Surface-modified alumina nanoparticles-filled aramid fiber-reinforced epoxy nanocomposites: preparation and mechanical properties

Iranian Polymer Journal - Surface of Al2O3 nanoparticles was modified with a silane coupling agent, and aramid fiber-reinforced epoxy nanocomposites were produced using these particles. Three...     

Emulsifier‐free cationic latexes based on vinylbenzyl chloride and 2‐(dimethylamino)ethyl methacrylate with adjusted hydrophilic–hydrophobic properties

Functional emulsifier‐free cationic latexes based on styrenic monomer vinylbenzyl chloride (VBC) and acrylic monomer 2‐(dimethylamino)ethyl methacrylate (DMA) were successfully prepared with dual quaternary ammonium ions (36–63 mol %) on both monomer moieties in two‐stages. First, [2‐(methacryloyloxy)ethyl]dimethylhexadecylammonium bromide monomer (DMA(C₁₆)), prepared via quaternization of DMA with 1‐bromohexadecane, was utilized as a comonomer (5–20%) as well as a surfactant in the emulsion polymerization of VBC. Next, the quaternization of chloromethyl groups in the VBC moiety in latex particles with trimethylamine and N,N‐dimethylhexadecylamine created a second type of quaternized sites on the latex particles. The percentages of the quaternary ammonium ions of the first‐stage latexes (P[VBC‐DMA(C₁₆‐x)]) and the second‐stage latexes (P[VBC(R)‐DMA(C₁₆‐x)]) were determined using bromide and chloride ion‐selective electrodes. The particles were characterized with a scanning electron microscope, Zetasizer, measuring water contact angles of their pellets. The polymer structure and the alkyl group length in their quaternary ammonium ions played an important role on the sizes, zeta potentials and hydrophilic–hydrophobic balances of the latexes. The water contact angles of the pellets of the latex particles varied from 50.3 to 109.6° depending on both the polymer structure and the alkyl group length. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42775.     

Determination of Some Endocrine-Disrupting Metals and Organochlorinated Pesticide Residues in Baby Food and Infant Formula in Turkish Markets

There is a paucity of data in respect of the nutritional quality of complementary foods for infants and young children aged between 6 and 12 months. In this study, we developed and validated an analytical method for determination of the endocrine-disrupting organochlorine pesticides (OCPs) and elements (As, Cd, and Pb) in infant formula and baby foods. Therefore, it found out the contamination level of the both OCPs and some trace metals (As, Cd, and Pb) in widely consumed infant formula and baby food in Turkey. Metal concentrations in baby foods and infant formula were determined by inductively coupled plasma mass spectrometry. Samples were digested with nitric acid and hydrogen peroxide in a microwave oven. Determination of 24 organochlorine pesticide residues in baby foods and infant formula was completed by using gas chromatography double mass spectrometry. QuEChERS extraction method was carried out in the sample preparation part. The analytical performance of the entire procedure, such as linearity, the detection of limit, limit of quantification, specificity/selectivity, recovery (%), and precision, were assessed. The recoveries ranged from 93% (As) to 100% (Pb) for elements 78–98% for organochlorine pesticide residues (OCPs) at 100 ng mL^?1. According to the results, lead, cadmium, and pesticides were not detected in any of the samples, while arsenic was detected in 16 samples.     

Review and comparative evaluation of symbolic dynamic filtering for detection of anomaly patterns

Symbolic dynamic filtering (SDF) has been recently reported in literature as a pattern recognition tool for early detection of anomalies (i.e., deviations from the nominal behavior) in complex dynamical systems. This paper presents a review of SDF and its performance evaluation relative to other classes of pattern recognition tools, such as Bayesian Filters and Artificial Neural Networks, from the perspectives of: (i) anomaly detection capability, (ii) decision making for failure mitigation and (iii) computational efficiency. The evaluation is based on analysis of time series data generated from a nonlinear active electronic system. This work has been supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office under Grant No. W911NF-07-1-0376, by the U.S. Office of Naval Research under Grant No. N00014-08-1-380, and by NASA under Cooperative Agreement No. NNX07AK49A.     

EEG source localization using a sparsity prior based on Brodmann areas

Localizing the sources of electrical activity in the brain from electroencephalographic (EEG) data is an important tool for noninvasive study of brain dynamics. Generally, the source localization process involves a high‐dimensional inverse problem that has an infinite number of solutions and thus requires additional constraints to be considered to have a unique solution. In this article, we propose a novel method for EEG source localization. The proposed method is based on dividing the cerebral cortex of the brain into a finite number of “functional zones” which correspond to unitary functional areas in the brain. To specify the sparsity profile of human brain activity more concisely, the proposed approach considers grouping of the electrical current dipoles inside each of the functional zones. In this article, we investigate the use of Brodmann's areas as the functional zones while sparse Bayesian learning is used to perform sparse approximation. Numerical experiments are conducted on a realistic head model obtained from segmentation of MRI images of the head and includes four major compartments namely scalp, skull, cerebrospinal fluid (CSF), and brain with relative conductivity values. Three different electrode setups are tested in the numerical experiments. The results demonstrate that the proposed approach is quite promising in solving the EEG source localization problem. In a noiseless environment with 71 electrodes, the proposed method was found to accurately locate up to 6 simultaneously active sources with accuracy >70%.     

