The study aimed to know the effect of the use alcoholic ethanol extraction of Boswellia Carterii In prolonging the period of preservation cooled ground meat in 4C for 6 days, it has been mixing ground meat with 150,300,450 mg/ml of alcoholic extract Consecutive, Where (0 was the control sample), All samples were stored separately for 0 , 3 , 6 days in Refrigerator temperature 4 C, Conducted by some microbial tests, Results have shown that mixing the ground meat with Boswellia Carterii extraction Led to prolong the storage of meat for 6 days at 4 C .and the Best result came when adding alcoholic ethanol extract of Boswellia Carterii by 450mg/ml Which Equal 0.9 g ,that reducing microbial load more higher than 150&300 mg/ml. All of thes

Eighty five samples were taken from patients suffering from pneumonia. Seventy-eight isolates were diagnosed as following: Staphylococcus aureus (23), klebsiella pneumoniae (29), Streptococcus pneumoniae (15), Serratia sp. (4), Haemophilus influenzae (4) and Pseudomonas aeruginosa (3). The clinical isolates were tested for antibiotics sensitivity. They appeared highly resistance to penicillin G and Ampicillin at percentage 89.7 and 84.6% respectly while the results showed highly sensitivity to streptomycin at percentege of (12.8%). To study the antibacterial activity of Alium sativum, Eucalyptus microtheca leaves and Cydonia oblonga seeds extracts, five multi resistant strains were used by using agar well diffusion and disk methods at c

Positive and negative parity states for 114Te have been studied applying the vibration al limit U(5) of Interacting boson model (IBM- 1 ) . The present results have shown their good agreement with experimental data in addition to the determination of the spin/parity of new energy levels are not assigned experimentally as the levels 0+2 and 5+1 and the levels 3"1 and 5-1 . Then back propagation multiLayer neural network used for positive and negative parity states for 114Te and shown their membership to the Vibration limit U(5) the network implemented by MATLAB system.

Steps were taken to obtain the Kojic acid crystals from local fungal isolation A. flavus WJF81 by separating the fermentation products from the fungus mycelium from the production plant at the centrifuge at a speed of 5000 cycles for 10 minutes. The extraction was followed by ethyl acetate then supernatant concentrate by using rotary evaporator, and dried with heat oven 37ºC. Long, yellowish, pristine acid crystals were obtained that examined the optical microscope with a magnification force of 10x and 40x. The melting point of kojic acid was determined between 152.9-153.5 °C Results of the diagnosis of Kojic acid by applying High pressure liquid chromatography HPLC technique showed that the acid was at one peak, which was close to the

A multistep synthesis was established for the preparation of a new vanillic acid-1, 2, 4-1triazole-3-thiol conjugate (4). Finally, several aromatized aldehydes reacted with compound (4) to produce Schiff bases derivatives (5–11). The purpose of this research is to prepare new vanillic acid derivatives with 1, 2, 4-triazole-3-thiol heterocyclic ring structures and to evaluate their antimicrobial activity in a preliminary assessment. Fourier-transform infrared (FT-IR) and proton nuclear magnetic resonance spectroscopy (¹H-NMR) were used to verify the structures of the newly synthesized compounds. all the final synthesized compounds (

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

Background: Painful elbow joint over the lateral epicondyle especially with resisted wrist extension are common signs of lateral epicondyle tendinopathy, also called tennis elbow.

Objective: To evaluate the clinical outcome of local platelet rich plasma (PRP) injection in patients with chronic tennis elbow compared with a steroid (Depomedrol 40 mg) injection.

Methods: A total of 88 patients with chronic tennis elbow were treated at Al-Kindy Teaching Hospital and private clinics. All patients had chronic pain for about 24 weeks or more and had failed first line treatment. The patients dividing into two groups, Group A injected with PRP (n = 44), and group B injected with d

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%.