The stability and releasing profile of 2:1 core: wall ratio ibuprofen microcapsules prepared by aqueous coacervation (gelatin and acacia polymers coat) and an organic coacervation methods (ethyl cellulose and sodium alginate polymers coat) in weight equivalent to 300mg drug, were studied using different storage temperatures 40°C, 50°C ,60°C and refrigerator temperature 4°C in an opened and closed container for three months (releasing profile) and four months (stability study).It was found that, these ibuprofen microcapsules were stable with expiration dates of 4.1 and 3.1 years for aqueous and an organic method respectively.Aqueous prepared ibuprofen microcapsules were found more stable than those microcapsules prepared by or

The structure, optical, and electrical properties of SnSe and its application as photovoltaic device has been reported widely. The reasons for interest in SnSe due to the magnificent optoelectronic properties with other encouraging properties. The most applications that in this area are PV devices and batteries. In this study tin selenide structure, optical properties and surface morphology were investigated and studies. Thin-film of SnSe were deposit on p-Si substrates to establish a junction as solar cells. Different annealing temperatures (as prepared, 125,200, 275) °C effects on SnSe thin films were investigated. The structure properties of SnSe was studied through X-ray diffraction, and the results appears the increasing of the peaks

Break in the bond and its impact on the difference of scholars

Malaysia will be an ageing population by 2030 as the number of those aged 60 years and above has increased drastically from 6.2 percent in 2000 and is expected to reach 13.6 percent by 2030. There are many challenges that will be faced due to the ageing population, one of which is the increasing cost of pensions in the future. In view of that, it is necessary to investigate the effect of actuarial assumptions on pension liabilities under the perspective of ageing. To estimate the pension liabilities, the Projected Unit Credit method is used in the study and commutation functions are employed in the process. Demographic risk and salary risk have been identified as major risks in analyzing pension liabilities in this study. The sensitivity

The study aimed to investigate the effect of fungicides chlorothalonil at different concentrations ( 0.1 , 0.5 , 5 , 25 , 50 ) × 10 - 5 M on some cytogenetic parameters of human peripheral blood lymphocytes . The genotoxicity parameters were estimated by the number of chromosomal aberrations (CAs) and their types and by estimating the induced micronuclei (Mn) . Cytotoxic effect recorded by estimating the mitotic index (MI) . Results revealed that the fungicide increased the CAs in dose – response pattern with positive correlation coefficient ( r = + 0.964) , there was a significant differences among the concentrations (P<0.01) . The major CAs records chromosomal breakage at concentrations. 0.5 , 5 , 25 , and 50 , while the lowest concen

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

SKF Sami I. Jafar, Mohammad J. Kadhim, Engineering and Technology Journal, 2018 - Cited by 4

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database