After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosphomolybdic acid (PMA) in a basic medium (pH 9.0). The resulting product absorbs light at λmax 750 nm. The colorimetric methods can be used either as sensors to detect the SEM by bare eye observation as little as 10 ppm and 2.0 ppm within 4−2 min or by spectrophotometry as the determination methods with linearity ranges 8.0−180 ppm and 0.5−30 ppm for the 1st and 2nd methods respectively. The developed methods were successfully applied to determine the SEM in the commercial bread products with a relative standard deviation (RSD) <3 %, <2 % and recovery of 94–103 %, 96–101 % for methods (1st and 2nd) respectively. The visual detection limits of the sensors can be used as a platform for SEM field-portable detection due to their lower limitations than the reported SEM in flour products, which opens the doors for on-site detection of SEM with instrument free.
The present study combines UV-Vis spectrophotometry and dispersive liquid-liquid microextraction (DLLME) for the preconcentration and determination of trace level clidinium bromide (Clid) in pharmaceutical preparation and real samples. The method is based on ion-pair formation between Clid and bromocresol green in aqueous solution using citrate buffer (pH = 3). The colored product was first extracted using a mixture of 800 µL acetonitrile and 300 µL chloroform solvents. Then, a spectrophotometric measurement of sediment phase was performed at λ = 420 nm. The important parameters affecting the efficiency of DLLME were optimized. Under the optimum conditions, the calibration graphs of standard -1 (Std.), drug, urine and serum were ranged
... Show MoreThe aim of this research was to study the concentrations of Uranium in the phosphorus fertilizers using Nuclear track detector (CR-39). Our present investigation is based on the study of 10 types samples for different kinds of phosphorus fertilizers which were available in the local market Some of them were Iraqi made and the others from different countries like, (Iran, Italy, Holland, Lebanon and Jordan) .. The result obtained shows that the Uranium concentration in phosphorus fertilizers samples varies from (3.59ppm) to(2.59ppm). Based on the radioactive concentration of Uranium in the samples all the results obtained between(3.59ppm) in the Iraqi super phosphate to (2.59ppm) in the mixture Iraqi phosphate fertilizer are withi
... Show MoreWith the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show MoreData mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
... Show MoreA field study was conducted on a sample of the public in Baghdad to study the audience's exposure to the television promotion of pharmaceutical products and their trends in order to determine the rate of exposure of the public to the television promotion of pharmaceutical products according to the theory of uses and rumors and to determine the public's attitudes towards television promotion of pharmaceutical products. A survey of (25) a questions was distributed to a sample of the audience of 150 people. The statistical program SPSS was used to unload the data and for the calculation of frequencies and percentages and correlation coefficients. The research reached several results, Most importantly, the television promotion is well receiv
... Show MoreData of multispectral satellite image (Landsat- 5 and Landsat-7) was used to monitoring the case of study area in the agricultural (extension and plant density), using ArcGIS program by the method of analysis (Soil adjusted vegetative Index). The data covers the selected area at west of Baghdad Government with a part of the Anbar and Karbala Government. Satellite image taken during the years 1990, 2001 and 2007. The scene of Satellite Image is consists of seven of spectral band for each satellite, Landsat-5(TM) thematic mapper for the year 1990, as well as satellite Landsat-7 (ETM+) Enhancement thematic mapper for the year 2001 and 2007. The results showed that in the period from 1990 to 2001 decreased land area exposed (bare) and increased
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