Anticyclone of synoptic studies that influence weather and climate of Iraq, The aim of
the study is to clarify the effect variation of repetition of Anticyclone and effect on thermal
characteristic in Iraq were pressure level has been analyzed (1000) millibars and that because
of pressure level is the closet to the earth surface and the clarity of climatic phenomenon
based on a systematic analysis of synoptic seeking maps and observation and (12:00)
according to timing GMT for five climatic stations which is (Mosul, Kirkuk, Baghdad, Rutba,
and Basra) and so far three consecutive climatic cycles which is first climatic cycle for period
(1986-1976). and second climatic cycle for period (1997-1987) and third climatic cycle for
period (2008-1998).It become clear from the result. That study reach, It become clear that a clear depression
in repetition of Anticyclone from climatic session to another climatic session followed by
three climatic session and on all level of study area stations. The contrast repetition of
Anticyclone is one of the factors that help to raise the temperature due to air stillness and the
clarity of the sky that led to the concentration of pollutant and slow in their transition to other
areas. These pollutant increase rising temperatures air textures to the surface of earth because
it absorb ground radiation at night and reflect it to surface of earth as well as the clarity of the
sky during the day helped to increase the amount of solar radiation to the earth it is found
rising temperatures Siberian is the station (Mosul, Kirkuk, Rutba) for October month for
second climatic cycle for period (1997-1987) and third for period (2008-1998) as well as
increase temperatures maximum rate with increasing repetition rate of high semi-orbital in the
stations Mosul, Kirkuk, and Rutba area for each month of January and October in the second
climatic session for period (1997- 19987) as well as in the third climatic cycle for period
(2008-1998) in all stations of studying area for months of January and march and October and
the high rate of maximum temperature with high rate repetition of European Anticyclone in
all stations of studying area in the second climatic cycle for period(1997-1987) 0f January,
march, October months, Notice increase repetition rate of Siberian Anticyclone in the month
of October for two climatic cycle second and third as well as Basra station recorded increase
in minimum temperature rate with increase repetition rate of high semi-orbital in the second
climatic cycle for period (1997-1987) for January as well as in all stations of studying area in
the third climatic cycle for period (2008-1998) for march also in stations of Mosul, Kirkuk,
Basra for two climatic cycle the second and the third for October. And high rate of minimum
temperature with high repetition rate of European Anticyclone in the stations of Kirkuk and
Basra in January for the second climatic cycle period (1997-1987) as well as recorded in
march month in stations of Mosul and Kirkuk, Basra for two climatic cycle the second and
third also in October for the second climatic cycle for stations of studying area.
Catalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne
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In this work, enhancement to the fluorescence characteristics of laser dye solutions hosting highly-pure titanium dioxide nanoparticles as random gain media. This was achieved by coating two opposite sides of the cells containing these media with nanostructured thin films of highly-pure titanium dioxide. Two laser dyes; Rhodamine B and Coumarin 102, were used to prepare solutions in hexanol and methanol, respectively, as hosts for the nanoparticles. The nanoparticles and thin films were prepared by dc reactive magnetron sputtering technique. The enhancement was observed by the narrowing of fluorescence linewidth as well as by increasing the fluorescence intensity. These parameters were compared to those of the dye only and the dye solution
... Show MoreIn this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aerugi
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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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A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
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Adsorption of lead ions from wastewater by native agricultural waste, precisely tea waste. After the activation and carbonization of tea waste, there was a substantial improvement in surface area and other physical characteristics which include density, bulk density, and porosity. FTIR analysis indicates that the functional groups in tea waste adsorbent are aromatic and carboxylic. It can be concluded that the tea waste could be a good sorbent for the removal of Lead ions from wastewater. Different dosages of the adsorbents were used in the batch studies. A random series of experiments indicated a removal degree efficiency of lead reaching (95 %) at 5 ppm optimum concentration, with adsorbents R2 =97.75% for tea. Three mo
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