The purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of 0.99730 and 0.99942, respectively. The suggested approach’s ease of use, affordability, and environmental friendliness make it a suitable replacement for the use of hazardous chemicals in the routine investigation of the selected drugs
The current study highlighted the violations and the steady depletion of , and agricultural and green areas in and around cities , which is an accurate scientific research problem that affects the future perspectives of these areas, their production and their consequences for the life of cities and their vital surroundings. This research took Baghdad city as a model of this critical phenomenon in order to study the reality of these regions, the size of violations, and to set a future concept and strategy, in addition to the proper treatment that preserves the assets of this great wealth , It was one of the most important conclusions Urban planning disruption of Baghdad city formations ,One of the most important recommendations , Scaling Bag
... Show MoreA plant mixture containing indigenous Australian plants was examined for synergistic antimicrobial activity using selected test microorganisms. This study aims to investigate antibacterial activities, antioxidant potential and the content of phenolic compounds in aqueous, ethanolic and peptide extracts of plant mixture
Well diffusion, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays were used to test antibacterial activity against four pathogenic bacteria namely
Two series of bent and liner core mesogen containing 1,2,4-traizole ring [VI]a,g and series were synthesized by many steps starting from esterification of isophthalic acid and terephathalic acid with methanol to yield diester compound [I]a,b which was converted to their acid hydrazide [II]a,b and the acid hydrazide reacted with ammonium thiocyanate or diester reacted with thiosemicarbazide to yield compounds [III]a,b. Then cyclization by 4% NaOH to yielded 1,2,4 traizole-3- thiol compounds [IV]a,b , afterword adding hydrazine hydrate to yield compounds [V]a,b. These compounds condensated with different substituted aldehyde to give new Schiff bases[VI]a,b ,[VII]a,b . Also , reaction acid hydrazide [II]a,b with aldehyde [VII] to yielded Schif
... Show MoreThe current work is characterized by simplicity, accuracy and high sensitivity Dispersive liquid - Liquid Micro Extraction (DLLME). The method was developed to determine Telmesartan (TEL) and Irbesartan (IRB) in the standard and pharmaceutical composition. Telmesartan and Irbesartan are separated prior to treatment with Eriochrom black T as a reagent and formation ion pair reaction dye. The analytical results of DLLME method for linearity range (0.2- 6.0) mg /L for both drugs, molar absorptivity were (1.67 × 105- 5.6 × 105) L/ mole. cm, limit of detection were (0.0242and0.0238), Limit of quantification were (0.0821and0.0711), the Distribution coefficient were
... Show MoreThe purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals
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