Development of a precise and delicate reaction has been acquired for the determination of vancomycin hydrochloride using batch and cloud point extraction (CPE) methods. The first method is based on the formation of azo dye as a result of diazotized dapsone coupled with vancomycin HCl (VAN) in a basic medium. The sensitivity of this reaction was enhanced by utilizing a nonionic surfactant (Triton X-114) and the cloud point extraction technique (second method). The azo dye formed was extracted into the surfactant-rich phase, dissolved in ethanol and detected at λ_max 440 nm spectrophotometrically. The reaction was investigated using both batch and CPE methods (with and without extraction), and a simple comparison between the two

Societies developed throughout history with the development of life technology, that ideas presented by the contemporary art have been crystallized. The development included all the artistic fields such as the dramatic arts which depend on many effects and elements that led to the completion of the structure of the theater show. Scenography is considered one of the most important elements that the theatre show depends on such as the decoration, lighting, sound effects, costumes and accessories. The research addressed the following question: what are the characteristics and traits of scenography in the theatre show?
The research importance has become clear because it sheds lights on the characteristics of scenography in the Iraqi thea

The aim of this study was extraction of jojoba oil using different solvents. A mixture of waterhexane and water-ethanol are used as solvents to extract jojoba oil in a batch extraction process and compared with a pure solvent extraction process. The effects of particle size of crushed seeds, solvent-to-water ratio and time on jojoba oil extraction were investigated. The best recovery of oil was obtained at the boiling temperature of the solvent and four hour of extraction time. When seed particle size was 0.45 mm and a pure ethanol was used (45% yield of oil extraction), whereas, it was 40% yield of oil at 25% water-hexane mixture. It was revealed that the water-ethanol and water-hexane mixtures have an effect on the oil extraction yield. T

The extraction of iron from aqueous chloride media in presence of aluminum was studied at different kinds of extractants(cyclohexanone, tributyl phosphate, diethyl ketone), different values of normality (pH of the feed solution), agitation time, agitation speed, operating temperature, phase ratio (O/A), iron concentration in the feed, and extractant concentration]. The stripping of iron from organic solutions was also studied at different values of normality (pH of the strip solution) and phase ratio (A/O). Atomic absorption spectrophotometer was used to measure the concentration of iron and aluminum in the aqueous phase throughout the experiments.The best values of extraction coefficient and stripping coefficient are obtained under the

Background: The surgical extraction of impacted third molar usually results in postoperative inflammation manifested as pain, facial swelling and trismus which may cause deterioration in the patient’s quality of life. Methods: This randomized controlled study included 56 patients indicated for surgical extraction of IMTM under local anesthesia. These patients were randomly assigned into two groups: a study group that included patients who received Tibrolin® postoperatively and a control group that did not. The predictor variable was whether to use SET or not. Pain measured by the pain numerical rating scale (NRS), facial swelling, and the degree of trismus were the outcome variables. The Arabic version of the Oral Health Impact P

In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

Since the beginning of the last century, the competition for water resources has intensified dramatically, especially between countries that have no agreements in place for water resources that they share. Such is the situation with the Euphrates River which flows through three countries (Turkey, Syria, and Iraq) and represents the main water resource for these countries. Therefore, the comprehensive hydrologic investigation needed to derive optimal operations requires reliable forecasts. This study aims to analysis and create a forecasting model for data generation from Turkey perspective by using the recorded inflow data of Ataturk reservoir for the period (Oct. 1961 - Sep. 2009). Based on 49 years of real inflow data

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the