Electrocoagulation is an electrochemical process of treating polluted water where sacrificial anode corrodes to produce active coagulant (usually aluminum or iron cations) into solution. Accompanying electrolytic reactions evolve gas (usually as hydrogen bubbles). The present study investigates the removal of phenol from water by this method. A glass tank with 1 liter volume and two electrodes were used to perform the experiments. The electrode connected to a D.C. power supply. The effect of various factors on the removal of phenol (initial phenol concentration, electrode size, electrodes gab, current density, pH and treatment time) were studied. The results indicated that the removal efficiency decreased as initial phenol concentration increased, the highest removal obtained at pH in the range (6-8), the removal enhanced with increasing electrode size and decreasing the gab between the electrodes. The optimum current density obtained at 221 A/m2.
A lower extracellular pH is one of the few well-documented physiological differences between tumour and normal tissues. On the other hand, elevated glutathione (GSH) level has been detected in many tumours compared with healthy surrounding tissues. The compound II: 3-(9H-purin-6-yl-thio) carbonothionyl methyl-8-oxo-7-(2-thiophen-2-yl) acetamido-5-thia-1-azabicyclo-4-octo-ene-carboxylic acid was a cephalothin derivative contain 6-mercaptopurine (6-MP). Compound II react with general base catalysis in slightly acidic pH or with sulfhydryl nucleophiles to release the chemotherapeutic drug 6-MP. The generation of compound II was accomplished following multistep reaction procedures. The structure of compound II and its intermediate was confir
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We can see the phenomena of small and medium-sized enterprises, by important and a new subject contemporary, thro related between important concept that develop and add. This research focused on the important concept of small and medium-sized enterprises, in public and privet sectors. small and medium-sized enterprises discrimination by large filer ratio in the especially at the first years when they started because of the limited managerial skills, financial recourses and marketing problems. On it they will creative new procedures. this research treatment the core issues about wakens local and international enterprises, so threat. the goals of this research are extended malty dimension concept o
... Show MoreSolubility problem of many of effective pharmaceutical molecules are still one of the major obstacle in theformulation of such molecules. Candesartan cilexetil (CC) is angiotensin II receptor antagonist with very low water solubility and this result in low and variable bioavailability. Self- emulsifying drug delivery system (SEDDS) showed promising result in overcoming solubility problem of many drug molecules. CC was prepared as SEDDS by using novel combination of two surfactants (tween 80 and cremophore EL) and tetraglycol as cosurfactant, in addition to the use of triacetin as oil. Different tests were performed in order to confirm the stability of the final product which includes thermodynamic study, determination of self-emulsificat
... Show MoreThe main objective of present work is to describe the feasibility of friction stir welding (FSW) for
joining of low carbon steel with dimensions (3 mm X 80 mm X 150 mm). A matrix (3×3) of welding
parameters (welding speed and tool rotational speed) was used to see influence of each parameter on
properties of welded joint .Series of (FSW) experiments were conducted using CNC milling machine
utilizing the wide range of rotational speed and transverse speed of the machine. Effect of welding
parameters on mechanical properties of weld joints were investigated using different mechanical tests
including (tensile and microhardness tests ). Micro structural change during (FSW) process was
studied and different welding zones
Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
... Show MoreSamples of Iraqi bentonitic sediments, representing local montmorillonite brought from Traifawi region near the Syrian border. Mineralogical the samples were characterized as low grade of Ca-smectite, particle size, chemical analysis, XRD, and BET surface area analyses of the samples were carried out to examine the structure of bentonite before and after acid activation. The goal is to prepare a bleaching earth for edible oil production. Iraqi Bentonite was beneficiated and activated by series of physical and chemical steps, using 4N & 6N concentration of hydrochloric acid and at a temperature of 70-80 ° C. Surface area and pore volume of the samples were determined to assess the bleaching power
This work deals with the preparation of a zeolite/polymer flat sheet membrane with hierarchical porosity and ion-exchange properties. The performance of the prepared membrane was examined by the removal of chromium ions from simulated wastewater. A NaY zeolite (crystal size of 745.8 nm) was prepared by conventional hydrothermal treatment and fabricated with polyethersulfone (15% PES) in dimethylformamide (DMF) to obtain an ion-exchange ultrafiltration membrane. The permeate flux was enhanced by increasing the zeolite content within the membrane texture indicating increasing the hydrophilicity of the prepared membranes and constructing a hierarchically porous system. A membrane contain
Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
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