Doxorubicin (DOX) is an efficient antineoplastic agent with a broad antitumor spectrum; however, doxorubicin-associated cardiotoxic adverse effect through oxidative damage and apoptosis limits its clinical application. Cafestol (Caf) is a naturally occurring diterpene in unfiltered coffee with unique antioxidant, antimutagenic, and anti-inflammatory activities by activating the Nrf2 pathway. The present study aimed to investigate the potential chemoprotective effect of cafestol on DOX-induced cardiotoxicity in rats. Wistar albino rats of both sexes were administered cafestol (5 mg/kg/day) for 14 consecutive days by oral gavage alone or with doxorubicin which was injected as a single dose (15 mg/kg intraperitoneally at day 14) to i

The two objectives of the current research are :-

1. Uncover the views and opinions of the students of Artistic Education Department about the relation between educational novelty and its relation with visual . 
2. Identifying the capabilities of the students of artistic education department .

            The society of the research is the  fourth class students of artistic education department -  College of Fine Arts  ( 83 students from both sexes ) .  It was chosen ( 60 ) students sample of  from both sexes by the researcher in order to conduct test upon them .The researcher has adopted descr

YouTube is not just a platform that individuals share, upload, comment on videos; teachers and educators can utilize it to the best maximum so that students can have benefits. This study aims at investigating how active and influential YouTube can be in the educational process and how it is beneficial for language teachers to enhance the skills of students. The study demonstrates different theoretical frameworks that tackle the employment of technology to enhance the learning/teaching process. It relies on the strategies of Berk (2009) for using multimedia media, video clips in particular to develop the abilities of teachers for using technology in classrooms. To achieve the objective of the study, the researchers develop a questionnair

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod