Characterization of functionalized multiwalled carbon nanotubes and application as an effective filter for heavy metal removal from aqueous solutions☆

Filtration efficiency of Ni(II) from aqueous solution using pristine and modified MWCNTs filters was investigated as a function of Ni(II) ion concentration, pH, and filter mass. MWCNTs were synthesized by CVD method and modified using two complementary treatments, purification (using a mixture of hydrochloric acid and hydrogen peroxide) and functionalization (using nitric acid). The effect and mechanism of each treatment on the structural integrity of pristine MWCNTs has been studied. Morphology of the pristine and modified filters was investigated by Raman Spectrometry (RS), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), Fourier Transform Infrared (FTIR) spectrometry and Thermogravimetric analysis. It was found from Raman spec-tra that the ratio of the intensity of D-band to that of G-band decreased by purification process, and increased by functionalization process. The adsorption mechanism of Ni(II) onto the surface functional groups of modified MWCNTs was confirmed by FTIR spectrum. The filtration results showed that the removal efficiency of Ni(II) is strongly dependent on pH and could reach 85%at pH=8. Also, modified MWCNT filters can be reused through many cycles of regeneration with high performance. Functionalized MWCNTs filters may be a promising adsor-bent candidate for heavy metal removal from wastewater.     

Conjugate mixture models for clustering multimodal data

The problem of multimodal clustering arises whenever the data are gathered with several physically different sensors. Observations from different modalities are not necessarily aligned in the sense there there is no obvious way to associate or compare them in some common space. A solution may consist in considering multiple clustering tasks independently for each modality. The main difficulty with such an approach is to guarantee that the unimodal clusterings are mutually consistent. In this letter, we show that multimodal clustering can be addressed within a novel framework: conjugate mixture models. These models exploit the explicit transformations that are often available between an unobserved parameter space (objects) and each of the observation spaces (sensors). We formulate the problem as a likelihood maximization task and derive the associated conjugate expectation-maximization algorithm. The convergence properties of the proposed algorithm are thoroughly investigated. Several local and global optimization techniques are proposed in order to increase its convergence speed. Two initialization strategies are proposed and compared. A consistent model selection criterion is proposed. The algorithm and its variants are tested and evaluated within the task of 3D localization of several speakers using both auditory and visual data.     

On simultaneous on-line state and parameter estimation in non-linear state-space models

On-line estimation plays an important role in process control and monitoring. Obtaining a theoretical solution to the simultaneous state-parameter estimation problem for non-linear stochastic systems involves solving complex multi-dimensional integrals that are not amenable to analytical solution. While basic sequential Monte-Carlo (SMC) or particle filtering (PF) algorithms for simultaneous estimation exist, it is well recognized that there is a need for making these on-line algorithms non-degenerate, fast and applicable to processes with missing measurements. To overcome the deficiencies in traditional algorithms, this work proposes a Bayesian approach to on-line state and parameter estimation. Its extension to handle missing data in real-time is also provided. The simultaneous estimation is performed by filtering an extended vector of states and parameters using an adaptive sequential-importance-resampling (SIR) filter with a kernel density estimation method. The approach uses an on-line optimization algorithm based on Kullback–Leibler (KL) divergence to allow adaptation of the SIR filter for combined state-parameter estimation. An optimal tuning rule to control the width of the kernel and the variance of the artificial noise added to the parameters is also proposed. The approach is illustrated through numerical examples.     

Continuous-time norm-constrained Kalman filtering

This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two separate optimization problems, one which solves for the optimal observer gain associated with the unconstrained state estimates, while the other solves for the optimal observer gain associated with the constrained state estimates. The optimal constrained state estimate is found by projecting the time derivative of an unconstrained estimate onto the tangent space associated with the norm constraint. The special case where the entire state estimate is norm-constrained is briefly discussed. The utility of the filtering results developed are highlighted through a spacecraft attitude estimation example. Numerical simulation results are included.     

The effect of carbon on oxygen precipitation in high carbon CZ silicon crystals

To clarify the role of carbon impurities in the formation of oxygen precipitates, the behavior of CZ silicon wafers with varying carbon concentrations from 0.2 ppm to 2 ppm were studied under different heat treatment conditions. It is found that the rate of reduction in interstitial oxygen is not a function of carbon concentration as reported previously for both the cases of medium and low temperature annealing. Under medium temperature (1050°C) annealing no carbon reduction was detected, even though the reduction in interstitial oxygen can be very large, while with low temperature (750°C) annealing, oxygen reduction is always associated with the carbon reduction, but is not dependent on carbon concentration alone. A heterogenous precipitation model is presented to explain the observed phenomena.     

Characterization of IS1547, a new member of the IS900 family in the Mycobacterium tuberculosis complex, and its association with IS6110

Unlike classically defined insertion sequence (IS) elements, which are delimited by their inverted terminal repeats, some IS elements do not have inverted terminal repeats. Among this group of atypical IS elements, IS116, IS900, IS901, and IS1110 have been proposed as members of the IS900 family of elements, not only because they do not have inverted terminal repeats but also because they share other features such as homologous transposases and particular insertion sites. In this study, we report a newly identified IS sequence, IS1547, which was first identified in a clinical isolate of Mycobacterium tuberculosis. Its structure, insertion site, and putative transposase all conform with the conventions of the IS900 family, suggesting that it is a new member of this family. IS1547 was detected only in isolates of the M. tuberculosis complex, where it had highly polymorphic restriction fragment length polymorphism patterns, suggesting that it may be a useful genetic marker for identifying isolates of the M. tuberculosis complex and for distinguishing different strains of M. tuberculosis. ipl is a preferential locus for IS6110 insertion where there are eight known different insertion sites for IS6110. Surprisingly, the DNA sequence of ipl is now known to be a part of IS1547, meaning that IS1547 is a preferential site for IS6110 insertion.     

River wildlife databases and their value for sensitive environmental management

A survey over a 3-year period, which commenced in 1987, of the plant and bird communities along 1200 km of river in Lincolnshire and South Humberside, Eastern England, is described. Analysis of data from 247 km of river recorded a great diversity of wildlife, comprising 570 species of plant and 80 species of breeding birds. The management value of such surveys is discussed and these include the preparation of detailed maps of each 500m section of river, which illustrate the habitat structure, and plant and bird communities. A maintenance procedure for each 500 m section of river is then agreed between conservation and operations personnel, preventing areas of wildlife importance from being accidentally destroyed. An index which combines both the diversity and rarity of the plant and bird communities is proposed as a measure of conservation importance. This index allows sections of river to be graded according to their conservation value into one of five groups. The surveys also enable predictions to be made of the effects of management actions on the wildlife and provide information by which fundamental reviews of operational activities can be carried out.     

A model for the channel noise of MESFETs including hot electron effects

Noise is an important consideration in the reliability of microelectronic circuits determining the sensitivity of the circuits and placing a lower limit on the regions of operation. Proper modeling of noise in integrated circuits is essential for reliable operation. A derivation is given for the channel noise coefficient of FET’s operating in the saturation region. Some simple approximations are made for hot electron effects which can be incorporated into the derivation and accounted for by a numerical integration technique. Experimental results of measured and calculated noise coefficients are compared for depletion mode MESFETs of different gate lengths. This model gives a much more realistic representation of the channel noise coefficients for short gate length devices rather than the simple 2/3 value currently used in circuit simulations.