In this study, ceramic purifier (CP) was produced from a mixture of Iraqi raw materials. This ceramic mixture was prepared using Bentonite as a Clay, Porcelanite as a Silica, and Limestone as a flux. The produced ceramic filter was formed by semi-dry compressing method and was fired at 1200 C?. Physical properties of the produced CP were measured. A hydraulic test rig was constructed to study the hydraulic conductivity of the produced CP. The average hydraulic conductivity of the produced CP was 55 times that of commercial types of ceramic filters. The mineral composition of the produced ceramics was found by X-Ray tests. Tests results showed that all of the produced ceramics filters composed mainly of low Cristobalte and Tridoymite in addi

This work includes synthesis of sugar tetrazole derivative, D-ribose reacted with acetone in the presence of sulfuric acid H2SO4 to give 2, 3-O-isopropylidene-D-ribose (1). The Aldol condensation of (1) with formaldehyde in methanolic K2CO3 solution gave 2-hydroxymethyl (2, 3-O-isopropylidene-D-ribose)(2). Which was tosylated by Tosyl chloride in pyridine to yield compound (3), SN2 reaction of (3) with sodium cyanide in DMSO afforded compound (4). The [2+ 3] cycloaddition reaction of (4) with sodium azide gave the targeted compound (5). All prepared compounds have been characterized by: TLC, Specific rotation, Microelemental analysis and [FTIR and 1 H NMR spectroscopy]

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

Ultraviolet photodetectors have been widely utilized in several applications, such as advanced communication, ozone sensing, air purification, flame detection, etc. Gallium nitride and its compound semiconductors have been promising candidates in photodetection applications. Unlike polar gallium nitride-based optoelectronics, non-polar gallium nitride-based optoelectronics have gained huge attention due to the piezoelectric and spontaneous polarization effect–induced quantum confined-stark effect being eliminated. In turn, non-polar gallium nitride-based photodetectors portray higher efficiency and faster response compared to the polar growth direction. To date, however, a systematic literature review of non-polar gallium nitride-