The study aimed to evaluate injuries and economic losses which caused by rose beetle Maladerainsanabilis (Brenske) on ornamental and fruit plants as introduced insect in Iraq during 2015 and determine infested host plants in addition to evaluate efficacy of pathogenic fungi Metarhiziumanisopiliae (1x10⁹ spore/ ml) and Beauvariabassiana (1x10⁸spore/ ml) in mortality of insect larvae in laboratory and field.The results showed that the insect was polyphagous infested many host plants (20 host plant)Which caused degradation and dead the plants through adult feeding on leaves and flower but large injury caused by larvae feeding on root plants which caused obligate dead to infested plant, the percentage mortality of rose plants 68.6%, pear 45% lantana camare 18.3%, apricot 15.1 and zizphus 1.7% during October 2016. Due to the number of larvae present around root plant, the insect preferred rose and pear plant which recorded high numbers of larvae compared the lowest number of larvae on ziziphus which least preferred. The results were confirmed that the employment of the Metarhiziumanisoplae and Beauveriabassiana formulation in the field to treatment the soil were not effective to causing mortality of the larvae because of the very high temperature during the experiments time. Although, using the same fungi in the laboratory afford efficiency when the formulations were sprayed directly on the larvae or on the soil. The directly treatments with B. bassianaand M. anisoplae were achieved very high mortality reached 100% after 32 and 42 day respectively. While when the formulations were sprayed on the soil the mortality was reached 100% after 63 day for both fungus.
TNF-α-induced osteoclastogenesis is central to post-menopausal and inflammatory bone loss, however, the effect of phytoestrogens on TNF-α-induced bone resorption has not been studied. The phytoestrogens genistein, daidzein, and coumestrol directly suppressed TNF-α-induced osteoclastogenesis and bone resorption. TRAP positive osteoclast formation and resorption area were significantly reduced by genistein (10(-7) M), daidzein (10(-5) M), and coumestrol (10(-7) M), which was prevented by the estrogen antagonist ICI 182,780. TRAP expression in mature TNF-α-induced osteoclasts was also significantly reduced by these phytoestrogen concentrations. In addition, in the presence of ICI 182,780 genistein and coumestrol (10(-5) -10(-6) M) augmente
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silver nanoparticle which synthesized by.
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This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators
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A theoretical analysis studied was performed to study the opacity broadening of spectral lines emitted from aluminum plasma produced by Nd-YLF laser. The plasma density was in the range 1028-1026 )) m-3 with length of plasma about ?300) m) , the opacity was studied as function of plasma density & principle quantum number. The results show that the opacity broadening increases as plasma density increases & decreases with the spacing between energy levels of emission spectral line.
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In the present study, free convection heat and mass transfer of fluid in a square packed bed enclosure is numerically investigated. For the considered geometrical shape, the left vertical wall of enclosure was assumed to be kept at high temperature and concentration while the opposite wall was kept at low temperature and concentration with insulating both the top and bottom walls of enclosure. The Brinkman– Forchheimer extended Darcy model was used to solve the momentum equations, while the energy equations for fluid and solid phases were solved by using the local thermal non-equilibrium (LTNE) model.Computations are performed for a range of the Darcy number from 10-5 to 10-1, the porosity from 0.5 to 0.9, and buoyancy ratio from -15 t
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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
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