and occipital lobes, basal ganglia, thalamus, centrum semiovale and cerebrospinal fluid in the lateral ventricle. These values were compared with the normal prenatal ADC values from a radiological study published in the literature. RESULTS: All fetuses had moderate or severe bilateral supratentorial ventricular dilatation that was compatible with hydrocephalus. On conventional T1- and T2-weighted imaging, cerebral parenchyma had normal signal pattern and ADC values were significantly lower than those reported for fetuses with normal brain. These values were lower in hydrocephalic fetuses with statistical significance (P<.05-.01). CONCLUSION: DWI is a sensitive technique to investigate cerebral microstructure. The reduction in cerebral blood flow and alterations in cerebral energy metabolism in cases with hydrocephalus have been shown before. Changes in cerebral blood flow and energy metabolism, as a consequence of cerebral compression, may occur in hydrocephalus. Elevated ventricular pressure may cause cerebral ischemia. The anaerobic glycolysis seen in the hydrocephalic brain tissue by increasing the lactate concentration and intracellular fluid flux may be the reason for the reduced ADC values in hydrocephalic fetuses. However, long-term prospective trials on the correlation of ADC values and neurological outcome are necessary to exploit the full benefit of that novel technique.     

FAAS slurry analysis of lead and copper ions preconcentrated on titanium dioxide nanoparticles coated with a silver shell and modified with cysteamine

We report on the separation and preconcentration of lead(II) and copper(II) ions using silver-coated titanium dioxide nanoparticles modified with cysteamine, and their determination by slurry analysis via flame atomic absorption spectrometry. The ions were adsorbed via a conventional batch technique, and the ion-loaded slurry was separated and directly introduced into the spectrometer, thereby eliminating a number of drawbacks. The effects of pH, amount of sorbent, slurry volume, sample volume and other ions on the recovery were investigated. Under optimized experimental conditions, copper and lead can be recovered within the 95% confidence level in certificated waste water, but also in spiked sea water samples. The technique is fast, simple, and leads to complete elution. The limit of detection (3δ, at n?=?10) was 0.37 μg L^?1 for Cu(II), and 0.38 μg L^?1 for Pb(II).

Slurry sampling electrothermal atomic absorption spectrometric determination of chromium after separation/enrichment by mercaptoundecanoic acid modified gold coated TiO2 nanoparticles

In this study, a novel preconcentration/separation technique based on the slurry analysis of chromium loaded on mercaptoundecanoic acid modified TiO₂ core-Au shell nanoparticles prior to its determination by electrothermal atomic absorption spectrometry was described. For this purpose, at first, TiO₂ nanoparticles were coated with gold shell and then modified with mercaptoundecanoic acid (MUA). Cr (III) was collected on the prepared sorbent by conventional batch technique. After separation of liquid phase, slurry of the sorbent was prepared and directly introduced into graphite furnace of atomic absorption spectrometry. By this way, all drawbacks due to elution procedure were eliminated. Optimum conditions for quantitative sorption and preparation of the slurry were investigated. The chromium in certificated sea-water and spiked drinking water was recovered in the range of 95% confidence level. The proposed technique was fast and simple as well as the risks of contamination and loss during elution were low. The limit of detection (3σ, N = 10) was 0.34 μg L^{− 1}.     

The miniaturised process for lead removal from water samples using novel bioconjugated sorbents

ABSTRACT

In the present study, novel bioconjugated sorbents (peptide and oligo-nucleotide on the cobalt aluminate nanomaterials) were used to remove lead through miniaturised process and the concentration of lead was measured by inductively coupled plasma mass spectrometry. For this aim, lead was collected on sorbent in mini tube, and the influences of experimental conditions (e.g. pH of sample, amount of sorbent, concentration of eluent, foreign ions) and retention parameters on the recovery of the lead element were examined. After the optimisation of experimental parameters, a successful separation was obtained at pH 7.5 with high (>95%) quantitative recovery and high precision (<10% relative standard deviation). Using the proposed bioconjugated sorbents, the lead in sea water and tap water samples could be practically and easily removed with 95% confidence level. The detection limits of this method for lead using oligonucleotide and peptide on the cobalt aluminate nanomaterials were 0.14 and 0.12 µg/L (3σ, N = 10) with sample-matched blanks. This method can be widely used as promising and cost-effective nanomaterials to remove lead from water systems.