Ultraviolet spectrophotometric studies for antibiotic (amino glycoside) derivatives including, Neomycin, Streptomycin, Gentamycin and Kanamycin with special reagents, which are benzoyl chloride; benzene sulfonyl chloride, toluenesulfonyl chloride and phthalic anhydride were made. Amino glycosides derivatives were followed through measurements of the ultraviolet absorbance (A) from which the absorptivity (ε) of the complexes was deduced and molar absorbances using Ultraviolet for products and calculate the number of reagents molecule that combine to amino glycosides.

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

This study synthesized zeolite 4A, and hierarchical composite structure consisting of zeolite 4A- carbon were successfully prepared. Hydrothermal method was used to grow a layer of zeolite 4A over porous carbon surfaces to enhance mass transfer and increase surface area of zeolite. The products then were used to remove radioactive cesium¹³⁷Cs from liquid wastewater. Iraqi dates leaves midribs (DM) were used as locally available agricultural waste to prepare low- cost porous carbon, using carbonization method in tubular furnace at 900C for two hours. Hierarchical porous structures including zeolite are prepared by mechanically activating the carbon surface via Ultrasonicating nanoparticles suspension of ground zeolite type 4A.F

      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m³  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45^o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45^o instelled  in the bottom of TESB of vertical SC. The TESB was

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Abstract: Choosing suitable artificial teeth for partially edentulous patients and arranging these teeth in a way to look natural is difficult. An important factor in dentures construction is the mesiodistal width of anterior teeth, because a denture would not appearance natural if artificial teeth are of incorrect size. While for a successful orthodontic treatment, mesiodeistal width of teeth is important for space analysis and for establishing proper occlusion. The aim of this study is to determine the correlation between the average mesiodistal width of anterior and posterior teeth in male and female Iraqi population. 40 Iraqi subjects with normal occlusion participated in this study. Mesiodistal measurement of all teeth was carried out

The aim of the research is to prepare motor sense exercises for developing motor and physiological abilities of backstroke and forward stroke service skill in badminton and investigated their effect. The research is adopted the experimental method with two groups design. The sample of the research is 8 players (13-15 years). The sample is divided into two groups of 4 players for each group. Both groups are exposed to pre and post tests, after the experimented were finished, the results are statically analyzed. The results have showed that there are positive developing abilities of motor and physiological of service skill in badminton. Finally, these prepared exercises are recommended for developing players’ abilities in badminton.