A new method is characterized by simplicity, accuracy and speed for determination of Oxonuim ion in ionisable inorganic acid such as hydrochloric (0.1 - 10) ,Sulphuric ( 0.1 - 6 ),nitric ( 0.1 - 10 ), perchloric ( 0.1 - 7 ), acetic (0.1 - 100 ) and phosphoric ( 0.1 - 30 ) ( mMol.L-1 )acids. By continuous flow injection analysis. The proposed method was based on generation of bromine from the Bro-3-Br-- H3O+. Bromine reacts with fluorescein to quenches the fluorescence . A sample volume no.1 (31μl) and no.2 (35μl) were used with flow rate of 0.95 mL.min-1 using H2O line no.1as carrier stream and 1.3 mL.min-1 using fluorescein sodium salt line no.2. Linear regression of the concentration ( mMol.L-1 ) Vs quenched fluorescence gives a correlation coefficient of ( 89.33 -99.72 ) for all studies of acids in various parameters were optimized. The proposed method was applied successfully for the determination of Oxonium ion in commercial samples. Using paired t-test between the newly developed method and classical method; shows that there were no significant differences between either methods. On this basis the new method can be accepted as an alternative analytical method for determination of Oxonium ion in commercial samples.
A simple, accurate and sensitive spectrophotometric way is used to determine Bisacodyl in pure and pharmaceutical preparations. The proposed method depends on using 2,4-Dinitrophenylhydrazine as chromogenic reagent . The method was based on the oxidative coupling reaction of Bisacodyl with 2,4-Dinitrophenylhydrazine with Sodium periodate in the presence of sodium hydroxide as alkaline media to form red water soluble dye product , that has a maximum absorption at ?max 522nm . Beer ,s law is obeyed in the concentration of (2.00–20.00) ?g.ml -1 .The molar absorptivity is (6505) L.mol-1.cm-1,a sandall sensitivity of(0.0555) ?g.cm-2), correlation coefficient of (0.9970) , Limitof detection (LOD) (0.0312 ?g.ml-1), limit of Quantitation (LOQ) (
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Several industrial wastewater streams may contain heavy metal ions, which must be effectively removal
before the discharge or reuse of treated waters could take place. In this paper, the removal of copper( II)
by foam flotation from dilute aqueous solutions was investigated at laboratory scale. The effects of
various parameters such as pH, collector and frother concentrations, initial copper concentration, air flow
rate, hole diameter of the gas distributor, and NaCl addition were tested in a bubble column of 6 cm inside
diameter and 120 cm height. Sodium dodecylsulfate (SDS) and Hexadecyl trimethyl ammonium bromide
(HTAB) were used as anionic and cationic surfactant, respectively. Ethanol was used as frothers and the
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The present work deals with five species of parasitic Hymenoptera belonging to Pteromalidae, Eupelmidae and Eurytornidae which have been reared from brachid beetles. A new species, Eurytoma irakensis is described and the species, Bruchocida orientalis Crawford is recorded for the first time from Iraq.
Two specie's of terrnitls are described as new to science from Iraq Amitermes corpnlentus sp. n. and Anacanthotermes savvensis sp. n., with two figures.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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This study aimed at some of the criteria used to determine the form of the river basins, and exposed the need to modify some of its limitations. In which, the generalization of the elongation and roundness ratio coefficient criterion was modified, which was set in a range between (0-1). This range goes beyond determining the form of the basin, which gives it an elongated or rounded feature, and the ratio has been modified by making it more detailed and accurate in giving the basin a specific form, not only a general characteristic. So, we reached a standard for each of the basins' forms regarding the results of the elongation and circularity ratios. Thus, circular is (1-0.8), and square is (between 0.8-0.6), the blade or oval form is (0.6-0
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A procedure for the mutual derivatization and determination of thymol and Dapsone was developed and validated in this study. Dapsone was used as the derivatizing agent for the determination of thymol, and thymol was used as the derivatizing agent for the determination of Dapsone. An optimization study was performed for the derivatization reaction; i.e., the diazonium coupling reaction. Linear regression calibration plots for thymol and Dapsone in the direct reaction were constructed at 460 nm, within the concentration range of 0.3-7 μg ml-1 for thymol and 0.3-4 μg ml-1 for Dapsone, with limits of detection 0.086 and 0.053 μg ml-1, respectively. Corresponding plots for the cloud point extraction of thymol and Dapsone were constructed
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