Effect of ionic content,solid content,degree of neutralization,and chain extension on aqueous polyurethane dispersions prepared by prepolymer method

There are many variables in the preparation of aqueous polyurethane (PU) dispersions. Carboxylic acid content, solid content, degree of pre/postneutralization of the carboxylic acids, and chain extension all impact dispersion particle size, viscosity, pH, molecular weights, and glass transition temperature. This study evaluated the impact of these variables on a given PU dispersion formulation prepared from isophorone diisocyanate, an aliphatic polyester polyol, dimethylol propionic acid, and hexamethylene diamine with triethyl amine as the neutralizing base and N‐methyl pyrrolidone as the cosolvent. Changes in carboxylic acid content, degree of preneutralization, and chain extension were found to have the expected impacts on dispersions properties. Increased ionic content in the dispersion step led to lower particle size and higher viscosity, increased chain extension with its concurrent increase in molecular improved subsequent film properties. Surprising results were obtained by varying the amount of postneutralization and from increased solids content at the time of dispersion. Unexpectedly, both of these variations led to much higher dispersion viscosities and particle size in solution. To have these changes take place, it is theorized that there is a major change in solution morphology caused by these modifications. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 2514–2520, 2005     

TP63 Is Significantly Upregulated in Diabetic Kidney

The role of tumor protein 63 (TP63) in regulating insulin receptor substrate 1 (IRS-1) and other downstream signal proteins in diabetes has not been characterized. RNAs extracted from kidneys of diabetic mice (db/db) were sequenced to identify genes that are involved in kidney complications. RNA sequence analysis showed more than 4- to 6-fold increases in TP63 expression in the diabetic mice’s kidneys, compared to wild-type mice at age 10 and 12 months old. In addition, the kidneys from diabetic mice showed significant increases in TP63 mRNA and protein expression compared to WT mice. Mouse proximal tubular cells exposed to high glucose (HG) for 48 h showed significant decreases in IRS-1 expression and increases in TP63, compared to cells grown in normal glucose (NG). When TP63 was downregulated by siRNA, significant increases in IRS-1 and activation of AMP-activated protein kinase (AMPK (p-AMPK-Th¹⁷²)) occurred under NG and HG conditions. Moreover, activation of AMPK by pretreating the cells with AICAR resulted in significant downregulation of TP63 and increased IRS-1 expression. Ad-cDNA-mediated over-expression of tuberin resulted in significantly decreased TP63 levels and upregulation of IRS-1 expression. Furthermore, TP63 knockdown resulted in increased glucose uptake, whereas IRS-1 knockdown resulted in a decrease in the glucose uptake. Altogether, animal and cell culture data showed a potential role of TP63 as a new candidate gene involved in regulating IRS-1 that may be used as a new therapeutic target to prevent kidney complications in diabetes.     

Bile acid metabolism in mammals: VI. Effect of ethionine upon bile acids of rat bile

Sex differences in the effect of ethionine upon rat liver metabolism prompted our investigation into possible sex differences in the effect of ethionine upon bile acid metabolism. The bile ducts of 24 rats, 12 male and 12 female, were cannulated. After 1 hr of bile collection, 6 rats of each sex were given ethionine, 1 mg/g body wt, by feeding tube. The bile acid composition of the bile collected during the subsequent 4 hr was analyzed by combined thin layer and gas chromatography. Ethionine induced a reduction in bile flow (3rd and 4th hr) and in bile acid concentration (4th hr) in female rats. The amino acid had no effect upon bile flow but did increase biliary secretion of bile acids (1st and 2nd hr) in male rats. Cholic acid accounted for the bulk of the reduction in total bile acid secretion in the female studies. The increase in total bile acid secretion in the male studies involved all bile acids. The effects of ethionine upon bile acid secretion were delayed in the female studies, immediate in the male. The changes in bile acid secretion involved only the taurine conjugates in the female studies, both taurine and glycine conjugates in the male. There are substantial sex differences in the effect of ethionine upon bile acid metabolism in the rat.     

