Pathogenic microorganisms from hospitals, communities, and the environment remain great threats to human health. The increasing concern about antibiotic resistance has also necessitated the search for robust alternatives. Therefore, this study aims to isolate, screen and evaluate the antibiotic susceptibility of Pseudomonas aeruginosa isolated from a soil sample taken from northern, western and eastern parts of Kelana Jaya Lake against four antibiotics (gentamycin, tetracycline, ampicillin, and penicillin) on a Mueller-Hinton Agar media plate. Pseudomonas identification was done by using API 20 kit. Disc diffusion was employed as well as the oxidase test. From the positive oxidase result, the isolated bacteria were identified as Burkhold

Pollen morphology of 4 species (A. aucheri , A. auriculata, A. caucasica, A. nova) belonging to the genus Arabis L. in Iraq was examined by light microscope and scanning electron microscope to determine the significance of pollen features as a taxonomic characters. The results showed pollen grains of the species were monades, homopolar, tricolpate, and with medium size, but the species varied in shapes (polar and equatorial view), colpus length and width, exine thickness and exine ornamentation. Pollen colors were brown convert to brownish yellow.

Nineteenth century Gothic literature was deeply concerned with the threats against masculinity. Perhaps one of the most important changes that happened at that time was the emergence of the New Woman model which posed a great threat against masculinity and the male role in the Victorian society. Bram Stoker’s Dracula (1897) portrays female characters who embody this transition in female roles from the domestic wife to the New Woman. This paper focuses on the female characters Mina Murray and Lucy Westenra, their roles in their society, and the different fates they face at the end of the novel, with special focus on Mina’s transformation to the model of the New Woman.

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

The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ

Three isolated bacteria were examined to remove heavy metals from the industrial wastewater of the Diala State Company of Electrical Industries, Diyala-Iraq. The isolated bacteria were identified as Pseudomonas aeruginosa, Escherichia coli and Sulfate Reducing Bacteria (SRB). The three isolates were used as an adsorption factor for different concentrations of Lead and Copper (100, 150, and 200 ppm.), in order to examine the adsorption efficiency of these isolates. In addition, the effect of three factors on heavy metals adsorption were examined; temperature (25, 30, and 37 ?C), pH (3 and 4.5) and contact time (2 and 24 hrs). The results showed that the highest level of lead adsorption was obtained at 37 ?C by E. coli, P, aerugenosa and