One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

 Fusobacterium are compulsory anaerobic gram-negative bacteria, long thin with pointed ends, it causes several illnesses to humans like pocket lesion gingivitis and periodontal disease; therefore our study is constructed on molecular identification and detection of the fadA gene which is responsible for bacterial biofilm formation. In this study, 10.2% Fusobacterium spp. were isolated from pocket lesion gingivitis. The isolates underwent identification depending on several tests under anaerobic conditions and biochemical reactions. All isolates were sensitive to Imipenem (IPM₁₀) 42.7mm/disk, Ciprofloxacin (CIP₁₀) 27.2mm/disk and Erythromycin (E₁₅) 25mm/disk, respectively. 100% of

Yersinia enterocolitica has ranked a third among the pathogens that most frequently cause gastrointestinal disorders transmitted to humans through food materials, especially contaminated meats. The meat infected with Yersinia enterocolitica had no change in apparent texture or smell. The aim of this research is to survey the frequency of Y. enterocolitica in ovine meat, compare their ratio of infection between the season, To carry out this study (125) samples of local ovine meat were collected by random sampling from the middle region of Iraq. The samples were divided into two groups steak and mince, then many microbiological tests (culture, & staining, biochemical Tests Api 20E, Vitik 2 and species-specific PCR amplicon for 16S RNA gene) w

This study was designed for isolation and molecular identification of Nontuberculous Mycobacterium (NTM) from fish during the period between October and December 2017 from Karbla province, Iraq. This study included 200 fresh fish samples from four different species including Spondyliosoma cantharus, Liza abu, Carassius carassius and Cyprinuscarpio. Three samples of each fish were taken including gills, muscles and all internal organs. The samples were processed by decontamination, concentration of 4% sodium hydroxide, and 0.1 ml of sediment was streaking on Löwenstein Johnson (LJ) media; then the bacterial cultures were incubated at 28-30 °C for 3days up to 4 weeks and suspected colonies were stained with acid fast stain to confir

Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacter