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.

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Objective: The research aims to clarify the natural factors of the Tanjero River Basin. The Tanjero River Basin is located within the complex region in terms of topography in northeastern Iraq, eastern Iraqi Kurdistan region, and southwest of Sulaymaniyah Governorate. It is bordered on the eastern side by the Shahrazur Plain, the Sourin Mountains, and the Kweiza and Azmar Heights. On the western side, it is bordered by the Bernan mountain range, and on the northern side it is adjacent to the starting point of the Doula Rut Heights and Birah Mah Karun Mountain, and it is surrounded from the south by Darbandikhan Lake administratively.   Methodology: The current research relied on the descriptive and analytical approach in describing

As an alternative to Ordinary Portland Cement (OPC), the alkali-activated binders have been developed with better technical characteristics and more extended durability. The Alkali-Activated Iraqi Natural Pozzolans (AANP) could produce geopolymer cementation building materials and make them ecologically acceptable. The primary advantage of geopolymer cement is that it has a lower environmental effect that contributes to it. The engineering characteristics of geopolymer concrete produced using activated Iraqi natural Pozzolan are summarized in this research. The mechanical properties, modulus of elasticity, and ultrasonic pulse velocity of various concrete mixes were determined via experimental study. The impact of essential variables like w

Resulted in scientific and technological developments to the emergence of changes in the educational process and methods of teaching modern formats commensurate with the level of mental retardation. Which called for educational institutions, including the University of Baghdad / College of Fine Arts to urge and guide researchers to study and follow-up of recent developments in the educational process in order to develop in the fine arts in general and technical education in particular being play an important role in achieving educational goals. The educational methods of modern educational require effort-intensive and advanced for the development of technical skills among students, and thus worked researcher to employ computer technology

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This