AA Noaimi, IRAQI JOURNAL OF COMMUNITY MEDICINE, 2013 - Cited by 1

The study aims to investigate the antimicrobial activity of propolis obtained from different regions of Iraq compared with that of propolis obtained from Iran. Samples were investigated for their antimicrobial activity against Staphylococcus aureus, Pseudomonas aeruginosa, Eschericha coli, Klebsiella pneumoniae, Bacillus cereus , Staphylococcus epidermidis and Candida albicans using standard antimicrobial assays. Marked variations in the antimicrobial activity of the different propolis samples were observed, the method of extraction selected gives the highest antimicrobial activity and the best alcohol concentration using in the extraction of propolis , then the crude extract of propolis showed synergistic effect with some antibiotics in

The Role of the Deubiquitylase MYSM1 During Alphavirus Infection Amer Nubgan The members of the genus Alphavirus are positive-sense RNA viruses and it is one of two within the family Togaviridae. Most alphaviruses are predominantly transmitted to susceptible vertebrates by a mosquito vector. Alphavirus disease in humans can be severely debilitating, and depending on the particular viral species, infection may result in encephalitis and possibly life threatening symptoms. Chikungunya virus (CHIKV) is the aetiological agent represents a substantial health burden to affected populations, with clinical symptoms that include severe joint and muscle pain, rashes, and fever, as well as prolonged periods of disability in some patients. In recent

This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used