The significant shortage of usable water resources necessitated the creation of safe and non-polluting ways to sterilize water and rehabilitate it for use. The aim of the present study was to examine the ability of using a gliding arc discharge to inactivate bacteria in water. Three types of Bacteria satisfactory were used to pollute water which are Escherichia coli (Gram-negative), Staphylococcus aurous (Gram-positive) and salmonella (Gram-negative). A DC power supply 12V at 100 Hz frequency was employed to produce plasma. pH of water is measured gradually during the plasma treatment process. Contaminated water treated by gliding arc discharge at steadying the gas flow rate (1.5 l/min) and changing the exposure time of the polluted water to the plasma during periods of 10, 20 and 30 min.The bacteria which used show different responses when expose to produced plasma, most of them inactivated when treated with plasma for 30minutes.That’s means Survival rate decreased with treatment time. Results show that gliding arc plasma is a powerful and green tool to treatment water without generating any byproducts.
Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo
... Show MoreStrong and ∆-convergence for a two-step iteration process utilizing asymptotically nonexpansive and total asymptotically nonexpansive noneslf mappings in the CAT(0) spaces have been studied. As well, several strong convergence theorems under semi-compact and condition (M) have been proved. Our results improve and extend numerous familiar results from the existing literature.
In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern
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