The free electron laser is considered one of these important and advanced inventions because it provides a laser beam within various wavelengths of the electromagnetic spectrum. In any laser system device, several parameters must be available on which the efficiency and performance of the laser system are dependent. The Pierce parameter is one of the important parameters in measuring the performance quality of the free electron laser. In this paper, the simulation results were obtained using the MATLAB program to show the important effect of the Pierce parameter on the performance of the free electron laser system. The simulation results showed that the values of the Pierce parameter ranged between (0.01 - 0.03) for the laser beam with long wavelengths, while it ranged between (0.001-0.0001) for the short wavelengths. The results showed an increase in the efficiency values of the free electron laser system with increasing the values of the Pierce parameter, which represents the ratio between the saturation power and the power of the electron; therefore, it can be used as a specific threshold to measure the efficiency of the laser system. Additionally, the simulation of the Pierce parameter has a direct relation to the small signal gain per unit length.
Commercial, industrial, and military activity, largely in the 19th and 20th centuries, have led to environmental pollution that can threaten human health and ecosystem function, liquid gas petroleum (LPG) products are the major sources of energy for industry and daily life that cause environmental contamination during various stages of production, transportation, refining and use. Screening of bacterial isolate by using clear zone techniques and biomass and optical density. Results revealed that isolate Burkholdaria cepatia showed a high ability for hydrocarbons biodegradation and this isolate identified depending on morphological cultural, gram stain, microscopic features, biochemical tests, and VITEK2 compact. In this study,
... Show MoreThis study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).
... Show MoreThe dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreS Khalifa E, N Adil A, AS Mazin M…, 2008
Automated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health
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