Complex formation of montmorillonite clay with polymers. Part 2: The use of montmorillonite clay–vinyl monomer complex as a comonomer in the copolymerization reaction of styrene–acrylonitrile monomers

The bulk copolymerization of styrene–acrylonitrile monomers using styrene‐N⁺–montmorillonite complex as a comonomer in the polymerization was studied. The X‐ray diffraction (XRD) analysis showed that part of the styrene‐N⁺–montmorillonite complex remained non‐dispersed (immiscible) and the copolymer was excluded from the interlayer of the immiscible part of the clay. The successive chemical extraction process revealed that a reasonable amount of the styrene–acrylonitrile copolymer was directly attached to the styrene‐N⁺–montmorillonite complex and enveloped the clay. Highly exfoliated clay lamella and nanospheres (3–5 nm) were observed by transmission electron microscopy (TEM). The montmorillonite clay assume two different morphologies, immiscible and exfoliated, on the basis of the XRD and TEM data. A simple method of calculation of the ratio of the exfoliated/immiscible amounts of the clay indicated that the amount of the styrene‐N⁺–montmorillonite complex exfoliated into separate lamella was 40 % (w/w) of the amount of the clay samples containing 2 % of the (styrene‐N⁺–montmorillonite complex) clay. This amount of exfoliated clay decreases with the increase of the concentration of the clay. The presence of the styrene‐N⁺–montmorillonite clay in the copolymerization reaction had a minor effect on both the copolymer composition and the molecular weight. Modification of the clay with the derivatized styrene monomer can achieve a nanocomposite using a percentage no more than 4 % (w/w) of complex in the copolymer. Copyright © 2004 Society of Chemical Industry     

Coronavirus disease 2019 (COVID-19): survival analysis using deep learning and Cox regression model

Pattern Analysis and Applications - Coronavirus (COVID-19) is one of the most serious problems that has caused stopping the wheel of life all over the world. It is widely spread to the extent that...     

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, we propose a seamless migration technique for complex edge computing structures. The developed migration scheme enables services to adapt to the required load on the radio channels. The proposed algorithm is analyzed for various use cases, and a test bench has been developed to emulate the operator’s infrastructure. The obtained results are introduced and discussed.     

Mutual effects of chemical reaction and thermal radiation on MHD peristaltic transport of Jeffrey nanofluids: Tumor tissues treatment

As thermal radiation is one of the fundamental means of heat transfer, therefore, this study analyzes the impacts of thermal radiation and magnetic field on the peristaltic transport of a Jeffrey nanofluid in a nonuniform asymmetric channel. Further, Two models of viscosity are debated: Model (I), in which all parameters dependent on viscosity behave as a constant (as treated before in nanofluid research); Model (II), in which these known parameters are considered to vary with the temperature of the flow. Under the condition of long wavelength and low Reynolds number, the problem is rearranged. The resulting system of partial differential equations (PNE) is solved with aid of Mathematica 11. Furthermore, the streamline graphs are presented by significance of trapping bolus phenomenon. To emphasize the quality of solutions, comparisons between the previous results and recent published results by Reddy et al. have been made and signified. The comparisons are shown in Table 1 and are found to be in good agreement. As the thermal radiation increases, the diameter of nanoparticles rises (thermal radiation is a diminishing function of temperature, and with a decrease in the temperature, the diameter of the nanoparticles increases, that is, the size of nanoparticles increases and they become more active near malignant tumor tissues). Therefore, its work as agents for radiation remedy, produce limited radiation quantities, and selectively target malignant tumor for controlled mutilation (radiotherapy of oncology). Such a model is appropriate for the transportation of physiological flows in the arteries with heat and mass transfer (blood flow models).     

Composite Nanoarchitectonics with Polythiophene,MWCNTs-G,CuO and Chitosan as a Voltammetric Sensor for Detection of Cd(II) Ions

Journal of Inorganic and Organometallic Polymers and Materials - In this study, we describe an electrochemical method for detecting Cd(II) ions, utilizing a glassy carbon electrode (GCE) modified...     

