A new spectrophotometric method for individual and simultaneous determination of cefixime and cephalexin depending on the first and second derivative mode techniques. The first and second derivative spectra of these compounds permitted individual and simultaneous determination of cefixime and cephalexin in concentration interval of (4– 24μg.ml-1 ) by measuring the amplitude of peak-to-base line, pea to peak at certain wavelengths and the area under peak at selected spectrum intervals. The methods showed reasonable precision and accuracy and have been applied to determine cefixime and cephalexin in two different pharmaceutical preparations.

The Sonic Scanner is a multifunctional instrument designed to log wells, assess elastic characteristics, and support reservoir characterisation. Furthermore, it facilitates comprehension of rock mechanics, gas detection, and well positioning, while also furnishing data for geomechanical computations and sand management. The present work involved the application of the Sonic Scanner for both basic and advanced processing of oil-well-penetrating carbonate media. The study aimed to characterize the compressional, shear, Stoneley slowness, rock mechanical properties, and Shear anisotropy analysis of the formation. Except for intervals where significant washouts are encountered, the data quality of the Monopole, Dipole, and Stoneley modes is gen

A high settlement may take place in shallow footing when resting on liquefiable soil if subjected to earthquake loading. In this study, a series of shaking table tests were carried out for shallow footing resting on sand soil. The input motion is three earthquake loadings (0.05g, 0.1g, and 0.2g). The study includes a reviewing of theoretical equations (available in literatures), which estimating settlement of footings due to earthquake loading, calibration, and verification of these equations with data from the shaking table test for improved soil by grouting and unimproved soil. It is worthy to note that the grouting materials considered in this study are the Bentonite and CKD slurries. A modification to the seismic set

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

The wear behavior of alumina particulate reinforced A332 aluminium alloy composites produced by a stir casting process technique were investigated. A pin-on-disc type apparatus was employed for determining the sliding wear rate in composite samples at different grain size (1 µm, 12µm, 50 nm) and different weight percentage (0.05-0.1-0.5-1) wt% of alumina respectively. Mechanical properties characterization which strongly depends on microstructure properties of reinforcement revealed that the presence of ( nano , micro) alumina particulates lead to simultaneous increase in hardness, ultimate tensile stress (UTS), wear resistances. The results revealed that UTS, Hardness, Wear resistances increases with the increase in the percentage of

A variety of single-engine driven files and inematics have been introduced to improve the clinical performance of NiTi rotary files. The purpose of this in vitro study was to measure and compare the incidence of dentinal defects after root canal preparation with different single file systems.

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The present study investigated the total content of phenolic compounds, antioxidant and antimicrobial activities of water extracts oat (Avena sativa) and basil (Ocimum basilicum), medicinal plants. The Folin-ciocalteu reagent assay was used to estimate the total phenolic content of plants extract. The antioxidant capacity of the plants extract was tested by ferric reducing/antioxidant power Assay (FRAP) and ferric reducing scavenging activity using DPPH method, and the antimicrobial activity was measured against [Staphylococcus epidermidis; Staphylococcus aureus; Proteus spp.; Klebsiella spp.; Escherichia coli; Candida albicans] as tester strains. The total phenolic content of Avena sativa and Ocimum basilicum extracts revealed that the