6-Amino-4-(4-hydroxyphenyl)-5-cyano-3-methyl-1-phenyl-1, 4-dihydropyrano [2,3-c] pyrazole (compound 2) was prepared by condensation of 2-(4-hydroxylbenzylidine) malononitrile (compound 1) [which was prepared by Knoevenagel condensation of malononitrile with 4-hydroxy benzaldehyde ] with 3-methyl-1-phenyl-2-pyrazolin-5-one. Reactions of compound 2 with different reagents formic acid, formamide, and ammonium thiocyanate under microwave irradiation leads to the synthesis of 4-(4-hydroxyphenyl)- 3-methyl-1-phenyl-4,6-dihydro- pyrazolo [3', 4':5,6] pyrano [2,3-d] pyrimidine-5-one (compound 3), 4-(4-hydroxyphenyl)- 3-methyl-1-phenyl-4, 6-dihydro- pyrazolo [3', 4':5,6]pyrano[2,3-d]pyrimidine-5-imine (compound 4) and N-[4-(4-hydroxyphenyl)- 3-me

We propose two simple, rapid, and convenient spectrophotometric methods which are described for the determination of cephalexin in bulk and its pharmaceutical preparations. They are based on the measurement of the flame atomic emission of potassium ion (in the first method) and colorimetric determination of the green colored solution at 610 nm formed after the reaction of cephalexin with potassium permanganate as an oxidant agent (in the second method) in basic medium. The working conditions of the methods are investigated and optimized. Beer's law plot shows a good correlation in the concentration range of 5-40?g ml-1. The detection limits are 2.573,2.814 ?g ml-1 for the flame emission photometric method and 1.844,2.016 ?g ml-1 for colo

      The current work involves synthesis of 6-amino-4-(4-hydroxyl-3-methoxyphenyl)-3-methyl-1-phenyl-1,4- dihydropyrano[2,3-c]pyrazole-5-carbonitrile (2) by condensation of 2-(4-hydroxyl-3-methoxybenzylidine) malononitrile (1) with 3-methyl-1-phenyl-2-pyrazolin-5-one. The product 2 was then reacted with various aldehydes to form a series of Schiff base derivatives 3a-h. The reaction of the chosen Schiff base derivatives (3a and 3b) with mercaptoacetic acid gave thiazolidinone derivatives (4a and 4b). The structures of prepared compounds were confirmed using FT-IR, ¹H NMR, and ¹³

The present work aims to study the removal of dyes from wastewater by reverse osmosis process. Two dyes were used direct blue 6, and direct yellow. Experiments were performed with feed concentration (75 – 450 ppm), operation temperature (30 – 50 oC) and time (0.2 – 2.0 hr). The membrane used is thin film composite membrane (TFC). It was found that modal permeate concentration decreases with increasing feed concentration and time operating, while permeate concentration increases with increasing feed temperature. Also it was found that product rate increase with increasing temperature, but it decrease with increasing feed concentration and time. The concentration of reject solution showed an increase with increasing feed concentratio

The research took the spatial autoregressive model: SAR and spatial error model: SEM  in an attempt to provide practical evidence that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial and that includes all of the spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. The spatial analysis had been applied to Iraq Household Socio-Economic Survey: IHS

 Pan sharpening (fusion image) is the procedure of merging suitable information from two or more images into a single image. The image fusion techniques allow the combination of different information sources to improve the quality of image and increase its utility for a particular application. In this research, six pan-sharpening method have been implemented between the panchromatic and multispectral images, these methods include Ehlers, color normalize, Gram-Schmidt, local mean and variance matching, Daubechies of rank two and Symlets of rank four  wavelet transform. Two images captured by two different sensors such as landsat-8 and world view-2 have been adopted to achieve the fusion purpose. Different fidelity metric like MS

A Raman spectroscopy method was optimised to examine the chemical changes of aspirin tablets after interaction with helium temperatures. Several aspirin tablets were exposed to plasma-assisted desorption ionisation flame for different times (10, 30, 50, 60, 180 and 300s) and then analysed by Raman spectroscopy using optimal conditions. The changes in chemistry between exposed and fresh (without exposure to plasma) tablets were compared. The vibrational peaks of the aspirin molecule in the Raman spectrum were identified by checking the peak position. The results showed clear spectra with increases in intensity of vibrational peaks until 30s, whereas no spectra were measured for the exposed tablets to plasma flame after 50s. It can, the

Dandruff and seborrheic dermatitis (SD) are common skin disorders affecting the scalp and extending to other body sites in the case of SD. They are associated with pruritus and scaling, causing an esthetical disturbance in the population affected.   Treatment of such conditions involves using a variety of drugs for long terms, thus optimizing drug formulation is essential to improve therapeutic efficacy and patient compliance. Conventional topical formulations like shampoos and creams have been widely used but their use is associated with disadvantages. To overcome such effects, novel topical nanotechnology-based formulations are currently under investigation. In the following article, we highlight recently published formulatio

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod