The study was conducted to estimate the economic losses caused by insect mole cricket Gryllotalpa gryllotalpa on some agricultural crops and Potato tubers in collage of Agriculture- Abu Ghraib season 2012-2013. Study showed Mole cricket caused percentage of infestation in spring potato tubers variety Luciana reached to 11.61% and the percentage of loss in weight of tubers reached 18.88%. The study showed that addition of animal manure (organic fertilizer) to the soil when planting potatoes in the autumn increased the incidence of infestation and the number of tunnels caused by mole cricket which led to from increased economic losses. When matured potato tubers were left for a longer period in the soil percentage of infestation by mole cricket was increased and resulted in an increasing of the economic losses on potato tubers. It was evident from the study that the injury by mole cricket different plant depends on the growth of plants and the development of radical totaling stage where the focus of infection insect during the month of April and the percentage of lost plants 22.5 % on cowpeas, sunflower 20.5 % and okra 18 %, watermelon 17.7 % and cucumbers 15.34% During the month of May and June the percussion pumpkin 14 % and some bush 24 % plants and the lack of tunnels insect during July and August, plants and emerged injury on the autumnal cucumber plants during September and October and the peas and some jungle plants during January and February and March, and that there is significant correlation between the number of tunnels the insect and the percentage of loss in different economic hosts.
The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in
... Show MoreA study was carried out to analysis of some heavy metals in nine different types of vinegar, belong to Grape, Apple, Synthetic White, Date, Hawthorn, Garlic, Cactus, Pomegranate and Ginger vinegar, which are locally available in Iraqi folk medicine markets. The concentrations of heavy metals in the studied samples including, Cr, Mg, Mn, Zn, Fe, Cd, Ni, Pb and Ag, were determining by using flame atomic absorption spectrophotometry. All data were subjected to statistical analysis by calculating accuracy, precision and correlation coefficient for each concentrations level. The results indicate that Ni was recorded the highest concentration in all studied samples except, Ginger and cactus vinegar, each one receded the highest concentration valu
... Show MoreIn the current research, the work concentrated on studying the effect of curvature of solar parabolic trough solar collector on wind loading coefficients and dynamic response of solar collector. The response of collector to the aerodynamic loading was estimated numerically and experimentally. The curvature of most public parabolic trough solar collectors was investigated and compared. The dynamic response of solar collector due to wind loading was investigated by using numerical solution of fluid-structure interaction concept. The experimental work was done to verify the numerical results and shows good agreement with numerical results. The numerical results were obtained by using finite element software package (ANSYS 14). It was found
... Show MoreSeeds of Nigella sativa were sown in containers containing 15kg Loamy soil. The seeds were divided before sewing into two groups. The first group was soaked with ordinary tap water end the second group was treated with magnetized water for 24hrs. The irrigation process was completed until 75% of capacity field with two types of water (tap water of magnetized water with three replications).The magnetized water was obtained from special electric device designed for this purposeRecorded measurements (plants height, the number of branches/ plant, dry weight ofplant, number of flowers, 1000 seed weight) during the harvest period.Results indicated that the seed group which was treated with magnetized water was more significant than the one which
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This Study aimed to studying the effect of Volatile oil extracted from the leaves of Myrtus communis on the growth and activities of the following types of bacteria: Staphylococcus aureus, Streptococcus pyogenes, Klebsilla pneumoniae, Pseudomonas aeruginosa, and the yeast Candida albicans. The results showed an inhibitory effect of the oil on both the growth and activity of the tested microbes. This was reflected by the minimum inhibitory concentration (MIC) of Staphylococcus aureus, Streptococcus pyogenes, Klebsilla pneumoniae, Pseudomonas aeruginosa which was: (2.5, 1.25, and 2.5,5 % respectively), and the yeast (5) %. Also, the Minimum bactericidal concentration (MBC) to the bacteria mentioned above was (5, 2.5,5,10 % respectivel
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Two field experiments were conducted during the spring season 2020 in Karbala governorate to study the effect of irrigation systems, irrigation intervals, biofertilizers and polymers on some characteristics of vegetative growth and potato production. The results showed that there were significant differences in the values of the average plant height due to the effect of the double interference between the irrigation system and the improvers, The height of potato plant under any irrigation system was superior when adding conditioners compared to the control treatment, as it reached 48.56, 58.00 and 64.33cm when adding polymer, biofertilizer, and polymers+ biofertilizers, respectively compared with the control treatment of 44.64cm in the surf
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Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
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