Acinetobacter baumannii is highly adapted to hospital environments, causing persistent chronic infections due to its ability to form biofilms. In this work, the antibiofilm activity of AuNPs with a subMIC concentration of 9.34 μg/ml was investigated by the microtiter plate method against 80 clinical isolates of A. baumannii. The results revealed that the biofilm was significantly (P< 0.05) reduced by 48.2 – 82.1%.

Chemical spray pyrolysis technique was used at substrate temperature 250 ˚C with annealing temperature at 400 ˚C (for 1hour) to deposition tungsten oxide thin film with different doping concentration of Au nanoparticle (0, 10, 20, 30 and 40)% wt. on glass substrate with thickness about 100 nm. The structural, optical properties were investigated. The X-ray diffraction shows that the films at substrate temperature (250 ˚C) was amorphous while at annealing temperature have a polycrystalline structure with the preferred orientation of (200), all the samples have a hexagonal structure for WO3 and Au gold nanoparticles have a cubic structure. Atomic force microscopy (AFM) was used to characterize the morphology of the films. The optical pr

The main object of the current work was to determine the antifungal efficiency of secondary metabolites product called synephrine that extracted from Citrus sinesis peels and the ability of synephrine to biosynthesis gold nanoparticles from HAucl4 which consider environmentally favourable method, then determine their activity against pathogenic human dermatophyte. The identification of synephrine done by Thin layer chromatography (TLC), High Performance Liquid Chromatography (HPLC) and The Fourier Transform Infrared (FTIR). The characterization of gold nanoparticles by using Ultra Violet-Visible Spectroscopy (UV-Vis), Field – Emission Scanning Electron Microscopy (FESEM) and Fourier Transform Infrared (FTIR), confirmed the biosynt

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

          New nitrone and selenonitrone compounds were synthesized. The condensation method between N-(2-hydroxyethyl) hydroxylamine and substituted carbonyl compounds such as [benzil, 4, 4́-dichlorobenzil and  2,2́ -dinitrobenzil] afforded a variety of new nitrone compounds while the condensation between N-benzylhydroxylamine and substituted selenocarbonyl compounds such as [di(4-fluorobenzoyl) diselenide and (4-chlorobenzoyl selenonitrile] obtained selenonitrone compounds. The condensation of N-4-chlorophenylhydroxylamine with dibenzoyl diselenide obtained another type of selenonitrone compounds. The structures of the synthesized compounds were assigned based on spectroscopic data (FT-IR,

Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate