The products of composites material are very sesetive to many variables, such as manufacturing process, additive materials, …. etc. Filler or additive plays a major role to determine the formation of the properties and behavior of the composites. In this study, polyethylene terephthalate-based compounds were produced and characterized. The work is concerned to prepare samples of Polyethylene terephthalate (PET) - zinc-ferrite (ZnFe2O4) with different addition ratio as zinc-ferrite (1, 2, 5, 10, 15 and 20) wt% obtained from mixing the solution with a hot pressing method applied under optimum conditions. The densities of the composites for all samples were calculated. Through the work the diffusion of zinc-ferrite into the grain of Polyethylene terephthalate has been noted. Structural properties are studied by using X-ray powder pattern, the results of the XRD diffraction analysis showed that the structure for pure PET has four broad peaks at the (2θ=16.46°,17.45°, 22.72°,25.98°). The non-crystalline behavior of the polymer and the ceramic compound indicates the presence of a crystalline phase with a single cubic structure with a space group fd-3m (227)) (a=b=c=8.44 Å, V=601.45 (Å)³). While adding zinc-ferrite to PET in different concentrations to obtain (PET / ZnFe2O4) composites material will increase the intensity of the X-ray peaks, and change the location of the peaks with the addition of zinc-ferrite. It is noted that X-ray diffraction patterns for PET / ZnFe2O4 (20%) indicates that there was no apparent variation of the patterns of pure Zn-ferrite ceramic diffraction which showed that the crystalline structure remains stable in PET / ZnFe2O4. In addition, the electrical properties of the compounds represented by the dielectric constant (real and imaginary), dielectric loss ( tanδ) and the A.C conductivity as a function of a range of frequencies (50Hz-1MHz) have been measured. The results indicated that these properties increase with increasing concentrations of ceramic addition. On the other hand, these properties decrease with increasing frequency due to the change in polarization mechanisms. It has been proven that these prepared superposed materials possess good stability properties in a wide range of frequencies, making these polymeric overlays of wide use in many applications. As for the measurements of Shore D hardness, it has been shown that the hardness of the compounds increases with increasing ceramic concentrations.
Background: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach
... Show MoreWe aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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