The antibacterial effect of (Eruca sativa) extract was evaluated by an in vitro study testing the growth of various Gram-Positive and Gram-Negative bacteria . The bactericidal activity of this extract was analyzed by serial dilution in tubes. This study,found that Gram-Negative and Gram-Positive bacteria susceptible to very low eruca concentrations. On the other hand, Gram-positive bacteria were more susceptible than Gram-negative bacteria, the minimal bactericidal concentration of Gram-positive bacteria was 5 mg ml-1 but minimal bactericidal concentration of Gram-negative bacteria was 10 mg ml-1 that mean duble inhibation concentration of Gram-positive bacteria . this study suggest that Eruca sativa leaves have inhibation effect on Gra

A total of 50 fertile human hydatid cases {33(66%) females and (34%) males}, obtained from Al-Ramadi public Hospital during the period from December 2003 to July 2004 were examined to study any bacterial infections. The specimens were obtained from hydatid fluid and then cultured on appropriate culture media to distinguish some species of bacteria which resulted in obtaining: Staphylococcus aureus (18%), Pseudomonas aeruginosa(12%), Escherichia coli(6%) and Streptococcus pneumonia (4%). These bacteria were confirmed by isolation from interacyst fluid and blood culture technique. The possible routs of infection may be through blood, biliary ducts and bronchioles .The selectivity permeable of the cyst wall may be absent and that may allow

Endophytic bacteria produced analogous secondary metabolites of their hosts. Similarly, the ability to generate antioxidants is not an exception. Dragon scales (Pyrrosia piloselloides), an epiphytic plant of the Polypodiaceae family, are frequently overlooked. This research aims to isolate antioxidant-producing bacteria from dragon-scale fern leaves. The antioxidant activities were tested after the extraction procedure using ethanolic extract. Bacteria were characterized and selected as candidates for antioxidant production by screening for the production of total phenolic compounds. Antioxidant levels were determined utilizing the ABTS, FRAP, and DPPH techniques. The preliminary findings of the entire phenolic compound test rev

Some microorganisms can produce nanocellulose, which is known as bacterial nanocellulose (BNC); the most active bacterial producer is acetic acid bacteria (AAB), which is a gram-negative, motile and obligate aerobic belongs to the family Acetobacteraceae. Bacterial nanocellulose has excellent attention in medical (surgical domain), industrial and pharmaceutical fields because of its flexible properties, characteristics and advantages. So, in this study, the AAB (5AC) isolate was isolated from apple vinegar. The production of BNC was performed by using a natural medium called palm dates liquid medium, the produced bacterial Cellulose was purified by using the sodium hydroxide method; it was observed that the wet weight of the BNC was a

Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face m

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.

Plagiarism Detection Systems play an important role in revealing instances of a plagiarism act, especially in the educational sector with scientific documents and papers. The idea of plagiarism is that when any content is copied without permission or citation from the author. To detect such activities, it is necessary to have extensive information about plagiarism forms and classes. Thanks to the developed tools and methods it is possible to reveal many types of plagiarism. The development of the Information and Communication Technologies (ICT) and the availability of the online scientific documents lead to the ease of access to these documents. With the availability of many software text editors, plagiarism detections becomes a critical

Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and

Making the data secure is more and more concerned in the communication era. This research is an attempt to make a more secured information message by using both encryption and steganography. The encryption phase is done with dynamic DNA complementary rules while DNA addition rules are done with secret key where both are based on the canny edge detection point of the cover image. The hiding phase is done after dividing the cover image into 8 blocks, the blocks that are used for hiding selected in reverse order exception the edge points. The experiments result shows that the method is reliable with high value in PSNR

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co