Mefenamic acid (MA) is one of the non-steroidal anti-inflammatory drugs, it is widely used probably due to having both anti-inflammatory and analgesic activity, the main side effects of mefenamic acid include gastrointestinal tract (GIT) disturbance mainly diarrhea, peptic ulceration, and gastric bleeding. The analgesic effects of NSAIDs are probably linked to COX-2 inhibition, while COX-1 inhibition is the major cause of this classic adverse effects. Introduction of thiazolidinone may lead to the increase in the bulkiness leads to the preferential inhibition of COX-2 rather than COX-1 enzyme. The study aimed to synthesize derivatives of mefenamic acid with more potency and to decrease the drug's potential side effects, new series of 4-t

This study was conducted in Baghdad, Iraq from December 2021 to May 2022. The goal was to determine the effect of Toxoplasma gondii on liver function by examining the relationship between Toxoplasma infection and hormones. One hundred and twenty male patients with Chronic liver disease (CLD) (age:14-75 years) and 120 control males (age: 24-70 years) participated in this study. Serum samples were taken from all individuals and were then analysed for anti-Toxoplasma antibodies. Hormonal tests were conducted for all participants which included (Cortisol, testosterone, prolactin, insulin, and thyroid-stimulating hormone TSH). Biochemical tests included (Prothrombin time PT, international normalized ratio INR and albumin); liver enzymes

The present study aims at knowing the effect of instrumental enrichment in the acquisition of geographical concepts for first grade student in intermediate school. The study is restricted in the students of first grade student in intermediate school\ The EducationalDirectorate of Rusafa for academic (2013/2014),for the purpose of achieving the objective, the following hypotheses:

There is no statistical significant different at the level of (0.5) between the scores of the experimental group  who study geography according to the instrumental enrichment and the scores of the control group who learned geographical according to the traditional methods.

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IRA Dawood, JOURNAL OF SPORT SCIENCES, 2016 - Cited by 3

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