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

The goal of the research is to theoretically establish the variable of brilliant leadership and explain the importance of this variable and the philosophical orientation of researchers in taking it as an original variable in their research as an independent variable. The descriptive approach and theoretical framing of brilliant leadership were followed. We relied on secondary data represented by books, dissertations, dissertations, scientific research, and the information network (the Internet) as a tool for collecting data. The scientific value was represented by the importance of consolidating brilliant leadership and reviewing the most important things that were confirmed by the research and studies that dealt with this research.

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

Background: Inflammation of the brain parenchyma brought on by a virus is known as viral encephalitis. It coexists frequently with viral meningitis and is the most prevalent kind of encephalitis. Objectives: To throw light on viral encephalitis, its types, epidemiology, symptoms and complications. Results: Although it can affect people of all ages, viral infections are the most prevalent cause of viral encephalitis, which is typically seen in young children and old people. Arboviruses, rhabdoviruses, enteroviruses, herpesviruses, retroviruses, orthomyxoviruses, orthopneumoviruses, and coronaviruses are just a few of the viruses that have been known to cause encephalitis. Conclusion: As new viruses emerge, diagnostic techniques advan

The purpose of this article is to provide a comprehensive definition of corporate governance and to review the existing literature on the subject. The researchers examine various corporate governance theories, including agency theory, stakeholder theory, and resource-based theory. The study concludes by emphasizing that the primary goal of corporate governance theories is not to examine how managers govern but rather to analyze how governance operates in an company.

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

Background: To assess the alveolar bone crest level (ABCL) by Cone Beam Computed To-mography (CBCT) and to investigate several variables as predictors for the height of the alveolar bone in adolescents. Materials and methods: Age, sex, and ethnic groups were rec-orded for each patient. CBCT images were used to obtain measurements of the interproximal alveolar bone level from the cementoenamel junction (CEJ) to the alveolar crest. The highest measurement in each sextant was recorded along with any presence of a vertical bone defect or calculus. Results: Total of 720 measurements were recorded for 120 subjects. No vertical bony defects or calculus were observed radiographically. Statistically significant (P< 0.05) differences were observed be