Broadband dielectric spectroscopy of nanostructured maleated polypropylene/polycarbonate blends prepared by in situ polymerization and compatibilization

The miscibility and molecular dynamics of nanostructured maleated polypropylene (mPP)/polycarbonate (PC) blends prepared by in situ polymerization of macrocyclic carbonates with polypropylene modified with 0.5 wt% of maleic anhydride-reactive groups were investigated over a wide range of frequencies (10⁻²-0.5 × 10⁷ Hz) at different constant temperatures using broadband dielectric spectroscopy and scanning transmission electron microscope (STEM). The molecular dynamics of the glass relaxation process of the blend (α-relaxation process) appeared at a lower temperature range compared with that of the pure PC. This shift in the molecular relaxation process is attributed to the partial miscibility of the two polymer components in the blends as previously confirmed by the morphology via STEM. Nanoscale morphologies with average domain diameters as small as 50 nm were obtained for the different blend compositions studied. The STEM photographs show that the graft mPP-g-PC prefers to locate at the interfaces as previously reported. The relaxation spectrum of pure PC and mPP/PC blends was resolved into α- and β-relaxation processes using the Havriliak-Negami equation and ionic conductivity. The dielectric relaxation parameters, such as relaxation peak broadness, maximum frequency, f_max, and dielectric strength, Δ? (for the α- and β-relaxation processes), were found to be blend composition dependent. The kinetics of the α-relaxation processes of the blends were well described by Vogel-Fulcher-Tammann (VFT) equation. The local process of PC was resolved into two relaxation processes β₁ and β₂, associated with the carbonyl groups' motion and the combined motions of carbonyl and phenylene groups, respectively. Only β₂ shifted to lower frequency in the blend while β₁ was relatively not affected by blending. The electric modulus of the blends was used to get a sufficient resolution of the different relaxation processes in the samples, i.e., α-, β-relaxation processes, ionic conductivity, and interfacial polarization. In addition, the blending method used was found to increase the d.c. conductivity without affecting the charge carrier transport mechanism, making it possible to develop novel polymer blends with tunable dielectric properties and morphology from existing polymers.     

The effect of epoxy‐polyester hybrid resin on mechanical properties,rheological behavior,and water absorption of polypropylene wood flour composites

The effect of epoxy resin on mechanical and Rheological properties, and moisture absorption of wood flour polypropylene composites (WPCs) were investigated. The reactive mixing of epoxy resin with 30, and 40 wt% wood flour and polypropylene (PP) was carried out in twin screw extruder with a special screw elements arrangement. PP grafted maleic anhydrides (MPP) were used as coupling agent to improve the interfacial interactions of wood flour, epoxy resin, and PP. The tensile strength of composites decreased, and elastic modulus and moisture absorption increased with increasing epoxy resin content. The complex viscosity η* increased with increasing epoxy resin content of composites, and a synergistic effect in increasing the η* was observed at 3 wt% resin. The epoxy resin modified wood‐PP composites that chemically coupled by MPP showed minimum water absorption with highest elastic modulus. The experimental oscillation rheologyical data were used to drive a model to predict the flow behavior of WPCs, in a wide range of frequencies. POLYM. ENG. SCI., 47:2041–2048, 2007. © 2007 Society of Plastics Engineers     

Heavy-fuel flame radiation in gas turbine combustors—exploratory results

With lower costs and greater availability, heavy fuel oil appears as an attractive alternative to the conventional gas oil used in industrial gas turbines. However, higher levels of radiation and smoke are expected, and this note reports on some preliminary tests made with a combustion chamber burning fuels of different carbon content, ranging from kerosine to a 25% blend of residual fuel oil in gas oil, at a chamber pressure of 10 atm^*. The combustion rig was equipped with a total-radiation pyrometer and black-body furnace capable of measurement at different axial stations along the spray-stabilized flame. The presence of the residual fuel oil in the gas oil was found to promote significant increases in the mean levels of radiation, emissivity and smoke density, with a modest increase in liner temperature.     

Applying gravitational search algorithm in the QoS-based Web service selection problem

With the growing use of service-oriented architecture for designing next generation software systems,the service composition problem and its execution complexity have become even more important in resp...     

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%.

     

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.     

Intrusion Detection Systems Using Blockchain Technology: A Review,Issues and Challenges

Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches. However, the current approaches have challenges in detecting intrusions, which may affect the performance of the overall detection system as well as network performance. For the time being, one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains trust between individuals no matter how far apart they are. Recently, blockchain was integrated into intrusion detection systems to enhance their overall performance. Blockchain has also been adopted in healthcare, supply chain management, and the Internet of Things. Blockchain uses robust cryptography with private and public keys, and it has numerous properties that have leveraged security’s performance over peer-to-peer networks without the need for a third party. To explore and highlight the importance of integrating blockchain with intrusion detection systems, this paper provides a comprehensive background of intrusion detection systems and blockchain technology. Furthermore, a comprehensive review of emerging intrusion detection systems based on blockchain technology is presented. Finally, this paper suggests important future research directions and trending topics in intrusion detection systems based on blockchain technology.