Dental implants can be made of various materials, and amongst them, titanium and titanium alloy were the materials of choice for dental implants for many years because of their biocompatibility. The two alloys have a high level of biocompatibility, a lower modulus of elasticity, and better corrosion resistance than other alloys. Thus, they are frequently utilized in biomedical applications and mostly replace stiff fabrics. The latest advances in a new strontium oxide–cp titanium composite alloy are the main topic of this research. With regard to biomedical applications, additions of strontium oxide were synthesized at three distinct weight percentages (2%, 4%, and 6% by wt%). Powder metallurgy was used to create the alloys, which were then sintered by heating the samples. The effects of adding strontium oxide were analyzed by utilizing measurements of the Brinell hardness, X-ray diffraction, porosity, diametral tensile strength, roughness, and wettability of the finished surfaces. The results show that adding more strontium oxide (gradually increasing the ratio from 2% SrO to a 6% addition) raised the roughness and porosity. However, the microhardness and diametral tensile strength were enhanced with an increase in the volume fraction of strontium oxide particles. In conclusion, the alloy that contained 6 wt% strontium oxide microparticles had reasonably high mechanical properties and might be regarded as suitable for use in dental and medical applications due to its high wettability or, in other words, its low contact angle. The Brinell testing results for the diametral tensile strength, microhardness, and porosity of the generated strontium oxide–cp titanium composite alloy demonstrate its high potential for usage as a biomaterial, particularly in dental applications.
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
... Show MoreThis experiment presented essential oils by GC/MS, pigment content, and their antioxidant activities as well as sensory evaluation of delight samples. Limonene (66.88%) was the most prevalent yield. The peels of clementine had DPPH and ABT Scavenging activity. All levels of pigment extract had better scores for all sensory values and recorded acceptable scores in terms of appearance, color, aroma, and overall acceptability compared to control delight. Besides, delight samples containing 15 mg astaxanthin pigment extract showed maximum sensory scores compared to other samples and control delight. On the other hand, the product was less acceptable to the panelists compared to control in the case of the addition of 3.75 mg astaxanthin pigme
... 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