The family Chalcididae (Order: Hymenoptera) is known as one of the large chalcidoid wasps with some distinct morphological characters. The first occurrence of two parasitoid species belonging to this family was reported in the Al-Husayniya district Karbala Province, Iraq; which are: Brachymeria podagrica (Fabricius, 1787) and Chalcis myrifex (Sulzer, 1776). Both species were collected by using the sweeping net from orchards during July 2020.

The settlement rate and pore water pressure dissipation rate are mainly controlled by the permeability of soil. Both laboratory and field tests show that the permeability is varied during the loading and consolidation process. It is known that consolidation process is accompanied by decrease in void ratio which leads to decrease in the coefficient of permeability. The importance of the decrease of the coefficient of permeability on the time rate of settlement and pore water pressure needs to be investigated.
This paper takes into account the change in coefficient of permeability during consolidation and studies its effect on consolidation characteristics of a clay layer. The finite element method is used in the analysis and the packag

An optoelectronic flow-through detector for active ingredients determination in pharmaceutical formulations is explained. Two consecutive compact photodetector’s devices operating according to light-emitting diodes-solar cells concept where the LEDs acting as a light source and solar cells for measuring the attenuated light of the incident light at 180˚ have been developed. The turbidimetric detector, fabricated of ten light-emitting diodes and five solar cells only, integrated with a glass flow cell has been easily adapted in flow injection analysis manifold system. For active ingredients determination, the developed detector was successfully utilized for the development and validation of an analytical method for warfarin determination

In this study, (50–110 nm) magnetic iron oxide (α-Fe2O3) nanoparticles were synthesized by pulsed laser ablation of iron target in dimethylformamide (DMF) and sodium dodecyl sulfate (SDS) solutions. The structural properties of the synthesized nanoparticles were investigated by using Fourier Transform Infrared (FT-IR) spectroscopy, UV–VIS absorption, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). The effect of laser fluence on the characteristics of these nanoparticles was studied. Antibacterial activities of iron oxide nanoparticles were tested against Gram-positive; Staphylococcus aureus and Gram-negative; Escherichia coli, Pseudomonas aeruginosa and Serratia marcescens. The results sh

Objective: The aim of this study was to formulate and in vitro evaluate fast dissolving oral film of practically insoluble bromocriptine mesylate to enhance its solubility and to improve its oral bioavailability by avoiding first pass effect as well as to produce an immediate release action of the drug from the film for an efficient management of diabetes mellitus type II in addition to an improvement of the patient compliance to this patient- friendly dosage form. Methods: The films were prepared by the solvent casting method using hydroxypropyl methylcellulose of grades (E3, E5, E15), polyvinyl alcohol (PVA), pectin and gelatin as film-forming polymers in addition to polyethene glycol 400 (PEG400), propylene glycol (PG) and glycerin were

In the present study, advanced oxidation treatment, the TiO₂ /UV/H₂O₂  process was applied to decolorisation of the reactive yellow dyes in aqueous solution. The UV radiation was carried out with a 6 W low-pressure mercury lamp. The rate of color removal was studied by measuring the absorbency at a characteristic wavelength. The effects of H2O2 dosage, dye initial concentration and pH on decolorisation kinetics in the batch photoreactor were investigated. The highest decolorisation rates were observed (98.8) at pH range between 3 and 7. The optimal levels of H₂O₂ needed for the process were examined. It appears that high levels of H₂O₂ could reduce decolori

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