Local food samples investigated for the presence of pathogenic bacteria. Hash meat sample was used to isolate Escherichia coli and chicken meat (poultry) was used to isolate Salmonella typhi. Biochemical tests and API20E system used in order to identify these isolates. Two natural vinegar samples (dates & apple cider) were used in order to study its antibacterial activity against the two tested bacteria. Disc diffusion method was used, the results showed that two vinegar samples have antibacterial activity against the two tested bacteria. Date vinegar showed inhibition zone 19mm against E. coli & 9mm against S. typhi, while Apple cider vinegar showed diameter of inhibition zone 20mm against S. typhi and 13mm against E. coli, also the results showed that control (water) have no antibacterial activity against the two tested bacteria.
Isolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin. Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicill
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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The objective behind this work was to find out the bacteriological profile of post burn infections in wound. The study was carried out from December 2010 to February 2011 at the Burns Unit of Al –Kindy Hospital and Al-Yarmook Hospital in Baghdad. Sixty burn patients have been investigated for bacterial profile of burn wound infections. Specimens were collected in the form of wound swabs. The organisms were isolated and identified by standard microbiological methods. Antimicrobial susceptibility test has been done by ATB-PSE5 kit(BioMereiux). Pseudomonas aeruginosa 35(58.3 %) was found to be the most common isolate followed by Klebsiella pneumonae 10(16.6%), Staphylococcus aureus 7(10%). ,E.coli 3(5%), Proteus merabilis 1(1.6 %), others 2
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