In this work, we focused on studying 1,4-naphthoquinones and their derivatives, and knowing the methods of preparing them using different auxiliary agents and forming derivatives containing heterocyclic rings, active groups and saturated rings containing heterogeneous elements . In addition, due to their strong antibacterial, antifungal and anticancer activity, 1,4-naphthoquinone compounds biological importance and are considered a source of various pharmaceutical compounds.

Three complexes of copper(II) and iron(II) with mixed ligands acetylacetonebis(thio-semicarbazone)- ABTSH2 and benzaldazine- BA have been prepared and characterized using different physico-chemical techniques including the determination of metal contents, mole-cular weight, measurement of molar conductivity, magnetic moment, molar refraction, infrared and electronic spectra. Accordingly, octahedral complexes having general formulaes [Cu2(ABTSH2)2(BA)2Cl2]Cl2 and [M2(ABTSH2)2(BA)2(SO4)2] {M= Cu(II) or (Fe(II)} have been proposed. The resulted complexes screened for antifungal activity in vitro against the citrus pathogen Aspergillus niger and Fusarium sp. which caused root rot of sugar and the beans pathogen Alternaria sp. All the complex

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

Mango fruit is one of the most nutritionally rich fruits with unique flavor, this fruit belonged to family of Anacardiaceae and it is an excellent source of vitamins specially vitamin A, carotene pigments and potassium. In this study the antimicrobial activity of mango seeds extract has been investigated against gram positive bacteria (Staphylococcus aureus and Bacillus spp.) and gram negative bacteria (Pseudomonas aeruginosa and E. coli) and yeast Candida albicans by well diffusion method in nutrient agar and the results were expressed as the diameter of bacterial inhibition zones surrounding the wells, and the antibiofilm of its extracts was observed against Staphylococcus aureus. The seeds extractions prepared by two solvents: 8

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system