Gum Arabic is a natural gummy exudate gained from the trees of Acacia species (Acacia senegal and Acacia seyal), Family: Fabaceae. Gum Arabic considers as a dietary fiber with a high percentage of carbohydrates and low protein content. Sugars arabinose and ribose were originally discovered and isolated from gum Arabic and it is representing the original source of these sugars. A gum emanation from trees occurs under stress conditions such as heat, poor soil fertility, drought, and injury. Mainly gum is produced in belt region of Africa, mainly Sudan, Chad, and Nigeria. In the food industry, it is used in confectionery; in the pharmaceutical industry, it is used as emulsifier, film coating and others. Traditionally the gum used for chronic renal failure, digestive discomfort, and others. Although gum Arabic considered as an inert substance, recent information demonstrated multiple pharmacological and medical effects, such as weight reduction, antihypertensive, antihyperlipidemic, anticoagulant, antibacterial, antidiabetic, anti-inflammatory, nephroprotective and other effects.
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
... Show MoreBackground: 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
... Show MoreDeep 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
... Show MoreThe outbreak of a current public health coronavirus 2019 disease is a causative agent of a serious acute respiratory syndrome and even death. COVID-19 has exposed to multi-suggested pharmaceutical agents to control this global disease. Baricitinib, a well-known antirheumatic agent, was one of them. This article reviews the likely pros and cons of baricitinib in attenuation of COVID-19 based on the mechanism of drug action as well as its pharmacokinetics. The inhibitory effect of baricitinib on receptor mediated endocytosis promoter, AKK1, and on JAK-STAT signaling pathway is benefacial in inhibition of both viral assembling and inflammation. Also, its pharmacokinetic has encouraged the physicians toward the drug
... Show MoreBoltzmann mach ine neural network bas been used to recognize the Arabic speech. Fast Fourier transl(>lmation algorithm has been used t() extract speciral 'features from an a caustic signal .
The spectral feature size is reduced by series of operations in
order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network.
The neural network recognized Arabic. After Boltzmann Machine Neura l network training the system with
... Show MorePersonification in Arab poetry is not confined to the abstract items in nature: it trespasses them to include more than that. We found after reviewing the anthologies of the poets tens of the personified items are full of human attributes - via personification- such as speaking, moving, feeling human feelings.. Personification formed a remarkable feature in the relationship between poets and war, which was clear in the Pre-Islamic poetry, because it occupied the minds of the ancient Arab mindset. The poets have envisioned war as ugly as a force that brings destruction and devastation. The paper aims at stating the position in which poets personified war with female tributes. Thus, it is impregnated, conceived, and produced birth like a w
... Show MoreThe present study examines the main points of differences in the subject of greetings between the English language and the Arabic language. From the review of the related literature on greetings in both languages, it is found that Arabic greeting formulas are more elaborate than the English greetings, because of the differences in the social customs and the Arabic traditions and the Arabic culture. It is also found that Arabic greetings carry a religious meaning basing on the Islamic principle of “the same or more so”, which might lead to untranslatable loopholes when rendered in English.
In this work , a hybrid scheme tor Arabic speech for the recognition
of the speaker verification is presented . The scheme is hybrid as utilizes the traditional digi tal signal processi ng and neural network . Kohonen neural network has been used as a recognizer tor speaker verification after extract spectral features from an acoustic signal by Fast Fourier Transformation Algorithm(FFT) .
The system was im plemented using a PENTIUM processor , I000
MHZ compatible and MS-dos 6.2 .
Abstract Purpose of research: The purpose of the article is to conduct a comparative analysis of the concept and types of puns in the Russian and Arabic languages. The main focus is on identifying similarities and differences in the definition of a pun, as well as analyzing its various types in both languages. The purpose of the study is to understand how puns are used to achieve comic or semantic effect in different cultural contexts. Methods: The study includes an analysis of literature providing information about puns in Russian and Arabic. For comparative analysis, methods were used to compare concepts, definitions and types of puns in both languages. The phonetic, semantic and syntactic aspects of the pun are considered, and cultural f
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