Surface and bulk properties of ancient Egyptian mortars. Part I: X-ray diffraction studies

A series of Ancient Egyptian Mortars were extracted from the great Giza Pyramid, the second Giza Pyramid and the Sphinx and its adjoining temple. X-Ray Diffraction studies revealed the presence of gypsum, calcite and silica in most of the samples with a clearcut predominance of gypsum in the samples extracted from the Sphinx. Calcium silicates of different crystallographic modifications seem to be present in a large proportion of the samples. X-Ray studies carried out on heat-treated samples indicated the prevalence of the hemihydrate or γ-CaSO₄ modification until a temperature as high as 400°C.     

Copy-move forgery detection of duplicated objects using accurate PCET moments and morphological operators

This paper presents a new method for copy-move forgery detection of duplicated objects. A bounding rectangle is drawn around the detected object to form a sub-image. Morphological operator is used to remove the unnecessary small objects. Highly accurate polar complex exponential transform moments are used as features for the detected objects. Euclidian distance and correlation coefficient between the feature vectors are calculated and used for searching the similar objects. A set of 20 forged images with duplicated objects is carefully selected from previously published works. Additional 80 non-forged images are edited by the authors and forged by duplicating different kinds of objects. Numerical simulation is performed where the results show that the proposed method successfully detect different kinds of duplicated objects. The proposed method is much faster than the previously existing methods. Also, it exhibits high robustness to various attacks such as additive white Gaussian noise, JPEG compression, rotation, and scaling.     

Rakeness with block sparse Bayesian learning for efficient ZigBee‐based EEG telemonitoring

Future healthcare systems are shifted toward long‐term patient monitoring using embedded ultra‐low power devices. In this paper, the strengths of both rakeness‐based compressive sensing (CS) and block sparse Bayesian learning (BSBL) are exploited for efficient electroencephalogram (EEG) transmission/reception over wireless body area networks. A binary sensing matrix based on the rakeness concept is used to find the most energetic signal directions. A balance is achieved between collecting energy and enforcing restricted isometry property to capture the underlying signal structure. Correct presentation of the EEG oscillatory activity, EEG wave shape, and main signal characteristics is provided using the discrete cosine transform based BSBL, which models the intra‐block correlation. The IEEE 802.15.4 wireless communication technology (ZigBee) is employed, since it targets low data rate communications in an energy efficient manner. To alleviate noise and channel multipath effects, a recursive least square based equalizer is used, with an adaptation algorithm that continually updates the filter weights using successive input samples. For the same compression ratio (CR), results indicate that the proposed system permits a higher reconstruction quality compared with the standard CS algorithm. For higher CRs, lower dimensional projections are allowed, meanwhile guaranteeing a correct reconstruction. Thus, low computational high quality data compression/reconstruction are achieved with minimal energy expenditure at the sensors nodes.     

Entropy with Local Binary Patterns for Efficient Iris Liveness Detection

Iris anti-spoofing is one of the most important topics, in which the development is increasing rapidly. This paper introduces an efficient system for detecting iris attacks. The system avoids the segmentation and the normalization stages employed traditionally in fake detection systems. Wavelet packets (WPs) are used to decompose the original image into wavelet approximation and detail channels. Entropy values are extracted from the wavelet channels, and also from the local binary pattern (LBP) images of the channels. These features are used for discriminating between real and fake iris images. Support vector machines are used for the classification purpose. The aim is to contribute for improved classification accuracy with less computational complexity and reduced processing time. Entropy of the WP channels gives 99.9237% classification accuracy, and the entropy of the LBP images yields 99.781%, using ATVS-FIr-DB. Fusion of these features yields 100% classification accuracy. Entropy of the wavelet channels is sufficient to obtain 100% accuracy using CASIA-Iris-Syn database, without fusion. All images in both databases are used, without the need to discard images with unsuccessful segmentation. Segmented images from both databases are used for comparison. Results show that more discriminative features can be obtained using the proposed algorithm. System complexity and processing time are reduced noticeably, and the system is robust to different types of fakes.