The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.     

Adsorptive removal of phenol from aqueous solutions on activated carbon prepared from tobacco residues: equilibrium, kinetics and thermodynamics

This study consists of producing high surface area activated carbon from tobacco residues by chemical activation and its behavior of phenol removal from aqueous solutions. K(2)CO(3) and KOH were used as chemical activation agents and three impregnation ratios (50, 75 and 100 wt.%) were applied on biomass. Maximum BET surface areas of activated carbons were obtained from impregnation with 75 wt.% of K(2)CO(3) and 75 wt.% of KOH as 1635 and 1474 m(2)/g, respectively. Optimum adsorption conditions were determined as a function of pH, adsorbent dosage, initial phenol concentration, contact time and temperature of solution for phenol removal. To describe the equilibrium isotherms the experimental data were analyzed by the Langmuir, Freundlich, Dubinin-Radushkevich (D-R) and Temkin isotherm models. Pseudo-first order, pseudo-second order and intraparticle diffusion kinetic models were used to find out the kinetic parameters and mechanism of adsorption process. The thermodynamic parameters such as ΔG°, ΔH° and ΔS° were calculated for predicting the nature of adsorption. According to the experimental results, activated carbon prepared from tobacco residue seems to be an effective, low-cost and alternative adsorbent precursor for the removal of phenol from aqueous solutions.     

The elasto-plastic impact analysis of functionally graded circular plates under low-velocities

In this study, three-dimensional elasto-plastic analysis of functionally graded (FG) circular plates under low-velocity impact loads is presented. The FG circular plate is composed of ceramic (SiC) and metal (Al) phases, varying in a predetermined fashion through the plate thickness. The elasto-plastic behaviour of the FG circular plate is described by the TTO model. In the analyses, the ceramic phase is taken to be an isotropic elastic material whereas the metal phase is taken to be elasto-plastic material in accordance with the TTO model. The locally effective material properties were evaluated using homogenization method which is based on the Mori–Tanaka scheme. The effects of compositional gradient exponent and impactor velocity on the elasto-plastic impact response of the FG circular plates are investigated, and results are presented graphical form. The compositional gradient exponent and impactor velocity have significant effects on the elasto-plastic impact response of the FG circular plates. The elasto-plastic impact response of FG circular plates is similar to those of homogeneous plates. Therefore, the TTO model can be used to describe the mechanical behaviour of FG plates beyond the elastic range, assuming that the material response is essentially governed by the spreading of plasticity in the metal phase.     

The impact of data aggregation on the performance of wireless sensor networks

With the increasing need for different energy saving mechanisms in Wireless Sensor Networks (WSNs), data aggregation techniques for reducing the number of data transmissions by eliminating redundant information have been studied as a significant research problem. These studies have shown that data aggregation in WSNs may produce various trade‐offs among some network related performance metrics such as energy, latency, accuracy, fault‐tolerance and security. In this paper, we investigate the impact of data aggregation on these networking metrics by surveying the existing data aggregation protocols in WSNs. Our aim is twofold: First, providing a comprehensive summary and comparison of the existing data aggregation techniques with respect to different networking metrics. Second, pointing out both the possible future research issues and the need for collaboration between data management and networking research communities working on data aggregation in WSNs. Copyright © 2006 John Wiley & Sons, Ltd.     

Revised stratigraphy of the Tertiary deposits of Istanbul and their engineering properties

For over 50 years, the Upper Oligocene–Upper Miocene sedimentary sequence in Istanbul has been considered to be formed of two distinct sequences separated by an unconformity. However, recent field observations and an analysis of numerous borehole data indicate the Gürp?nar, Çukurçe?me and Güngören Formations are in fact a single sequence of alternating clay–sand/sandstone beds/lenses, here named the Avc?lar Formation. The Bak?rköy Formation, which is typically composed of carbonate rocks, conformably overlies the Avc?lar Formation. The paper provides the geotechnical parameters of the units within the Avc?lar Formation which it is hoped will facilitate selecting suitable geotechnical and engineering geological parameters to represent the deposits and minimize errors in the interpretation/evaluation of in-situ conditions.