The systemic and resistant nature of metastatic castration-resistant prostate cancers (mCRPC) renders it largely incurable even after intensive multimodal therapy. Proliferation, survival, and epithelial-mesenchymal transition (EMT) are three fundamental events that are deeply linked to carcinogenesis.  Hence, it is necessary to find a new combination of several therapies, targeting those vital mechanisms without causing side effects. Significant research works have shown differential low expression of the metabolic Farnesoid X receptor (FXR) in primary and metastatic prostate cancer suggesting their importance in prostate pathogenesis. Obticholic acid (INT 747), a potent FXR agonist is widely used in primary biliary chola

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

This study investigated a novel application of forward osmosis using different types of draw solutions for oilfield produced water treatment from the East Baghdad oilfield affiliated to the Midland Oil Company (Iraq). Magnesium chloride (MgCl2) and magnesium sulfate (MgSO4) were used as draw solutions in forward osmosis process to evaluate their effectiveness. Experiments were conducted in a laboratory scale forward osmosis system with cellulose triacetate hollow fiber membrane. In this work, sodium chloride solution was used as a feed solution with a concentration of 76 g/L (same concentration as the East Baghdad oilfield produced water) and the applied external pressure on the feed solution side was 2 bar. The impact of draw solution (DS)

     This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being  0.66975075, 0.470