The bacterial contamination of lipsticks and face cream may become a great important matter in the medical laboratories. The present study was designed to determine the types of bacterial contamination in the face cream and lipsticks of undergraduate students. Also, the study aimed to determine the sensitivity of the isolated bacteria against many antibacterial agents. The study included 190 swabs samples from 190 face cream and lipsticks samples of the females’ students from five departments in the Medical Technology Institute, Almansour, Middle Technical University were collected in February 2018. The swab samples were collected with sterile condition and cultured on enriched Blood agar and MacConkey agar. Serial dilutions were made up

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

In recent years, there has been a significant increase in research demonstrating the new and diverse uses of non-thermal food processing technologies, including more efficient mixing and blending processes, faster energy and mass transfer, lower temperature and selective extraction, reduced thermal and concentration gradients, reduced equipment size, faster response to extraction control, faster start-up, increased production, and a reduction in the number of steps in preparation and processing. Applications of ultrasound technology have indicated that this technology has a promising and significant future in the food industry and preservation, and there is a wide scope for its use due to the higher purity of final products and the

One hundred forty three of Klebsiellapneumoniae isolates had been collected from some hospitals in Baghdad city. The isolates were taken from different clinical specimens.Antimicrobial susceptibility test was carried out towards fifteen antimicrobial agents by using Vitek2 system with Antimicrobial susceptibility test cards. The results of antibiogram showed that the local isolates were possess highly resistance towards most antimicrobial agents under study. The high resistance wastoAmpicillin while the low resistance was to Imipenem.Two methods were used for detection of Extended Spectrum Beta Lactamases (ESBLs) production; first methods by using of Vitek2 system,thesecondmethods by using of polymerase chain reaction (PCR) technique to dis

Out of 150 different specimens, 67 S. aureus isolate were isolated. However, 16sRNA gene was located only in 60 isolates. Moreover, mecA gene was located in 48 isolates; thereby MRSA covered 80% of all S. aureus isolates. Of considerable interest, pvl gene was detected in only six isolates (10%). Hence, the present work emphasizes the notion suggested that pvl is not an indicative of CA-MRSA.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d