Fatty Acid Methyl Ester (FAME) produced from biomass offers several advantages such as renewability and sustainability. The typical production process of FAME is accompanied by various impurities such as alcohol, soap, glycerol, and the spent catalyst. Therefore, the most challenging part of the FAME production is the purification process. In this work, a novel application of bulk liquid membrane (BLM) developed from conventional solvent extraction methods was investigated for the removal of glycerol from FAME. The extraction and stripping processes are combined into a single system, allowing for simultaneous solvent recovery whereby low-cost quaternary ammonium salt-glycerol-based deep eutectic solvent (DES) is used as the membrane phase.

The aim of this study was ‎the‎ discrimination of Salmonella‎‎ isolated from chicken and their feed ‎and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, ‎including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five ‎different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, ‎and serology were used for bacterial identification. Random amplified polymorphic ‎DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships ‎among Salmonella‎‎ isolates. The isolation rate of Salmonella‎‎ spp. was 21.1% (61/289). While the ‎water samples constituted the highest rate (30.4%), a rate of

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

This research deals with the attitude of oil press towards oil industry in the world and the extent of their concerns with the stages of oil industry relating to the abundance of oil and natural gas, as it is an international strategic and complementary industry. The researcher uses the survey method for content analysis of the initial article and the press news for two: years (2011-2012). The results if the study are as follows
1- Oil press is concerned with developing and the stages of the Arabic oil industry in the interest of OAPEC in the first place.
2- It is concerned with exploring, extracting, and marketing oil in the first place, then with refining operations in refineries and petrochemical plants in the second place, an