The aim of this study was to develop a sensor based on a carbon paste electrodes (CPEs) modified with used MIP for determination of organophosphorus pesticides (OPPs). The modified electrode exhibited a significantly increased sensitivity and selectivity of (OPPs). The MIP was prepared by thermo-polymerization method using N,N-diethylaminoethymethacrylate (NNDAA) as functional monomer, N,N-1,4-phenylenediacrylamide (NNPDA) as cross-linker, the acetonitrile used as solvent and (Opps) as the template molecule. The three OPPs (diazinon, quinalphos and chlorpyrifos) were chosen as the templates, which have been selected as base analytes which used widely in agriculture sector. The extraction efficiency of the imprinted polymers has been evaluat

The removal of fluoride ions from aqueous solution onto algal biomass as biosorbent in batch and continuous fluidized bed systems was studied. Batch system was used to study the effects of process parameters such as, pH (2-3.5), influent fluoride ions concentration (10- 50 mg/l), algal biomass dose (0–1.5 g/ 200 ml solution), to determine the best operating conditions. These conditions were pH=2.5, influent fluoride ions concentration= 10 mg/l, and algal biomass dose=3.5 mg/l. While, in continuous fluidized bed system, different operating conditions were used; flow rate (0.667- 0.800 l/min), bed depth (8-15 cm) corresponded to bed weight of (80- 150 g). The results show that the breakthrough time increases with the inc

Vitrifications process one of the important methods to immobilize nuclear waste.  In this research nuclear waste (Strontium Oxides) with molecular weight (5%) was immobilized by vitrification methods in two types of borosilicate glass (c-type) which are glass and glass-ceramics. To investigate the physical, chemical and mechanical properties of glass and glass-ceramic after immobilize nuclear waste these samples irradiated by gamma ray radiation. Co-60 was used as gamma a irradiation with dose rate 0.38 kGy/hr for different period of time. It’s found that gamma radiation affected the glass and glass-ceramic properties. From phase analysis by the x-ray diffraction for glass-ceramic samples proved that at doses 343kGy change the cry

Steel fiber aluminum matrix composites were prepared by atomization technique. Different air atomization conditions were considered; which were atomization pressure and distance between sample and nozzle. Tensile stress properties were studied. XRF and XRD techniques were used to study the primary compositions and the structure of the raw materials and the atomized products. The tensile results showed that the best reported tensile strength observed for an atomization pressure equal to 4 mbar and sample to nozzle distance equal to 12 cm. Young modulus results showed that the best result occurred with an air atomization pressure equal to 8 mbar and sample to nozzle distance equal to 16cm

Zinc oxide thin films were deposited by chemical spray pyrolysis onto glass substrates which are held at a temperature of 673 K. Some structural, electrical, optical and gas sensing properties of films were studied. The resistance of ZnO thin film exhibits a change of magnitude as the ambient gas is cycled from air to oxygen and nitrogen dioxide

Green synthesis methods have emerged as favorable techniques for the synthesis of nano-oxides due to their simplicity, cost-effectiveness, eco-friendliness, and non-toxicity. In this study, Nickel oxide nanoparticles (NiO-NPs) were synthesized using the aqueous extract of Laurus nobilis leaves as a natural capping agent. The synthesized NiO-NPs were employed as an adsorbent for the removal of Biebrich Scarlet (BS) dye from aqueous solution using adsorption technique. Comprehensive characterization of NiO-NPs was performed using various techniques such as atomic force microscopy (AFM), Fourier transform infrared (FTIR), X-ray diffraction (XRD), Brunauer-Emmett and Teller (BET) analysis, and scanning electron microscopy (SEM). Additionally, o

The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach