This Study is conducted to evaluate effects of (leaves, fruits) powder and (oil, alcohol) extract of Coriander (Coriandrum sativum) plant on some biological and physiological aspects of House fly, Musca domestica at laboratory conditions. Result show that these preparations caused biological effects represented in high dead percentage in second instar, fed on different concentrations of food treated with them reached to 27.6, 55.3 at concentration 20% of leaf and fruit powder respectively and 67.3, 77.2% at 10% of oil and alcohol extract of fruit, respectively. Furthermore, study also show reduction in pupation and adults emergence percentage. However, leafs powder had slighter effect than powder and extract of fruit of tested plant. The study show physiological effects in treated larvae such as molting failure at subsequent molt to larvae , pupa or to adult, also morphological aberration represented in small size, dark pigment, reduce age and folding of the adult wings. In almost cases, the higher concentration the more morphogenetic aberration. This study leads us to conclude that coriander had chemical compounds which played a negative role in some biological and physiological aspects of house fly.
In this paper, some relations between the flows and the Enveloping Semi-group were studied. It allows to associate some properties on the topological compactification to any pointed flows. These relations enable us to study a number of the properties of the principles of flows corresponding with using algebric properties. Also in this paper proofs to some theorems of these relations are given.
In this paper, the concept of normalized duality mapping has introduced in real convex modular spaces. Then, some of its properties have shown which allow dealing with results related to the concept of uniformly smooth convex real modular spaces. For multivalued mappings defined on these spaces, the convergence of a two-step type iterative sequence to a fixed point is proved
In this paper, a new class of non-convex functions called semi strongly (
The current study presents an experimental investigation of heat transfer and flow characteristic for subcooled flow boiling of deionized water in the microchannel heat sink. The test section consisted of a single microchannel having 300μm wide nominal dimensions and 300μm height (hydraulic diameter of 300μm). The test section formed of oxygen-free copper with 72mm length and 12mm width. Experimental operation conditions spanned the heat flux (78-800) kW/m2, mass flux (1700 and 2100) kg/m2.s at 31˚C subcooled inlet temperature. The boiling heat transfer coefficient is measured and compared with existing correlations. Also, the experimental pressure drop is measured and compared with microscale p
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Contents IJPAM: Volume 116, No. 3 (2017)
Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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