The present study was carried out to assay the bioaccumulation of ammonia ,nitrite ,nitrate in fresh water and the concentration of heavy metals (Lead, Cupper, Cadmium, Manganes and Zinc) in water and tissues of Tilapia niloticus selected from El-marryotia canal (one of the river Nile ramification in Al-Giza city) in Egypt, samples were collected during the period of July to October 2011 to determine water safety for human consumption and the hazardous effect of these metals on the histopathology of selected tissues and organs of fish. Two samples were collected from two locations of canal, pH of water samples were measured and the concentration of ammonia, nitrate and nitrite were determined in these samples. Twenty Tilapia were also collected from different locations of the canal, One gram of liver, abdominal and dorsal muscles tissue from each fish were taken for determination of lead, Cupper, Cadmium, manganese and Zinc in the selected tissues. Specimens of gills, muscles, liver, kidney and intestine from each fish were fixed in 10% buffered neutral formalin, and processed for pathological study. The results revealed that water samples polluted with ammonia, nitrite and nitrate respectively.,significant differences were recorded in concentration of Mn and Zn in both water samples. The mean concentration of Pb was 0.216±0.0108, 0.204±0.009 and Mn 0.901±0.041, 0.73±0.003 in both water samples which was above the World Health Organization safety standard, the results indicated that water were polluted with both two heavy metals. More concentration of Pb1.362±0.0657 was noted in liver of fish , concentration of Pb (1.2±0.062), Cd (0.01.2±0.062) was the highest in abdominal muscles and lowest in the remaining tissues of fish , the mean concentration of Cu (0.6.2±0.032) was higher in abdominal muscle , Mn (0.54±0.02) and Zn (1,19.2±0.054) was more concentrated in dorsal muscles and all the heavy metals studied gave results with the permissible limits in fish tissue recorded by the standards of WHO. The main histopathological changes observed were edema and sloughing of lamellar epithelia in gills of fish. In liver, it was noticed vacuolation of most hepatocytes with nuclear pyknosis . The findings in kidneys exhibited the presence of periglomerular edema and vacuolar degeneration of most of renal tubules .The fish muscle showed degeneration and edema with focal areas of necrosis of some muscle fibres.
Protection of the oil pipelineswhich extracted from the wells was found to shut the well and prevent the leakage of oil when broken using safety valve. This valve is automatically activated by loss of pressure between the well and pipelines, which take the pressure, signal from hydraulic pressure sensor through pressure control valve which has constant or variable value but it is regulated manually. The manual regulatory process requires the presence of monitoring workers continuously near the wells which are always found in remote areas. In this paper, a smart system has been proposed that work with proportional pressure control valve and also electronic pressure sensor through Arduino controller, which is programmed in a way that satisfie
... Show MoreThe CuInSe2 (CIS) nanocrystals are synthesized by arrested precipitation from molecular precursors are added to a hot solvent with organic cap- ping ligands to control nanocrystal formation and growth. CIS thin films deposited onto glass substrate by spray - coating, then selenized in Ar- atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as -deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illumination. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CIS have the chalcopyrite structure as the major phase with a preferred orientation along (112) direction and the atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2
Case Report.
To present a case of a previous complicated mandibular orthognathic surgery that aimed to setback the mandible in a female cleft lip and palate (CLP) patient, which led to bone necrosis on one side with subsequent severe mandibular deviation and facial asymmetry. We additionally reviewed the previous reports of similar complications, the pathophysiology and the factors that could lead to this dreadful result.
A 27-year-old female patient presented with a severe dentofacial deformity secondary to a complicated bilateral sagittal spli
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
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Experimental investigation for small horizontal portable wind turbine (SHPWT) of NACA-44, BP-44, and NACA-63, BP-63 profiles under laboratory conditions at different wind velocity range of (3.7-5.8 m/s) achieved in present work. Experimental data tabulated for 2, 3, 4, and 6- bladed rotor of both profiles within range of blade pitch angles . A mathematical model formulated and computer Code for MATLAB software developed. The least-squares regression is used to fit experimental data. As the majority of previous works have been presented for large scale wind turbines, the aims were to present the performance of (SHPWT) and also to make a comparisons between both profiles to conclude which is the best performance. The overall efficiency and el
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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