The current study is concerned  over the  benefits  from  our Prophet  ' Surah , these   benefits  are seven  which are : the first : (  The  losing  , disappointment ,  weakness  in the affairs  of those disbelievers ,the second : showing the affairs of the believers   in respect to integrity ,  forgiveness   and rest, the third :  Indicating  the big difference  between the believers and disbelievers , each team has   his own characteristics that being distinguished from the other,  I have explained  the benefit   that the disbelievers are in a difficult

ackground: Escherichia coli is one of the most
important bacterial pathogen that can cause several
disease to human being . In our study we try to
investigate the sensitivity resistance pattern of
Escherichia coli against three antibiotics ( Amikacin,
Nalidixic acid and Cephalexin).
Methods: For this purpose we collected 51 clinical
isolates of Escherichia coli from stool and urine of
outpatient and inpatient patients from different wards
of AL-SADER Teaching Hospital in AL-NAJAF
AL-ASHRAf, IRAQ, and tested by culture and
sensitivity test .
Results: The results appeared that Amikacin show
the highest percentage of sensitivity ( 66.66 % ) ,
while Cephalexin show the lowest percentage of
sensiti

The adsorption process of 5-Fluorouracil (5FU) drugs on Aluminum nitride nanotubes surface (AlNNTs) have been evaluated through density functional theory (DFT). The DFT results show that the interaction of AlNNTs with the F atoms of 5FU drugs is strong due to the fact that the amount of adsorption energy was about − 29.65 kcal.mol−1. Conversely, the interaction of the 5FU through O atoms with the AlNNTs was weaker due to the lower value of adsorption energy. Also, based on the values of Gibbs free energy, the 5FU adsorption on the surfaces of AlNNTs was spontaneous. In addition, based on natural bond orbital (NBO) analysis, the direction of charge transfer was from fluorine’s σ orbitals of the drug to nitrogen’s and aluminum’s n*

A novel series of mixed-ligand complexes of the type, [ML1(L2)3]Clx [M= Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiff base (HL1) as main ligand, nicotinamide (L2) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR,1H-NMR,13C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiff base ligand, HL1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxygen atoms, whereas the sec

    Urinary tract infections (UTI) are some of the most common infections experienced by humans, exceeded in frequency among ambulatory patient only by respiratory and gastrointestinal infections. It is also the most common cause of nosocomial infection in adults.   A total of three hundred urine sample were collected in age (1-69 years old)   in both gender, with (UTI) symptoms referred to AL-Yarmok Teaching Hospital at Baghdad city during the period from January 2010 till August 2010.  The commonest isolates were Escherichia coli (E.Coli), Proteus mirabilis and Klebsiella pneumoniae (These represented 49.2%, 22 %, and16 % of isolates respectively). The percentage of bacteria incidence in females

The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin