A field experiment was carried out in Horticulture Department / Collage of Agricultur e/University of Baghdad to study influence of adding ascorbic acid(asa) and bread yeast extract in snap bean cv.primel under irrigation with saline water using sodium chloride salt (NaCl) during spr ing season of 2016 .A factorial experiment using Randomized Complete Block Design( RCBD) with three replications wereconducted . The first factor includes three treatments of salinity which were tap water ( S0), 4ds.m-1(S1) and 8ds.m-1 (S2) . The second factor includes three treatments which were control treatment without any adding (C) ,ascorbic acid 0.3g.l-1( A ) and yeast extract 12g.l -1( Y ). Results showed significant and gradually decreases in all studied traits of vegetative growth , yield , leaves content of prolien and rhizobia viability by increasing salinity level. The superiority of yeast extract ( Y ) adding was observed in root nodules/plant ,dry weight/plant, pods number/plant, pod weight, pods yield/plant,prolien content and rhizobia viability while highest value observed in both of plant height and leaf area due to ascorbic acid .The correlatio ns among all the studied traits were significant and positive except in prolien content with other traits were negative and sig nificant .
The aim of this study was to isolate and identify the cyanobacterium Scytonema hofmanni Var. calcicolum from the domestic drinking tanks as a new record in Iraqi drinking water. Scytonema hofmanni var. calcicolum, a filamentous freshwater cyanobacterium (blue-green alga). This alga was isolated from the walls of the domestic plastic water tanks in Al- karkh/ Baghdad city on July 2014. The sampling was performed by collecting three samples from this tanks, the three examined samples microscopically revealed the dominance of this cyanobacterium as unialgal in the studied samples. The results showed this alga has the ability to tolerate high temperature up to 42 Cº and very low light intensity inside the tanks which up to 10 μE/m²/s.
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro
Visualization of water flow around different bluff bodies at different Reynolds number ranging (1505 - 2492) was realized by designing and building a test rig which contains an open channel capable to ensure water velocity range (4-8cm/s) in this channel. Hydrogen bubbles generated from the ionized water using DC power supply are visualized by a light source and photographed by a digital camera. Flow pattern around a circular disk of (3.6cm) diameter and (3mm) thickness, a sphere of (3.8cm) diameter and a cylinder of
(3.2cm) diameter and (10cm) length are studied qualitatively. Parameters of the vortex ring generated in the wake region of the disk and the separation angle of water stream lines from the surface of the sphere are plott
Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.
Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Direct measurements of drag force on two interacting particles arranged in the longitudinal direction for particle Reynolds numbers varying from J O to 103 are conducted using a micro-force measurement system. The effect of the interparticle distance and Reynolds number on the drag forces is examined. An empirical equation is obtained to describe the effect of the interparticle distance (l/d) on the dimensionless drag.