In the present work the Buildup factor for gamma rays were studied in shields from epoxy reinforced by lead powder and by aluminum powder, for NaI(Tl) scintillation detector size ( ×? ), using two radioactive sources (Co-60 and Cs-137). The shields which are used (epoxy reinforced by lead powder with concentration (10-60)% and epoxy reinforced by aluminum powder with concentration (10-50)% by thick (6mm) and epoxy reinforced by lead powder with concentration (50%) with thick (2,4,6,8,10)mm. The experimental results show that: The linear absorption factor and Buildup factor increase with increase the concentration for the powders which used in reinforcement and high for aluminum powder than the lead powder and decrease with inc

Acinetobacter baumannii ability to form biofilm makes it to be opportunistic pathogen causing of nosocomial infections and to be good survivor in adverse environmental conditions including medical devices and hospital environments. Six isolates of A. baumannii were isolated from drinking water and tested to investigate biofilm formation capacity on three different type of abiotic surface, also several factors were examined such as hydrophobicity, PH and temperature. All A. baumannii isolates displayed a positive biofilm on congored aga test CRA (pigmented colonies with black color) and Christensen's test (adhesive layer of stained material to the inside surface of the tube).The obtained data of microbial adhesion to hydrocarbons assay (MATH

The aesthetic and technical expertise help  in producing the artistic work and achieving results in aesthetic formulations that reflect the aesthetic and  expressive dimensions and the reflective dimensions of the pottery, surpassing its traditions, asserting  its active presence in life, cherishing it  even when it  breaks  or get damaged   by employing techniques that are originated  from  the Japanese environment.

                       The research problem is to study how ( Kintsugi) technique and similar techniques are used to create  new rebirths of pottery piec

Identifying phenolic compounds in some genera belonging in the Amaranthaceae family by HPLC technique

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

Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to find the best bacteria to remove kerosene from soil. The active bacteria are isolated for kerosene degradation process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradation which is 88.5%. The optimum conditions of kerosene degradation by Klebsiella pneumonia sp. are pH5, 48hr incubation period, 35°C temperature and 10000ppm the best kerosene concentration. The results 10000ppm showed that the maximum kerosene degradation can reach 99.58% after 48 h of incubation. Higher Kerosene degradation which was 99.83% was obtained at pH5. Kerosene degradation was found to be maximum at 3

Isolated Bacteria from the roots of barley were studied; two stages of processes Isolated and screening were applied in order to nd the best bacteria to remove kerosene from soil. The acve bacteria are isolated for kerosene degradaon process. It has been found that Klebsiella pneumoniae sp. have the highest kerosene degradaon which is 88.5%. The opmum condions of kerosene degradaon by Klebsiella pneumonia sp. are pH5, 48hr incubaon period, 35°C temperature and 10000ppm the best kerosene concentraon. The results 10000ppm showed that the maximum kerosene degradaon can reach 99.58% aer 48 h of incubaon. Higher Kerosene degradaon which was 99.83% was obtained at pH5. Kerosene degradaon was found

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.