The removal of cationic dyes from aqueous solutions by adsorption onto pistachio hull waste

The efficacy of pistachio hull powder (PHP) prepared from agricultural waste was investigated in this study as a novel adsorbent for the elimination of dye molecules from contaminated streams. Removal of methylene blue (MB) as a cationic model dye by PHP from aqueous solution was studied under different experimental conditions. The selected parameters were solution pH (2–10), PHP dosage (0.5–3 g/L), MB concentrations (100–400 mg/L), contact time (1–70), and solution temperature (20–50 °C). The experimental results indicated that the maximum MB removal could be attained at a solution pH of 8. The dosage of PHP was also found to be an important variable influencing the MB removal percentage. The removal efficiency of MB improved from 94.6 to 99.7% at 70 min contact time when the MB concentration was decreased from 300 to 100 mg/L at a pH and PHP dosage of 8 and 1.5 g/L, respectively. The kinetic analysis showed that the pseudo-second-order model had the best fit to the experimental data. The Langmuir equation provided the best fit for the experimental data of the equilibrium adsorption of MB onto PHP at different temperatures. In addition, the maximum adsorption capacity increased from 389 to 602 mg/g when the temperature was increased from 20 to 50 °C. The thermodynamic evaluation of MB adsorption on PHP revealed that the adsorption phenomenon under the selected conditions was a spontaneous physical process. Accordingly, pistachio hull waste was shown to be a very efficient and low-cost adsorbent, and a promising alternative for eliminating dyes from industrial wastewaters.     

Mechanical and water binding properties of carboxymethyl cellulose/multiwalled carbon nanotube nanocomposites

Carboxymethyl cellulose (CMC) composite films were prepared from CMC solutions (2% w/v) containing multiwalled carbon nanotubes (MWCNT) as nanofiller and glycerol (25% w/w CMC) as plasticizer. Tensile strength, elongation at break (EAB), young's modulus, water solubility, water swelling, water uptake, and water vapor permeability (WVP) for CMC films were 27.5 ± 2.5 MPa, 11.2 ± 0.8%, 198 ± 18 MPa, 57 ± 1.5%, 738 ± 25%, 124 ± 4%, and 0.55 ± 0.036 g.mm/m².kPa.h, respectively. By increasing the relative humidity from 11.4 to 85.5%, the moisture absorption (MA) of CMC films was increased from 4 to 38%. Incorporation of MWCNT into the matrix caused a significant increase in the tensile strength, decrease in EAB, increase in young's modulus, decrease in water solubility, decrease in water swelling, decrease in water uptake, and decrease in MA. CMC/MWCNT films containing 1% MWCNT showed the lowest WVP. Scanning electron microscopy showed a good dispersion of MWCNT in the CMC matrix. CMC/MWCNT films containing >1% MWCNT showed significant antibacterial activities against both Gram‐positive and Gram‐negative bacteria in a dose‐dependent manner. Thus, good mechanical properties and water resistance along with strong antibacterial activities make CMC films grafted with MWCNT as a suitable packaging material. POLYM. COMPOS., 36:145–152, 2015. © 2014 Society of Plastics Engineers     

Fabrication and magnetic study of Co/Pt multilayer nanowires and Co–Pt alloy nanowires electrodeposited into porous Si substrates

In this work, we grow composite structures consisting of magnetic and non-magnetic metal or alloy nanowires electrodeposited into the ion etched tracks previously created inside Si substrates. The holes are then filled by Co–Pt alloys and Co/Pt multilayers using electrodeposition technique making a large number of parallel nanowires. This process takes place in a single electrolyte containing Co⁺² and Pt⁺⁴ ions by applying a proper deposition potential using a computer control potentiostat. The magnetic properties of the sample were studied using vibrating sample magnetometer. Magnetoresistive behaviour of the nanowire samples was then studied by subjecting the samples to an external magnetic field. The results show that the Co/Pt multilayered nanowires exhibit a large magnetoresistance, while the Co–Pt alloys only show anisotropic magnetoresistance. This result could be of a great interest for the sensor fabrication community as they will provide a view on a very important direction of the development of the wide spread sensor industry, and more importantly for understanding the physical phenomena underlying the magnetic/non-magnetic nanostructures.     

