Three hundred and sixty different samples were collected from different sources, including wound, burn, nasal, and oral swabs from several hospitals in Baghdad. A number of 150 (53%) Staphylococcus aureus samples were isolated and identified among a total of 283 samples. Then, the spread of the Toxic Shock Syndrome Toxin-1 gene (tsst-1) was investigated in β-lactamase resistant S. aureus. According to the source of samples, the distribution of S. aureus  isolates was found to be significantly higher (p < 0.01) in wound samples as compared to other sources. According to the age, a highly significant  distribution (p < 0.01) was recorded in the age group of 15-30 years,

Plant tissue culture considers a benefit biotechnological technique for scientific research especially the production of undifferentiation callus cells and regeneration through suspension or static media. The seedlings of Peganum harmala was used as a source to produce callus mass in vitro in static media through different tissue culture media supplemented by varying combinations of plant growth regulators (PGR). The result illustrates that 2 mg/l of Kinitine with 0.5 mg/l of 2, 4-D was efficient to stimulate callus induction with percent 100% in stem and root of P. harmala and this combination gave a high fresh weight, 1954 mg in root and 1170
mg in stem and high dry weight in root and stem was 74.6

     Digital images are open to several manipulations and dropped cost of compact  cameras and mobile phones due to the robust image editing tools. Image credibility is therefore become doubtful, particularly where photos have power, for instance, news reports and insurance claims in a criminal court. Images forensic methods therefore measure the integrity of image  by apply different highly technical methods established in literatures. The present work deals with copy move forgery images of Media Integration and Communication Center Forgery (MICC-F2000) dataset for detecting and revealing the areas that have been tampered portion in the image, the image is sectioned into non overlapping blocks using Simple

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.

This work is related to the investigation of the effects of porous silicon (PSi) morphologies on the performance of plasmonic gold nanoparticles (Au-NPs) hot spot SERS sensors for the detection of amoxicillin molecules. Two Si wafers with different resistivity values of 10 and 100 Ω.cm were used to synthesize a PSi layer of pores- and mud-like structures, respectively, by pulsed photo chemical etching process. The hot spot SERS sensors were synthesized by incorporating the Au-NPs within the PSi morphologies of pores- and mud- like structures which are characterized by high density of nucleation sites. Plasmonic Au- NPs with different sizes and hot spot regions were incorporated into the porous structures by the ion reduction proces

This study aims to analyze spectra in real-time for λ Draconids, σ Hydrids, μ Virginid, and one sporadic meteor using spectroscopic chemical analysis and diagnose plasma parameters. Good-resolution spectroscopy and a CCD camera for meteor observation were used concurrently to examine the ablation spectra of these meteorites in situ. The Boltzmann and Lorentz methods were then used to determine the temperature and density of electrons, the length of Debye, and the frequency of plasma. Furthermore, spectra data can be analyzed and compared to data from other sources. Spectrum tests can be utilized to identify the chemical structure of meteorites' plasma.

This study was conducted to isolate and identify killer yeast Hanseniaspora uvarum from dates vinegar and measurement the ability of this yeast to produce killer toxin. The antimicrobial activity of the concentrated supernatant containing partially purified concentrated killer toxin was also detected against several pathogenic bacteria and yeast species, which includes two types of yeast Rhodotorula mucilaginosa and Candida tropicalis and four human pathogenic bacteria Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeurginosa. In addition, the antagonistic activity of examined yeast have been studied toward four types of fungi, where two are pathogenic