Citric Acid Used as a Cross-Linking Agent for Grafting β-Cyclodextrin onto Wool Fabric

Modification of woolen fabrics were achieved by grafting β-cyclodextrin and β-chloro triazinylcyclodextrin in the presence of citric acid (CA) as cross-linking agent and phosphorous salts such as sodium hypophosphite (SHP) and sodium dihydrogen phosphate (SDP) using the pad dry cure technique. CA is expected to react with the β-CD (or wool) hydroxyl groups and wool terminal amino groups, to form ester cross-linkages or ionic bonds. The improved properties of wool fabrics were evaluated using urea bisulfite solubility test, tensile strength, elongation and crease recovery angle. Also, yellowness index and scanning electron microscopy were performed. Woolen fabrics treated with CA alone and CA/ CD shows antimicrobial properties.     

Encoding Information on the Excited State of a Molecular Spin Chain

The quantum states of nano-objects can drive electrical transport properties across lateral and local-probe junctions. This raises the prospect, in a solid-state device, of electrically encoding information at the quantum level using spin-flip excitations between electron spins. However, this electronic state has no defined magnetic orientation and is short-lived. Using a novel vertical nanojunction process, these limitations are overcome and this steady-state capability is experimentally demonstrated in solid-state spintronic devices. The excited quantum state of a spin chain formed by Co phthalocyanine molecules coupled to a ferromagnetic electrode constitutes a distinct magnetic unit endowed with a coercive field. This generates a specific steady-state magnetoresistance trace that is tied to the spin-flip conductance channel, and is opposite in sign to the ground state magnetoresistance term, as expected from spin excitation transition rules. The experimental 5.9 meV thermal energy barrier between the ground and excited spin states is confirmed by density functional theory, in line with macrospin phenomenological modeling of magnetotransport results. This low-voltage control over a spin chain's quantum state and spintronic contribution lay a path for transmitting spin wave-encoded information across molecular layers in devices. It should also stimulate quantum prospects for the antiferromagnetic spintronics and oxides electronics communities.     

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%.

     

Z-transform implementation of the perfectly matched layer for truncating FDTD domains

A simple algorithm for implementing the perfectly matched layer (PML) is presented for truncating finite difference time domain (FDTD) computational domains. The algorithm is based on incorporating the Z-transform method into the PML FDTD implementation. The main advantage of the algorithm is its simplicity as it allows direct FDTD implementation of Maxwell's equations in the PML region. In addition, the formulations are independent of the material properties of the FDTD computational domain. Numerical examples are included to demonstrate the effectiveness of these formulations.     

Age-related response of male melon fliesDacus cucurbitae (Diptera: Tephritidae) to cue-lure

Laboratory-reared and wild adults of the melon fly,Dacus cucurbitae Coquillett, were tested for response to cue-lure at various ages. Virgin laboratory (4, 6, 8, 10, 12, and 14 days old) and wild (10, 12, 14, 16, 18, 20, and 22 days old) flies were released into outdoor field cages and trapped from 0800 until 1600 hr. Response of males to cue-lure increased with age and corresponded with sexual maturity for each strain. Females of both strains were relatively nonresponsive to cue-lure. Failure to eradicate in past male annihilation programs againstD. cucurbitae may be explained in part by the fact that only older males, which may have already mated with gravid females, respond to cue-lure.     

Maximal limited similarity-based rough set model

Non-symmetric similarity relation-based rough set model (NS-RSM) is viewed as mathematical tool to deal with the analysis of imprecise and uncertain information in incomplete information systems with “?” values. NS-RSM relies on the concept of non-symmetric similarity relation to group equivalent objects and generate knowledge granules that are then used to approximate the target set. However, NS-RSM results in unpromising approximation space when addressing inconsistent data sets that have lots of boundary objects. This is because objects in the same similarity classes are not necessarily similar to each other and may belong to different target classes. To enhance NS-RSM capability, we introduce the maximal limited similarity-based rough set model (MLS-RSM) which describes the maximal collection of indistinguishable objects that are limited tolerance to each other in similarity classes. This allows accurate computation to be done for the approximation space. Furthermore, approximation accuracy comparisons have been conducted among NS-RSM and MLS-RSM. The results demonstrate that MLS-RSM model outperforms NS-RSM and can approximate the target set more efficiently.     

Electrolyte—solvent interaction in the dipolar aprotic solvent dimethyl sulphoxide at 25°C

Conductance measurements are reported for s-alkylisothiouronium bromide, iodide and picrate salts in the dipolar aprotic solvent DMSO at 25°C. The data were analysed by Fuoss's equation (1975–1980) for 1:1 electrolytes, from which the values of Λ₀, the Gurney's cosphere diameter R and K_A are obtained. The results are discussed in the light of the recorded values of the constants K_R and K_S and the free energy term G_s.     

Z-transform-based FDTD algorithm for anisotropic perfectly matched layer

An efficient method based on the Z-transform theory and the D-H anisotropic perfectly matched layer formulations is presented for truncating general FDTD grids. The formulations are simple and independent of the material properties of the FDTD domain. Numerical examples for radiation and guided-wave problems are included to validate the proposed formulations.     

The Tail Effect of Some Prepared Cationic Surfactants on Silver Nanoparticle Preparation and Their Surface,Thermodynamic Parameters,and Antimicrobial Activity

The surface parameters of some cationic surfactants having different hydrophobic alkyl chains were assessed in aqueous solution using different techniques; surface tension, ultraviolet-Visible (UV–Vis) spectroscopy, and conductivity measurements. The obtained critical micelle concentration (CMC) for N-(2-((3,4-dimethoxybenzylidene)amino)ethyl)-N,N-dimethyloctan-1-aminium bromide (DBAO), N-(2-((3,4-dimethoxybenzylidene)amino)ethyl)-N,N-dimethyldodectan-1-aminium bromide (DBAD), and N-(2-((3,4-dimethoxybenzylidene)amino)ethyl)-N,N-dimethylhexadectan-1-aminium bromide (DBAH) in aqueous solution using three techniques are nearly the same. Increasing the hydrophobic chain length enhances micelle formation. Raising the solution temperature from 25 to 65 °C also shows the same trend. The thermodynamic calculations outlined the adsorption propensity of the surfactants at the surface compared to their affinity to form micelles. Both micellization and adsorption processes are enhanced with both the hydrocarbon elongation and with raising the solution temperature. The effect of the surfactant tail on the preparation process of the silver nanoparticles (AgNP) was assessed and confirmed using transmission electron microscope (TEM), dynamic light scattering (DLS), and UV–Vis spectra. Increasing the surfactant tail leads to a smaller particle size with a narrow distribution. The stability of the prepared AgNP is enhanced with hydrophobic surfactant tail elongation as proved with increasing the zeta-potential of the prepared AgNP colloid. The foaming power, interfacial tension, and emulsification stability of the DBAO, DBAD, and DBAH surfactants were determined. The DBAO, DBAD, and DBAH surfactants showed good antimicrobial activities against both bacteria (Gram positive and negative) and fungi, which have been enhanced because of incorporation of AgNP.     

Equality test with an anonymous authorization in cloud computing

Wireless Networks - With the rapid popularity and wide adoption of cloud storage, providing privacy-preserving by protecting sensitive information becomes a matter of grave concern. The most...