Several million tons of solid waste are produced each year as a result of construction and demolition activities around the world, and brick waste is one of the most widely wastes. Recently, there has been growing number in studies that conducted on using of recycling brick waste (RBW) to produce environmentally friendly concrete. The use of brick waste (BW) as potential partial cement or aggregate replacement materials is summarized in this review where the performance is discussed in the form of the mechanical strength and properties that related to durability of  concrete. It was found that, because the pozzolanic activity of clay brick powder, it can be utilized as substitute for cement in replacement level up t

Several million tons of solid waste are produced each year as a result of construction and demolition activities around the world, and brick waste is one of the most widely wastes. Recently, there has been growing number in studies that conducted on using of recycling brick waste (RBW) to produce environmentally friendly concrete. The use of brick waste (BW) as potential partial cement or aggregate replacement materials is summarized in this review where the performance is discussed in the form of the mechanical strength and properties that related to durability of  concrete. It was found that, because the pozzolanic activity of clay brick powder, it can be utilized as substitute for cement in replacement level up to 10%. Whereas,

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Kamil, S.H. 2024. Effects of Aqueous and Alcoholic Extracts of Lemongrass, Cymbopogon citratus on Some Biological Aspects of the Fig Moth, Ephestia cautella. Arab Journal of Plant Protection, 42(3): 377-381. https://doi.org/10.22268/AJPP-001245 This study evaluated the effects of aqueous and ethanolic extracts of lemongrass on the third instar larvae of the date moth Ephestia cautella Walker (Lepidoptera: Pyralidae). The results obtained showed that there were toxic effects of aqueous extract, which produced the highest mortality rate of 43.35% at 5% concentration72 hours after treatment, whereas the lowest mortality rate of 17% was obtained at 0.5% concentration, 72 hours after treatment. The LC50 was 0.082%. The results indicated

n this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the types of the kernel boundary func

Wastewater recycling for non-potable uses has gained significant attention to mitigate the high pressure on freshwater resources. This requires using a sustainable technique to treat natural municipal wastewater as an alternative to conventional methods, especially in arid and semi-arid rural areas. One of the promising techniques applied to satisfy the objective of wastewater reuse is the constructed wetlands (CWs) which have been used extensively in most countries worldwide through the last decades. The present study introduces a significant review of the definition, classification, and components of CWs, identifying the mechanisms controlling the removal process within such units. Vertical, horizontal, and hybrid CWs

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when