Background: Gotu Kola (Centella asiatica) has been used as a traditional medicine for many years to cure different kinds of diseases. Studies have been reported that Gotu Kola extracts might be used as a cure for oral diseases such as periodontal disease. In the present study, Gotu Kola leaves extracted with water will be used to evaluate its effect on some microorganisms living in the human saliva using minimum inhibitory concentration (MIC) method. Material and Method:Gotu Kola fresh leaves extract have been used with water as a solvent, a rotary evaporator was used to separate the solvent from the extract. The following microorganisms: Streptococci, Lactobacilli, and Staphylococcus aureus have been isolated fromthe Saliva of ten voluntee

The exchanges in various fields,like economics, science, culture, etc., have been enhanced unceasingly among different countries around the world in the twenty-first century, thus, the university graduate who masters one foreign language does not meet the need of the labor market in most countries.So, many universities began to develop new programs to cultivate students who can use more foreign languages to serve the intercultural communication. At the same time, there is more scientific research emerged which is related to the relationship between the second and third languages. This humble research seeks to explain the relevant concepts and analyze the real data collected from Shanghai International Studies University in China, to expl

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

تتبلور فكرة البحث حول التوصل لنوع العلاقة التي تربط التعليم الالكتروني خلال جائحة كورونا برفع المهارات التكنولوجية للأساتذة والطلاب، وتبرز أهمية البحث في ان نجاح الوصول لهذه العلاقة يمكن الإفادة منها في تغيير منهجية تطوير المهارات التكنولوجية مستقبلا وذلك باعتماد الجوانب التطبيقية الفعلية بدلا من الدورات وورش العمل والتي قد لا تضاهي الطريقة العملية في رفع مستوى المهارات المختلفة سواء التدريسية او التكنو

The numerical response of Chrysoperla mutata MacLachlan was achieved by exposing the larvae of the predators to various densities of dubas nymphs Ommatissus lybicus DeBerg. Survival rate of predators’ larvae and adults emergence increased with increasing consumption . Repriductive response of predator was highly correlated with the amount of food consumed (+0.996).

In despite of the expansion of using the dummy variables as a explanatory variables, but their using as a dependent variables is still limited, and the reason of that may be return to may problems when using dummy variables as a dependent variables. the study aimed to using the quality Response Models to Measuring Efficiency of cows farms by random sample including (19) farm from (Abi gherak district). The study estimating the transcendental logarithmic production function by using stochastic frontier Analysis (SFA) to interpret the relation between the return achieved from the cows farms as a dependent variables and each of labor and capital as an independent variables. the function indicates that increasing in labor by (100%) will

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog