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bsj-5522
Flow Injection Analysis with Turbidity Detection for the Quantitative Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations
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The main objective of this paper is to develop and validate flow injection method, a precise, accurate, simple, economic, low cost and specific turbidimetric method for the quantitative determination of mebeverine hydrochloride (MbH) in pharmaceutical preparations.  A homemade NAG Dual & Solo (0-180º) analyser which contains two identical detections units (cell 1 and 2) was applied for turbidity measurements. The developed method was optimized for different chemical and physical parameters such as perception reagent concentrations, aqueous salts solutions, flow rate, the intensity of the sources light, sample volume, mixing coil and purge time. The correlation coefficients (r) of the developed method were 0.9980 and 0.9986 for cell 1 and 2 respectively and showed the linearity of response against concentration over the range of 1.0 to 6.5 and 0.7-6.5mmol/L for cell 1 & 2 respectively. The limit of detections (LOD) for cell 1 and cell 2 were 0.28 and 0.21 mmol/L respectively. The intra-day and inter-day precision for two serial estimations of 3.5 and 5.5 mmol/L of MBH exhibited a relative standard deviation of 0.46%, 0.28%, 0.23%, 0.26% and 0.39%, 0.79%, 0.14%, 0.05% for cell 1 & 2 respectively. The accuracy of the developed method has expressed a recovery percentage (Rec %) and error % which was between 99.22 to 101.13 and 99.39 to 101.17 for cell 1 and cell 2 respectively. The ICH guidelines were followed for method validation. The developed method was successfully applied for the determination of MbH in pure and pharmaceutical preparations and the method can be conveniently used for routine analysis in laboratory as a quality control method since the method permits quantitively determination of 60 samples/h.

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Publication Date
Mon May 04 2020
Journal Name
Environmental Engineering Research
Experimental and modeling study of water defluoridation using waste granular brick in a continuous up-flow fixed bed
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Contamination of surface and groundwater with excessive concentrations of fluoride is of significant health hazard. Adsorption of fluoride onto waste materials of no economic value could be a potential approach for the treatment of fluoride-bearing water. This experimental and modeling study was devoted to investigate for the first the fluoride removal using unmodified waste granular brick (WGB) in a fixed bed running in continuous mode. Characterization of WGB was carried out by FT-IR, SEM, and EDX analysis. The batch mode experiments showed that they were affected by several parameters including contact time, initial pH, and sorbent dosage. The best values of these parameters that provided maximum removal percent (82%) with the in

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Publication Date
Tue Sep 01 2020
Journal Name
Ain Shams Engineering Journal
Estimating server utilization rate in single server queuing models using an approximate solution of stiff fluid flow model
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Publication Date
Fri Jan 26 2024
Journal Name
Journal Of Information Systems Engineering And Management
Application of Material Flow Cost Accounting Technology to Support Green Productivity and Its Reflection in Achieving Sustainable Development
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As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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Publication Date
Mon Aug 01 2011
Journal Name
International Journal Of Research And Reviews In Computer Science
Detection of the photon number splitting attack by using decoy states quantum key distribution system
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The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

Publication Date
Tue Dec 23 2025
Journal Name
Scientific And Technical Journal Of Information Technologies, Mechanics And Optics
Aerodynamic analysis of SD7037 airfoil with flex-skin flap at low angles of attack and low Reynolds numbers
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This work concentrates on the effect of a flex-skin trailing edge flap on the aerodynamic characteristics of SD7037 airfoil at low Reynolds numbers, in the range of 2^10 to 5^10 using computational methods. The study used a range of angle of attack (AOA) associated with the take-off phase and different flap angles. The numerical model was set up in Siemens STAR-CCM+ package using the κ-ω shear stress transport turbulence model and the (γ-Reθ) transition model which ensured the approximate solution of Navier-Stokes equations. The verification of the computational solution was done by the comparison with the available experimental data of the plain flap, and it was discovered that the results matched pretty well at lower AoAs. Results in

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Publication Date
Mon Aug 05 2024
Journal Name
Pharmacia
A validated spectrophotometric analysis for simultaneous estimation of vincristine sulfate and bovine serum albumin in pure preparations using Vierordt’s method
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The novel Vierordt’s approach, or simultaneous equation method, was created and validated for the concurrent determination of vincristine sulfate (VCS) and bovine serum albumin (BSA) in pure solutions utilizing UV spectrophotometry. It is simple, precise, economical, rapid, reliable, and accurate. This method depends on measuring absorbance at two wavelengths, 296 nm and 278 nm, which correspond to the λmax of VCS and BSA in deionized water, respectively. The calibration curves of VCS and BSA are linear at concentration ranges of 10–60 μg/mL and 200–1600 μg/mL, with correlation coefficient values (R2) of 1 and 0.999, respectively. The limits of detection (LOD) and quantification (LO

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Integration between value chain analysis and balanced scorecard to for performance evaluation
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The performance evaluation process requires a set of criteria and for the purpose of measuring the level of performance achieved by the Unit and the actual level of development of its activities, and in view of the changes and of rapid and continuous variables surrounding the Performance is a reflection of the unit's ability to achieve its objectives, as these units are designed to achieve the objectives of exploiting a range of economic resources available to it, and the performance evaluation process is a form of censorship, focusing on the analysis of the results obtained from the achievement All its activities with a view to determining the extent to which the Unit has achieved its objectives using the resources available to it and h

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Publication Date
Thu Jan 06 2022
Journal Name
Kuwait Journal Of Science
AVO analysis for high amplitude anomalies using 2D pre-stack seismic data
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Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the

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