Psidium guajava, belonging to the Myrtaceae family, thrives in tropical and subtropical regions worldwide. This important tropical fruit finds widespread cultivation in countries like India, Indonesia, Syria, Pakistan, Bangladesh, and South America. Throughout its various parts, including fruits, leaves, and barks, guava boasts a rich reservoir of bioactive compounds that have been traditionally utilized as folkloric herbal medicines, offering numerous therapeutic applications. Within guava, an extensive array of Various compounds with antioxidative properties and phytochemical constituents are present, including essential oils, polysaccharides, minerals, vitamins, enzymes, triterpenoids, alkaloids, steroids, glycosides, tannins, flavonoids, and saponins. Notably, different components of the plant, comprising leaves and fruits, contribute to a spectrum of medicinal benefits. These encompass antimicrobial potency and potential anti-cancer properties. This study Investigates the phytochemical constituent and pharmacological activity of Guava by using previous studies and reports to collect more information about the guava plant. versatile properties extend to various therapeutic domains. The fruit has showcased its potential in domains like antidiabetic, antidiarrheal, hepatoprotective, anticancer, antioxidant, anti-inflammatory, antimicrobial, anti-allergy, and anti-plasmodial effects. Both guava leaves and fruits have been historically employed to address an array of conditions, including gastroenteritis, hypertension, diabetes, dental caries, and pain relief. While guava's pharmacological attributes are well-recognized, also all parts of guava have many phytochemical constituents. This review study shows the most important phytochemical constituents and pharmacological properties, it is vital to emphasize the need for further research. Enhanced understanding of the main mechanisms of action and the possible health advantages associated with guava necessitates continued investigation.
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
... Show MoreIn this study, pebble bed as an absorber and storage material was placed in a south facing, flat plate air-type solar collector at fixed tilt angle of (45°). The effect of this material and differ- ent parameters on collector efficiency has been investigated experimentally and
theoretically. Two operation modes were employed to study the performance of the solar air heater. An inte- grated mode of continuous operation of the system during the period of (11:00 am – 3:00 pm) and non-integrated mode in which the system stored the solar energy through the day then used the stored energy during the period of (3:00 pm – 8:00 pm). The results of parametric study in case of continuous operating showed that the maximum average temperatur
Background: Knowledge about the prevalence and distribution of pathologies in a particular location is important when a differential diagnosis is being formulated. The aim of this study was to describe the prevalence and the clinicopathological features of odontogenic cysts and tumors affecting the maxilla and to discuss the unusual presentation of those lesions within maxillary sinus.
Materials and Methods: A multicenter retrospective analysis was performed on pathology archives of patients who were diagnosed with maxillary odontogenic cysts and tumors from 2010 to 2020. Data were collected with respect to age, gender and location.
Result: A total of 384 cases was identified, 320 (83.3%) cases were diagnosed as odontogenic
... Show MoreDBN Rashid, Talent Development & Excellence, 2020
