This study aimed to make an inventory of leguminous plants for the purpose of identifying the plants that were collected over long periods and stored in the herbarium of Iraq Natural History Museum. It was found that the herbarium contains a large and varied number of plants from different parts of Iraq and in different and varied environments. It was collected and arranged according to a specific system in the herbarium to remain an important source for all graduate students and researchers to take advantage of these plants. Also, the flowering and fruiting periods of these plants in Iraq were recorded for different regions. Most of these plants begin to flower in the spring and thrive in fields and farms.

In this study, a total of 209 individuals of leeches were collected from Al-Hindyia River / Babil Province. 116 individuals were identified as Erpobdella octaculata (Linnaeus, 1758), 50 individuals as Erpobdella punctata (Leidy,1870) and  43 individuals as Hemiclepsis marginata (Müller, 1774).  Four samples were collected monthly during a period from February to June 2018. Some physical and chemical water properties were also examined, including air and water temperature, potential of hydrogen pH, Electrical Conductivity EC, Total Dissolved Solid TDS, Dissolved Oxygen DO, and the Biological Oxygen Demand BOD₅.  Air and water temperature were r

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