A hybrid feature extraction method for SAR image registration

Extracting and matching correct correspondence between two images are significant stages for feature-based synthetic aperture radar (SAR) image registration. Two methods of feature extraction were employed in this study. Blob features were obtained by combining a Gaussian-guided filter (GGF) with a scale invariant feature transform, and corner features were obtained from the GGF. A GGF can store edge information and operate more effectively than a Gaussian filter. The ratio of average was used to compute gradients in order to reduce the speckle effect. Fast sample consensus (FSC) algorithm was combined with complete graph method for feature correspondence matching. Although FSC algorithm can extract valid correspondence, it may not be efficient enough to deal with SAR images due to its random nature and the large number of outliers in the data. Therefore, a graph-based algorithm was employed to solve the problem by eliminating outliers. The proposed hybrid method was tested on several real SAR images having different properties. The results showed that the proposed method performed the automated registration of SAR images more accurately and efficiently.     

Analysis of DLL Jitter due to Voltage-Controlled Delay Line

In this paper we analyze jitter in a delay-locked loop (DLL) due to uncertainties in the voltage-controlled delay line (VCDL). To obtain a closed-form equation for jitter in the DLL, time-domain equations of the DLL are used. The jitter at the intermediate stages of the VCDL and the jitter of a conventional delay cell are analyzed. The simulation results show that the jitter of the DLL due to mismatch of the delay cells is zero at the beginning and end of the VCDL and is highest at the middle of the VCDL. Also, a DLL is designed in TSMC 0.18 μm CMOS technology to show the accuracy of the proposed analytical method.     

Modeling triplet spike-timing-dependent plasticity using memristive devices

Triplet-based spike-timing-dependent plasticity (TSTDP) is an advanced synaptic plasticity rule that results in improved learning capability compared to the conventional pair-based STDP (PSTDP). The TSTDP rule can reproduce the results of many electrophysiological experiments, where the PSTDP fails. This paper proposes a novel memristive circuit that implements the TSTDP rule. The proposed circuit is designed using three voltage (flux)-driven memristors. Simulation results demonstrate that our memristive circuit induces synaptic weight changes that arise due to the timing differences among pairs and triplets of spikes. The presented memristive design is an initial step toward developing asynchronous TSTDP learning architectures using memristive devices. These architectures may facilitate the implementation of advanced large-scale neuromorphic systems with applications in real-world engineering tasks such as pattern classification.     

Experimental and numerical evaluation of rigid column to baseplate connection under cyclic loading

One of the most important connections in steel structures is column to the baseplate connection. This kind of connection has a complex nature, due to different behaviors of the constituents, including baseplate, grout, foundation, and anchor bolts. Studying the impact of this connection in general behavior of structure seems to be an essential issue, especially during earthquake, which is more likely to be associated with plastic hinge forming. The main goal of this work is to provide a hybrid modeling for describing hysteresis behavior of column to the baseplate connection. Within hybrid modeling, a mechanical model is accomplished by using neural network model components. Our findings reveal that hybrid models are able to show pinched hysteresis complex behavior of baseplate connections. Also, the proposed hybrid developed model is robust and reliable approaches for predicting behaviors of a recent designed connection.     

Robust reservoir rock fracture recognition based on a new sparse feature learning and data training method

Multidimensional Systems and Signal Processing - In this paper, the main goal is to identify the sine fractures of reservoir rock automatically. Therefore, a five-step algorithm is applied on the...     

Artificial Neural Networks for Hardness Prediction of HAZ with Chemical Composition and Tensile Test of X70 Pipeline Steels

A neural network with feed-forward topology and back propagation algorithm was used to predict the effects of chemical composition and tensile test parameters on hardness of heat affected zone(HAZ)in X70 pipeline steels.The mass percent of chemical compositions(i.e.carbon equivalent based upon the International Institute of Welding equation(CEIIW),the carbon equivalent based upon the chemical portion of the Ito-Bessyo carbon equivalent equation(CEPcm),the sum of the niobium,vanadium and titanium concentrations(CVTiNb),the sum of the niobium and vanadium concentrations(CNbV),the sum of the chromium,molybdenum,nickel and copper concentrations(CCrMoNiCu)),yield strength(YS)at 0.005 offset,ultimate tensile strength(UTS)and percent elongation(El)were considered as input parameters to the network,while Vickers microhardness with 10 Nload was considered as its output.For the purpose of constructing this model,104 different data were gathered from the experimental results.Scatter diagrams and two statistical criteria,i.e.absolute fraction of variance(R2)and mean relative error(MRE),were used to evaluate the prediction performance of the developed model.The developed model can be further used in practical applications of alloy and thermo-mechanical schedule design in manufacturing process of pipeline steels.