A biostimulant is any microorganism or substance used to enhance the efficiency of nutrition, tolerance to abiotic stress and/or quality traits of crops, depending on its contents from nutrients. Plant biostimulants like honey bee (HB) and silymarin (Sm) are a strategic trend for managing stressed crops by promoting nutritional and hormonal balance, regulating osmotic protectors, antioxidants, and genetic potential, reflecting plant growth and productivity. We applied diluted honey bee (HB) and silymarin-enriched honey bee (HB- Sm) as foliar nourishment to investigate their improving influences on growth, yield, nutritional and hormonal balance, various osmoprotectant levels, different components of antioxidant system, and genetic p

     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

Abstract

   Mitoxantrone is an antitumor agent used in the treatment of breast and prostate cancer, acute leukemia, lymphoma, and also in the treatment of multiple sclerosis due to its immunosuppressive properties. The mitoxantrone's cardiotoxicity is irreversible, dose-dependent, and it may occur years after treatment. Zinc is considered as an essential mineral for cell division and the synthesis of DNA and protein; furthermore, such mineral has an important role in states of cardiovascular diseases; and may have protective effects in coronary artery disease and cardiomyopathy.

Objective: The current study is designed to investigate effects of two different doses of zinc sulfat

To investigate the effects of losartan and enalapril on serum uric acid in hypertensive patients with metabolic syndrome, one hundred and twenty six newly diagnosed mild hypertensive patients, having markers of metabolic syndrome included  in the study. The patients were divided into two groups. Group 1 (60 patients) was given losartan (50 mg/ day) and group 2 (66 patients)  enalapril (20 mg/ day) for a duration of 2 months. A control group of seventy apparently healthy individuals were included. Metabolic syndrome was diagnosed according to diagnostic criteria of metabolic syndrome related to the American National Cholesterol Education Program-Adult Treatment Panel III. Serum uric acid levels were measured bef

Abstract: non-alcoholic fatty liver disease (NAFLD) is one of the widespread chronic liver diseases; it is ranging from simple fat buildup in the liver (steatosis) to non-alcoholic steatohepatitis (NASH) presence of inflammation and hepatocyte injury.                                                                                                                                        &nb

Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param