Commercial graphite (CGT) powder was used as an adsorbent surface for cationic dye, Janus green (JG), from aqueous solutions. This study aims to highlight the practical significance of using inexpensive CGT as an efficient adsorbent for the removal of JG dye from industrial wastewater. CGT was characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, and X-ray diffraction. The adsorption process was investigated by examining parameters like the weight of the adsorbent, contact time, and temperature. Pseudo-second-order kinetic (PSO), pseudo-first-order, and intraparticle diffusion were used for analyzing the kinetic data. JG dye's adsorption kinetics fit the PSO kinetic model well (R2= 0.999). Furthermo

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

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and t

This paper discusses the method for determining the permeability values of Tertiary Reservoir in Ajeel field (Jeribe, dhiban, Euphrates) units and this study is very important to determine the permeability values that it is needed to detect the economic value of oil in Tertiary Formation. This study based on core data from nine wells and log data from twelve wells. The wells are AJ-1, AJ-4, AJ-6, AJ-7, AJ-10, AJ-12, AJ-13, AJ-14, AJ-15, AJ-22, AJ-25, and AJ-54, but we have chosen three wells (AJ4, AJ6, and AJ10) to study in this paper. Three methods are used for this work and this study indicates that one of the best way of obtaining permeability is the Neural network method because the values of permeability obtained be

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.