This study aimed to explore and separate the phytochemicals of the whole plant Conyza canadensis, a naturally growing plant in Iraq, since no phytochemical research was done previously in Iraq. The whole plant of C. canadensis was defatted by maceration in hexane for 24 hours. The defatted plant materials were extracted using Soxhlet apparatus, the aqueous ethanol 85% as a solvent extraction for 9 hours, and fractionated by petroleum ether, chloroform, ethyl acetate, and n-butanol. The petroleum ether, chloroform, and ethyl acetate fractions were analyzed by high-performance liquid chromatography (HPLC) for their steroids, alkaloids, and polyphenolic (phenolic acids and flavonoids) contents. One alkaloid was isolated from chloroform fractio

    This study aims to detect cadmium accumulation in the soil of Baghdad. Twenty soil samples were collected randomly during November 2020 to cover the study area, emphasizing the nature of each area (agricultural, commercial, industrial, residential, roadside, and waste dumping sites). All soil samples were subjected to geochemical analysis using atomic absorption spectrometry (ASS) to determine the concentration of cadmium in Baghdad soil. The laboratory data was utilized to design the spatial analysis map using Arc GIS 10.4.1 to investigate the spatial distribution of cadmium. The results demonstrated that the total content of cadmium in the study area ranged from 0.121to 1.78 mg/kg. All results of cadmium concentrations are withi

    Coronavirus disease 2019 (COVID-19) is a systemic disease with a substantial impact on the hematopoietic system and hemostasis. Neutrophilia is an early indicator of SARS-CoV-2 infection, while lymphopenia acts as a biomarker of the severity of infection, and the neutrophil-to-lymphocyte ratio (NLR) is the main indicator of cytokine storms. Thus, this study aimed to provide local data about hematological parameters among COVID-19 patients and estimate their correlation with viral load and other factors in severe cases. A total of 99 nasopharyngeal swabs and whole blood specimens were collected from individuals suspected with COVID-19 between October and December 2020. Samples were tested by real time reverse transcript

The coma gasses consist of molecules liberated from the nucleus by solar heating and relative sublimation. Once they have left the nucleus, these molecules in the coma are exposed to direct solar radiation and can be damaged in various ways due to the combined action of these reactions.

   One of some complex problems facing the research in this field is that the Maxwell-Boltzmann equation gives distribution function for one kind of particles which have same masses, but the gas has multi-groups of particles (Carbon, Neon, Sodium … etc.), where all these components must be in one program to extract average velocity of all and calculate particles velocity to each band. This problem is solved here by Matlab program a

In this paper, a mathematical model consisting of a prey-predator system incorporating infectious disease in the prey has been proposed and analyzed. It is assumed that the predator preys upon the nonrefugees prey only according to the modified Holling type-II functional response. There is a harvesting process from the predator. The existence and uniqueness of the solution in addition to their bounded are discussed. The stability analysis of the model around all possible equilibrium points is investigated. The persistence conditions of the system are established. Local bifurcation analysis in view of the Sotomayor theorem is carried out. Numerical simulation has been applied to investigate the global dynamics and specify the effect

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