Field experiment was conducted to test the effect of saline water and fertilizers rate on Pisum sativum L. plants . Treatments of the experiment included two levels of water salinity (2, 7 dSm-1) as a main plot and three levels of potash fertilization K2SO4 (44%K) namely 150 control, 300 and 450 kg/Donum as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-¹ caused a significant decrease in K and P contents specially in the upper parts of the plants , the percentage of the K increased (2.80%) under 2 dSm-¹of irrigation water and 300 kg/ donum fertilizer rate in the upper leaves, However K decreased(1.10%) in lower leaves under 7 dSm-¹ and 300 kg/donum fertilizer. while P increased in pods under same water salinity but with 150kg/ donum potash fertilizer. although P decreased( 0. 3 %) in pods under 7 dSm-¹ salinity water with 150 kg/donum fertilizer. However the results showed irrigation with 7 dSm-¹ saline water and 150kg/ donum fertilizer increased Ca, Mg and Na percentage ( 3.1 ,0.45 ,1.19 % ) in the roots of plants respectively , the lowest Ca ,Mg percentage was in pods of plants irrigated with 7 dSm-¹ saline water and fertilized with 150kg/ donum (0.39,0.05%), beside Na lowest percentage was ( 0.16 %) in upper leaves after using 2 dSm-¹ saline water and fertilized with 300kg/ donum. Accordingly, conclusion could be made that potassium fertilization may reduce the inhibitory effect of increasing salinity of irrigation water on pea.
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
... Show MoreThe goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.
The complete genome sequence of bacteriophage VPUSM 8 against O1 El Tor Inaba
The aim of this research is to identify the availability of visual thinking skills in the chemistry textbook scheduled for the third intermediate grade for the academic year (2020-2021) in the Republic of Iraq. The study sample consisted of all (85) images contained in the chemistry course for the third intermediate grade, which are (85) form using the curriculum. Analytical descriptive A list of visual thinking skills was prepared, and the unit of form was adopted as a unit of analysis and repetition as a unit of counting, and frequencies and percentages were used for statistical treatment, and validity and reliability were calculated. And using the Holste equation. The following results were reached: The skill
... Show MoreThe present work introduces, external morphological study of the leafhopper Neoalitarus
fenestratus Herrich-Schäeffer (Deltocephalinae:Oposiini), particularly the male genitalia
which were dissected and illustrated.
Objective(s): The study aims Finding relationship between UTI and demographic variable include: child's age, child's gender, if males are circumcised or not, child's order in his family, father's level of education, mother's level of education, place of residence and family socioeconomic status. Methodology: A descriptive study was conducted on students of primary schools for both sexes, for the period from 19th. February 2014 through to 4th March 2014. A selected sample from two steps the first stage is to choose a school by a stratified- cluster sample, getting schools that have been selected (12) sch
Aim of the study: Using surface roughness and tensile bond strength tests, the objective of this investigation was to ascertain the impact of laser surface modification on the binding strength of injectable thermoplastic acrylic denture base material to acrylic-based soft-liner material. Materials and methods: Acrylic base soft liner material was bonded to injectable thermoplastic acrylic resin (Deflex). Forty specimens were created (20 disc, 20 dumbbells) 10 of each specimen type as control specimens, and 10 were treated with nano pulse Nd: YAG laser. The data were analyzed using the Kruskal-Wallis test and unpaired t-test (a=.05) and the roughness test was performed utilizing a double column universal test machine. Results: Compar
... Show MoreThe goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy
Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal. The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in
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