Effects of processing on oxidative stability of sesame oil extracted from intact and dehulled seeds

Oxidative stability of oils extracted from intact and dehulled sesame seeds was determined by monitoring changes in fatty acid composition, iodine value (IV), peroxide value (PV), conjugated diene (CD), para-anisidine value (p-AV), and 2-thiobarbituric acid (TBA) value and by nuclear magnetic resonance spectroscopy after storage under Schaal oven conditions at 65°C for up to 35 d. The oils from coated seeds were more stable, as reflected in PV, CD, p-AV and TBA values, than those extracted from dehulled seeds after roasting at 200°C, steaming at 100°C, roasting at 200°C plus steaming, or microwaving at 2450 MHz, except for TBA values of oil from microwaved seeds. After 35 d of storage at 65°C, the CD, p-AV, and TBA values of extracted oil from dehulled microwaved seeds were 17.72, 10.20, and 1.22, respectively, while those of their coated counterparts were significantly (P<0.05) different at 14.20, 16.47, and 1.26, respectively. Few significant changes were evident in the fatty acid composition of oil obtained from either coated and dehulled seeds subjected to different treatments. Nuclear magnetic resonance analyses found that R_ao (aliphatic to olefinic protons) and R_ad (aliphatic to diallylmethylene protons) ratios increased steadily over the entire storage period, which indicated progressive oxidation of unsaturated fatty acids.     

Reinforcement of maleated polyethylene/ground tire rubber thermoplastic elastomers using talc and wood flour

Maleated polyethylene (MAPE)/Ground tire rubber (GTR) thermoplastic elastomer with 50 vol % GTR was reinforced by incorporation of talc powder and wood flour. Scanning electron microscopy (SEM) reveals that maleated polyethylene (MAPE) has good compatibility with wood flour, but the adhesion with talc particles is weak. Tensile moduli of MAPE/GTR increase more significantly after inclusion of talc particles compared to wood flour. Prediction of the tensile modulus of hybrid MAPE/GTR/particle composites is successfully performed using a combination of Kerner and Halpin‐Tsai models. Elastic moduli are shown to depend strongly on both aspect ratio and level of particle dispersion in the matrix. Measurement of compression sets shows that elastic recovery of the compounds decreases after addition of solid particles. Samples having better particles/matrix compatibility show higher elastic recovery. Thermogravimetric analysis shows that inclusion of wood flour decreases thermal stability of compounds. Density and hardness of MAPE/GTR are also shown to increase after inclusion of particulate reinforcements. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40195.     

Synthesis of MIL-101@g-C<Subscript>3</Subscript>N<Subscript>4</Subscript> nanocomposite for enhanced adsorption capacity towards CO<Subscript>2</Subscript>

MIL-101@g-C₃N₄ nanocomposite was prepared by solvothermal synthesis and used for CO₂ adsorption. The parent materials (MIL-101 and g-C₃N₄) and the MIL-101@g-C₃N₄ were characterized by X-ray diffraction, argon adsorption/desorption, Fourier transform infrared spectroscopy, thermal analysis (TG/DTA), transmission electronic microscopy, and Energy-dispersive X-ray spectroscopy. The results confirmed the formation of well-defined MIL-101@g-C₃N₄ with interesting surface area and pore volume. Furthermore, both MIL-101 and MIL-101@g-C₃N₄ were accomplished in carbon dioxide capture at different temperatures (280, 288, 273 and 298 K) at lower pressure. The adsorption isotherms show that the nanocomposite has a good CO₂ adsorption affinity compared to MIL-101. The best adsorption capacity is about 1.6 mmol g^?1 obtained for the nanocomposite material which is two times higher than that of MIL-101, indicating strong interactions between CO₂ and MIL-101@g-C₃N₄. This difference in efficacy is mainly due to the presence of the amine groups dispersed in the nanocomposite. Finally, we have developed a simple route for the preparation of an effective and new adsorbent for the removal of CO₂, which can be used as an excellent candidate for gas storage, catalysis, and adsorption.     

A New and Accurate Modeling Technique for Glass Resistance in Multiphase Multielectrode Glass Furnaces

One of the design elements involved in sizing the electrical power equipment for glass furnaces is the determination of the glass resistances between the operating electrodes. All methods used for this purpose to date are approximate and are based on a simple model considering the resistance between only two electrodes at the time. This paper presents a technique to develop a resistance model for any general configuration of electrodes and supply voltages in glass furnaces. The technique is based on relating the glass conductivity as represented by Ohm's law to the electrostatic property as represented by Gauss's law. The resistance model is then derived in a matrix form using the bus admittance frame of reference. A digital computer program has been developed to implement the proposed technique and example results are presented.     

Estimation of generalized entropies with sample spacing

In addition to the well-known Shannon entropy, generalized entropies, such as the Renyi and Tsallis entropies, are increasingly used in many applications. Entropies are computed by means of nonparametric kernel methods that are commonly used to estimate the density function of empirical data. Generalized entropy estimation techniques for one-dimensional data using sample spacings are proposed. By means of computational experiments, it is shown that these techniques are robust and accurate, compare favorably to the popular Parzen window method for estimating entropies, and, in many cases, require fewer computations than Parzen methods.     

Volume Changes of Iron Oxide Compacts under Isothermal Reduction Conditions

Compacts made from chemically grade Fe₂O₃ were fired at 1473K for 6 hrs. The fired compacts were isothermally reduced either by hydrogen or carbon monoxide at 1073–1373K. The O₂ weight‐loss resulting from the reduction process was continuously recorded as a function of time using TGA technique, whereas the volume change at different reduction conditions was measured by displacement method. Porosity measurements, microscopic examination and X‐ray diffraction analysis were used to characterize the fired and reduced products. The rate of reduction at both the initial and final stages was increased with temperature. The reduction mechanism deduced from the correlations between apparent activation energy values, structure of partially reduced compacts and application of gas‐solid reaction models revealed the reduction rate (dr/dt) at both the initial and final stages. At early stages, the reduction was controlled by a combined effect of gaseous diffusion and interfacial chemical reaction mechanism, while at the final stages the interfacial chemical reaction was the rate determining step. In H₂ reduction, maximum swelling (80%) was obtained at 1373K, which was attributed to the formation of metallic iron plates. In CO reduction, catastrophic swelling (255%) was obtained at 1198K due to the formation of metallic iron plates and whiskers.     

Thermodynamic properties of two ternary systems {yCsCl+(1−y)LiCl}(aq) and {yCsCl+(1−y)NaCl}(aq) at temperature 298.15 K

Thermodynamic properties of the mixed aqueous electrolyte systems of the lithium and cesium chlorides and sodium and cesium chlorides have been studied by the hygrometric method at 298.15 K. The water activities of these systems were measured at total molalities from 0.3 mol kg⁻¹ to saturation for different ionic strength fractions y of CsCl for the systems CsCl–LiCl(aq) and CsCl–NaCl(aq) with y=0.33, 0.50 and 0.67. The results allow the deduction of osmotic coefficients. The experimental results are compared with calculations made using the Zdanovskii–Stokes–Robinson (ZSR), Kusik and Meissner (KM), Robinson and Stokes (RS), Lietzke and Stoughton (LSII), Reilly, Wood and Robinson (RWR) rules, and the Pitzer model. From these measurements, the Pitzer mixing ionic parameters are determined and used to obtain the solute activity coefficients of the mixture for different ionic strength fractions y.     

The antioxidant activity of amino acids in two vegetable oils

Of 27 amino acids studied, most had some antioxidant activity when added in aqueous solution to either safflower oil or a mixture of sunflower and cottonseed oil (active oxygen and storage methods). Cysteine-HCl, glutamic acid-HCl (in the mixture), and glutamic acid-HCl (in safflower oil) behaved as prooxidants. When added as a solid, most amino acids were ineffective. The protection factors of these amino acids were less than 1.3 in safflower oil with methionine, proline, lysine and cysteine providing the highest activ-ity. In the oil mixture (which had a higher metal content) lysine, arginine, glutamic acid, methionine, and hydroxyproline were anti-oxidant with protection factors of up to 1.85. Chelation of metals by amino acids was presumably responsible for the antioxidant activity. The increase in cysteine concentration up to 1% has more than doubled the protection factor in Bint oil (compared with the 0.01% level), whereas with some other amino acids the increase was either small or slight.     

RF MEMS continuous reversible variable inductor based on a microfluidic network

In this work, RF MEMS continuous reversible variable inductor has been fabricated by using microelectronic technology and lamination process. We review, evaluate and compare this variable inductor with other work. The proposed inductor is a dual circular coil and has an inductance of few nH. The fundamental idea is to place a liquid droplet between the metal turns of a coil in order to modify the capacitive/resistive coupling between metal tracks and hence to change the stored magnetic energy. The SU-8 resin was used to realize the microfluidic channels and Au as metallic tracks. To prove the reversibility of the inductor, two cases were studied: filling and emptying of channels. The tuning range of the inductance is approximately 107 % at 1.6 GHz, making these devices very suitable as building blocks in many RF applications.     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.