In this study, experimental mortar combinations with 1% micro steel fibers, were examined to create geopolymer mortars. To test the effect of the fibers on the mortar's resistance, the geopolymer mortar was designed with various proportions of more environmentally friendly materials fly ash and slag. The percentage of fly ash by weight was 50, 60, and 70% of the slag. The best results were obtained when a 50:50 ratio of fly ash and slag were mixed with 1% micro steel fibers. The results showed that the mixtures containing fibers performed better in the considered tests (toughness index, ductility index, and resilience index). In the impact resistance test, the mixture contained 50% fly ash by weight of the slag with a temperature of

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Schiff bases were prepared prepared Baaan NMR to some elements of which have contributed to the results of different methods in diagnosis prove structural formulas of compounds prepared

This work deals with preparation of Sulfated Zirconia catalyst (SZ) for isomerization of n-hexane model and refinery light naphtha, as well as enhanced the role of promoters to get the target with the mild condition, stability, and to prevent formation of coke precursors on strong acidic sites of the catalyst. The prepared SZ catalysts were characterization by fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer –Emmett-Teller (BET) surface area analysis, Thermogravimetric Analysis (TGA), Scanning Electron Microscope (SEM) and atomic force microscopy (AFM) Analyzer. The results illustrate that the maximum conversion and selectivity for n-hexane isomerization with Ni-WSZ and operating temperature of 150 °C

As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According